Intelligent Assessment and Retrofitting of Existing Building Structures for Sustainable and Resilient Cities

Dear Colleagues,

The global urban building stock continues to grow and age, making its safety, durability, and sustainability core determinants of urban resilience. In the face of dual challenges from extreme disaster threats due to climate change and the "Dual Carbon" strategic goals, the intelligent maintenance and functional upgrading of existing building structures have become particularly urgent. Traditional detection, assessment, and strengthening methods are increasingly inadequate in terms of efficiency, accuracy, and systematicity to meet the demands of modern urban refined management.

Fortunately, advanced technologies such as intelligent detection, new building materials, artificial intelligence, and digital twins are reshaping the research paradigms and practical approaches for existing building structures. These technologies provide unprecedented solutions for real-time perception of structural conditions, accurate prediction of performance evolution, rapid safety assessment, and low-carbon retrofitting. Establishing new theoretical frameworks adapted to these advancements is key to driving this field from experience-driven practices towards a dual-driven approach based on data and models.

This Special Issue, entitled "Intelligent Assessment and Retrofitting of Existing Building Structures for Sustainable and Resilient Cities," aims to provide a high-level academic exchange platform for this interdisciplinary frontier. We cordially invite submissions addressing the following innovative directions, including, but not limited to, the following:

• Intelligent Detection Technologies and Advanced Sensing Systems: including, but not limited to, automatic identification of surface damage based on UAVs and machine vision, structural response monitoring using distributed optical fiber and wireless sensor networks, and the development and application of novel intelligent sensors.
• Performance and Engineering Applications of Emerging Building Materials: focusing on the mechanical properties, durability, and long-term effectiveness of materials such as self-healing concrete, ultra-high performance concrete (UHPC), shape memory alloys, and eco-friendly composite materials in the strengthening and repair of existing structures.
• Data-Driven Rapid Assessment Methods and Theoretical Frameworks: exploring machine learning and deep learning-based models for rapid screening of structural safety conditions, damage diagnosis, and residual life prediction, as well as new theoretical systems integrating physical mechanisms and data science.
• Digital Twin Model Construction and Application: research on the construction theory, dynamic updating methods, and verification mechanisms for high-fidelity digital twin models of building structures; exploring their application in real-time mapping of structural status, performance evolution prediction, and intelligent maintenance decision-making; promoting the deep integration of digital twins with Building Information Modeling (BIM) and IoT monitoring data.
• Building Structural Resilience Assessment and Enhancement Strategies: focusing on quantitative resilience theory and assessment methods for building structures under extreme disaster environments; researching multi-hazard action mechanisms and cascade effect analysis; developing performance-based resilience design methods and rapid functional recovery technologies to enhance building adaptability and recoverability under disaster conditions.
• Sustainable Retrofitting Design and Life Cycle Management: covering BIM-based collaborative retrofit design, structural functional adaptability enhancement technologies, exploring low-carbon/zero-carbon upgrade paths and circular construction strategies, and building intelligent decision support systems that integrate environmental benefits and economic costs to promote the sustainable development of existing building structures throughout their life cycle.

We welcome various types of submissions, including original research articles, comprehensive reviews, and representative high-level engineering case studies, to collectively advance the management and maintenance of building structures towards an intelligent, low-carbon, and resilient future.

Please do not hesitate to contact us if you have any questions about this Special Issue.

Dr. Kuangyu Dai
Dr. Lei Li
Dr. Yumeng Qiao
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• existing building structures
• structural health monitoring
• digital twin
• machine learning
• structural resilience
• seismic strengthening
• sustainable upgrading
• building information modeling (BIM)
• computer vision
• high-performance materials