diff --git a/src/Cases.py b/src/Cases.py
index b36e193f..0984d4da 100644
--- a/src/Cases.py
+++ b/src/Cases.py
@@ -546,8 +546,8 @@ def _specs_optimizer(cls):
     bayesian_opt.addSub(acquisitionSub)
 
     #======== Kernel for BO========#
-    seedSub = InputData.parameterInputFactory('initialSeed', contentType=InputTypes.IntegerType,
-                                                descr=r"""The initial seed for random number generator used
+    seedSub = InputData.parameterInputFactory('seed', contentType=InputTypes.IntegerType,
+                                                descr=r"""The seed for random number generator used
                                                 for sampling the model within the Bayesian Optimizer.""",
                                                 default='RAVEN-determined')
     bayesian_opt.addSub(seedSub)
@@ -593,9 +593,6 @@ def _specs_optimizer(cls):
                                                        and number of trajectories for Gradient Descent.""")
     optimizer.addSub(initialCountSub)
 
-
-    # optimizer.addSub(modelSelection)
-
     #== Convergence Sub Node ==#
     convergence = InputData.parameterInputFactory('convergence',
                                                   descr=r"""defines the optimization convergence criteria.""")
diff --git a/templates/template_driver.py b/templates/template_driver.py
index fe42d92d..3e4e7a9a 100644
--- a/templates/template_driver.py
+++ b/templates/template_driver.py
@@ -761,8 +761,8 @@ def _modify_outer_optimizers(self, template, case):
           model_node.find('Duration').text = str(model_settings['duration'])
           model_node.find('Method').text = model_settings['method']
         # setting initial seed if requested
-        if BOsettings and 'initialSeed' in BOsettings.keys():
-          seed_node = xmlUtils.newNode('initialSeed', text=BOsettings['initialSeed'])
+        if BOsettings and 'seed' in BOsettings.keys():
+          seed_node = xmlUtils.newNode('initialSeed', text=BOsettings['seed'])
           opt_node.find(".//samplerInit").append(seed_node)
       elif strategy == 'GradientDescent':
         GDsettings = optimization_settings['algorithm'][strategy]
diff --git a/tests/integration_tests/mechanics/optimization_settings/heron_input.xml b/tests/integration_tests/mechanics/optimization_settings/heron_input.xml
index f75f7e60..0116058e 100644
--- a/tests/integration_tests/mechanics/optimization_settings/heron_input.xml
+++ b/tests/integration_tests/mechanics/optimization_settings/heron_input.xml
@@ -35,7 +35,7 @@
       <algorithm>
         <BayesianOpt>
           <acquisition>LowerConfidenceBound</acquisition>
-          <initialSeed>180</initialSeed>
+          <seed>180</seed>
         </BayesianOpt>
       </algorithm>
       <opt_metric>NPV</opt_metric>