The Role of Programming in the Formulation of Ideas
2002
Sign up for access to the world's latest research
Abstract
Classical mechanics is deceptively simple. It is surprisingly easy to get the right answer with fallacious reasoning or without real understanding. To address this problem we use computational techniques to communicate a deeper understanding of Classical Mechanics. Computational algorithms are used to express the methods used in the analysis of dynamical phenomena. Expressing the methods in a computer language forces them to be unambiguous and computationally effective. The task of formulating a method as a computerexecutable program and debugging that program is a powerful exercise in the learning process. Also, once formalized procedurally, a mathematical idea becomes a tool that can be used directly to compute results.
Related papers
Physics Today, 1998
DiBenedetto, Emmanuele
, except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights.
Proceedings of the …, 2010
Much of the research done by modern physicists would be impossible without the use of computation. And yet, while computation is a crucial tool of practicing physicists, physics curricula do not generally reflect its importance and utility. To more tightly connect undergraduate preparation with professional practice, we integrated computational instruction into middle-division classical mechanics at the University of Colorado Boulder. Our model for integration works within the constraints of faculty who do not specialize in computation teaching standard physics courses by placing a strong emphasis on an adaptable curriculum. Our model includes the construction of computational learning goals, the design of computational activities consistent with those goals, and the assessment of students' computational fluency. We present critiques of our model as we work to develop an effective and sustainable model for computational instruction in the undergraduate curriculum.
Springer eBooks, 2018
The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
2016
A native of Fairfax, VA, he enrolled in the major in January 2015. In addition to the curriculum, he researches the mechanics of dynamic systems as a research assistant to the Department Chair, Oscar Barton, Jr., PhD, PE. In particular, his researches focuses on the computer modeling of vibrations in dynamic systems. Mr. Howe also provides academic support as a tutor for mathematics, science, and engineering in the Volgeneau School of Engineering, and is the Secretary of the George Mason University Chapter of the American Society of Mechanical Engineers.
Proceedings of the 6th international workshop on Challenges of large applications in distributed environments - CLADE '08, 2008
Large scale scientific applications generally experience different execution phases at runtime and each phase has different computational and communication requirements. An optimal solution or numerical scheme for one execution phase might not be appropriate for the next phase of the application execution. In this paper we present Physics Aware Programming (PAP) paradigm that supports dynamic changes of the application solution if it optimizes the application performance at runtime. In the PAP approach, the application execution state is periodically monitored and analyzed to identify its current execution phase (state). For each change in the application execution phase, we will exploit the spatial and temporal attributes of the application physics to select the numerical algorithms/solvers that optimize its performance. We have applied our approach to a Ten-Tusscher's model of human ventricular epicardia myocyte paced at a varied cycle length (1000 to 50 ms). At runtime, we recognize the current phase of the heart simulation and based on the detected phase, we adopt the simulation ∆t that maximizes the performance and maintains the required accuracy. Our experimental results show that we can achieve a speedup of three orders of magnitude while maintaining the required accuracy.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authors or the editors give a warranty, express or implied, with respect to the material contained herein or for any errors or omissions that may have been made.

Loading Preview
Sorry, preview is currently unavailable. You can download the paper by clicking the button above.