SCIENCE@home

Search for accurate RSM metamodels for structural engineering

K. Kalita,Partha Dey,S. Haldar

Published 2019 in Journal of reinforced plastics and composites

ABSTRACT

With rapid advancement in computing power and development of numerical tools and scientific theories in fields like structural engineering, simple experiments can now be carried out in-silico. However, simulating many real-life phenomena in analytical fields still remains largely intractable or requires huge computational resources. A number of researchers have developed suitable metamodels to reduce the computational time needed to solve complex structural problems. As such, response surface method has become quite popular due to its versatility and ability to reduce even the most hard-to-model engineering problems into a simple polynomial form. The number and type of sampling points needed for building the response surface approximation are selected by design of experimentation techniques like Box–Behnken design, central composite design, D-optimal design, etc. One design may be appropriate for some particular problems, while a different design would perform better on others. To assess the performance of such metamodels, statistical measures like R 2 and error-based metrics like root-mean-squared error have been commonly used by researchers. In this paper, extensive numerical experiments are performed to gauge the performance of Box–Behnken design, central composite design and D-optimal designs as a metamodeling tool in structural engineering. The insufficiency of classical statistical accuracy measures like R 2 , R 2 adj and R 2   pred is demonstrated, and the need for measures based on external test data such as Q F 1 2 , Q F 2 2 or Q F 3 2 is stressed. Subsequently, some recommendations are also made on building metamodels for structural engineering problems.

PUBLICATION RECORD

  • Publication year

    2019

  • Venue

    Journal of reinforced plastics and composites

  • Publication date

    2019-07-18

  • Fields of study

    Materials Science, Engineering

  • Identifiers
    DOI 10.1177/0731684419862346
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

CITATION MAP

EXTRACTION MAP

CLAIMS

  • No claims are published for this paper.

CONCEPTS

  • No concepts are published for this paper.

REFERENCES

Showing 1-50 of 50 references · Page 1 of 1

CITED BY

Showing 1-30 of 30 citing papers · Page 1 of 1