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Structural steel project development integrating structural design and construction engineering: quantitative methods and AI-based tools

Structural steel project development integrating structural design and construction engineering: quantitative methods and AI-based tools
结构设计与施工工程相结合的钢结构项目开发:定量方法和基于人工智能的工具
批准号:
579062-2022
负责人:
Imanpour, AliA
金额:
$2.37万
依托单位:
依托单位国家:
加拿大
项目类别:
Alliance Grants
财政年份:
2022
资助国家:
加拿大
项目状态:
已结题
起止时间:
2022-01-01 至 2023-12-31

项目摘要

项目成果

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中文摘要
翻译
加拿大钢铁行业建筑项目的设计和执行涉及几项相互关联的任务,包括结构设计和分析、连接细节、制造和安装。目前,钢铁行业从业者在项目各个阶段的决策中严重依赖经验和经验法则,这不一定考虑到结构设计对各个施工阶段和任务的重大影响,从而导致可施工性问题,安装问题,低生产率,不经济的结构,有时甚至是结构安全问题。随着目前数据驱动技术的进步及其在其他学科中的广泛应用,并考虑到结构设计和建筑工程之间的相互作用,加拿大的建筑行业,包括顾问,制造商,安装商和连接设计师与省和联邦政府合作,有足够的机会提高安全和质量,成本效率,为更可持续的钢铁建筑行业做出贡献。该项目将根据从钢结构行业收集的数据和人工智能技术的应用,制定出完善的方法,以提供有效的决策支持,并补充传统的基于经验的决策方法。预计拟议的研究将提高加拿大钢结构建筑行业的建筑生产力,并确保公共安全。此外,该项目将培养具有结构工程和施工管理专业知识的下一代工程师,他们可以为加拿大钢结构建筑行业的发展做出贡献。最后,拟议的研究将使加拿大成为人工智能在钢结构应用领域的全球领导者。
英文摘要
Design and execution of construction projects in the Canadian steel industry involve several interconnected tasks, including structural design and analysis, connection detailing, fabrication, and erection. Currently, steel industry practitioners rely heavily on experience and rules-of-thumb in decision-making for various phases of the project, which does not necessarily take into account the significant impact of structural design on various construction phases and tasks, resulting in constructability issues, erection problems, low productivity, uneconomical structures, and sometimes structural safety issues. With current advancements in data-driven technologies and their wide use in other disciplines and considering the interaction between structural design and construction engineering, there is ample opportunity for the construction industry in Canada, including consultants, fabricators, erectors, and connection designers in conjunction with the provincial and federal governments, to improve safety and quality, cost efficiency, contributing to a more sustainable steel construction industry. This project will produce well-formulated methods based on data collected from the steel construction industry and the application of artificial intelligence techniques to render effective decision support and complement conventional experience-based decision-making methods. It is expected that the proposed research will improve construction productivity in the Canadian steel construction industry and ensure public safety. Moreover, this project will train next-generation of engineers with expertise in structural engineering and construction management who can contribute to the advancement of steel construction industry in Canada. Finally, the proposed research will place Canada as a global leader in the field of the application of artificial intelligence in steel construction.
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