Nonlinear Assessment and Optimization Methods for Concrete Structures

混凝土结构的非线性评估与优化方法

• 批准号: RGPIN-2018-05643
• 负责人: Bentz, Evan
• 金额: $ 2.26万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=713758
• 关键词: Nonlinear; Assessment; Optimization; Methods; Concrete

The current practice of Canadian structural engineering is based on traditional analysis methods that go back many years and have shown themselves to be safe, economical and efficient. At the same time there are analysis and design methods in Canadian and International Universities that go well beyond this level of understanding and allow structures to be designed and built which have a series of advantages: a) improved safety against unexpected events such as earthquakes, b) lower overall cost for the same, or higher, level of safety, and c) higher efficiency in terms of lower consumption of energy-intensive construction materials. The problem with these advanced methods is that they tend to be slow to operate and complex to use. Over the past decades, there has also been a dramatic increase in computer power and structural engineers are not yet using that in the most efficient way possible. Indeed we are now at the state where it is possible to achieve some of the goals in the first paragraph with computers doing the optimization process "by themselves" with the engineer merely watching the computer act. This form of unguided optimization is of a concern from the perspective of generation of understanding for engineers but it hasn't generally been a problem yet as the analysis tools are often too complex to be used with optimization methods anyway. Given that such tools are now possible, however, there is a research need to develop optimization methods which include the engineer as a fundamental part of the process. To achieve design optimization of this type, it is necessary that the faster methods of analysis be extended to 3D. In my previous NSERC Discovery grant I planned to generate efficient 2D methods of analysis that more accurately can predict building behaviour accounting for the nonlinear aspects of cracking, yielding and crushing of the concrete. This has now been achieved and it is now possible to extend this to 3D models of buildings with slabs and walls. This type of modelling will allow optimization of 3D buildings to go ahead reasonably efficiently While using computers to optimize designs will allow more efficient structures to be designed, it will also be necessary to develop the optimization process in a way that increases the engineer's understanding of the problems rather than decreasing it as "blind" optimization could do. Thus it will be a key component of the proposed guided optimization that human beings remain part of the design process as the skills generated from that are what are needed to diagnose problems in buildings and come up with truly new design options for the future. That is: the design process must itself be designed to ensure that Canadian engineers remain at the forefront of methods and technologies used around the world.

加拿大结构工程目前的做法是基于传统的分析方法，可以追溯到许多年，并已证明自己是安全的，经济的和有效的。与此同时，加拿大和国际大学的分析和设计方法远远超出了这种理解水平，并允许设计和建造具有一系列优势的结构：a）提高了对诸如地震的意外事件的安全性，B）对于相同或更高的安全水平，降低了总成本，以及c）更高的效率，即减少能源密集型建筑材料的消耗。这些先进方法的问题是它们往往操作缓慢且使用复杂。 在过去的几十年里，计算机能力也有了显著的增长，而结构工程师还没有以最有效的方式使用它。 事实上，我们现在处于这样一种状态，即有可能实现第一段中的一些目标，计算机“自己”进行优化过程，而工程师只需要观察计算机的行为。从工程师理解的角度来看，这种形式的无指导优化是一个问题，但它通常还不是一个问题，因为分析工具通常太复杂，无法与优化方法一起使用。 鉴于这些工具现在是可能的，但是，有一个研究需要开发优化方法，其中包括工程师作为一个基本的一部分，这一过程。 为了实现这种类型的设计优化，有必要将更快的分析方法扩展到3D。 在我之前的NSERC发现资助中，我计划生成高效的2D分析方法，可以更准确地预测建筑行为，考虑混凝土开裂，屈服和破碎的非线性方面。 现在已经实现了这一点，现在可以将其扩展到具有楼板和墙壁的建筑物的3D模型。 这种类型的建模将允许3D建筑物的优化合理有效地进行 虽然使用计算机优化设计将允许更有效的结构被设计，它也将是必要的，以提高工程师的理解问题的方式，而不是减少它的“盲目”优化可以做的优化过程。因此，这将是拟议的引导优化的一个关键组成部分，即人类仍然是设计过程的一部分，因为从中产生的技能是诊断建筑物问题所需的，并为未来提出真正新的设计方案。 那就是：设计过程本身必须确保加拿大工程师保持在世界各地使用的方法和技术的最前沿。