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arXiv 1401.4582cs.SE
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多学科工程模型:电子表格分析中的方法和案例研究

Multidisciplinary Engineering Models: Methodology and Case Study in Spreadsheet Analytics

David Birch, Helen Liang, Paul H J Kelly, Glen Mullineux, Tony Field, Joan Ko, Alvise Simondetti

摘要:

本文展示了一种方法,以帮助从业者最大限度地利用复杂的多学科工程模型实现电子表格,一个领域提出了独特的挑战。作为动机,我们调查的综合资源管理(ESTA)模型,评估城市总体规划设计的可持续性的扩大使用。可持续发展模型通过整合来自许多学科的模型,反映了多学科可持续发展分析的内在复杂性。这种复杂性使得它们的使用非常耗时,并降低了它们的采用率。我们提出了一种方法和工具包,用于分析多学科的工程模型实施电子表格,以减轻这些问题,并增加其采用。对于给定的输出,通过计算模型和跨学科指标提取、可视化和分析模型的相关切片。提取模型的敏感性分析支持工程师的优化工作。这些方法暴露、管理和降低模型复杂性和风险,同时让从业者深入了解多学科模型组成。我们报告的方法应用到几代的工业可持续发展模型和详细的见解,特别是考虑到模型的演变。

英文摘要:

This paper demonstrates a methodology to help practitioners maximise the utility of complex multidisciplinary engineering models implemented as spreadsheets, an area presenting unique challenges. As motivation we investigate the expanding use of Integrated Resource Management(IRM) models which assess the sustainability of urban masterplan designs. IRM models reflect the inherent complexity of multidisciplinary sustainability analysis by integrating models from many disciplines. This complexity makes their use time-consuming and reduces their adoption. We present a methodology and toolkit for analysing multidisciplinary engineering models implemented as spreadsheets to alleviate such problems and increase their adoption. For a given output a relevant slice of the model is extracted, visualised and analysed by computing model and interdisciplinary metrics. A sensitivity analysis of the extracted model supports engineers in their optimisation efforts. These methods expose, manage and reduce model complexity and risk whilst giving practitioners insight into multidisciplinary model composition. We report application of the methodology to several generations of an industrial IRM model and detail the insight generated, particularly considering model evolution.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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