diff --git a/LArCalorimeter/LArConfiguration/python/LArConfigFlags.py b/LArCalorimeter/LArConfiguration/python/LArConfigFlags.py
index 99ef6334f38a6e168a1f049c5043333f1dce8382..44a2844c33fa83385a4a235affc29d942d7bb6dc 100644
--- a/LArCalorimeter/LArConfiguration/python/LArConfigFlags.py
+++ b/LArCalorimeter/LArConfiguration/python/LArConfigFlags.py
@@ -34,12 +34,23 @@ def createLArConfigFlags():
     lcf.addFlag("LAr.ForceIOVRunNumber", "")
     # Include Shape folder
     lcf.addFlag("LAr.UseShape", True)
-    # Number of samples in LAr digitization + ROD emulation
-    lcf.addFlag("LAr.RODnSamples", 5)
-    # Index of first sample in LAr digitization + ROD emulation
-    lcf.addFlag("LAr.RODFirstSample", 0)
     # DataBase server string
     lcf.addFlag("LAr.DBConnection", "")
+
+    # Number of samples in LAr digitization + ROD emulation
+    lcf.addFlag("LAr.ROD.nSamples", 5)
+    # Index of first sample in LAr digitization + ROD emulation
+    lcf.addFlag("LAr.ROD.FirstSample", 0)
+    # Force using the highest gain autocorrelation function
+    # when doing OFC optimization
+    lcf.addFlag("LAr.ROD.UseHighestGainAutoCorr", False)
+    # Flag not to use pileup noise neither average constrain in EMB and EMEC-OW,
+    # and both pileup noise and average constrain everywhere else
+    lcf.addFlag("LAr.ROD.DoOFCMixedOptimization", False)
+    ### option to use average constraint in OFC computation
+    ### 0 = not use Delta, 1 = only EMECIW/HEC/FCAL, 2 = all , 3 = only EMECIW
+    lcf.addFlag("LAr.ROD.UseDelta", 0)
+     
     return lcf
 
 
diff --git a/LArCalorimeter/LArDigitization/python/LArDigitizationConfigNew.py b/LArCalorimeter/LArDigitization/python/LArDigitizationConfigNew.py
index 88ff15126780f8982cf285f3104e967c28aeae07..f9519090b127ee194d57fac846f8cc27084117b9 100644
--- a/LArCalorimeter/LArDigitization/python/LArDigitizationConfigNew.py
+++ b/LArCalorimeter/LArDigitization/python/LArDigitizationConfigNew.py
@@ -106,8 +106,8 @@ def LArPileUpToolCfg(flags, name="LArPileUpTool", **kwargs):
     # if doing MC+MC overlay
     if flags.Input.isMC and flags.Detector.OverlayLAr:
           kwargs.setdefault("isMcOverlay", True)
-    kwargs.setdefault("Nsamples", flags.LAr.RODnSamples)
-    kwargs.setdefault("firstSample", flags.LAr.RODFirstSample)
+    kwargs.setdefault("Nsamples", flags.LAr.ROD.nSamples)
+    kwargs.setdefault("firstSample", flags.LAr.ROD.FirstSample)
     if flags.Detector.OverlayLAr:
         kwargs.setdefault("RandomDigitContainer", "LArDigitContainer_MC")
     # cosmics digitization
diff --git a/LArCalorimeter/LArRecUtils/python/LArRecUtilsConfig.py b/LArCalorimeter/LArRecUtils/python/LArRecUtilsConfig.py
index 2fc85d314a7dc660f3ef73f3dbf9fa2a69598a2f..f4355193b9b422263fad37e6359bcc507c93c6cf 100644
--- a/LArCalorimeter/LArRecUtils/python/LArRecUtilsConfig.py
+++ b/LArCalorimeter/LArRecUtils/python/LArRecUtilsConfig.py
@@ -40,7 +40,7 @@ def LArAutoCorrNoiseCondAlgCfg(flags, name="LArAutoCorrNoiseCondAlg", **kwargs):
     """Return ComponentAccumulator with configured LArAutoCorrNoiseCondAlg"""
     acc = LArOnOffIdMappingCfg(flags)
     acc.merge(LArMCSymCondAlgCfg(flags))
-    kwargs.setdefault("nSampl", flags.LAr.RODnSamples)
+    kwargs.setdefault("nSampl", flags.LAr.ROD.nSamples)
     acc.addCondAlgo(LArAutoCorrNoiseCondAlg(name, **kwargs))
     return acc