转载丨【1号通知】DigiTwin 2024 第四届数字孪生国际会议分会预告—数字孪生智能建造（SC）

DigiTwin2024

Special Session on

Digital Twin Smart Construction (SC)

数字孪生智能建造（SC）

时间：10月15日，16:30 - 18:30；21:00 - 23:00（北京时间）

形式：线上

一、专会主席 Session Chairs

Chair

Zhansheng Liu

Professor, Beijing University of Technology (China)

Lzs4216@163.com

Co-Chair

Zhe Sun

Assistant Professor, Beijing University of Technology (China)

zhesun@bjut.edu.cn

Co-Chair

Fengjuan Chen

Associate Professor, Beijing University of Technology (China)

fengjuanchen@bjut.edu.cn

二、专会目标Session Aim & Scope

三、专会报告Session Presentations

Title: Enhancing Nuclear Power Production with Digital Twin and Artificial Intelligence

Abstract:

Integrating artificial intelligence (AI) with digital twin technology offers transformative potential for enhancing nuclear power production. Digital twins create precise virtual models of physical assets, while AI enhances these models with real-time data analysis, predictive maintenance, and process optimization. This combination boosts operational efficiency, safety, and reliability in nuclear power plants. AI-driven insights, supported by digital twins, can streamline maintenance, optimize energy output, and improve overall plant management. As advancements continue, particularly in explainable AI, the synergy of these technologies is poised to revolutionize nuclear energy, driving innovation and regulatory developments in the industry.

Title: Digital Twins Supporting Decommissioning of Heavy Water Research Reactor

Abstract:

Heavy Water Research Reactor (HWRR) is the first reactor in China. According to the plan of China Institute of Atomic Energy (CIAE), immediate dismantling is selected as the strategy of HWRR decommissioning. Nuclear reactor decommissioning is a complex engineering. Digital Twins of nuclear facilities recreate a facility’s technology and structures and support effective design, operation, and maintenance. This research puts forward digital twins technology application in HWRR decommissioning, supporting the characterization, dismantling, and radioactive waste management.

Title: Solution of Digital Twin Application in Supply Chain of Manufacturing Enterprises

Abstract:

An intelligent construction platform is built with industrial software as the core to revolutionize the traditional project management, break down data silos, realize the whole process collaboration, and "one model to the end, construction with no drawing, and full-process transparency". According to practices, the platform effectively improves the construction period, costs and project quality to lead the construction industry to digital transformation, and drive deep integration of the industrial chain.

Title: Leveraging Artificial Intelligence for Predictive Analysis of Pavement Condition and Maintenance Costs in the Context of Natural Hazards

Abstract:

Natural hazards significantly impact pavement integrity and maintenance costs, posing challenges to infrastructure management. This research integrates artificial intelligence (AI) to analyze a dataset of 100 records on natural hazards, pavement conditions, and maintenance costs. By utilizing machine learning models, the study aims to predict pavement deterioration and estimate future maintenance expenses, enabling proactive planning. The AI-driven models will consider factors like hazard type, pavement materials, traffic load, and maintenance history. The findings will provide infrastructure managers with insights to optimize maintenance strategies, reduce costs, and improve pavement resilience, advancing the role of AI in civil infrastructure management.

Title: The Application of Digital Twins in Infrastructure

Abstract:

The construction industry is currently grappling with issues such as low productivity, labour shortages, and frequent safety incidents. In this context, the applications of intelligent construction and digital twins have garnered widespread attention from both academia and industry. Digital twin technology, as one of the primary core technologies of intelligent construction, combined with sensing technology, AI and machine learning, holds promise in effectively addressing challenges such as 3D reconstruction, real-time monitoring, predictive maintenance and net zero carbon. This report primarily explores the application of digital twin technology in infrastructures, especially for construction and maintenance. Through real-world case studies, this report showcases the value and impact of digital twins in the realm of intelligent and sustainable construction.

Title: Building of A Digital Platform for Intelligent Construction of Civil Engineering Structures

Abstract:

Construction of a digital platform for intelligent construction of civil engineering structures relies on physical models and mathematical algorithms. Utilizing BIM modeling, multidimensional digital modeling, and advanced simulation technologies, the built digital platform integrates big data and intelligent decision support systems. Notable applications include the design and case analysis of the Beijing Daxing International Airport, the Beijing Winter Olympics venues, and digital simulations for nuclear reactor decommissioning projects, demonstrating comprehensive capabilities in enhancing construction efficiency and safety through advanced digitalization.

Title: Solution of Digital Twin Application in Supply Chain of Manufacturing Enterprises

Abstract:

The digital upgrading of the supply chain is a megatrend and direction for enterprise development. This talk will present the current status and pain points of manufacturing enterprise supply chains, and combine a digital twin construction method to introduce the solution and technical route of "simulation+intelligent decision-making" empowering the digital transformation of enterprise supply chain.