How to use the gpkit.constraints.sigeq.SignomialEquality function in gpkit

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convexengineering / SPaircraft / stand_alone_TASOPT_profile.py View on Github

C_1 = Variable('C_1', 1.458E-6, "kg/(m*s*K^0.5)",
                       'Sutherland coefficient')

        with SignomialsEnabled():
            constraints = [
                # Pressure-altitude relation
                (p_atm/p_sl)**(1/5.257) == T_atm/T_sl,

                # Ideal gas law
                rho == p_atm/(R_atm/M_atm*T_atm),

                #temperature equation
                SignomialEquality(T_sl, T_atm + L_atm*alt['h']),

                #constraint on mu
                SignomialEquality((T_atm + T_s) * mu, C_1 * T_atm**1.5),
##                TCS([(T_atm + T_s) * mu >= C_1 * T_atm**1.5])
                ]

        #like to use a local subs here in the future
        subs = None

        return constraints

convexengineering / SPaircraft / VT_simple_profile.py View on Github

C_1 = Variable('C_1', 1.458E-6, "kg/(m*s*K^0.5)",
                       'Sutherland coefficient')

        with SignomialsEnabled():
            constraints = [
                # Pressure-altitude relation
                (p_atm/p_sl)**(1/5.257) == T_atm/T_sl,

                # Ideal gas law
                rho == p_atm/(R_atm/M_atm*T_atm),

                #temperature equation
                SignomialEquality(T_sl, T_atm + L_atm*alt['h']),

                #constraint on mu
                SignomialEquality((T_atm + T_s) * mu, C_1 * T_atm**1.5),
                ]

        #like to use a local subs here in the future
        substitutions = None

        Model.__init__(self, None, constraints, substitutions)

convexengineering / SPaircraft / basic_HT.py View on Github

TCS([W_start &gt;= wing['W_{wing}']+ ht['W_{HT}'] + W_payload + W_fuel]),
                    TCS([W_end &gt;= wing['W_{wing}']+ ht['W_{HT}'] + W_payload]),
                    W_avg == (W_start*W_end)**.5,
                    TCS([wingP['L'] &gt;= W_avg + htP['L_{h}']]),

                    #lift coefficient constraints
                    wingP['C_{L}'] == 2*pi*alpha,
##                    htP['C_{L_{h}}'] &lt;= 2.2*pi*alpha,
##                    htP['C_{L_{h}}'] &gt;= 1.8*pi*alpha,

                    #arbitrary, sturctural model will remove the need for this constraint
                    ht['b_{h}'] &lt;= .33*wing['b_{max}'],

                    #HT sizing constraints
                    #compute mrat, is a signomial equality
                    SignomialEquality(ht['m_{ratio}']*(1+2/wing['AR']), 1 + 2/ht['ARh']),

                    #tail volume coefficient
                    ht['V_{h}'] == ht['Sh']*ht['l_{h}']/(wing['S']*wing['MAC']),

                    #enforce max tail location is the end of the fuselage
                    ht['l_{h}'] &lt;= fuse['l_{fuse}'],

                    #Stability constraint, is a signomial
##                    TCS([ht['SM_{min}'] + ht['\\Delta x_{CG}']/wing['MAC'] &lt;= ht['V_{h}']*ht['m_{ratio}'] + wingP['c_{m_{w}}']/wing['C_{L_{max}}'] + ht['V_{h}']*ht['CL_{h_{max}}']/wing['C_{L_{max}}']]),
                    SignomialEquality(ht['SM_{min}'] + ht['\\Delta x_{CG}']/wing['MAC'], ht['V_{h}']*ht['m_{ratio}'] + wingP['c_{m_{w}}']/wing['C_{L_{max}}'] + ht['V_{h}']*ht['CL_{h_{max}}']/wing['C_{L_{max}}']),

                    # Trim condidtion for each flight segment
##                    TCS([wingP['x_{ac}']/wing['MAC'] &lt;= wingP['c_{m_{w}}']/wingP['C_{L}'] + xcg/wing['MAC'] + ht['V_{h}']*(htP['C_{L_{h}}']/wingP['C_{L}'])]),
                    SignomialEquality(wingP['x_{ac}']/wing['MAC'], wingP['c_{m_{w}}']/wingP['C_{L}'] + xcg/wing['MAC'] + ht['V_{h}']*(htP['C_{L_{h}}']/wingP['C_{L}'])),

                    xcg == 15*units('m'),

convexengineering / SPaircraft / engine_flight_profile_integration.py View on Github

C_1 = Variable('C_1', 1.458E-6, "kg/(m*s*K^0.5)",
                       'Sutherland coefficient')

        with SignomialsEnabled():
            constraints = [
                # Pressure-altitude relation
                (p_atm/p_sl)**(1/5.257) == T_atm/T_sl,

                # Ideal gas law
                rho == p_atm/(R_atm/M_atm*T_atm),

                #temperature equation
                SignomialEquality(T_sl, T_atm + L_atm*alt['h']),

                #constraint on mu
                SignomialEquality((T_atm + T_s) * mu, C_1 * T_atm**1.5),
                ]

        #like to use a local subs here in the future
        subs = None

        return constraints

convexengineering / SPaircraft / new_d8_wing_imports.py View on Github

mu  = Variable('\\mu', 'kg/(m*s)', 'Dynamic viscosity')

        T_s = Variable('T_s', 110.4, "K", "Sutherland Temperature")
        C_1 = Variable('C_1', 1.458E-6, "kg/(m*s*K^0.5)",
                       'Sutherland coefficient')

        with SignomialsEnabled():
            constraints = [
                # Pressure-altitude relation
                (p_atm/p_sl)**(1/5.257) == T_atm/T_sl,

                # Ideal gas law
                rho == p_atm/(R_atm/M_atm*T_atm),

                #temperature equation
                SignomialEquality(T_sl, T_atm + L_atm*alt['h']),

                #constraint on mu
                SignomialEquality((T_atm + T_s) * mu, C_1 * T_atm**1.5),
                ]

        return constraints

convexengineering / SPaircraft / TASOPT_VT_yaw_rate_and_EO_simple_profile.py View on Github

#engine out CL computation

                Avt == bvt**2/Svt,
                          
                Svt &lt;= bvt*(croot + ctip)/2, # [SP]
                # Tail geometry relationship

                # TCS([dxtrail &gt;= croot + dxlead]),
                # Tail geometry constraint

                # Fuselage length constrains the tail trailing edge
                TCS([p &gt;= 1 + 2*taper]),
                TCS([2*q &gt;= 1 + p]),
                zmac == (bvt/3)*q/p,
##                TCS([(2./3)*(1 + taper + taper**2)*croot/q &gt;= cma]), # [SP]
                SignomialEquality((2./3)*(1 + taper + taper**2)*croot/q, cma),
                taper == ctip/croot,
                # Define vertical tail geometry

                Lvmax == 0.5*rho0*Vne**2*Svt*CLvmax,
                #compute the max force

                # TODO: Constrain taper by tip Reynolds number
                taper &gt;= 0.25,
                
                #Enforce a minimum vertical tail volume
                Vvt &gt;= Vvtmin,
                ])

        return constraints

convexengineering / SPaircraft / VT_yaw_rate_and_EO_simple_profile.py View on Github

mu  = Variable('\\mu', 'kg/(m*s)', 'Dynamic viscosity')

        T_s = Variable('T_s', 110.4, "K", "Sutherland Temperature")
        C_1 = Variable('C_1', 1.458E-6, "kg/(m*s*K^0.5)",
                       'Sutherland coefficient')

        with SignomialsEnabled():
            constraints = [
                # Pressure-altitude relation
                (p_atm/p_sl)**(1/5.257) == T_atm/T_sl,

                # Ideal gas law
                rho == p_atm/(R_atm/M_atm*T_atm),

                #temperature equation
                SignomialEquality(T_sl, T_atm + L_atm*alt['h']),

                #constraint on mu
                SignomialEquality((T_atm + T_s) * mu, C_1 * T_atm**1.5),
                ]

        #like to use a local subs here in the future
        substitutions = None

        Model.__init__(self, None, constraints, substitutions)

convexengineering / SPaircraft / VT_simple_profile.py View on Github

mu  = Variable('\\mu', 'kg/(m*s)', 'Dynamic viscosity')

        T_s = Variable('T_s', 110.4, "K", "Sutherland Temperature")
        C_1 = Variable('C_1', 1.458E-6, "kg/(m*s*K^0.5)",
                       'Sutherland coefficient')

        with SignomialsEnabled():
            constraints = [
                # Pressure-altitude relation
                (p_atm/p_sl)**(1/5.257) == T_atm/T_sl,

                # Ideal gas law
                rho == p_atm/(R_atm/M_atm*T_atm),

                #temperature equation
                SignomialEquality(T_sl, T_atm + L_atm*alt['h']),

                #constraint on mu
                SignomialEquality((T_atm + T_s) * mu, C_1 * T_atm**1.5),
                ]

        #like to use a local subs here in the future
        substitutions = None

        Model.__init__(self, None, constraints, substitutions)

convexengineering / SPaircraft / VT_simple_profile_int.py View on Github

mu  = Variable('\\mu', 'kg/(m*s)', 'Dynamic viscosity')

        T_s = Variable('T_s', 110.4, "K", "Sutherland Temperature")
        C_1 = Variable('C_1', 1.458E-6, "kg/(m*s*K^0.5)",
                       'Sutherland coefficient')

        with SignomialsEnabled():
            constraints = [
                # Pressure-altitude relation
                (p_atm/p_sl)**(1/5.257) == T_atm/T_sl,

                # Ideal gas law
                rho == p_atm/(R_atm/M_atm*T_atm),

                #temperature equation
                SignomialEquality(T_sl, T_atm + L_atm*alt['h']),

                #constraint on mu
                SignomialEquality((T_atm + T_s) * mu, C_1 * T_atm**1.5),
                ]

        #like to use a local subs here in the future
        substitutions = None

        Model.__init__(self, None, constraints, substitutions)

convexengineering / SPaircraft / new_d8_wing_imports.py View on Github

TCS([Dwing &gt;= (.5*wing['S']*state.atm['\\rho']*state['V']**2)*(Cdw + wing['K']*CL**2)]),

                Re == state['\\rho']*state['V']*wing['mac']/state['\\mu'],
                1 &gt;= (2.56*CL**5.88/(Re**1.54*wing['\\tau']**3.32*Cdw**2.62)
                   + 3.8e-9*wing['\\tau']**6.23/(CL**0.92*Re**1.38*Cdw*9.57)
                   + 2.2e-3*Re**0.14*wing['\\tau']**0.033/(CL**0.01*Cdw**0.73)
                   + 6.14e-6*CL**6.53/(Re**0.99*wing['\\tau']**0.52*Cdw*5.19)
                   + 1.19e4*CL**9.78*wing['\\tau']**1.76/(Re*Cdw**0.91)),

            CL == CLaw*alpha,
            alpha &lt;= wing['\\alpha_{max,w}'],
            ])

        with SignomialsEnabled():
            constraints.extend([
               SignomialEquality((wing['AR']/wing['\\eta'])**2*(1 + wing['\\tan(\\Lambda)']**2 - state['M']**2) + 8*pi*wing['AR']/CLaw
                  , (2*pi*wing['AR']/CLaw)**2),
                ])

        return constraints

How to use the gpkit.constraints.sigeq.SignomialEquality function in gpkit

To help you get started, we’ve selected a few gpkit examples, based on popular ways it is used in public projects.

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