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myCobyla= class=Cobyla class=OptimizationAlgorithmImplementation problem=class=OptimizationProblem implementation=class=OptimizationProblemImplementation objective=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[] evaluationImplementation=class=NoEvaluation name=Unnamed gradientImplementation=class=NoGradient name=Unnamed hessianImplementation=class=NoHessian name=Unnamed equality constraint=none inequality constraint=none bounds=none minimization=true dimension=0 startingPoint=class=Point name=Unnamed dimension=0 values=[] maximumIterationNumber=100 maximumCallsNumber=400 maximumAbsoluteError=1e-10 maximumRelativeError=1e-10 maximumResidualError=1e-10 maximumConstraintError=1e-10 rhoBeg=0.1
Analytical= class=Analytical nearestPointAlgorithm=class=OptimizationAlgorithm implementation=class=Cobyla class=OptimizationAlgorithmImplementation problem=class=OptimizationProblem implementation=class=OptimizationProblemImplementation objective=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[] evaluationImplementation=class=NoEvaluation name=Unnamed gradientImplementation=class=NoGradient name=Unnamed hessianImplementation=class=NoHessian name=Unnamed equality constraint=none inequality constraint=none bounds=none minimization=true dimension=0 startingPoint=class=Point name=Unnamed dimension=4 values=[50,1,10,5] maximumIterationNumber=100 maximumCallsNumber=400 maximumAbsoluteError=1e-10 maximumRelativeError=1e-10 maximumResidualError=1e-10 maximumConstraintError=1e-10 rhoBeg=0.1 event=class=RandomVector implementation=class=ThresholdEventImplementation antecedent=class=CompositeRandomVector function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[E,F,L,I,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[E,F,L,I] outputVariablesNames=[y0] formulas=[-F*L^3/(3*E*I)] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[E,F,L,I] outputVariablesNames=[y0] formulas=[-F*L^3/(3*E*I)] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[E,F,L,I] outputVariablesNames=[y0] formulas=[-F*L^3/(3*E*I)] antecedent=class=UsualRandomVector distribution=class=Normal name=Normal dimension=4 mean=class=Point name=Unnamed dimension=4 values=[50,1,10,5] sigma=class=Point name=Unnamed dimension=4 values=[1,1,1,1] correlationMatrix=class=CorrelationMatrix dimension=4 implementation=class=MatrixImplementation name=Unnamed rows=4 columns=4 values=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1] operator=class=Less name=Unnamed threshold=-3 physicalstartingPoint=class=Point name=Unnamed dimension=4 values=[50,1,10,5]
event= class=RandomVector implementation=class=ThresholdEventImplementation antecedent=class=CompositeRandomVector function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[E,F,L,I,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[E,F,L,I] outputVariablesNames=[y0] formulas=[-F*L^3/(3*E*I)] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[E,F,L,I] outputVariablesNames=[y0] formulas=[-F*L^3/(3*E*I)] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[E,F,L,I] outputVariablesNames=[y0] formulas=[-F*L^3/(3*E*I)] antecedent=class=UsualRandomVector distribution=class=Normal name=Normal dimension=4 mean=class=Point name=Unnamed dimension=4 values=[50,1,10,5] sigma=class=Point name=Unnamed dimension=4 values=[1,1,1,1] correlationMatrix=class=CorrelationMatrix dimension=4 implementation=class=MatrixImplementation name=Unnamed rows=4 columns=4 values=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1] operator=class=Less name=Unnamed threshold=-3
nearest point algorithm= class=OptimizationAlgorithm implementation=class=Cobyla class=OptimizationAlgorithmImplementation problem=class=OptimizationProblem implementation=class=OptimizationProblemImplementation objective=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[] evaluationImplementation=class=NoEvaluation name=Unnamed gradientImplementation=class=NoGradient name=Unnamed hessianImplementation=class=NoHessian name=Unnamed equality constraint=none inequality constraint=none bounds=none minimization=true dimension=0 startingPoint=class=Point name=Unnamed dimension=4 values=[50,1,10,5] maximumIterationNumber=100 maximumCallsNumber=400 maximumAbsoluteError=1e-10 maximumRelativeError=1e-10 maximumResidualError=1e-10 maximumConstraintError=1e-10 rhoBeg=0.1
result= class=AnalyticalResult standardSpaceDesignPoint=class=Point name=Unnamed dimension=0 values=[] physicalSpaceDesignPoint=class=Point name=Unnamed dimension=0 values=[] limitStateVariable=class=RandomVector implementation=class=ThresholdEventImplementation antecedent=class=CompositeRandomVector function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[] evaluationImplementation=class=NoEvaluation name=Unnamed gradientImplementation=class=NoGradient name=Unnamed hessianImplementation=class=NoHessian name=Unnamed antecedent=class=RandomVectorImplementation operator=class=Less name=Unnamed threshold=0 isStandardPointOriginInFailureSpace=false hasoferReliabilityIndex=0 importanceFactors=class=PointWithDescription name=Unnamed dimension=0 description=[] values=[] classicalImportanceFactors=class=PointWithDescription name=Unnamed dimension=0 description=[] values=[] hasoferReliabilityIndexSensitivity=[]
result= class=AnalyticalResult standardSpaceDesignPoint=class=Point name=Standard Space Design Point dimension=4 values=[-0.0310354,0.841942,0.445404,-0.332238] physicalSpaceDesignPoint=class=Point name=Physical Space Design Point dimension=4 values=[49.969,1.84194,10.4454,4.66776] limitStateVariable=class=RandomVector implementation=class=ThresholdEventImplementation antecedent=class=CompositeRandomVector function=class=Function name=Unnamed implementation=class=FunctionImplementation name=Unnamed description=[E,F,L,I,y0] evaluationImplementation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[E,F,L,I] outputVariablesNames=[y0] formulas=[-F*L^3/(3*E*I)] gradientImplementation=class=SymbolicGradient name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[E,F,L,I] outputVariablesNames=[y0] formulas=[-F*L^3/(3*E*I)] hessianImplementation=class=SymbolicHessian name=Unnamed evaluation=class=SymbolicEvaluation name=Unnamed inputVariablesNames=[E,F,L,I] outputVariablesNames=[y0] formulas=[-F*L^3/(3*E*I)] antecedent=class=UsualRandomVector distribution=class=Normal name=Normal dimension=4 mean=class=Point name=Unnamed dimension=4 values=[50,1,10,5] sigma=class=Point name=Unnamed dimension=4 values=[1,1,1,1] correlationMatrix=class=CorrelationMatrix dimension=4 implementation=class=MatrixImplementation name=Unnamed rows=4 columns=4 values=[1,0,0,0,0,1,0,0,0,0,1,0,0,0,0,1] operator=class=Less name=Unnamed threshold=-3 isStandardPointOriginInFailureSpace=false hasoferReliabilityIndex=1.00925 importanceFactors=class=PointWithDescription name=Unnamed dimension=0 description=[] values=[] classicalImportanceFactors=class=PointWithDescription name=Unnamed dimension=0 description=[] values=[] hasoferReliabilityIndexSensitivity=[]
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