diff --git a/process/core/init.py b/process/core/init.py
index 139e8be09..9dce55691 100644
--- a/process/core/init.py
+++ b/process/core/init.py
@@ -22,7 +22,6 @@
 from process.data_structure.buildings_variables import init_buildings_variables
 from process.data_structure.ccfe_hcpb_module import init_ccfe_hcpb_module
 from process.data_structure.constraint_variables import init_constraint_variables
-from process.data_structure.cost_2015_variables import init_cost_2015_variables
 from process.data_structure.cost_variables import init_cost_variables
 from process.data_structure.cs_fatigue_variables import init_cs_fatigue_variables
 from process.data_structure.current_drive_variables import init_current_drive_variables
@@ -302,7 +301,6 @@ def init_all_module_vars():
     init_cs_fatigue_variables()
     init_blanket_library()
     init_dcll_module()
-    init_cost_2015_variables()
     init_power_variables()
     init_neoclassics_variables()
 
diff --git a/process/core/model.py b/process/core/model.py
index 4cfa60747..5b6dc659b 100644
--- a/process/core/model.py
+++ b/process/core/model.py
@@ -1,6 +1,7 @@
 import abc
 from dataclasses import dataclass, fields
 
+from process.data_structure.cost_2015_variables import Cost2015Data
 from process.data_structure.water_usage_variables import WaterUseData
 
 initialise_later = object()
@@ -9,6 +10,7 @@
 @dataclass(kw_only=True)
 class DataStructure:
     water_use: WaterUseData = initialise_later
+    costs_2015: Cost2015Data = initialise_later
 
     def __post_init__(self):
         for f in fields(self):
diff --git a/process/data_structure/cost_2015_variables.py b/process/data_structure/cost_2015_variables.py
index 2e6c82a16..eedb2c130 100644
--- a/process/data_structure/cost_2015_variables.py
+++ b/process/data_structure/cost_2015_variables.py
@@ -1,53 +1,33 @@
-import numpy as np
-
-mean_electric_output: float = None
-
-annual_electric_output: float = None
-
-maintenance: float = None
-
-total_costs: float = None
+from dataclasses import dataclass, field
 
-s_label: list[str] = None
-
-s_kref: list[float] = None
-
-s_k: list[float] = None
-
-s_cref: list[float] = None
+import numpy as np
 
-s_cost: list[float] = None
 
-s_cost_factor: list[float] = None
+@dataclass
+class Cost2015Data:
+    mean_electric_output: float = 0.0
 
+    annual_electric_output: float = 0.0
 
-def init_cost_2015_variables():
-    global mean_electric_output
-    mean_electric_output = 0.0
+    maintenance: float = 0.0
 
-    global annual_electric_output
-    annual_electric_output = 0.0
+    total_costs: float = 0.0
 
-    global maintenance
-    maintenance = 0.0
+    s_label: list[str] = field(
+        default_factory=lambda: np.array(["not used"] * 100, dtype=object)
+    )
 
-    global total_costs
-    total_costs = 0.0
+    s_kref: list[float] = field(default_factory=lambda: np.zeros(100, dtype=np.float64))
 
-    global s_label
-    s_label = np.array(["not used"] * 100, dtype=object)
+    s_k: list[float] = field(default_factory=lambda: np.zeros(100, dtype=np.float64))
 
-    global s_kref
-    s_kref = np.zeros(100, dtype=np.float64)
+    s_cref: list[float] = field(default_factory=lambda: np.zeros(100, dtype=np.float64))
 
-    global s_k
-    s_k = np.zeros(100, dtype=np.float64)
+    s_cost: list[float] = field(default_factory=lambda: np.zeros(100, dtype=np.float64))
 
-    global s_cref
-    s_cref = np.zeros(100, dtype=np.float64)
+    s_cost_factor: list[float] = field(
+        default_factory=lambda: np.zeros(100, dtype=np.float64)
+    )
 
-    global s_cost
-    s_cost = np.zeros(100, dtype=np.float64)
 
-    global s_cost_factor
-    s_cost_factor = np.zeros(100, dtype=np.float64)
+CREATE_DICTS_FROM_DATACLASS = Cost2015Data
diff --git a/process/main.py b/process/main.py
index 0e6fd1551..da4f94a76 100644
--- a/process/main.py
+++ b/process/main.py
@@ -776,7 +776,7 @@ def costs(self, value: CostsProtocol):
     def models(self) -> tuple[Model, ...]:
         # At the moment, this property just returns models that implement the Model interface.
         # Eventually every Model will comply and then this method can be used as the caller/outputter!
-        return (self.water_use,)
+        return (self.water_use, self._costs_2015)
 
     def setup_data_structure(self):
         # This Models class should be replaced with a dataclass so we can
diff --git a/process/models/costs/costs_2015.py b/process/models/costs/costs_2015.py
index f832d933c..eb4316cbc 100644
--- a/process/models/costs/costs_2015.py
+++ b/process/models/costs/costs_2015.py
@@ -7,7 +7,6 @@
 from process.core.model import Model
 from process.data_structure import (
     build_variables,
-    cost_2015_variables,
     cost_variables,
     current_drive_variables,
     first_wall_variables,
@@ -60,55 +59,57 @@ def run(self):
         self.calc_remaining_subsystems()
 
         # Calculate total capital cost
-        cost_2015_variables.total_costs = (
-            cost_2015_variables.s_cost[8]
-            + cost_2015_variables.s_cost[12]
-            + cost_2015_variables.s_cost[20]
-            + cost_2015_variables.s_cost[26]
-            + cost_2015_variables.s_cost[30]
-            + cost_2015_variables.s_cost[33]
-            + cost_2015_variables.s_cost[34]
-            + cost_2015_variables.s_cost[60]
+        self.data.costs_2015.total_costs = (
+            self.data.costs_2015.s_cost[8]
+            + self.data.costs_2015.s_cost[12]
+            + self.data.costs_2015.s_cost[20]
+            + self.data.costs_2015.s_cost[26]
+            + self.data.costs_2015.s_cost[30]
+            + self.data.costs_2015.s_cost[33]
+            + self.data.costs_2015.s_cost[34]
+            + self.data.costs_2015.s_cost[60]
         )
 
         # Save as concost, the variable used as a Figure of Merit (M$)
-        cost_variables.concost = cost_2015_variables.total_costs / 1.0e6
+        cost_variables.concost = self.data.costs_2015.total_costs / 1.0e6
 
         # Electrical output (given availability) for a whole year
-        cost_2015_variables.mean_electric_output = (
+        self.data.costs_2015.mean_electric_output = (
             heat_transport_variables.p_plant_electric_net_mw * cost_variables.cpfact
         )
-        cost_2015_variables.annual_electric_output = (
-            cost_2015_variables.mean_electric_output * 24.0e0 * 365.25e0
+        self.data.costs_2015.annual_electric_output = (
+            self.data.costs_2015.mean_electric_output * 24.0e0 * 365.25e0
         )
 
         # Annual maintenance cost.
-        cost_2015_variables.maintenance = (
-            cost_2015_variables.s_cost[26] + cost_2015_variables.s_cost[37]
+        self.data.costs_2015.maintenance = (
+            self.data.costs_2015.s_cost[26] + self.data.costs_2015.s_cost[37]
         ) * cost_variables.maintenance_fwbs + (
-            cost_2015_variables.s_cost[8]
-            + cost_2015_variables.s_cost[30]
-            + cost_2015_variables.s_cost[33]
-            + cost_2015_variables.s_cost[34]
-            + cost_2015_variables.s_cost[40]
-            + cost_2015_variables.s_cost[42]
-            + cost_2015_variables.s_cost[44]
-            + cost_2015_variables.s_cost[46]
-            + cost_2015_variables.s_cost[47]
-            + cost_2015_variables.s_cost[48]
-            + cost_2015_variables.s_cost[49]
-            + cost_2015_variables.s_cost[50]
-            + cost_2015_variables.s_cost[51]
-            + cost_2015_variables.s_cost[52]
-            + cost_2015_variables.s_cost[53]
-            + cost_2015_variables.s_cost[57]
+            self.data.costs_2015.s_cost[8]
+            + self.data.costs_2015.s_cost[30]
+            + self.data.costs_2015.s_cost[33]
+            + self.data.costs_2015.s_cost[34]
+            + self.data.costs_2015.s_cost[40]
+            + self.data.costs_2015.s_cost[42]
+            + self.data.costs_2015.s_cost[44]
+            + self.data.costs_2015.s_cost[46]
+            + self.data.costs_2015.s_cost[47]
+            + self.data.costs_2015.s_cost[48]
+            + self.data.costs_2015.s_cost[49]
+            + self.data.costs_2015.s_cost[50]
+            + self.data.costs_2015.s_cost[51]
+            + self.data.costs_2015.s_cost[52]
+            + self.data.costs_2015.s_cost[53]
+            + self.data.costs_2015.s_cost[57]
         ) * cost_variables.maintenance_gen
 
         # Levelized cost of electricity (LCOE) ($/MWh)
-        if cost_2015_variables.annual_electric_output > 0.00001:
-            cost_variables.coe = (1.0e0 / cost_2015_variables.annual_electric_output) * (
-                cost_2015_variables.total_costs / cost_variables.amortization
-                + cost_2015_variables.maintenance
+        if self.data.costs_2015.annual_electric_output > 0.00001:
+            cost_variables.coe = (
+                1.0e0 / self.data.costs_2015.annual_electric_output
+            ) * (
+                self.data.costs_2015.total_costs / cost_variables.amortization
+                + self.data.costs_2015.maintenance
             )
 
         # Switch on output if there is a NaN error
@@ -119,12 +120,12 @@ def run(self):
 
             for i in range(100):
                 nan_diags = [
-                    cost_2015_variables.s_label[i],
-                    cost_2015_variables.s_kref[i],
-                    cost_2015_variables.s_k[i],
-                    cost_2015_variables.s_cref[i],
-                    cost_2015_variables.s_cost[i],
-                    cost_2015_variables.s_cost_factor[i],
+                    self.data.costs_2015.s_label[i],
+                    self.data.costs_2015.s_kref[i],
+                    self.data.costs_2015.s_k[i],
+                    self.data.costs_2015.s_cref[i],
+                    self.data.costs_2015.s_cost[i],
+                    self.data.costs_2015.s_cost_factor[i],
                 ]
 
                 nan_diags_str = ",".join(str(x) for x in nan_diags)
@@ -142,7 +143,7 @@ def calc_fwbs_costs(self):
         """
 
         for i in range(21, 27):
-            cost_2015_variables.s_cost_factor[i] = cost_variables.cost_factor_fwbs
+            self.data.costs_2015.s_cost_factor[i] = cost_variables.cost_factor_fwbs
 
         # Enrichment
         # Costs based on the number of separative work units (SWU) required
@@ -181,27 +182,27 @@ def calc_fwbs_costs(self):
                 )
 
             # Reference cost
-            cost_2015_variables.s_label[21] = "Lithium enrichment"
-            cost_2015_variables.s_cref[21] = 0.1e6
-            cost_2015_variables.s_k[21] = 64.7e0
-            cost_2015_variables.s_kref[21] = 64.7e0
-            cost_2015_variables.s_cost[21] = (
-                cost_2015_variables.s_cost_factor[21]
-                * cost_2015_variables.s_cref[21]
-                * (cost_2015_variables.s_k[21] / cost_2015_variables.s_kref[21])
+            self.data.costs_2015.s_label[21] = "Lithium enrichment"
+            self.data.costs_2015.s_cref[21] = 0.1e6
+            self.data.costs_2015.s_k[21] = 64.7e0
+            self.data.costs_2015.s_kref[21] = 64.7e0
+            self.data.costs_2015.s_cost[21] = (
+                self.data.costs_2015.s_cost_factor[21]
+                * self.data.costs_2015.s_cref[21]
+                * (self.data.costs_2015.s_k[21] / self.data.costs_2015.s_kref[21])
                 ** cost_variables.costexp
             )
-            if abs(cost_2015_variables.s_cost[21] - 0.1e6) / 0.1e6 < 1.0e-3:
+            if abs(self.data.costs_2015.s_cost[21] - 0.1e6) / 0.1e6 < 1.0e-3:
                 po.ocmmnt(self.outfile, "Reference cost for enrichment CORRECT")
             else:
                 po.ocmmnt(self.outfile, "Reference cost for enrichment ERROR")
 
         # Lithium 6 enrichment cost ($)
-        cost_2015_variables.s_label[21] = "Lithium enrichment"
+        self.data.costs_2015.s_label[21] = "Lithium enrichment"
 
         # Zero cost for natural enrichment
         if fwbs_variables.f_blkt_li6_enrichment <= 7.42e0:
-            cost_2015_variables.s_cost[21] = 0.0e0
+            self.data.costs_2015.s_cost[21] = 0.0e0
         else:
             # Percentage of lithium 6 in the product
             product_li6 = min(fwbs_variables.f_blkt_li6_enrichment, 99.99e0) / 100.0e0
@@ -230,84 +231,84 @@ def calc_fwbs_costs(self):
             total_swu = swu * mass_li
 
             # Reference cost for lithium enrichment (2014 $)
-            cost_2015_variables.s_cref[21] = 0.1e6
+            self.data.costs_2015.s_cref[21] = 0.1e6
             # Reference case of lithium SWU
-            cost_2015_variables.s_k[21] = total_swu
-            cost_2015_variables.s_kref[21] = 64.7e0
-            cost_2015_variables.s_cost[21] = (
-                cost_2015_variables.s_cost_factor[21]
-                * cost_2015_variables.s_cref[21]
-                * (cost_2015_variables.s_k[21] / cost_2015_variables.s_kref[21])
+            self.data.costs_2015.s_k[21] = total_swu
+            self.data.costs_2015.s_kref[21] = 64.7e0
+            self.data.costs_2015.s_cost[21] = (
+                self.data.costs_2015.s_cost_factor[21]
+                * self.data.costs_2015.s_cref[21]
+                * (self.data.costs_2015.s_k[21] / self.data.costs_2015.s_kref[21])
                 ** cost_variables.costexp
             )
 
-        cost_2015_variables.s_label[22] = "Lithium orthosilicate pebble manufacturing"
+        self.data.costs_2015.s_label[22] = "Lithium orthosilicate pebble manufacturing"
         # Reference cost of lithium pebble manufacture (2014 $)
-        cost_2015_variables.s_cref[22] = 6.5e4
+        self.data.costs_2015.s_cref[22] = 6.5e4
         # Scale with mass of pebbles (kg)
-        cost_2015_variables.s_k[22] = fwbs_variables.m_blkt_li2o
-        cost_2015_variables.s_kref[22] = 10.0e0
-        cost_2015_variables.s_cost[22] = (
-            cost_2015_variables.s_cost_factor[22]
-            * cost_2015_variables.s_cref[22]
-            * (cost_2015_variables.s_k[22] / cost_2015_variables.s_kref[22])
+        self.data.costs_2015.s_k[22] = fwbs_variables.m_blkt_li2o
+        self.data.costs_2015.s_kref[22] = 10.0e0
+        self.data.costs_2015.s_cost[22] = (
+            self.data.costs_2015.s_cost_factor[22]
+            * self.data.costs_2015.s_cref[22]
+            * (self.data.costs_2015.s_k[22] / self.data.costs_2015.s_kref[22])
             ** cost_variables.costexp_pebbles
         )
 
-        cost_2015_variables.s_label[23] = "Titanium beryllide pebble manufacturing"
+        self.data.costs_2015.s_label[23] = "Titanium beryllide pebble manufacturing"
         #  Reference cost of titanium beryllide pebble manufacture (2014 $)
-        cost_2015_variables.s_cref[23] = 450.0e6
+        self.data.costs_2015.s_cref[23] = 450.0e6
         #  Scale with mass of titanium beryllide pebbles (kg)
-        cost_2015_variables.s_k[23] = fwbs_variables.m_blkt_beryllium
-        cost_2015_variables.s_kref[23] = 1.0e5
-        cost_2015_variables.s_cost[23] = (
-            cost_2015_variables.s_cost_factor[23]
-            * cost_2015_variables.s_cref[23]
-            * (cost_2015_variables.s_k[23] / cost_2015_variables.s_kref[23])
+        self.data.costs_2015.s_k[23] = fwbs_variables.m_blkt_beryllium
+        self.data.costs_2015.s_kref[23] = 1.0e5
+        self.data.costs_2015.s_cost[23] = (
+            self.data.costs_2015.s_cost_factor[23]
+            * self.data.costs_2015.s_cref[23]
+            * (self.data.costs_2015.s_k[23] / self.data.costs_2015.s_kref[23])
             ** cost_variables.costexp_pebbles
         )
 
-        cost_2015_variables.s_label[24] = "First wall W coating manufacturing"
+        self.data.costs_2015.s_label[24] = "First wall W coating manufacturing"
         #  Reference (PPCS A) first wall W coating cost (2014 $)
-        cost_2015_variables.s_cref[24] = 25.0e6
+        self.data.costs_2015.s_cref[24] = 25.0e6
         #  First wall W coating mass (kg)
-        cost_2015_variables.s_k[24] = (
+        self.data.costs_2015.s_k[24] = (
             first_wall_variables.a_fw_total
             * fwbs_variables.fw_armour_thickness
             * constants.DEN_TUNGSTEN
         )
-        cost_2015_variables.s_kref[24] = 29000.0e0
-        cost_2015_variables.s_cost[24] = (
-            cost_2015_variables.s_cost_factor[24]
-            * cost_2015_variables.s_cref[24]
-            * (cost_2015_variables.s_k[24] / cost_2015_variables.s_kref[24])
+        self.data.costs_2015.s_kref[24] = 29000.0e0
+        self.data.costs_2015.s_cost[24] = (
+            self.data.costs_2015.s_cost_factor[24]
+            * self.data.costs_2015.s_cref[24]
+            * (self.data.costs_2015.s_k[24] / self.data.costs_2015.s_kref[24])
             ** cost_variables.costexp
         )
 
-        cost_2015_variables.s_label[25] = (
+        self.data.costs_2015.s_label[25] = (
             "Blanket and shield materials and manufacturing"
         )
         # The cost of making the blanket was estimated for PPCS A.
         # This cost includes only manufacturing - not R&D, transport, or assembly in the reactor.
         # It includes the first wall, blanket and shield, but excludes the breeder and multiplier materials.
-        cost_2015_variables.s_cref[25] = 317.0e6
+        self.data.costs_2015.s_cref[25] = 317.0e6
         #  Scale with steel mass in blanket + shield mass
-        cost_2015_variables.s_k[25] = (
+        self.data.costs_2015.s_k[25] = (
             fwbs_variables.m_blkt_steel_total + fwbs_variables.whtshld
         )
-        cost_2015_variables.s_kref[25] = 4.07e6
-        cost_2015_variables.s_cost[25] = (
-            cost_2015_variables.s_cost_factor[25]
-            * cost_2015_variables.s_cref[25]
-            * (cost_2015_variables.s_k[25] / cost_2015_variables.s_kref[25])
+        self.data.costs_2015.s_kref[25] = 4.07e6
+        self.data.costs_2015.s_cost[25] = (
+            self.data.costs_2015.s_cost_factor[25]
+            * self.data.costs_2015.s_cref[25]
+            * (self.data.costs_2015.s_k[25] / self.data.costs_2015.s_kref[25])
             ** cost_variables.costexp
         )
 
-        cost_2015_variables.s_label[26] = "Total first wall and blanket cost"
-        cost_2015_variables.s_cost[26] = 0.0e0
+        self.data.costs_2015.s_label[26] = "Total first wall and blanket cost"
+        self.data.costs_2015.s_cost[26] = 0.0e0
         for j in range(21, 26):
-            cost_2015_variables.s_cost[26] = (
-                cost_2015_variables.s_cost[26] + cost_2015_variables.s_cost[j]
+            self.data.costs_2015.s_cost[26] = (
+                self.data.costs_2015.s_cost[26] + self.data.costs_2015.s_cost[j]
             )
 
     def output(self):
@@ -324,9 +325,9 @@ def output(self):
         for i in range(9):
             self.ocost(
                 self.outfile,
-                cost_2015_variables.s_label[i],
+                self.data.costs_2015.s_label[i],
                 i + 1,
-                cost_2015_variables.s_cost[i] / 1.0e6,
+                self.data.costs_2015.s_cost[i] / 1.0e6,
             )
 
         po.oshead(self.outfile, "Land (M$)")
@@ -334,9 +335,9 @@ def output(self):
         for j in range(9, 13):
             self.ocost(
                 self.outfile,
-                cost_2015_variables.s_label[j],
+                self.data.costs_2015.s_label[j],
                 j + 1,
-                cost_2015_variables.s_cost[j] / 1.0e6,
+                self.data.costs_2015.s_cost[j] / 1.0e6,
             )
 
         po.oshead(self.outfile, "TF Coils (M$)")
@@ -344,64 +345,64 @@ def output(self):
         for k in range(13, 21):
             self.ocost(
                 self.outfile,
-                cost_2015_variables.s_label[k],
+                self.data.costs_2015.s_label[k],
                 k + 1,
-                cost_2015_variables.s_cost[k] / 1.0e6,
+                self.data.costs_2015.s_cost[k] / 1.0e6,
             )
 
         po.oshead(self.outfile, "First wall and blanket (M$)")
         for l in range(21, 27):  # noqa: E741
             self.ocost(
                 self.outfile,
-                cost_2015_variables.s_label[l],
+                self.data.costs_2015.s_label[l],
                 l + 1,
-                cost_2015_variables.s_cost[l] / 1.0e6,
+                self.data.costs_2015.s_cost[l] / 1.0e6,
             )
 
         po.oshead(self.outfile, "Active maintenance and remote handling (M$)")
         self.ocost(
             self.outfile,
-            cost_2015_variables.s_label[27],
+            self.data.costs_2015.s_label[27],
             28,
-            cost_2015_variables.s_cost[27] / 1.0e6,
+            self.data.costs_2015.s_cost[27] / 1.0e6,
         )
         self.ocost(
             self.outfile,
-            cost_2015_variables.s_label[28],
+            self.data.costs_2015.s_label[28],
             29,
-            cost_2015_variables.s_cost[28] / 1.0e6,
+            self.data.costs_2015.s_cost[28] / 1.0e6,
         )
         self.ocost(
             self.outfile,
-            cost_2015_variables.s_label[30],
+            self.data.costs_2015.s_label[30],
             31,
-            cost_2015_variables.s_cost[30] / 1.0e6,
+            self.data.costs_2015.s_cost[30] / 1.0e6,
         )
 
         po.oshead(self.outfile, "Vacuum vessel and liquid nitrogen plant (M$)")
         for n in range(31, 34):
             self.ocost(
                 self.outfile,
-                cost_2015_variables.s_label[n],
+                self.data.costs_2015.s_label[n],
                 n + 1,
-                cost_2015_variables.s_cost[n] / 1.0e6,
+                self.data.costs_2015.s_cost[n] / 1.0e6,
             )
 
         po.oshead(self.outfile, "System for converting heat to electricity (M$)")
         self.ocost(
             self.outfile,
-            cost_2015_variables.s_label[34],
+            self.data.costs_2015.s_label[34],
             35,
-            cost_2015_variables.s_cost[34] / 1.0e6,
+            self.data.costs_2015.s_cost[34] / 1.0e6,
         )
 
         po.oshead(self.outfile, "Remaining subsystems (M$)")
         for q in range(35, 61):
             self.ocost(
                 self.outfile,
-                cost_2015_variables.s_label[q],
+                self.data.costs_2015.s_label[q],
                 q + 1,
-                cost_2015_variables.s_cost[q] / 1.0e6,
+                self.data.costs_2015.s_cost[q] / 1.0e6,
             )
 
         po.oblnkl(self.outfile)
@@ -409,13 +410,13 @@ def output(self):
             self.outfile,
             "TOTAL OVERNIGHT CAPITAL COST (M$)",
             "(total_costs)",
-            cost_2015_variables.total_costs / 1.0e6,
+            self.data.costs_2015.total_costs / 1.0e6,
         )
         self.ocost(
             self.outfile,
             "Annual maintenance cost (M$)",
             "(maintenance)",
-            cost_2015_variables.maintenance / 1.0e6,
+            self.data.costs_2015.maintenance / 1.0e6,
         )
         po.oblnkl(self.outfile)
         po.ovarrf(
@@ -432,15 +433,15 @@ def output(self):
             self.outfile,
             "Mean electric output (MW)",
             "(mean_electric_output)",
-            cost_2015_variables.mean_electric_output,
+            self.data.costs_2015.mean_electric_output,
             "OP ",
         )
         po.ovarrf(
             self.outfile,
             "Capital cost / mean electric output ($/W)",
             "",
-            cost_2015_variables.total_costs
-            / cost_2015_variables.mean_electric_output
+            self.data.costs_2015.total_costs
+            / self.data.costs_2015.mean_electric_output
             / 1.0e6,
             "OP ",
         )
@@ -465,131 +466,131 @@ def calc_building_costs(self):
         PROCESS Costs Paper (M. Kovari, J. Morris)
         """
         for i in range(9):
-            cost_2015_variables.s_cost_factor[i] = cost_variables.cost_factor_buildings
+            self.data.costs_2015.s_cost_factor[i] = cost_variables.cost_factor_buildings
 
         # Power plant admin buildings cost ($)
-        cost_2015_variables.s_label[0] = "Admin Buildings"
-        cost_2015_variables.s_cref[0] = (
+        self.data.costs_2015.s_label[0] = "Admin Buildings"
+        self.data.costs_2015.s_cref[0] = (
             129000.0e0 * cost_variables.light_build_cost_per_vol
         )
-        cost_2015_variables.s_cost[0] = (
-            cost_2015_variables.s_cost_factor[0] * cost_2015_variables.s_cref[0]
+        self.data.costs_2015.s_cost[0] = (
+            self.data.costs_2015.s_cost_factor[0] * self.data.costs_2015.s_cref[0]
         )
 
         # Tokamak complex excluding hot cell cost ($)
-        cost_2015_variables.s_label[1] = "Tokamak Complex (excluding hot cell)"
-        cost_2015_variables.s_cref[1] = (
+        self.data.costs_2015.s_label[1] = "Tokamak Complex (excluding hot cell)"
+        self.data.costs_2015.s_cref[1] = (
             1100000.0e0 * cost_variables.tok_build_cost_per_vol
         )
         # ITER cryostat volume (m^3)
-        cost_2015_variables.s_k[1] = (
+        self.data.costs_2015.s_k[1] = (
             (np.pi * fwbs_variables.r_cryostat_inboard**2)
             * 2.0e0
             * fwbs_variables.z_cryostat_half_inside
         )
-        cost_2015_variables.s_kref[1] = 18712.0e0
-        cost_2015_variables.s_cost[1] = (
-            cost_2015_variables.s_cost_factor[1]
-            * cost_2015_variables.s_cref[1]
-            * (cost_2015_variables.s_k[1] / cost_2015_variables.s_kref[1])
+        self.data.costs_2015.s_kref[1] = 18712.0e0
+        self.data.costs_2015.s_cost[1] = (
+            self.data.costs_2015.s_cost_factor[1]
+            * self.data.costs_2015.s_cref[1]
+            * (self.data.costs_2015.s_k[1] / self.data.costs_2015.s_kref[1])
         )
 
         # Neutral beam buildings cost ($)
-        cost_2015_variables.s_label[2] = "Neutral beam buildings"
-        cost_2015_variables.s_cref[2] = (
+        self.data.costs_2015.s_label[2] = "Neutral beam buildings"
+        self.data.costs_2015.s_cref[2] = (
             28000.0e0 * cost_variables.light_build_cost_per_vol
         )
         # Scale with neutral beam wall plug power (MW)
-        cost_2015_variables.s_k[2] = current_drive_variables.pwpnb
-        cost_2015_variables.s_kref[2] = 120.0e0
-        cost_2015_variables.s_cost[2] = (
-            cost_2015_variables.s_cost_factor[2]
-            * cost_2015_variables.s_cref[2]
-            * (cost_2015_variables.s_k[2] / cost_2015_variables.s_kref[2])
+        self.data.costs_2015.s_k[2] = current_drive_variables.pwpnb
+        self.data.costs_2015.s_kref[2] = 120.0e0
+        self.data.costs_2015.s_cost[2] = (
+            self.data.costs_2015.s_cost_factor[2]
+            * self.data.costs_2015.s_cref[2]
+            * (self.data.costs_2015.s_k[2] / self.data.costs_2015.s_kref[2])
         )
 
         # Cryoplant buildings cost ($)
-        cost_2015_variables.s_label[3] = "Cryoplant buildings"
-        cost_2015_variables.s_cref[3] = (
+        self.data.costs_2015.s_label[3] = "Cryoplant buildings"
+        self.data.costs_2015.s_cref[3] = (
             130000.0e0 * cost_variables.light_build_cost_per_vol
         )
         # Scale with the total heat load on the cryoplant at ~4.5K (kW)
-        cost_2015_variables.s_k[3] = heat_transport_variables.helpow / 1.0e3
-        cost_2015_variables.s_kref[3] = 61.0e0
-        cost_2015_variables.s_cost[3] = (
-            cost_2015_variables.s_cost_factor[3]
-            * cost_2015_variables.s_cref[3]
-            * (cost_2015_variables.s_k[3] / cost_2015_variables.s_kref[3])
+        self.data.costs_2015.s_k[3] = heat_transport_variables.helpow / 1.0e3
+        self.data.costs_2015.s_kref[3] = 61.0e0
+        self.data.costs_2015.s_cost[3] = (
+            self.data.costs_2015.s_cost_factor[3]
+            * self.data.costs_2015.s_cref[3]
+            * (self.data.costs_2015.s_k[3] / self.data.costs_2015.s_kref[3])
         )
 
         # PF Coil winding building cost ($)
-        cost_2015_variables.s_label[4] = "PF Coil winding building"
-        cost_2015_variables.s_cref[4] = (
+        self.data.costs_2015.s_label[4] = "PF Coil winding building"
+        self.data.costs_2015.s_cref[4] = (
             190000.0e0 * cost_variables.light_build_cost_per_vol
         )
         # Scale with the radius of the largest PF coil squared (m^2)
-        cost_2015_variables.s_k[4] = pfcoil_variables.r_pf_coil_outer_max**2
-        cost_2015_variables.s_kref[4] = 12.4e0**2
-        cost_2015_variables.s_cost[4] = (
-            cost_2015_variables.s_cost_factor[4]
-            * cost_2015_variables.s_cref[4]
-            * (cost_2015_variables.s_k[4] / cost_2015_variables.s_kref[4])
+        self.data.costs_2015.s_k[4] = pfcoil_variables.r_pf_coil_outer_max**2
+        self.data.costs_2015.s_kref[4] = 12.4e0**2
+        self.data.costs_2015.s_cost[4] = (
+            self.data.costs_2015.s_cost_factor[4]
+            * self.data.costs_2015.s_cref[4]
+            * (self.data.costs_2015.s_k[4] / self.data.costs_2015.s_kref[4])
         )
 
         # Magnet power supplies and related buildings cost ($)
-        cost_2015_variables.s_label[5] = "Magnet power supplies and related buildings"
-        cost_2015_variables.s_cref[5] = (
+        self.data.costs_2015.s_label[5] = "Magnet power supplies and related buildings"
+        self.data.costs_2015.s_cref[5] = (
             110000.0e0 * cost_variables.light_build_cost_per_vol
         )
         # Scale with TF current per coil (MA)
-        cost_2015_variables.s_k[5] = (
+        self.data.costs_2015.s_k[5] = (
             tfcoil_variables.c_tf_total / tfcoil_variables.n_tf_coils
         ) / 1.0e6
-        cost_2015_variables.s_kref[5] = 9.1e0
-        cost_2015_variables.s_cost[5] = (
-            cost_2015_variables.s_cost_factor[5]
-            * cost_2015_variables.s_cref[5]
-            * (cost_2015_variables.s_k[5] / cost_2015_variables.s_kref[5])
+        self.data.costs_2015.s_kref[5] = 9.1e0
+        self.data.costs_2015.s_cost[5] = (
+            self.data.costs_2015.s_cost_factor[5]
+            * self.data.costs_2015.s_cref[5]
+            * (self.data.costs_2015.s_k[5] / self.data.costs_2015.s_kref[5])
         )
 
         # Magnet discharge buildings cost ($)
-        cost_2015_variables.s_label[6] = "Magnet discharge buildings"
-        cost_2015_variables.s_cref[6] = (
+        self.data.costs_2015.s_label[6] = "Magnet discharge buildings"
+        self.data.costs_2015.s_cref[6] = (
             35000.0e0 * cost_variables.light_build_cost_per_vol
         )
         # Scale with total stored energy in TF coils (GJ)
-        cost_2015_variables.s_k[6] = tfcoil_variables.e_tf_magnetic_stored_total_gj
-        cost_2015_variables.s_kref[6] = 41.0e0
-        cost_2015_variables.s_cost[6] = (
-            cost_2015_variables.s_cost_factor[6]
-            * cost_2015_variables.s_cref[6]
-            * (cost_2015_variables.s_k[6] / cost_2015_variables.s_kref[6])
+        self.data.costs_2015.s_k[6] = tfcoil_variables.e_tf_magnetic_stored_total_gj
+        self.data.costs_2015.s_kref[6] = 41.0e0
+        self.data.costs_2015.s_cost[6] = (
+            self.data.costs_2015.s_cost_factor[6]
+            * self.data.costs_2015.s_cref[6]
+            * (self.data.costs_2015.s_k[6] / self.data.costs_2015.s_kref[6])
         )
 
         # Heat removal system buildings cost ($)
-        cost_2015_variables.s_label[7] = "Heat removal system buildings"
+        self.data.costs_2015.s_label[7] = "Heat removal system buildings"
         # ITER volume of cooling water buildings (m^3)
-        cost_2015_variables.s_cref[7] = (
+        self.data.costs_2015.s_cref[7] = (
             51000.0e0 * cost_variables.light_build_cost_per_vol
         )
         # Scale with total thermal power removed from the core (MW)
-        cost_2015_variables.s_k[7] = (
+        self.data.costs_2015.s_k[7] = (
             heat_transport_variables.p_plant_primary_heat_mw
             + heat_transport_variables.p_plant_secondary_heat_mw
         )
-        cost_2015_variables.s_kref[7] = 880.0e0
-        cost_2015_variables.s_cost[7] = (
-            cost_2015_variables.s_cost_factor[7]
-            * cost_2015_variables.s_cref[7]
-            * (cost_2015_variables.s_k[7] / cost_2015_variables.s_kref[7])
+        self.data.costs_2015.s_kref[7] = 880.0e0
+        self.data.costs_2015.s_cost[7] = (
+            self.data.costs_2015.s_cost_factor[7]
+            * self.data.costs_2015.s_cref[7]
+            * (self.data.costs_2015.s_k[7] / self.data.costs_2015.s_kref[7])
         )
 
         # Total cost of buildings ($)
-        cost_2015_variables.s_label[8] = "Total cost of buildings"
-        cost_2015_variables.s_cost[8] = 0.0e0
+        self.data.costs_2015.s_label[8] = "Total cost of buildings"
+        self.data.costs_2015.s_cost[8] = 0.0e0
         for j in range(8):
-            cost_2015_variables.s_cost[8] = (
-                cost_2015_variables.s_cost[8] + cost_2015_variables.s_cost[j]
+            self.data.costs_2015.s_cost[8] = (
+                self.data.costs_2015.s_cost[8] + self.data.costs_2015.s_cost[j]
             )
 
     def calc_land_costs(self):
@@ -598,10 +599,10 @@ def calc_land_costs(self):
         PROCESS Costs Paper (M. Kovari, J. Morris)
         """
         for i in range(9, 13):
-            cost_2015_variables.s_cost_factor[i] = cost_variables.cost_factor_land
+            self.data.costs_2015.s_cost_factor[i] = cost_variables.cost_factor_land
 
         # Land purchasing cost ($)
-        cost_2015_variables.s_label[9] = "Land purchasing"
+        self.data.costs_2015.s_label[9] = "Land purchasing"
         # ITER Land area (hectares)
         ITER_total_land_area = 180.0e0
         # ITER Land area for key buildings (hectares)
@@ -610,59 +611,59 @@ def calc_land_costs(self):
         ITER_buffer_land_area = ITER_total_land_area - ITER_key_buildings_land_area
 
         # Scale with area of cryostat (m)
-        cost_2015_variables.s_k[9] = np.pi * fwbs_variables.r_cryostat_inboard**2
-        cost_2015_variables.s_kref[9] = 638.0e0
+        self.data.costs_2015.s_k[9] = np.pi * fwbs_variables.r_cryostat_inboard**2
+        self.data.costs_2015.s_kref[9] = 638.0e0
         # Cost of land per hectare (2014 $ / ha)
-        cost_2015_variables.s_cref[9] = 318000.0e0
+        self.data.costs_2015.s_cref[9] = 318000.0e0
         # Cost of power plant land (2014 $)
-        cost_2015_variables.s_cost[9] = (
-            cost_2015_variables.s_cost_factor[9]
-            * cost_2015_variables.s_cref[9]
+        self.data.costs_2015.s_cost[9] = (
+            self.data.costs_2015.s_cost_factor[9]
+            * self.data.costs_2015.s_cref[9]
             * (
                 ITER_key_buildings_land_area
-                * (cost_2015_variables.s_k[9] / cost_2015_variables.s_kref[9])
+                * (self.data.costs_2015.s_k[9] / self.data.costs_2015.s_kref[9])
                 ** cost_variables.costexp
                 + ITER_buffer_land_area
             )
         )
 
         # Land improvement costs ($)
-        cost_2015_variables.s_label[10] = "Land improvement"
+        self.data.costs_2015.s_label[10] = "Land improvement"
         # Cost of clearing ITER land
-        cost_2015_variables.s_cref[10] = 214.0e6
+        self.data.costs_2015.s_cref[10] = 214.0e6
         # Scale with area of cryostat (m)
-        cost_2015_variables.s_k[10] = np.pi * fwbs_variables.r_cryostat_inboard**2
-        cost_2015_variables.s_kref[10] = 638.0e0
-        cost_2015_variables.s_cost[10] = (
-            cost_2015_variables.s_cost_factor[10]
-            * (cost_2015_variables.s_k[10] / cost_2015_variables.s_kref[10])
+        self.data.costs_2015.s_k[10] = np.pi * fwbs_variables.r_cryostat_inboard**2
+        self.data.costs_2015.s_kref[10] = 638.0e0
+        self.data.costs_2015.s_cost[10] = (
+            self.data.costs_2015.s_cost_factor[10]
+            * (self.data.costs_2015.s_k[10] / self.data.costs_2015.s_kref[10])
             ** cost_variables.costexp
-            * cost_2015_variables.s_cref[10]
+            * self.data.costs_2015.s_cref[10]
         )
 
         # Road improvements cost ($)
-        cost_2015_variables.s_label[11] = "Road improvements"
+        self.data.costs_2015.s_label[11] = "Road improvements"
         # Cost of ITER road improvements
-        cost_2015_variables.s_cref[11] = 150.0e6
+        self.data.costs_2015.s_cref[11] = 150.0e6
         # Scale with TF coil longest dimension
-        cost_2015_variables.s_k[11] = (
+        self.data.costs_2015.s_k[11] = (
             max(build_variables.dh_tf_inner_bore, build_variables.dr_tf_inner_bore)
             + 2.0e0 * build_variables.dr_tf_inboard
         )
-        cost_2015_variables.s_kref[11] = 14.0e0
-        cost_2015_variables.s_cost[11] = (
-            cost_2015_variables.s_cost_factor[11]
-            * cost_2015_variables.s_cref[11]
-            * (cost_2015_variables.s_k[11] / cost_2015_variables.s_kref[11])
+        self.data.costs_2015.s_kref[11] = 14.0e0
+        self.data.costs_2015.s_cost[11] = (
+            self.data.costs_2015.s_cost_factor[11]
+            * self.data.costs_2015.s_cref[11]
+            * (self.data.costs_2015.s_k[11] / self.data.costs_2015.s_kref[11])
             ** cost_variables.costexp
         )
 
         # Total land costs ($)
-        cost_2015_variables.s_label[12] = "Total land costs"
-        cost_2015_variables.s_cost[12] = 0.0e0
+        self.data.costs_2015.s_label[12] = "Total land costs"
+        self.data.costs_2015.s_cost[12] = 0.0e0
         for j in range(9, 12):
-            cost_2015_variables.s_cost[12] = (
-                cost_2015_variables.s_cost[12] + cost_2015_variables.s_cost[j]
+            self.data.costs_2015.s_cost[12] = (
+                self.data.costs_2015.s_cost[12] + self.data.costs_2015.s_cost[j]
             )
 
     def calc_tf_coil_costs(self):
@@ -672,108 +673,108 @@ def calc_tf_coil_costs(self):
         PROCESS Costs Paper (M. Kovari, J. Morris)
         """
         for i in range(13, 20):
-            cost_2015_variables.s_cost_factor[i] = cost_variables.cost_factor_tf_coils
+            self.data.costs_2015.s_cost_factor[i] = cost_variables.cost_factor_tf_coils
 
         # TF coil insertion and welding costs ($)
-        cost_2015_variables.s_label[13] = "TF Coil insertion and welding"
+        self.data.costs_2015.s_label[13] = "TF Coil insertion and welding"
         # ITER coil insertion and welding cost (2014 $)
-        cost_2015_variables.s_cref[13] = 258.0e6
+        self.data.costs_2015.s_cref[13] = 258.0e6
         # Scale with total TF coil length (m)
-        cost_2015_variables.s_k[13] = (
+        self.data.costs_2015.s_k[13] = (
             tfcoil_variables.n_tf_coils * tfcoil_variables.len_tf_coil
         )
-        cost_2015_variables.s_kref[13] = 18.0e0 * 34.1e0
-        cost_2015_variables.s_cost[13] = (
-            cost_2015_variables.s_cost_factor[13]
-            * cost_2015_variables.s_cref[13]
-            * (cost_2015_variables.s_k[13] / cost_2015_variables.s_kref[13])
+        self.data.costs_2015.s_kref[13] = 18.0e0 * 34.1e0
+        self.data.costs_2015.s_cost[13] = (
+            self.data.costs_2015.s_cost_factor[13]
+            * self.data.costs_2015.s_cref[13]
+            * (self.data.costs_2015.s_k[13] / self.data.costs_2015.s_kref[13])
             ** cost_variables.costexp
         )
 
         # TF coil winding costs ($)
-        cost_2015_variables.s_label[15] = "TF coil winding"
+        self.data.costs_2015.s_label[15] = "TF coil winding"
         # ITER winding cost (2014 $)
-        cost_2015_variables.s_cref[15] = 414.0e6
+        self.data.costs_2015.s_cref[15] = 414.0e6
         # Scale with the total turn length (m)
-        cost_2015_variables.s_k[15] = (
+        self.data.costs_2015.s_k[15] = (
             tfcoil_variables.n_tf_coils
             * tfcoil_variables.len_tf_coil
             * tfcoil_variables.n_tf_coil_turns
         )
-        cost_2015_variables.s_kref[15] = 82249.0e0
-        cost_2015_variables.s_cost[15] = (
-            cost_2015_variables.s_cost_factor[15]
-            * cost_2015_variables.s_cref[15]
-            * (cost_2015_variables.s_k[15] / cost_2015_variables.s_kref[15])
+        self.data.costs_2015.s_kref[15] = 82249.0e0
+        self.data.costs_2015.s_cost[15] = (
+            self.data.costs_2015.s_cost_factor[15]
+            * self.data.costs_2015.s_cref[15]
+            * (self.data.costs_2015.s_k[15] / self.data.costs_2015.s_kref[15])
             ** cost_variables.costexp
         )
 
         # Copper stand cost for TF coil ($)
-        cost_2015_variables.s_label[16] = "Copper strand for TF coil"
+        self.data.costs_2015.s_label[16] = "Copper strand for TF coil"
         # ITER Chromium plated Cu strand for TF SC cost (2014 $)
-        cost_2015_variables.s_cref[16] = 21.0e6
+        self.data.costs_2015.s_cref[16] = 21.0e6
         # Scale with total copper mass (kg)
-        cost_2015_variables.s_k[16] = (
+        self.data.costs_2015.s_k[16] = (
             tfcoil_variables.m_tf_coil_copper * tfcoil_variables.n_tf_coils
         )
-        cost_2015_variables.s_kref[16] = 244.0e3
-        cost_2015_variables.s_cost[16] = (
-            cost_2015_variables.s_cost_factor[16]
-            * cost_2015_variables.s_cref[16]
-            * (cost_2015_variables.s_k[16] / cost_2015_variables.s_kref[16])
+        self.data.costs_2015.s_kref[16] = 244.0e3
+        self.data.costs_2015.s_cost[16] = (
+            self.data.costs_2015.s_cost_factor[16]
+            * self.data.costs_2015.s_cref[16]
+            * (self.data.costs_2015.s_k[16] / self.data.costs_2015.s_kref[16])
             ** cost_variables.costexp
         )
 
         # superconductor strand cost ($)
-        cost_2015_variables.s_label[17] = (
+        self.data.costs_2015.s_label[17] = (
             "Strands with Nb3Sn superconductor and copper stabiliser"
         )
         # ITER Nb3Sn SC strands cost (2014 $)
-        cost_2015_variables.s_cref[17] = 526.0e6
+        self.data.costs_2015.s_cref[17] = 526.0e6
         # Scale with the total mass of Nb3Sn (kg)
-        cost_2015_variables.s_k[17] = (
+        self.data.costs_2015.s_k[17] = (
             tfcoil_variables.m_tf_coil_superconductor * tfcoil_variables.n_tf_coils
         )
-        cost_2015_variables.s_kref[17] = 210.0e3
-        cost_2015_variables.s_cost[17] = (
-            cost_2015_variables.s_cost_factor[17]
-            * cost_2015_variables.s_cref[17]
-            * (cost_2015_variables.s_k[17] / cost_2015_variables.s_kref[17])
+        self.data.costs_2015.s_kref[17] = 210.0e3
+        self.data.costs_2015.s_cost[17] = (
+            self.data.costs_2015.s_cost_factor[17]
+            * self.data.costs_2015.s_cref[17]
+            * (self.data.costs_2015.s_k[17] / self.data.costs_2015.s_kref[17])
             ** cost_variables.costexp
         )
 
         # Superconductor testing cost ($)
-        cost_2015_variables.s_label[18] = "Testing of superconducting strands"
+        self.data.costs_2015.s_label[18] = "Testing of superconducting strands"
         # ITER Nb3Sn strand test costs (2014 $)
-        cost_2015_variables.s_cref[18] = 4.0e6
-        cost_2015_variables.s_cost[18] = (
-            cost_2015_variables.s_cost_factor[18] * cost_2015_variables.s_cref[18]
+        self.data.costs_2015.s_cref[18] = 4.0e6
+        self.data.costs_2015.s_cost[18] = (
+            self.data.costs_2015.s_cost_factor[18] * self.data.costs_2015.s_cref[18]
         )
 
         # Superconductor cabling and jacketing cost ($)
-        cost_2015_variables.s_label[19] = "Cabling and jacketing"
+        self.data.costs_2015.s_label[19] = "Cabling and jacketing"
         # ITER cabling and jacketing costs (2014 $)
-        cost_2015_variables.s_cref[19] = 81.0e6
+        self.data.costs_2015.s_cref[19] = 81.0e6
         # Scale with total turn length.
-        cost_2015_variables.s_k[19] = (
+        self.data.costs_2015.s_k[19] = (
             tfcoil_variables.n_tf_coils
             * tfcoil_variables.len_tf_coil
             * tfcoil_variables.n_tf_coil_turns
         )
-        cost_2015_variables.s_kref[19] = 82249.0e0
-        cost_2015_variables.s_cost[19] = (
-            cost_2015_variables.s_cost_factor[19]
-            * cost_2015_variables.s_cref[19]
-            * (cost_2015_variables.s_k[19] / cost_2015_variables.s_kref[19])
+        self.data.costs_2015.s_kref[19] = 82249.0e0
+        self.data.costs_2015.s_cost[19] = (
+            self.data.costs_2015.s_cost_factor[19]
+            * self.data.costs_2015.s_cref[19]
+            * (self.data.costs_2015.s_k[19] / self.data.costs_2015.s_kref[19])
             ** cost_variables.costexp
         )
 
         # Total TF coil costs ($)
-        cost_2015_variables.s_label[20] = "Total TF coil costs"
-        cost_2015_variables.s_cost[20] = 0.0e0
+        self.data.costs_2015.s_label[20] = "Total TF coil costs"
+        self.data.costs_2015.s_cost[20] = 0.0e0
         for j in range(13, 20):
-            cost_2015_variables.s_cost[20] = (
-                cost_2015_variables.s_cost[20] + cost_2015_variables.s_cost[j]
+            self.data.costs_2015.s_cost[20] = (
+                self.data.costs_2015.s_cost[20] + self.data.costs_2015.s_cost[j]
             )
 
     def calc_remote_handling_costs(self):
@@ -781,46 +782,46 @@ def calc_remote_handling_costs(self):
         PROCESS Costs Paper (M. Kovari, J. Morris)
         """
         for i in range(27, 31):
-            cost_2015_variables.s_cost_factor[i] = cost_variables.cost_factor_rh
+            self.data.costs_2015.s_cost_factor[i] = cost_variables.cost_factor_rh
 
         # K:\Power Plant Physics and Technology\Costs\Remote handling
         # From Sam Ha.
 
-        cost_2015_variables.s_label[27] = "Moveable equipment"
-        cost_2015_variables.s_cref[27] = 1.0e6 * (
+        self.data.costs_2015.s_label[27] = "Moveable equipment"
+        self.data.costs_2015.s_cref[27] = 1.0e6 * (
             139.0e0 * cost_variables.num_rh_systems + 410.0e0
         )
         #  Scale with total mass of armour, first wall and blanket (kg)
-        cost_2015_variables.s_kref[27] = 4.35e6
-        cost_2015_variables.s_k[27] = fwbs_variables.armour_fw_bl_mass
-        cost_2015_variables.s_cost[27] = (
-            cost_2015_variables.s_cost_factor[27]
-            * cost_2015_variables.s_cref[27]
-            * (cost_2015_variables.s_k[27] / cost_2015_variables.s_kref[27])
+        self.data.costs_2015.s_kref[27] = 4.35e6
+        self.data.costs_2015.s_k[27] = fwbs_variables.armour_fw_bl_mass
+        self.data.costs_2015.s_cost[27] = (
+            self.data.costs_2015.s_cost_factor[27]
+            * self.data.costs_2015.s_cref[27]
+            * (self.data.costs_2015.s_k[27] / self.data.costs_2015.s_kref[27])
             ** cost_variables.costexp
         )
 
-        cost_2015_variables.s_label[28] = (
+        self.data.costs_2015.s_label[28] = (
             "Active maintenance facility with fixed equipment"
         )
-        cost_2015_variables.s_cref[28] = 1.0e6 * (
+        self.data.costs_2015.s_cref[28] = 1.0e6 * (
             95.0e0 * cost_variables.num_rh_systems + 2562.0e0
         )
         #  Scale with total mass of armour, first wall and blanket (kg)
-        cost_2015_variables.s_kref[28] = 4.35e6
-        cost_2015_variables.s_k[28] = fwbs_variables.armour_fw_bl_mass
-        cost_2015_variables.s_cost[28] = (
-            cost_2015_variables.s_cost_factor[28]
-            * cost_2015_variables.s_cref[28]
-            * (cost_2015_variables.s_k[28] / cost_2015_variables.s_kref[28])
+        self.data.costs_2015.s_kref[28] = 4.35e6
+        self.data.costs_2015.s_k[28] = fwbs_variables.armour_fw_bl_mass
+        self.data.costs_2015.s_cost[28] = (
+            self.data.costs_2015.s_cost_factor[28]
+            * self.data.costs_2015.s_cref[28]
+            * (self.data.costs_2015.s_k[28] / self.data.costs_2015.s_kref[28])
             ** cost_variables.costexp
         )
 
         # s(30) is not in use
 
-        cost_2015_variables.s_label[30] = "Total remote handling costs"
-        cost_2015_variables.s_cost[30] = (
-            cost_2015_variables.s_cost[27] + cost_2015_variables.s_cost[28]
+        self.data.costs_2015.s_label[30] = "Total remote handling costs"
+        self.data.costs_2015.s_cost[30] = (
+            self.data.costs_2015.s_cost[27] + self.data.costs_2015.s_cost[28]
         )
 
     def calc_n_plant_and_vv_costs(self):
@@ -830,43 +831,45 @@ def calc_n_plant_and_vv_costs(self):
         PROCESS Costs Paper (M. Kovari, J. Morris)
         """
         for i in range(31, 34):
-            cost_2015_variables.s_cost_factor[i] = cost_variables.cost_factor_vv
+            self.data.costs_2015.s_cost_factor[i] = cost_variables.cost_factor_vv
 
         #  Vacuum vessel
-        cost_2015_variables.s_label[31] = "Vacuum vessel"
+        self.data.costs_2015.s_label[31] = "Vacuum vessel"
         #  ITER reference vacuum vessel cost (2014 $)
-        cost_2015_variables.s_cref[31] = 537.0e6
+        self.data.costs_2015.s_cref[31] = 537.0e6
         #  Scale with outermost midplane radius of vacuum vessel squared (m2)
-        cost_2015_variables.s_k[31] = (
+        self.data.costs_2015.s_k[31] = (
             build_variables.r_shld_outboard_outer + build_variables.dr_vv_outboard
         ) ** 2
-        cost_2015_variables.s_kref[31] = 94.09e0
-        cost_2015_variables.s_cost[31] = (
-            cost_2015_variables.s_cost_factor[31]
-            * cost_2015_variables.s_cref[31]
-            * (cost_2015_variables.s_k[31] / cost_2015_variables.s_kref[31])
+        self.data.costs_2015.s_kref[31] = 94.09e0
+        self.data.costs_2015.s_cost[31] = (
+            self.data.costs_2015.s_cost_factor[31]
+            * self.data.costs_2015.s_cref[31]
+            * (self.data.costs_2015.s_k[31] / self.data.costs_2015.s_kref[31])
             ** cost_variables.costexp
         )
 
         #  Nitrogen plant
-        cost_2015_variables.s_label[32] = "Liquid nitrogen plant"
+        self.data.costs_2015.s_label[32] = "Liquid nitrogen plant"
         #  ITER reference cost (2014 $)
-        cost_2015_variables.s_cref[32] = 86.0e6
+        self.data.costs_2015.s_cref[32] = 86.0e6
         #  Scale with 4.5K cryopower (W)
-        cost_2015_variables.s_k[32] = heat_transport_variables.helpow
-        cost_2015_variables.s_kref[32] = 50.0e3
-        cost_2015_variables.s_cost[32] = (
-            cost_2015_variables.s_cost_factor[32]
-            * cost_2015_variables.s_cref[32]
-            * (cost_2015_variables.s_k[32] / cost_2015_variables.s_kref[32])
+        self.data.costs_2015.s_k[32] = heat_transport_variables.helpow
+        self.data.costs_2015.s_kref[32] = 50.0e3
+        self.data.costs_2015.s_cost[32] = (
+            self.data.costs_2015.s_cost_factor[32]
+            * self.data.costs_2015.s_cref[32]
+            * (self.data.costs_2015.s_k[32] / self.data.costs_2015.s_kref[32])
             ** cost_variables.costexp
         )
 
-        cost_2015_variables.s_label[33] = "Total liquid nitrogen plant and vacuum vessel"
-        cost_2015_variables.s_cost[33] = 0.0e0
+        self.data.costs_2015.s_label[33] = (
+            "Total liquid nitrogen plant and vacuum vessel"
+        )
+        self.data.costs_2015.s_cost[33] = 0.0e0
         for j in range(31, 33):
-            cost_2015_variables.s_cost[33] = (
-                cost_2015_variables.s_cost[33] + cost_2015_variables.s_cost[j]
+            self.data.costs_2015.s_cost[33] = (
+                self.data.costs_2015.s_cost[33] + self.data.costs_2015.s_cost[j]
             )
 
     def calc_energy_conversion_system(self):
@@ -875,18 +878,18 @@ def calc_energy_conversion_system(self):
         for a fusion power plant based on the costings in the PROCESS costs paper.
         PROCESS Costs Paper (M. Kovari, J. Morris)
         """
-        cost_2015_variables.s_label[34] = "Energy conversion system"
+        self.data.costs_2015.s_label[34] = "Energy conversion system"
         #  Set cost factor for energy conversion system
-        cost_2015_variables.s_cost_factor[34] = cost_variables.cost_factor_bop
+        self.data.costs_2015.s_cost_factor[34] = cost_variables.cost_factor_bop
         #  Cost of reference energy conversion system (Rolls Royce)
-        cost_2015_variables.s_cref[34] = 511.0e6
+        self.data.costs_2015.s_cref[34] = 511.0e6
         #  Scale with gross electric power (MWe)
-        cost_2015_variables.s_k[34] = heat_transport_variables.p_plant_electric_gross_mw
-        cost_2015_variables.s_kref[34] = 692.0e0
-        cost_2015_variables.s_cost[34] = (
-            cost_2015_variables.s_cost_factor[34]
-            * cost_2015_variables.s_cref[34]
-            * (cost_2015_variables.s_k[34] / cost_2015_variables.s_kref[34])
+        self.data.costs_2015.s_k[34] = heat_transport_variables.p_plant_electric_gross_mw
+        self.data.costs_2015.s_kref[34] = 692.0e0
+        self.data.costs_2015.s_cost[34] = (
+            self.data.costs_2015.s_cost_factor[34]
+            * self.data.costs_2015.s_cref[34]
+            * (self.data.costs_2015.s_k[34] / self.data.costs_2015.s_kref[34])
             ** cost_variables.costexp
         )
 
@@ -897,124 +900,124 @@ def calc_remaining_subsystems(self):
         PROCESS Costs Paper (M. Kovari, J. Morris)
         """
         for i in range(35, 60):
-            cost_2015_variables.s_cost_factor[i] = cost_variables.cost_factor_misc
+            self.data.costs_2015.s_cost_factor[i] = cost_variables.cost_factor_misc
 
-        cost_2015_variables.s_label[35] = "CS and PF coils"
+        self.data.costs_2015.s_label[35] = "CS and PF coils"
         # #  Cost of ITER CS and PF magnets
-        cost_2015_variables.s_cref[35] = 1538.0e6
+        self.data.costs_2015.s_cref[35] = 1538.0e6
         #  Scale with sum of (A x turns x radius) of CS and all PF coils
-        cost_2015_variables.s_k[35] = pfcoil_variables.itr_sum
-        cost_2015_variables.s_kref[35] = 7.4e8
-        cost_2015_variables.s_cost[35] = (
-            cost_2015_variables.s_cost_factor[35]
-            * cost_2015_variables.s_cref[35]
-            * (cost_2015_variables.s_k[35] / cost_2015_variables.s_kref[35])
+        self.data.costs_2015.s_k[35] = pfcoil_variables.itr_sum
+        self.data.costs_2015.s_kref[35] = 7.4e8
+        self.data.costs_2015.s_cost[35] = (
+            self.data.costs_2015.s_cost_factor[35]
+            * self.data.costs_2015.s_cref[35]
+            * (self.data.costs_2015.s_k[35] / self.data.costs_2015.s_kref[35])
             ** cost_variables.costexp
         )
 
-        cost_2015_variables.s_label[36] = (
+        self.data.costs_2015.s_label[36] = (
             "Vacuum vessel in-wall shielding, ports and in-vessel coils"
         )
         #  Cost of ITER VV in-wall shielding, ports and in-vessel coils
-        cost_2015_variables.s_cref[36] = 211.0e6
+        self.data.costs_2015.s_cref[36] = 211.0e6
         #  Scale with vacuum vessel mass (kg)
-        cost_2015_variables.s_k[36] = fwbs_variables.m_vv
-        cost_2015_variables.s_kref[36] = 5.2360e6
-        cost_2015_variables.s_cost[36] = (
-            cost_2015_variables.s_cost_factor[36]
-            * cost_2015_variables.s_cref[36]
-            * (cost_2015_variables.s_k[36] / cost_2015_variables.s_kref[36])
+        self.data.costs_2015.s_k[36] = fwbs_variables.m_vv
+        self.data.costs_2015.s_kref[36] = 5.2360e6
+        self.data.costs_2015.s_cost[36] = (
+            self.data.costs_2015.s_cost_factor[36]
+            * self.data.costs_2015.s_cref[36]
+            * (self.data.costs_2015.s_k[36] / self.data.costs_2015.s_kref[36])
             ** cost_variables.costexp
         )
 
-        cost_2015_variables.s_label[37] = "Divertor"
+        self.data.costs_2015.s_label[37] = "Divertor"
         #  Cost of ITER divertor
-        cost_2015_variables.s_cref[37] = 381.0e6
+        self.data.costs_2015.s_cref[37] = 381.0e6
         #  Scale with max power to SOL (MW)
-        cost_2015_variables.s_k[37] = physics_variables.p_plasma_separatrix_mw
-        cost_2015_variables.s_kref[37] = 140.0e0
-        cost_2015_variables.s_cost[37] = (
-            cost_2015_variables.s_cost_factor[37]
-            * cost_2015_variables.s_cref[37]
-            * (cost_2015_variables.s_k[37] / cost_2015_variables.s_kref[37])
+        self.data.costs_2015.s_k[37] = physics_variables.p_plasma_separatrix_mw
+        self.data.costs_2015.s_kref[37] = 140.0e0
+        self.data.costs_2015.s_cost[37] = (
+            self.data.costs_2015.s_cost_factor[37]
+            * self.data.costs_2015.s_cref[37]
+            * (self.data.costs_2015.s_k[37] / self.data.costs_2015.s_kref[37])
             ** cost_variables.costexp
         )
 
-        cost_2015_variables.s_label[38] = "not used"
-        cost_2015_variables.s_label[39] = "not used"
+        self.data.costs_2015.s_label[38] = "not used"
+        self.data.costs_2015.s_label[39] = "not used"
 
-        cost_2015_variables.s_label[40] = (
+        self.data.costs_2015.s_label[40] = (
             "Ex-vessel neutral beam remote handling equipment"
         )
         #  Cost of ITER Ex-vessel NBI RH equipment
         # Increased to 90 Mdollar because of press release
-        cost_2015_variables.s_cref[40] = 90.0e6
+        self.data.costs_2015.s_cref[40] = 90.0e6
         #  Scale with total aux injected power (MW)
-        cost_2015_variables.s_k[40] = current_drive_variables.p_hcd_injected_total_mw
-        cost_2015_variables.s_kref[40] = 50.0e0
-        cost_2015_variables.s_cost[40] = (
-            cost_2015_variables.s_cost_factor[40]
-            * cost_2015_variables.s_cref[40]
-            * (cost_2015_variables.s_k[40] / cost_2015_variables.s_kref[40])
+        self.data.costs_2015.s_k[40] = current_drive_variables.p_hcd_injected_total_mw
+        self.data.costs_2015.s_kref[40] = 50.0e0
+        self.data.costs_2015.s_cost[40] = (
+            self.data.costs_2015.s_cost_factor[40]
+            * self.data.costs_2015.s_cref[40]
+            * (self.data.costs_2015.s_k[40] / self.data.costs_2015.s_kref[40])
             ** cost_variables.costexp
         )
 
-        cost_2015_variables.s_label[41] = "not used"
+        self.data.costs_2015.s_label[41] = "not used"
 
-        cost_2015_variables.s_label[42] = "Vacuum vessel pressure suppression system"
+        self.data.costs_2015.s_label[42] = "Vacuum vessel pressure suppression system"
         #  Cost of ITER Vacuum vessel pressure suppression system
-        cost_2015_variables.s_cref[42] = 40.0e6
+        self.data.costs_2015.s_cref[42] = 40.0e6
         #  Scale with total thermal power removed from fusion core (MW)
-        cost_2015_variables.s_k[42] = (
+        self.data.costs_2015.s_k[42] = (
             heat_transport_variables.p_plant_primary_heat_mw
             + heat_transport_variables.p_plant_secondary_heat_mw
         )
-        cost_2015_variables.s_kref[42] = 550.0e0
-        cost_2015_variables.s_cost[42] = (
-            cost_2015_variables.s_cost_factor[42]
-            * cost_2015_variables.s_cref[42]
-            * (cost_2015_variables.s_k[42] / cost_2015_variables.s_kref[42])
+        self.data.costs_2015.s_kref[42] = 550.0e0
+        self.data.costs_2015.s_cost[42] = (
+            self.data.costs_2015.s_cost_factor[42]
+            * self.data.costs_2015.s_cref[42]
+            * (self.data.costs_2015.s_k[42] / self.data.costs_2015.s_kref[42])
             ** cost_variables.costexp
         )
 
-        cost_2015_variables.s_label[43] = "Cryostat"
+        self.data.costs_2015.s_label[43] = "Cryostat"
         #  Cost of ITER cryostat
-        cost_2015_variables.s_cref[43] = 351.0e6
+        self.data.costs_2015.s_cref[43] = 351.0e6
         #  Scale with cryostat external volume (m3)
-        cost_2015_variables.s_k[43] = (
+        self.data.costs_2015.s_k[43] = (
             (np.pi * fwbs_variables.r_cryostat_inboard**2.0e0)
             * 2.0e0
             * fwbs_variables.z_cryostat_half_inside
         )
-        cost_2015_variables.s_kref[43] = 18700.0e0
-        cost_2015_variables.s_cost[43] = (
-            cost_2015_variables.s_cost_factor[43]
-            * cost_2015_variables.s_cref[43]
-            * (cost_2015_variables.s_k[43] / cost_2015_variables.s_kref[43])
+        self.data.costs_2015.s_kref[43] = 18700.0e0
+        self.data.costs_2015.s_cost[43] = (
+            self.data.costs_2015.s_cost_factor[43]
+            * self.data.costs_2015.s_cref[43]
+            * (self.data.costs_2015.s_k[43] / self.data.costs_2015.s_kref[43])
             ** cost_variables.costexp
         )
 
-        cost_2015_variables.s_label[44] = "Heat removal system"
+        self.data.costs_2015.s_label[44] = "Heat removal system"
         #  Cost of ITER cooling water system
-        cost_2015_variables.s_cref[44] = 724.0e6
+        self.data.costs_2015.s_cref[44] = 724.0e6
         #  Scale with total thermal power removed from fusion core (MW)
-        cost_2015_variables.s_k[44] = (
+        self.data.costs_2015.s_k[44] = (
             heat_transport_variables.p_plant_primary_heat_mw
             + heat_transport_variables.p_plant_secondary_heat_mw
         )
-        cost_2015_variables.s_kref[44] = 550.0e0
-        cost_2015_variables.s_cost[44] = (
-            cost_2015_variables.s_cost_factor[44]
-            * cost_2015_variables.s_cref[44]
-            * (cost_2015_variables.s_k[44] / cost_2015_variables.s_kref[44])
+        self.data.costs_2015.s_kref[44] = 550.0e0
+        self.data.costs_2015.s_cost[44] = (
+            self.data.costs_2015.s_cost_factor[44]
+            * self.data.costs_2015.s_cref[44]
+            * (self.data.costs_2015.s_k[44] / self.data.costs_2015.s_kref[44])
             ** cost_variables.costexp
         )
 
-        cost_2015_variables.s_label[45] = "Thermal shields"
+        self.data.costs_2015.s_label[45] = "Thermal shields"
         #  Cost of ITER thermal shields
-        cost_2015_variables.s_cref[45] = 126.0e6
+        self.data.costs_2015.s_cref[45] = 126.0e6
         #  Scale with cryostat surface area (m2)
-        cost_2015_variables.s_k[45] = (
+        self.data.costs_2015.s_k[45] = (
             2.0e0
             * np.pi
             * fwbs_variables.r_cryostat_inboard
@@ -1022,238 +1025,240 @@ def calc_remaining_subsystems(self):
             * fwbs_variables.z_cryostat_half_inside
             + 2 * (np.pi * fwbs_variables.r_cryostat_inboard**2)
         )
-        cost_2015_variables.s_kref[45] = 3902.0e0
-        cost_2015_variables.s_cost[45] = (
-            cost_2015_variables.s_cost_factor[45]
-            * cost_2015_variables.s_cref[45]
-            * (cost_2015_variables.s_k[45] / cost_2015_variables.s_kref[45])
+        self.data.costs_2015.s_kref[45] = 3902.0e0
+        self.data.costs_2015.s_cost[45] = (
+            self.data.costs_2015.s_cost_factor[45]
+            * self.data.costs_2015.s_cref[45]
+            * (self.data.costs_2015.s_k[45] / self.data.costs_2015.s_kref[45])
             ** cost_variables.costexp
         )
 
-        cost_2015_variables.s_label[46] = "Pellet injection system"
+        self.data.costs_2015.s_label[46] = "Pellet injection system"
         #  Cost of ITER pellet injector and pellet injection system
-        cost_2015_variables.s_cref[46] = 25.0e6
+        self.data.costs_2015.s_cref[46] = 25.0e6
         #  Scale with fusion power (MW)
-        cost_2015_variables.s_k[46] = physics_variables.p_fusion_total_mw
-        cost_2015_variables.s_kref[46] = 500.0e0
-        cost_2015_variables.s_cost[46] = (
-            cost_2015_variables.s_cost_factor[46]
-            * cost_2015_variables.s_cref[46]
-            * (cost_2015_variables.s_k[46] / cost_2015_variables.s_kref[46])
+        self.data.costs_2015.s_k[46] = physics_variables.p_fusion_total_mw
+        self.data.costs_2015.s_kref[46] = 500.0e0
+        self.data.costs_2015.s_cost[46] = (
+            self.data.costs_2015.s_cost_factor[46]
+            * self.data.costs_2015.s_cref[46]
+            * (self.data.costs_2015.s_k[46] / self.data.costs_2015.s_kref[46])
             ** cost_variables.costexp
         )
 
-        cost_2015_variables.s_label[47] = "Gas injection and wall conditioning system"
+        self.data.costs_2015.s_label[47] = "Gas injection and wall conditioning system"
         # #  Cost of ITER gas injection system, GDC, Gi valve boxes
-        cost_2015_variables.s_cref[47] = 32.0e6
+        self.data.costs_2015.s_cref[47] = 32.0e6
         #  Scale with fusion power (MW)
-        cost_2015_variables.s_k[47] = physics_variables.p_fusion_total_mw
-        cost_2015_variables.s_kref[47] = 500.0e0
-        cost_2015_variables.s_cost[47] = (
-            cost_2015_variables.s_cost_factor[47]
-            * cost_2015_variables.s_cref[47]
-            * (cost_2015_variables.s_k[47] / cost_2015_variables.s_kref[47])
+        self.data.costs_2015.s_k[47] = physics_variables.p_fusion_total_mw
+        self.data.costs_2015.s_kref[47] = 500.0e0
+        self.data.costs_2015.s_cost[47] = (
+            self.data.costs_2015.s_cost_factor[47]
+            * self.data.costs_2015.s_cref[47]
+            * (self.data.costs_2015.s_k[47] / self.data.costs_2015.s_kref[47])
             ** cost_variables.costexp
         )
 
-        cost_2015_variables.s_label[48] = "Vacuum pumping"
+        self.data.costs_2015.s_label[48] = "Vacuum pumping"
         #  Cost of ITER vacuum pumping
-        cost_2015_variables.s_cref[48] = 201.0e6
+        self.data.costs_2015.s_cref[48] = 201.0e6
         #  Scale with fusion power (MW)
-        cost_2015_variables.s_k[48] = physics_variables.p_fusion_total_mw
-        cost_2015_variables.s_kref[48] = 500.0e0
-        cost_2015_variables.s_cost[48] = (
-            cost_2015_variables.s_cost_factor[48]
-            * cost_2015_variables.s_cref[48]
-            * (cost_2015_variables.s_k[48] / cost_2015_variables.s_kref[48])
+        self.data.costs_2015.s_k[48] = physics_variables.p_fusion_total_mw
+        self.data.costs_2015.s_kref[48] = 500.0e0
+        self.data.costs_2015.s_cost[48] = (
+            self.data.costs_2015.s_cost_factor[48]
+            * self.data.costs_2015.s_cref[48]
+            * (self.data.costs_2015.s_k[48] / self.data.costs_2015.s_kref[48])
             ** cost_variables.costexp
         )
 
-        cost_2015_variables.s_label[49] = "Tritium plant"
+        self.data.costs_2015.s_label[49] = "Tritium plant"
         #  Cost of ITER tritium plant
-        cost_2015_variables.s_cref[49] = 226.0e6
+        self.data.costs_2015.s_cref[49] = 226.0e6
         #  Scale with fusion power (MW)
-        cost_2015_variables.s_k[49] = physics_variables.p_fusion_total_mw
-        cost_2015_variables.s_kref[49] = 500.0e0
-        cost_2015_variables.s_cost[49] = (
-            cost_2015_variables.s_cost_factor[49]
-            * cost_2015_variables.s_cref[49]
-            * (cost_2015_variables.s_k[49] / cost_2015_variables.s_kref[49])
+        self.data.costs_2015.s_k[49] = physics_variables.p_fusion_total_mw
+        self.data.costs_2015.s_kref[49] = 500.0e0
+        self.data.costs_2015.s_cost[49] = (
+            self.data.costs_2015.s_cost_factor[49]
+            * self.data.costs_2015.s_cref[49]
+            * (self.data.costs_2015.s_k[49] / self.data.costs_2015.s_kref[49])
             ** cost_variables.costexp
         )
 
-        cost_2015_variables.s_label[50] = "Cryoplant and distribution"
+        self.data.costs_2015.s_label[50] = "Cryoplant and distribution"
         #  Cost of ITER Cryoplant and distribution
-        cost_2015_variables.s_cref[50] = 397.0e6
+        self.data.costs_2015.s_cref[50] = 397.0e6
         #  Scale with heat removal at 4.5 K approx (W)
-        cost_2015_variables.s_k[50] = heat_transport_variables.helpow
-        cost_2015_variables.s_kref[50] = 50000.0e0
-        cost_2015_variables.s_cost[50] = (
-            cost_2015_variables.s_cost_factor[50]
-            * cost_2015_variables.s_cref[50]
-            * (cost_2015_variables.s_k[50] / cost_2015_variables.s_kref[50])
+        self.data.costs_2015.s_k[50] = heat_transport_variables.helpow
+        self.data.costs_2015.s_kref[50] = 50000.0e0
+        self.data.costs_2015.s_cost[50] = (
+            self.data.costs_2015.s_cost_factor[50]
+            * self.data.costs_2015.s_cref[50]
+            * (self.data.costs_2015.s_k[50] / self.data.costs_2015.s_kref[50])
             ** cost_variables.costexp
         )
 
-        cost_2015_variables.s_label[51] = "Electrical power supply and distribution"
+        self.data.costs_2015.s_label[51] = "Electrical power supply and distribution"
         #  Cost of ITER electrical power supply and distribution
-        cost_2015_variables.s_cref[51] = 1188.0e6
+        self.data.costs_2015.s_cref[51] = 1188.0e6
         #  Scale with total magnetic energy in the poloidal field / resistive diffusion time (W)
         #  For ITER value see
         #  K:\Power Plant Physics and Technology\PROCESS\PROCESS documentation papers\resistive diffusion time.xmcd or pdf
-        cost_2015_variables.s_k[51] = (
+        self.data.costs_2015.s_k[51] = (
             pf_power_variables.ensxpfm * 1.0e6 / physics_variables.t_plasma_res_diffusion
         )
-        cost_2015_variables.s_kref[51] = 8.0e9 / 953.0e0
-        cost_2015_variables.s_cost[51] = (
-            cost_2015_variables.s_cost_factor[51]
-            * cost_2015_variables.s_cref[51]
-            * (cost_2015_variables.s_k[51] / cost_2015_variables.s_kref[51])
+        self.data.costs_2015.s_kref[51] = 8.0e9 / 953.0e0
+        self.data.costs_2015.s_cost[51] = (
+            self.data.costs_2015.s_cost_factor[51]
+            * self.data.costs_2015.s_cref[51]
+            * (self.data.costs_2015.s_k[51] / self.data.costs_2015.s_kref[51])
             ** cost_variables.costexp
         )
 
-        cost_2015_variables.s_label[52] = "Neutral beam heating and current drive system"
+        self.data.costs_2015.s_label[52] = (
+            "Neutral beam heating and current drive system"
+        )
         #  Cost of ITER NB H and CD
-        cost_2015_variables.s_cref[52] = 814.0e6
+        self.data.costs_2015.s_cref[52] = 814.0e6
         #  Scale with total auxiliary injected power (MW)
-        cost_2015_variables.s_k[52] = current_drive_variables.p_hcd_injected_total_mw
-        cost_2015_variables.s_kref[52] = 50.0e0
-        cost_2015_variables.s_cost[52] = (
-            cost_2015_variables.s_cost_factor[52]
-            * cost_2015_variables.s_cref[52]
-            * (cost_2015_variables.s_k[52] / cost_2015_variables.s_kref[52])
+        self.data.costs_2015.s_k[52] = current_drive_variables.p_hcd_injected_total_mw
+        self.data.costs_2015.s_kref[52] = 50.0e0
+        self.data.costs_2015.s_cost[52] = (
+            self.data.costs_2015.s_cost_factor[52]
+            * self.data.costs_2015.s_cref[52]
+            * (self.data.costs_2015.s_k[52] / self.data.costs_2015.s_kref[52])
             ** cost_variables.costexp
         )
 
-        cost_2015_variables.s_label[53] = "Diagnostics systems"
+        self.data.costs_2015.s_label[53] = "Diagnostics systems"
         #  Cost of ITER diagnostic systems
-        cost_2015_variables.s_cref[53] = 640.0e6
+        self.data.costs_2015.s_cref[53] = 640.0e6
         # No scaling
-        cost_2015_variables.s_cost[53] = (
-            cost_2015_variables.s_cost_factor[53] * cost_2015_variables.s_cref[53]
+        self.data.costs_2015.s_cost[53] = (
+            self.data.costs_2015.s_cost_factor[53] * self.data.costs_2015.s_cref[53]
         )
 
-        cost_2015_variables.s_label[54] = "Radiological protection"
+        self.data.costs_2015.s_label[54] = "Radiological protection"
         #  Cost of ITER radiological protection
-        cost_2015_variables.s_cref[54] = 19.0e6
+        self.data.costs_2015.s_cref[54] = 19.0e6
         #  Scale with fusion power (MW)
-        cost_2015_variables.s_k[54] = physics_variables.p_fusion_total_mw
-        cost_2015_variables.s_kref[54] = 500.0e0
-        cost_2015_variables.s_cost[54] = (
-            cost_2015_variables.s_cost_factor[54]
-            * cost_2015_variables.s_cref[54]
-            * (cost_2015_variables.s_k[54] / cost_2015_variables.s_kref[54])
+        self.data.costs_2015.s_k[54] = physics_variables.p_fusion_total_mw
+        self.data.costs_2015.s_kref[54] = 500.0e0
+        self.data.costs_2015.s_cost[54] = (
+            self.data.costs_2015.s_cost_factor[54]
+            * self.data.costs_2015.s_cref[54]
+            * (self.data.costs_2015.s_k[54] / self.data.costs_2015.s_kref[54])
             ** cost_variables.costexp
         )
 
-        cost_2015_variables.s_label[55] = "Access control and security systems"
+        self.data.costs_2015.s_label[55] = "Access control and security systems"
         #  Cost of ITER access control and security systems
         #  Scale with area of cryostat (m2)
-        cost_2015_variables.s_k[55] = np.pi * fwbs_variables.r_cryostat_inboard**2
-        cost_2015_variables.s_kref[55] = 640.0e0
-        cost_2015_variables.s_cref[55] = 42.0e6
-        cost_2015_variables.s_cost[55] = (
-            cost_2015_variables.s_cost_factor[55]
-            * cost_2015_variables.s_cref[55]
-            * (cost_2015_variables.s_k[55] / cost_2015_variables.s_kref[55])
+        self.data.costs_2015.s_k[55] = np.pi * fwbs_variables.r_cryostat_inboard**2
+        self.data.costs_2015.s_kref[55] = 640.0e0
+        self.data.costs_2015.s_cref[55] = 42.0e6
+        self.data.costs_2015.s_cost[55] = (
+            self.data.costs_2015.s_cost_factor[55]
+            * self.data.costs_2015.s_cref[55]
+            * (self.data.costs_2015.s_k[55] / self.data.costs_2015.s_kref[55])
             ** cost_variables.costexp
         )
 
-        cost_2015_variables.s_label[56] = "Assembly"
+        self.data.costs_2015.s_label[56] = "Assembly"
         #  Cost of ITER assembly
-        cost_2015_variables.s_cref[56] = 732.0e6
+        self.data.costs_2015.s_cref[56] = 732.0e6
         #  Scale with total cost of reactor items (cryostat and everything inside it)
-        cost_2015_variables.s_k[56] = (
-            cost_2015_variables.s_cost[20]
-            + cost_2015_variables.s_cost[26]
-            + cost_2015_variables.s_cost[31]
-            + cost_2015_variables.s_cost[35]
-            + cost_2015_variables.s_cost[36]
-            + cost_2015_variables.s_cost[37]
-            + cost_2015_variables.s_cost[43]
-            + cost_2015_variables.s_cost[45]
-            + cost_2015_variables.s_cost[48]
-        )
-        cost_2015_variables.s_kref[56] = (
-            cost_2015_variables.s_cref[20]
-            + cost_2015_variables.s_cref[26]
-            + cost_2015_variables.s_cref[31]
-            + cost_2015_variables.s_cref[35]
-            + cost_2015_variables.s_cref[36]
-            + cost_2015_variables.s_cref[37]
-            + cost_2015_variables.s_cref[43]
-            + cost_2015_variables.s_cref[45]
-            + cost_2015_variables.s_cref[48]
-        )
-        cost_2015_variables.s_cost[56] = (
-            cost_2015_variables.s_cost_factor[56]
-            * cost_2015_variables.s_cref[56]
-            * (cost_2015_variables.s_k[56] / cost_2015_variables.s_kref[56])
-        )
-
-        cost_2015_variables.s_label[57] = "Control and communication"
+        self.data.costs_2015.s_k[56] = (
+            self.data.costs_2015.s_cost[20]
+            + self.data.costs_2015.s_cost[26]
+            + self.data.costs_2015.s_cost[31]
+            + self.data.costs_2015.s_cost[35]
+            + self.data.costs_2015.s_cost[36]
+            + self.data.costs_2015.s_cost[37]
+            + self.data.costs_2015.s_cost[43]
+            + self.data.costs_2015.s_cost[45]
+            + self.data.costs_2015.s_cost[48]
+        )
+        self.data.costs_2015.s_kref[56] = (
+            self.data.costs_2015.s_cref[20]
+            + self.data.costs_2015.s_cref[26]
+            + self.data.costs_2015.s_cref[31]
+            + self.data.costs_2015.s_cref[35]
+            + self.data.costs_2015.s_cref[36]
+            + self.data.costs_2015.s_cref[37]
+            + self.data.costs_2015.s_cref[43]
+            + self.data.costs_2015.s_cref[45]
+            + self.data.costs_2015.s_cref[48]
+        )
+        self.data.costs_2015.s_cost[56] = (
+            self.data.costs_2015.s_cost_factor[56]
+            * self.data.costs_2015.s_cref[56]
+            * (self.data.costs_2015.s_k[56] / self.data.costs_2015.s_kref[56])
+        )
+
+        self.data.costs_2015.s_label[57] = "Control and communication"
         #  Cost of ITER control and data access and communication
-        cost_2015_variables.s_cref[57] = 219.0e6
+        self.data.costs_2015.s_cref[57] = 219.0e6
         #  Scale with total cost of reactor items (cryostat and everythign inside it)
-        cost_2015_variables.s_k[57] = (
-            cost_2015_variables.s_cost[20]
-            + cost_2015_variables.s_cost[26]
-            + cost_2015_variables.s_cost[31]
-            + cost_2015_variables.s_cost[35]
-            + cost_2015_variables.s_cost[36]
-            + cost_2015_variables.s_cost[37]
-            + cost_2015_variables.s_cost[43]
-            + cost_2015_variables.s_cost[45]
-            + cost_2015_variables.s_cost[48]
-        )
-        cost_2015_variables.s_kref[57] = (
-            cost_2015_variables.s_cref[20]
-            + cost_2015_variables.s_cref[26]
-            + cost_2015_variables.s_cref[31]
-            + cost_2015_variables.s_cref[35]
-            + cost_2015_variables.s_cref[36]
-            + cost_2015_variables.s_cref[37]
-            + cost_2015_variables.s_cref[43]
-            + cost_2015_variables.s_cref[45]
-            + cost_2015_variables.s_cref[48]
-        )
-        cost_2015_variables.s_cost[57] = (
-            cost_2015_variables.s_cost_factor[57]
-            * cost_2015_variables.s_cref[57]
-            * (cost_2015_variables.s_k[57] / cost_2015_variables.s_kref[57])
+        self.data.costs_2015.s_k[57] = (
+            self.data.costs_2015.s_cost[20]
+            + self.data.costs_2015.s_cost[26]
+            + self.data.costs_2015.s_cost[31]
+            + self.data.costs_2015.s_cost[35]
+            + self.data.costs_2015.s_cost[36]
+            + self.data.costs_2015.s_cost[37]
+            + self.data.costs_2015.s_cost[43]
+            + self.data.costs_2015.s_cost[45]
+            + self.data.costs_2015.s_cost[48]
+        )
+        self.data.costs_2015.s_kref[57] = (
+            self.data.costs_2015.s_cref[20]
+            + self.data.costs_2015.s_cref[26]
+            + self.data.costs_2015.s_cref[31]
+            + self.data.costs_2015.s_cref[35]
+            + self.data.costs_2015.s_cref[36]
+            + self.data.costs_2015.s_cref[37]
+            + self.data.costs_2015.s_cref[43]
+            + self.data.costs_2015.s_cref[45]
+            + self.data.costs_2015.s_cref[48]
+        )
+        self.data.costs_2015.s_cost[57] = (
+            self.data.costs_2015.s_cost_factor[57]
+            * self.data.costs_2015.s_cref[57]
+            * (self.data.costs_2015.s_k[57] / self.data.costs_2015.s_kref[57])
             ** cost_variables.costexp
         )
 
-        cost_2015_variables.s_label[58] = "Additional project expenditure"
+        self.data.costs_2015.s_label[58] = "Additional project expenditure"
         #  Cost of ITER additional ITER IO expenditure
-        cost_2015_variables.s_cref[58] = 1624.0e6
-        cost_2015_variables.s_cost[58] = (
-            cost_2015_variables.s_cost_factor[58] * cost_2015_variables.s_cref[58]
+        self.data.costs_2015.s_cref[58] = 1624.0e6
+        self.data.costs_2015.s_cost[58] = (
+            self.data.costs_2015.s_cost_factor[58] * self.data.costs_2015.s_cref[58]
         )
 
         # Calculate miscellaneous costs
-        cost_2015_variables.s_label[59] = "Logistics"
-        cost_2015_variables.s_cref[59] = 129.0e6
+        self.data.costs_2015.s_label[59] = "Logistics"
+        self.data.costs_2015.s_cref[59] = 129.0e6
         #  Scale with cryostat external volume (m)
-        cost_2015_variables.s_k[59] = (
+        self.data.costs_2015.s_k[59] = (
             np.pi
             * fwbs_variables.r_cryostat_inboard**2
             * 2.0e0
             * fwbs_variables.z_cryostat_half_inside
         )
-        cost_2015_variables.s_kref[59] = 18700.0e0
-        cost_2015_variables.s_cost[59] = (
-            cost_2015_variables.s_cost_factor[59]
-            * cost_2015_variables.s_cref[59]
-            * (cost_2015_variables.s_k[59] / cost_2015_variables.s_kref[59])
+        self.data.costs_2015.s_kref[59] = 18700.0e0
+        self.data.costs_2015.s_cost[59] = (
+            self.data.costs_2015.s_cost_factor[59]
+            * self.data.costs_2015.s_cref[59]
+            * (self.data.costs_2015.s_k[59] / self.data.costs_2015.s_kref[59])
             ** cost_variables.costexp
         )
 
-        cost_2015_variables.s_label[60] = "Total remaining subsystem costs"
-        cost_2015_variables.s_cost[60] = 0.0e0
+        self.data.costs_2015.s_label[60] = "Total remaining subsystem costs"
+        self.data.costs_2015.s_cost[60] = 0.0e0
         for j in range(35, 60):
-            cost_2015_variables.s_cost[60] = (
-                cost_2015_variables.s_cost[60] + cost_2015_variables.s_cost[j]
+            self.data.costs_2015.s_cost[60] = (
+                self.data.costs_2015.s_cost[60] + self.data.costs_2015.s_cost[j]
             )
 
     def value_function(self, x):
diff --git a/tests/unit/test_costs_2015.py b/tests/unit/test_costs_2015.py
index 9f6c4aad5..033a05709 100644
--- a/tests/unit/test_costs_2015.py
+++ b/tests/unit/test_costs_2015.py
@@ -1,13 +1,12 @@
-"""Unit tests for costs_2015.f90."""
+"""Unit tests for costs_2015.py."""
 
-from typing import Any, NamedTuple
+from dataclasses import dataclass
 
 import numpy as np
 import pytest
 
 from process.data_structure import (
     build_variables,
-    cost_2015_variables,
     cost_variables,
     current_drive_variables,
     fwbs_variables,
@@ -17,65 +16,43 @@
     physics_variables,
     tfcoil_variables,
 )
-from process.models.costs.costs_2015 import Costs2015
 
 
 @pytest.fixture
-def costs2015():
+def costs2015(process_models):
     """Provides Costs2015 object for testing.
 
     :return costs2015: initialised costs2015 object
     :type costs2015: process.costs2015.Costs2015
     """
-    return Costs2015()
-
-
-class CalcBuildingCostsParam(NamedTuple):
-    pwpnb: Any = None
-
-    r_pf_coil_outer_max: Any = None
-
-    p_plant_primary_heat_mw: Any = None
-
-    p_plant_secondary_heat_mw: Any = None
-
-    helpow: Any = None
-
-    c_tf_total: Any = None
-
-    n_tf_coils: Any = None
-
-    e_tf_magnetic_stored_total_gj: Any = None
-
-    r_cryostat_inboard: Any = None
-
-    z_cryostat_half_inside: Any = None
-
-    cost_factor_buildings: Any = None
-
-    light_build_cost_per_vol: Any = None
-
-    tok_build_cost_per_vol: Any = None
-
-    s_kref: Any = None
-
-    s_k: Any = None
-
-    s_cref: Any = None
-
-    s_cost: Any = None
-
-    s_cost_factor: Any = None
-
-    expected_s_kref: Any = None
-
-    expected_s_k: Any = None
-
-    expected_s_cref: Any = None
-
-    expected_s_cost: Any = None
-
-    expected_s_cost_factor: Any = None
+    return process_models._costs_2015  # noqa: SLF001
+
+
+@dataclass
+class CalcBuildingCostsParam:
+    pwpnb: float
+    r_pf_coil_outer_max: float
+    p_plant_primary_heat_mw: float
+    p_plant_secondary_heat_mw: float
+    helpow: float
+    c_tf_total: float
+    n_tf_coils: float
+    e_tf_magnetic_stored_total_gj: float
+    r_cryostat_inboard: float
+    z_cryostat_half_inside: float
+    cost_factor_buildings: float
+    light_build_cost_per_vol: float
+    tok_build_cost_per_vol: float
+    s_kref: list[float]
+    s_k: list[float]
+    s_cref: list[float]
+    s_cost: list[float]
+    s_cost_factor: list[float]
+    expected_s_kref: list[float]
+    expected_s_k: list[float]
+    expected_s_cref: list[float]
+    expected_s_cost: list[float]
+    expected_s_cost_factor: list[float]
 
 
 @pytest.mark.parametrize(
@@ -2356,72 +2333,52 @@ def test_calc_building_costs(calcbuildingcostsparam, monkeypatch, costs2015):
         "tok_build_cost_per_vol",
         calcbuildingcostsparam.tok_build_cost_per_vol,
     )
-
-    monkeypatch.setattr(cost_2015_variables, "s_kref", calcbuildingcostsparam.s_kref)
-
-    monkeypatch.setattr(cost_2015_variables, "s_k", calcbuildingcostsparam.s_k)
-
-    monkeypatch.setattr(cost_2015_variables, "s_cref", calcbuildingcostsparam.s_cref)
-
-    monkeypatch.setattr(cost_2015_variables, "s_cost", calcbuildingcostsparam.s_cost)
-
-    monkeypatch.setattr(
-        cost_2015_variables, "s_cost_factor", calcbuildingcostsparam.s_cost_factor
-    )
+    for field in ["s_kref", "s_k", "s_cref", "s_cost", "s_cost_factor"]:
+        monkeypatch.setattr(
+            costs2015.data.costs_2015, field, getattr(calcbuildingcostsparam, field)
+        )
 
     costs2015.calc_building_costs()
 
-    assert cost_2015_variables.s_kref == pytest.approx(
+    assert costs2015.data.costs_2015.s_kref == pytest.approx(
         calcbuildingcostsparam.expected_s_kref
     )
 
-    assert cost_2015_variables.s_k == pytest.approx(calcbuildingcostsparam.expected_s_k)
+    assert costs2015.data.costs_2015.s_k == pytest.approx(
+        calcbuildingcostsparam.expected_s_k
+    )
 
-    assert cost_2015_variables.s_cref == pytest.approx(
+    assert costs2015.data.costs_2015.s_cref == pytest.approx(
         calcbuildingcostsparam.expected_s_cref
     )
 
-    assert cost_2015_variables.s_cost == pytest.approx(
+    assert costs2015.data.costs_2015.s_cost == pytest.approx(
         calcbuildingcostsparam.expected_s_cost
     )
 
-    assert cost_2015_variables.s_cost_factor == pytest.approx(
+    assert costs2015.data.costs_2015.s_cost_factor == pytest.approx(
         calcbuildingcostsparam.expected_s_cost_factor
     )
 
 
-class CalcLandCostsParam(NamedTuple):
-    dr_tf_inner_bore: Any = None
-
-    dh_tf_inner_bore: Any = None
-
-    dr_tf_inboard: Any = None
-
-    r_cryostat_inboard: Any = None
-
-    cost_factor_land: Any = None
-
-    costexp: Any = None
-
-    s_kref: Any = None
-
-    s_k: Any = None
-
-    s_cref: Any = None
-
-    s_cost: Any = None
-
-    s_cost_factor: Any = None
-
-    expected_s_kref: Any = None
-
-    expected_s_k: Any = None
-
-    expected_s_cref: Any = None
-
-    expected_s_cost: Any = None
-
-    expected_s_cost_factor: Any = None
+@dataclass
+class CalcLandCostsParam:
+    dr_tf_inner_bore: float
+    dh_tf_inner_bore: float
+    dr_tf_inboard: float
+    r_cryostat_inboard: float
+    cost_factor_land: float
+    costexp: float
+    s_kref: float
+    s_k: float
+    s_cref: float
+    s_cost: float
+    s_cost_factor: float
+    expected_s_kref: float
+    expected_s_k: float
+    expected_s_cref: float
+    expected_s_cost: float
+    expected_s_cost_factor: float
 
 
 @pytest.mark.parametrize(
@@ -4639,74 +4596,53 @@ def test_calc_land_costs(calclandcostsparam, monkeypatch, costs2015):
     )
 
     monkeypatch.setattr(cost_variables, "costexp", calclandcostsparam.costexp)
-
-    monkeypatch.setattr(cost_2015_variables, "s_kref", calclandcostsparam.s_kref)
-
-    monkeypatch.setattr(cost_2015_variables, "s_k", calclandcostsparam.s_k)
-
-    monkeypatch.setattr(cost_2015_variables, "s_cref", calclandcostsparam.s_cref)
-
-    monkeypatch.setattr(cost_2015_variables, "s_cost", calclandcostsparam.s_cost)
-
-    monkeypatch.setattr(
-        cost_2015_variables, "s_cost_factor", calclandcostsparam.s_cost_factor
-    )
+    for field in ["s_kref", "s_k", "s_cref", "s_cost", "s_cost_factor"]:
+        monkeypatch.setattr(
+            costs2015.data.costs_2015, field, getattr(calclandcostsparam, field)
+        )
 
     costs2015.calc_land_costs()
 
-    assert cost_2015_variables.s_kref == pytest.approx(
+    assert costs2015.data.costs_2015.s_kref == pytest.approx(
         calclandcostsparam.expected_s_kref
     )
 
-    assert cost_2015_variables.s_k == pytest.approx(calclandcostsparam.expected_s_k)
+    assert costs2015.data.costs_2015.s_k == pytest.approx(
+        calclandcostsparam.expected_s_k
+    )
 
-    assert cost_2015_variables.s_cref == pytest.approx(
+    assert costs2015.data.costs_2015.s_cref == pytest.approx(
         calclandcostsparam.expected_s_cref
     )
 
-    assert cost_2015_variables.s_cost == pytest.approx(
+    assert costs2015.data.costs_2015.s_cost == pytest.approx(
         calclandcostsparam.expected_s_cost
     )
 
-    assert cost_2015_variables.s_cost_factor == pytest.approx(
+    assert costs2015.data.costs_2015.s_cost_factor == pytest.approx(
         calclandcostsparam.expected_s_cost_factor
     )
 
 
-class CalcTfCoilCostsParam(NamedTuple):
-    n_tf_coils: Any = None
-
-    len_tf_coil: Any = None
-
-    n_tf_coil_turns: Any = None
-
-    m_tf_coil_copper: Any = None
-
-    m_tf_coil_superconductor: Any = None
-
-    cost_factor_tf_coils: Any = None
-
-    costexp: Any = None
-
-    s_kref: Any = None
-
-    s_k: Any = None
-
-    s_cref: Any = None
-
-    s_cost: Any = None
-
-    s_cost_factor: Any = None
-
-    expected_s_kref: Any = None
-
-    expected_s_k: Any = None
-
-    expected_s_cref: Any = None
-
-    expected_s_cost: Any = None
-
-    expected_s_cost_factor: Any = None
+@dataclass
+class CalcTfCoilCostsParam:
+    n_tf_coils: float
+    len_tf_coil: float
+    n_tf_coil_turns: float
+    m_tf_coil_copper: float
+    m_tf_coil_superconductor: float
+    cost_factor_tf_coils: float
+    costexp: float
+    s_kref: float
+    s_k: float
+    s_cref: float
+    s_cost: float
+    s_cost_factor: float
+    expected_s_kref: float
+    expected_s_k: float
+    expected_s_cref: float
+    expected_s_cost: float
+    expected_s_cost_factor: float
 
 
 @pytest.mark.parametrize(
@@ -6933,67 +6869,50 @@ def test_calc_tf_coil_costs(calctfcoilcostsparam, monkeypatch, costs2015):
 
     monkeypatch.setattr(cost_variables, "costexp", calctfcoilcostsparam.costexp)
 
-    monkeypatch.setattr(cost_2015_variables, "s_kref", calctfcoilcostsparam.s_kref)
-
-    monkeypatch.setattr(cost_2015_variables, "s_k", calctfcoilcostsparam.s_k)
-
-    monkeypatch.setattr(cost_2015_variables, "s_cref", calctfcoilcostsparam.s_cref)
-
-    monkeypatch.setattr(cost_2015_variables, "s_cost", calctfcoilcostsparam.s_cost)
-
-    monkeypatch.setattr(
-        cost_2015_variables, "s_cost_factor", calctfcoilcostsparam.s_cost_factor
-    )
+    for field in ["s_kref", "s_k", "s_cref", "s_cost", "s_cost_factor"]:
+        monkeypatch.setattr(
+            costs2015.data.costs_2015, field, getattr(calctfcoilcostsparam, field)
+        )
 
     costs2015.calc_tf_coil_costs()
 
-    assert cost_2015_variables.s_kref == pytest.approx(
+    assert costs2015.data.costs_2015.s_kref == pytest.approx(
         calctfcoilcostsparam.expected_s_kref
     )
 
-    assert cost_2015_variables.s_k == pytest.approx(calctfcoilcostsparam.expected_s_k)
+    assert costs2015.data.costs_2015.s_k == pytest.approx(
+        calctfcoilcostsparam.expected_s_k
+    )
 
-    assert cost_2015_variables.s_cref == pytest.approx(
+    assert costs2015.data.costs_2015.s_cref == pytest.approx(
         calctfcoilcostsparam.expected_s_cref
     )
 
-    assert cost_2015_variables.s_cost == pytest.approx(
+    assert costs2015.data.costs_2015.s_cost == pytest.approx(
         calctfcoilcostsparam.expected_s_cost
     )
 
-    assert cost_2015_variables.s_cost_factor == pytest.approx(
+    assert costs2015.data.costs_2015.s_cost_factor == pytest.approx(
         calctfcoilcostsparam.expected_s_cost_factor
     )
 
 
-class CalcRemoteHandlingCostsParam(NamedTuple):
-    armour_fw_bl_mass: Any = None
-
-    cost_factor_rh: Any = None
-
-    costexp: Any = None
-
-    num_rh_systems: Any = None
-
-    s_kref: Any = None
-
-    s_k: Any = None
-
-    s_cref: Any = None
-
-    s_cost: Any = None
-
-    s_cost_factor: Any = None
-
-    expected_s_kref: Any = None
-
-    expected_s_k: Any = None
-
-    expected_s_cref: Any = None
-
-    expected_s_cost: Any = None
-
-    expected_s_cost_factor: Any = None
+@dataclass
+class CalcRemoteHandlingCostsParam:
+    armour_fw_bl_mass: float
+    cost_factor_rh: float
+    costexp: float
+    num_rh_systems: float
+    s_kref: float
+    s_k: float
+    s_cref: float
+    s_cost: float
+    s_cost_factor: float
+    expected_s_kref: float
+    expected_s_k: float
+    expected_s_cref: float
+    expected_s_cost: float
+    expected_s_cost_factor: float
 
 
 @pytest.mark.parametrize(
@@ -9203,78 +9122,53 @@ def test_calc_remote_handling_costs(
     monkeypatch.setattr(
         cost_variables, "num_rh_systems", calcremotehandlingcostsparam.num_rh_systems
     )
-
-    monkeypatch.setattr(
-        cost_2015_variables, "s_kref", calcremotehandlingcostsparam.s_kref
-    )
-
-    monkeypatch.setattr(cost_2015_variables, "s_k", calcremotehandlingcostsparam.s_k)
-
-    monkeypatch.setattr(
-        cost_2015_variables, "s_cref", calcremotehandlingcostsparam.s_cref
-    )
-
-    monkeypatch.setattr(
-        cost_2015_variables, "s_cost", calcremotehandlingcostsparam.s_cost
-    )
-
-    monkeypatch.setattr(
-        cost_2015_variables, "s_cost_factor", calcremotehandlingcostsparam.s_cost_factor
-    )
+    for field in ["s_kref", "s_k", "s_cref", "s_cost", "s_cost_factor"]:
+        monkeypatch.setattr(
+            costs2015.data.costs_2015,
+            field,
+            getattr(calcremotehandlingcostsparam, field),
+        )
 
     costs2015.calc_remote_handling_costs()
 
-    assert cost_2015_variables.s_kref == pytest.approx(
+    assert costs2015.data.costs_2015.s_kref == pytest.approx(
         calcremotehandlingcostsparam.expected_s_kref
     )
 
-    assert cost_2015_variables.s_k == pytest.approx(
+    assert costs2015.data.costs_2015.s_k == pytest.approx(
         calcremotehandlingcostsparam.expected_s_k
     )
 
-    assert cost_2015_variables.s_cref == pytest.approx(
+    assert costs2015.data.costs_2015.s_cref == pytest.approx(
         calcremotehandlingcostsparam.expected_s_cref
     )
 
-    assert cost_2015_variables.s_cost == pytest.approx(
+    assert costs2015.data.costs_2015.s_cost == pytest.approx(
         calcremotehandlingcostsparam.expected_s_cost
     )
 
-    assert cost_2015_variables.s_cost_factor == pytest.approx(
+    assert costs2015.data.costs_2015.s_cost_factor == pytest.approx(
         calcremotehandlingcostsparam.expected_s_cost_factor
     )
 
 
-class CalcNPlantAndVvCostsParam(NamedTuple):
-    r_shld_outboard_outer: Any = None
-
-    dr_vv_outboard: Any = None
-
-    helpow: Any = None
-
-    cost_factor_vv: Any = None
-
-    costexp: Any = None
-
-    s_kref: Any = None
-
-    s_k: Any = None
-
-    s_cref: Any = None
-
-    s_cost: Any = None
-
-    s_cost_factor: Any = None
-
-    expected_s_kref: Any = None
-
-    expected_s_k: Any = None
-
-    expected_s_cref: Any = None
-
-    expected_s_cost: Any = None
-
-    expected_s_cost_factor: Any = None
+@dataclass
+class CalcNPlantAndVvCostsParam:
+    r_shld_outboard_outer: float
+    dr_vv_outboard: float
+    helpow: float
+    cost_factor_vv: float
+    costexp: float
+    s_kref: float
+    s_k: float
+    s_cref: float
+    s_cost: float
+    s_cost_factor: float
+    expected_s_kref: float
+    expected_s_k: float
+    expected_s_cref: float
+    expected_s_cost: float
+    expected_s_cost_factor: float
 
 
 @pytest.mark.parametrize(
@@ -11489,67 +11383,51 @@ def test_calc_n_plant_and_vv_costs(calcnplantandvvcostsparam, monkeypatch, costs
 
     monkeypatch.setattr(cost_variables, "costexp", calcnplantandvvcostsparam.costexp)
 
-    monkeypatch.setattr(cost_2015_variables, "s_kref", calcnplantandvvcostsparam.s_kref)
-
-    monkeypatch.setattr(cost_2015_variables, "s_k", calcnplantandvvcostsparam.s_k)
-
-    monkeypatch.setattr(cost_2015_variables, "s_cref", calcnplantandvvcostsparam.s_cref)
-
-    monkeypatch.setattr(cost_2015_variables, "s_cost", calcnplantandvvcostsparam.s_cost)
-
-    monkeypatch.setattr(
-        cost_2015_variables, "s_cost_factor", calcnplantandvvcostsparam.s_cost_factor
-    )
+    for field in ["s_kref", "s_k", "s_cref", "s_cost", "s_cost_factor"]:
+        monkeypatch.setattr(
+            costs2015.data.costs_2015,
+            field,
+            getattr(calcnplantandvvcostsparam, field),
+        )
 
     costs2015.calc_n_plant_and_vv_costs()
 
-    assert cost_2015_variables.s_kref == pytest.approx(
+    assert costs2015.data.costs_2015.s_kref == pytest.approx(
         calcnplantandvvcostsparam.expected_s_kref
     )
 
-    assert cost_2015_variables.s_k == pytest.approx(
+    assert costs2015.data.costs_2015.s_k == pytest.approx(
         calcnplantandvvcostsparam.expected_s_k
     )
 
-    assert cost_2015_variables.s_cref == pytest.approx(
+    assert costs2015.data.costs_2015.s_cref == pytest.approx(
         calcnplantandvvcostsparam.expected_s_cref
     )
 
-    assert cost_2015_variables.s_cost == pytest.approx(
+    assert costs2015.data.costs_2015.s_cost == pytest.approx(
         calcnplantandvvcostsparam.expected_s_cost
     )
 
-    assert cost_2015_variables.s_cost_factor == pytest.approx(
+    assert costs2015.data.costs_2015.s_cost_factor == pytest.approx(
         calcnplantandvvcostsparam.expected_s_cost_factor
     )
 
 
-class CalcEnergyConversionSystemParam(NamedTuple):
-    p_plant_electric_gross_mw: Any = None
-
-    cost_factor_bop: Any = None
-
-    costexp: Any = None
-
-    s_kref: Any = None
-
-    s_k: Any = None
-
-    s_cref: Any = None
-
-    s_cost: Any = None
-
-    s_cost_factor: Any = None
-
-    expected_s_kref: Any = None
-
-    expected_s_k: Any = None
-
-    expected_s_cref: Any = None
-
-    expected_s_cost: Any = None
-
-    expected_s_cost_factor: Any = None
+@dataclass
+class CalcEnergyConversionSystemParam:
+    p_plant_electric_gross_mw: float
+    cost_factor_bop: float
+    costexp: float
+    s_kref: float
+    s_k: float
+    s_cref: float
+    s_cost: float
+    s_cost_factor: float
+    expected_s_kref: float
+    expected_s_k: float
+    expected_s_cref: float
+    expected_s_cost: float
+    expected_s_cost_factor: float
 
 
 @pytest.mark.parametrize(
@@ -13757,98 +13635,62 @@ def test_calc_energy_conversion_system(
     monkeypatch.setattr(
         cost_variables, "costexp", calcenergyconversionsystemparam.costexp
     )
-
-    monkeypatch.setattr(
-        cost_2015_variables, "s_kref", calcenergyconversionsystemparam.s_kref
-    )
-
-    monkeypatch.setattr(cost_2015_variables, "s_k", calcenergyconversionsystemparam.s_k)
-
-    monkeypatch.setattr(
-        cost_2015_variables, "s_cref", calcenergyconversionsystemparam.s_cref
-    )
-
-    monkeypatch.setattr(
-        cost_2015_variables, "s_cost", calcenergyconversionsystemparam.s_cost
-    )
-
-    monkeypatch.setattr(
-        cost_2015_variables,
-        "s_cost_factor",
-        calcenergyconversionsystemparam.s_cost_factor,
-    )
+    for field in ["s_kref", "s_k", "s_cref", "s_cost", "s_cost_factor"]:
+        monkeypatch.setattr(
+            costs2015.data.costs_2015,
+            field,
+            getattr(calcenergyconversionsystemparam, field),
+        )
 
     costs2015.calc_energy_conversion_system()
 
-    assert cost_2015_variables.s_kref == pytest.approx(
+    assert costs2015.data.costs_2015.s_kref == pytest.approx(
         calcenergyconversionsystemparam.expected_s_kref
     )
 
-    assert cost_2015_variables.s_k == pytest.approx(
+    assert costs2015.data.costs_2015.s_k == pytest.approx(
         calcenergyconversionsystemparam.expected_s_k
     )
 
-    assert cost_2015_variables.s_cref == pytest.approx(
+    assert costs2015.data.costs_2015.s_cref == pytest.approx(
         calcenergyconversionsystemparam.expected_s_cref
     )
 
-    assert cost_2015_variables.s_cost == pytest.approx(
+    assert costs2015.data.costs_2015.s_cost == pytest.approx(
         calcenergyconversionsystemparam.expected_s_cost
     )
 
-    assert cost_2015_variables.s_cost_factor == pytest.approx(
+    assert costs2015.data.costs_2015.s_cost_factor == pytest.approx(
         calcenergyconversionsystemparam.expected_s_cost_factor
     )
 
 
-class CalcRemainingSubsystemsParam(NamedTuple):
-    p_hcd_injected_total_mw: Any = None
-
-    p_plasma_separatrix_mw: Any = None
-
-    p_fusion_total_mw: Any = None
-
-    t_plasma_res_diffusion: Any = None
-
-    itr_sum: Any = None
-
-    ensxpfm: Any = None
-
-    p_plant_primary_heat_mw: Any = None
-
-    p_plant_secondary_heat_mw: Any = None
-
-    helpow: Any = None
-
-    m_vv: Any = None
-
-    r_cryostat_inboard: Any = None
-
-    z_cryostat_half_inside: Any = None
-
-    cost_factor_misc: Any = None
-
-    costexp: Any = None
-
-    s_kref: Any = None
-
-    s_k: Any = None
-
-    s_cref: Any = None
-
-    s_cost: Any = None
-
-    s_cost_factor: Any = None
-
-    expected_s_kref: Any = None
-
-    expected_s_k: Any = None
-
-    expected_s_cref: Any = None
-
-    expected_s_cost: Any = None
-
-    expected_s_cost_factor: Any = None
+@dataclass
+class CalcRemainingSubsystemsParam:
+    p_hcd_injected_total_mw: float
+    p_plasma_separatrix_mw: float
+    p_fusion_total_mw: float
+    t_plasma_res_diffusion: float
+    itr_sum: float
+    ensxpfm: float
+    p_plant_primary_heat_mw: float
+    p_plant_secondary_heat_mw: float
+    helpow: float
+    m_vv: float
+    r_cryostat_inboard: float
+    z_cryostat_half_inside: float
+    cost_factor_misc: float
+    costexp: float
+    s_kref: float
+    s_k: float
+    s_cref: float
+    s_cost: float
+    s_cost_factor: float
+    expected_s_kref: float
+    expected_s_k: float
+    expected_s_cref: float
+    expected_s_cost: float
+    expected_s_cost_factor: float
 
 
 @pytest.mark.parametrize(
@@ -16133,51 +15975,40 @@ def test_calc_remaining_subsystems(calcremainingsubsystemsparam, monkeypatch, co
 
     monkeypatch.setattr(cost_variables, "costexp", calcremainingsubsystemsparam.costexp)
 
-    monkeypatch.setattr(
-        cost_2015_variables, "s_kref", calcremainingsubsystemsparam.s_kref
-    )
-
-    monkeypatch.setattr(cost_2015_variables, "s_k", calcremainingsubsystemsparam.s_k)
-
-    monkeypatch.setattr(
-        cost_2015_variables, "s_cref", calcremainingsubsystemsparam.s_cref
-    )
-
-    monkeypatch.setattr(
-        cost_2015_variables, "s_cost", calcremainingsubsystemsparam.s_cost
-    )
-
-    monkeypatch.setattr(
-        cost_2015_variables, "s_cost_factor", calcremainingsubsystemsparam.s_cost_factor
-    )
+    for field in ["s_kref", "s_k", "s_cref", "s_cost", "s_cost_factor"]:
+        monkeypatch.setattr(
+            costs2015.data.costs_2015,
+            field,
+            getattr(calcremainingsubsystemsparam, field),
+        )
 
     costs2015.calc_remaining_subsystems()
 
-    assert cost_2015_variables.s_kref == pytest.approx(
+    assert costs2015.data.costs_2015.s_kref == pytest.approx(
         calcremainingsubsystemsparam.expected_s_kref
     )
 
-    assert cost_2015_variables.s_k == pytest.approx(
+    assert costs2015.data.costs_2015.s_k == pytest.approx(
         calcremainingsubsystemsparam.expected_s_k
     )
 
-    assert cost_2015_variables.s_cref == pytest.approx(
+    assert costs2015.data.costs_2015.s_cref == pytest.approx(
         calcremainingsubsystemsparam.expected_s_cref
     )
 
-    assert cost_2015_variables.s_cost == pytest.approx(
+    assert costs2015.data.costs_2015.s_cost == pytest.approx(
         calcremainingsubsystemsparam.expected_s_cost
     )
 
-    assert cost_2015_variables.s_cost_factor == pytest.approx(
+    assert costs2015.data.costs_2015.s_cost_factor == pytest.approx(
         calcremainingsubsystemsparam.expected_s_cost_factor
     )
 
 
-class ValueFunctionParam(NamedTuple):
-    x: Any = None
-
-    expected_v: Any = None
+@dataclass
+class ValueFunctionParam:
+    x: float
+    expected_v: float
 
 
 @pytest.mark.parametrize(