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Glossary

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 ANOVA
Analysis of variance. Used to perform variable screening by identifying insignificant variables.
Variable regression coefficients are ranked based on their significance as obtained through a partial F-test.
(See also variable screening).
 Bias error
The total error – the difference between the exact and computed response - is composed of a random and a bias component. The bias component is a systematic deviation between the chosen model (approximation type) and the exact response of the structure (FEA analysis is usually considered to be the exact response). Also known as the modeling error. (See also random error).
 Binout
The name of the binary output file generated by LS-DYNA (Version 970 onwards).
 Committee
A set of Neural Networks of the same order constructed using the same set of results. The nets are usually slightly different because a different weight initiator is typically used for the regression procedure of each individual net.
 Composite function
A function constructed by combining responses and design variables into a single value. Symbolized by F.
 Concurrent simulation
The running of simulation tasks in parallel without message passing between the tasks.
 Confidence interval
The interval in which a parameter may occur with a specified level of confidence. Computed using Student’s t-test. Typically applied to accompany the significance of a variable in the form of an error bar.
 Constraint
An absolute limit on a response variable specified in terms of an upper or lower limit.
 Constrained optimization
The mathematical optimization of a function subject to specified limits on other functions.
 Conventional Design
The procedure of using experience and/or intuition and/or ad hoc rules to improve a design.
 Crossplot
A curve obtained by using the two ordinate values at a coinciding abscissa obtained from two separate functions. The two ordinate values are used as the abscissa and ordinate in the new crossplot. In LS-OPT two separate time histories are typically used to construct a single crossplot.
 Dependent
A function which is dependent on variables. Dependent variable.
 Design of Experiments
See experimental design.
 Design parameter
See design variable.
 Design formula
A simple mathematical expression which gives the response of a design when the design variables are substituted. See response surface.
 Design space
A region in the n-dimensional space of the design variables (x1 through xn to which the design is limited. The design space is specified by upper and lower bounds on the design variables. Response variables can also be used to bound the design space.
 Design surface
The response variable as a function of the design variables, used to construct the formulation of a design problem. (See also response surface, design rule).
 Design sensitivity
The gradient vector of the response. The derivatives of the response function in terms of the design variables. df /dxi.
 Design variable
An independent design parameter which is allowed to vary in order to change the design. Symbolized by (xi or x (vector containing several design variables)).
 Discipline
An area of analysis requiring a specific set of simulation tools, usually because of the unique nature of the physics involved, e.g. structural dynamics or fluid dynamics. In the context of MDO, often used interchangeably with solver.
 DOE
Design of Experiments. See experimental design.
 D-optimal
The state of an experimental design in which the determinant of the moment matrix X T X of the least squares formulation is maximized.
 DSA
Design sensitivity analysis.
 Ensemble
A collection of neural nets of different (usually thought of as ascending) order based on the same set of results.
 Elliptic approximation
An approximation in which only the diagonal Hessian terms are used.
 Experiment
Evaluation of a single design.
 Experimental Design
The selection of designs to enable the construction of a design response surface. Sometimes referred to as the Point Selection Scheme.
 Feasible Design
A design which complies with the constraint bounds.
 Function
A mathematical expression for a response variable in terms of design variables. Often used interchangeably with “response”. Symbolized by f.
 Functionally efficient
See Pareto optimal.
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