Papers
Topics
Authors
Recent
Assistant
AI Research Assistant
Well-researched responses based on relevant abstracts and paper content.
Custom Instructions Pro
Preferences or requirements that you'd like Emergent Mind to consider when generating responses.
Gemini 2.5 Flash
Gemini 2.5 Flash 57 tok/s
Gemini 2.5 Pro 52 tok/s Pro
GPT-5 Medium 20 tok/s Pro
GPT-5 High 22 tok/s Pro
GPT-4o 93 tok/s Pro
Kimi K2 199 tok/s Pro
GPT OSS 120B 459 tok/s Pro
Claude Sonnet 4.5 34 tok/s Pro
2000 character limit reached

An adaptive time integration strategy based on displacement history curvature (1305.6857v1)

Published 29 May 2013 in cs.NA and math.NA

Abstract: This work introduces a time-adaptive strategy that uses a refinement estimator based on the first Frenet curvature. In dynamics, a time-adaptive strategy is a mechanism that interactively proposes changes to the time step used in iterative methods of solution. These changes aim to improve the relation between quality of response and computational cost. The method here proposed is suitable for a variety of numerical time integration problems, e.g., in the study of bodies subjected to dynamical loads. The motion equation in its space-discrete form is used as reference to derive the formulation presented in this paper. Our method is contrasted with other ones based on local error estimator and apparent frequencies. We check the performance of our proposal when employed with the central difference, the explicit generalized-alpha and the Chung-Lee integration methods. The proposed refinement estimator demands low computational resources, being easily applied to several direct integration methods.

Citations (18)

Summary

We haven't generated a summary for this paper yet.

Lightbulb Streamline Icon: https://streamlinehq.com

Continue Learning

We haven't generated follow-up questions for this paper yet.

List To Do Tasks Checklist Streamline Icon: https://streamlinehq.com

Collections

Sign up for free to add this paper to one or more collections.