Page 236 - Using ANSYS for Finite Element Analysis Dynamic, Probabilistic, Design and Heat Transfer Analysis

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Optimization data flow, 175 terminology, 72–74
Optimization design tools traditional (deterministic) vs.,
factorial tool, 179 71–72
gradient tool, 179 variables, 73
random tool, 178 Probabilistic design techniques
single loop analysis tool, 178 advantages, 96–97
sweep tool, 178–179 direct Monte Carlo sampling,
Optimization methods 97–98
description of, 175–176 Latin hypercube sampling, 98
first-order method, 177 Probabilistic model, 73
subproblem approximation Probabilistic sensitivities, 101–104
method, 176–177 Probability density function (pdf),
Optimization tree, 171 76–77
Optimization variables, 174 Probability distributions
Optimum design gallery of common continuous
applications, 172 distributions, 78–81
description, 167–169 lognormal distribution, 85–88
examples, 172 normal distribution, 81–83
fundamental concepts, 169–171 practical uses of, 75–76
uniform distribution, 83–85
P Weibull distribution, 88–91
pdf. See Probability density Problem formulation, 169
function Problem solution, 171
PMCs. See Polymer matrix
composites Q
Polymer matrix composites Quality, probabilistic design, 72
(PMCs)
definition of, 19 R
description of, 20–22 Random input variables, 72
loading of, 22–23 Random output variables, 73
with other structural materials, Random tool, 178
23–26 Random variable distribution
properties of, 20 exceedence values, 92
Postprocessing probabilistic mean values, 92
analysis measured data, 91
statistical postprocessing, no data, 93–95
99–101 output parameters, 95
trend postprocessing, 101–107 standard deviation, 92
PREP7, 181 Reduced method, modal analysis,
Probabilistic design analysis 16–17
circular plate bending, 107–143 Reliability, probabilistic design, 72
definition of, 69–70
reliability and quality issues, 72 S
steps using ANSYS, 74–75 Sample, 73