anchor.diff:        else
            denom = eta_e*c_nalpha_circ*( alpha-alpha0 )*tan(alpha)
         endif
  -      Get_f_c_from_Lookup =  min(fc_limit, (  Cc / denom  + Gonzales_factor ) **2 )
  +      Get_f_c_from_Lookup =  min(fc_limit, (  Cc / denom  + Gonzalez_factor ) **2 )
                     
      end if
  -      ! Apply an offset of 0.2 to fix cases where f_c should be negative, but we are using **2 so can only return positive values
  +      ! Apply an offset of Gonzalez_factor = 0.2 to fix cases where f_c should be negative, but we are using **2 so can only return positive values
         ! Note: because we include this offset, it must be accounted for in the final value of Cc, eqn 1.40.  This will be applied
         ! For both UA_Mod = 1,2, and 3 when using Flookup = T
      
  
positive.code:    integer(intki), parameter :: UA_Gonzalez      = 2   ! UAMod = 2 [Gonzalez's variant (changes in Cn,Cc,Cm)]
     integer(intki), parameter :: UA_MinemmaPierce = 3   ! UAMod = 3 [Minemma/Pierce variant (changes in Cc and Cm)]
     
     real(ReKi),     parameter :: Gonzales_factor = 0.2_ReKi   ! this factor, proposed by Gonzales (for "all" models) is used to modify Cc to account for negative values seen at f=0 (see Eqn 1.40)
     
     contains
     
  
negative.code:    
      
     if ( p%UAMod == UA_Gonzalez ) then
        KC%Cn_FS   = KC%Cn_alpha_q_nc + KC%Cn_q_circ + KC%Cn_alpha_q_circ *  ( (1.0_ReKi + 2.0_ReKi*sqrt(KC%fprimeprime) ) / 3.0_ReKi )**2     ! Eqn 1.39 [bjj: note that KC%Cn_alpha_q_circ doesn't match the equation 1.39 for the Gonzalez model]
     else
        KC%Cn_FS   = KC%Cn_alpha_q_nc + KC%Cn_alpha_q_circ *  ( (1.0_ReKi +          sqrt(KC%fprimeprime) ) / 2.0_ReKi )**2     ! Eqn 1.38   
     end if
  