diff --git a/electrolyzer/cell.py b/electrolyzer/cell.py
index 8836cac..fa5ad06 100644
--- a/electrolyzer/cell.py
+++ b/electrolyzer/cell.py
@@ -239,6 +239,8 @@ def calc_mass_flow_rate(self, Idc, dryer_loss=6.5):
         """
         eta_F = self.calc_faradaic_efficiency(Idc)
         mfr = eta_F * Idc * self.M / (self.n * F) * (1 - dryer_loss / 100.0)  # [g/s]
+
+        # mfr=eta_F*(Idc/self.cell_area)*self.M/(self.n*F)*(1-dryer_loss/100.0) # [g/s]
         # mfr = mfr / 1000. * 3600. # [kg/h]
         mfr = mfr / 1e3  # [kg/s]
         return mfr
diff --git a/electrolyzer/glue_code/run_lcoh.py b/electrolyzer/glue_code/run_lcoh.py
index fde474a..45a9e70 100644
--- a/electrolyzer/glue_code/run_lcoh.py
+++ b/electrolyzer/glue_code/run_lcoh.py
@@ -174,6 +174,6 @@ def run_lcoh(input_modeling, power_signal, lcoe, optimize=False):
     lcoh_dict, lcoh = _run_lcoh_full(cost_sys)
 
     if optimize:
-        return [np.sum(kg_produced), max_curr_density, lcoh]
+        return [np.sum(kg_produced), max_curr_density, lcoh, lcoh_dict, lcoh_options]
 
     return lcoh_dict, lcoh
diff --git a/electrolyzer/lcoh.py b/electrolyzer/lcoh.py
index bff89a3..008cc07 100644
--- a/electrolyzer/lcoh.py
+++ b/electrolyzer/lcoh.py
@@ -143,13 +143,17 @@ def calc_pem_capex(self):
         b_capex = np.log2(1 - lr)
         Sr0 = self.capex["ref_size_pem"]  # ref size [kW]
         Cr0 = self.capex["ref_cost_pem"]  # ref cost [$/kW]
-        # self.plant_rating_kW
-        Sr = (self.stack_rating_kW / Sr0) ** b_capex  # scale sized
+
+        if self.plant_rating_kW <= Sr0:
+            Sr = 1
+        else:
+            Sr = (self.plant_rating_kW / Sr0) ** b_capex  # scale sized
+
         adj_IF = 1 + self.IF * self.os
         Cr_uninstalled = Cr0 * Sr  # [$/kW]
         Cr_installed = adj_IF * Cr0 * Sr  # [$/kW]
-        capex_pem_dollars_installed = Cr_installed * self.stack_rating_kW
-        capex_pem_dollars_uninstalled = Cr_uninstalled * self.stack_rating_kW
+        capex_pem_dollars_installed = Cr_installed * self.plant_rating_kW
+        capex_pem_dollars_uninstalled = Cr_uninstalled * self.plant_rating_kW
         self.capex_summary["PEM"] = {
             "Uninstalled [$/kW]": Cr_uninstalled,
             "Installed [$/kW]": Cr_installed,
@@ -164,12 +168,17 @@ def calc_bop_capex(self):
         b_capex = np.log2(1 - lr)
         Sr0 = self.capex["ref_size_bop"]
         Cr0 = self.capex["ref_cost_bop"]
-        Sr = (self.stack_rating_kW / Sr0) ** b_capex  # scale sized
+
+        if self.plant_rating_kW <= Sr0:
+            Sr = 1
+        else:
+            Sr = (self.plant_rating_kW / Sr0) ** b_capex  # scale sized
+
         adj_IF = 1 + self.IF * self.os
         Cr_uninstalled = Cr0 * Sr  # [$/kW]
         Cr_installed = adj_IF * Cr0 * Sr  # [$/kW]
-        capex_bop_dollars_installed = Cr_installed * self.stack_rating_kW
-        capex_bop_dollars_uninstalled = Cr_uninstalled * self.stack_rating_kW
+        capex_bop_dollars_installed = Cr_installed * self.plant_rating_kW
+        capex_bop_dollars_uninstalled = Cr_uninstalled * self.plant_rating_kW
         self.capex_summary["BOP"] = {
             "Uninstalled [$/kW]": Cr_uninstalled,
             "Installed [$/kW]": Cr_installed,
@@ -187,7 +196,7 @@ def calc_total_capex(self):
 
         # pem_capex = self.calc_pem_capex(self.plant_rating_kW)
         # bop_capex = self.calc_bop_capex(self.plant_rating_kW)
-        sizeup_factor = self.plant_rating_kW / self.stack_rating_kW
+        sizeup_factor = self.plant_rating_kW / self.plant_rating_kW
         pem_capex = sizeup_factor * self.calc_pem_capex()
         bop_capex = sizeup_factor * self.calc_bop_capex()
         total_capex = pem_capex + bop_capex
diff --git a/tests/glue_code/test_run_lcoh.py b/tests/glue_code/test_run_lcoh.py
index 2599f5d..3375474 100644
--- a/tests/glue_code/test_run_lcoh.py
+++ b/tests/glue_code/test_run_lcoh.py
@@ -3,6 +3,7 @@
 
 import numpy as np
 import pandas as pd
+from pytest import approx
 from numpy.testing import assert_array_almost_equal
 from pandas.testing import assert_frame_equal
 
@@ -11,18 +12,23 @@
 
 lcoh_breakdown = pd.DataFrame(
     {
-        "Life Totals [$]": [5.388657e06, 1.079412e06, 1.1978406e07, 1.292115e06],
+        "Life Totals [$]": [
+            3644933.857141541,
+            1.079412e06,
+            1.1978406e07,
+            873998.0388080929,
+        ],
         "Life Totals [$/kg-H2]": [
-            1.3594040320184078,
-            0.2723048458021954,
-            3.021946178528131,
-            0.32378362036676683,
+            0.9355497543594925,
+            0.2770541303907053,
+            3.074512588406419,
+            0.22433017513212933,
         ],
     },
     index=["CapEx", "OM", "Feedstock", "Stack Rep"],
 )
 
-RESULT = (lcoh_breakdown, 5.066329157584628)
+RESULT = (lcoh_breakdown, 4.511446648288746)
 ROOT = Path(__file__).parent.parent.parent
 
 
@@ -51,7 +57,7 @@ def test_run_lcoh():
         atol=1e-1,
     )
 
-    assert np.isclose(calc_result[1], RESULT[1])
+    assert calc_result[1] == approx(RESULT[1])
 
 
 def test_run_lcoh_opt():
@@ -73,9 +79,9 @@ def test_run_lcoh_opt():
     lcoh_result = run_lcoh(fname_input_modeling, power_test_signal, lcoe, optimize=True)
 
     # h2 prod, max curr density, LCOH
-    assert len(lcoh_result) == 3
+    assert len(lcoh_result) == 5
 
     # results from regular optimize run should match
     assert_array_almost_equal(h2_result, lcoh_result[:2])
 
-    assert np.isclose(lcoh_result[2], 5.0099777502488525)
+    assert lcoh_result[2] == approx(4.4616439830304415)