Abstract

Engineering systems are typically governed by systems of high-order differential equations which require efficient numerical methods to provide reliable solutions, subject to imposed constraints. The conventional approach by direct approximation of system variables can potentially incur considerable error due to high sensitivity of high-order numerical differentiation to noise, thus necessitating improved techniques which can better satisfy the requirements of numerical accuracy desirable in solution of high-order systems. To this end, a novel inverse differential quadrature method (iDQM) is proposed for approximation of engineering systems. A detailed formulation of iDQM based on integration and DQM inversion is developed separately for approximation of arbitrary low-order functions from higher derivatives. Error formulation is further developed to evaluate the performance of the proposed method, whereas the accuracy through convergence, robustness and numerical stability is presented through articulation of two unique concepts of the iDQM scheme, known as Mixed iDQM and Full iDQM. By benchmarking iDQM solutions of high-order differential equations of linear and nonlinear systems drawn from heat transfer and mechanics problems against exact and DQM solutions, it is demonstrated that iDQM approximation is robust to furnish accurate solutions without losing computational efficiency, and offer superior numerical stability over DQM solutions.

Highlights

  • This study proposes a novel inverse differential quadrature method (iDQM) for numerical analysis of engineering systems

  • Given a system of high-order differential equations, the proposed iDQM approximates high-order variables rather than the original function which can be subsequently recovered by integration

  • To evaluate the performance of iDQM solutions, detailed derivations of iDQM error estimates based on integration and differential quadrature method (DQM) inversion are developed in this work, which are compared with DQM error estimates outlined in [23]

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Summary

Introduction

Engineering systems are typically governed by complex high-order differential equations which require numerical methods to provide accurate solutions.

Inverse differential quadrature method
Inverse differential quadrature method error
Numerical results and discussions
Computational efficiency of the inverse differential quadrature method
Conclusion

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