Computational and Data-Driven Modeling for Materials, Design and Construction
A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Construction Management, and Computers & Digitization".
Deadline for manuscript submissions: 31 October 2026 | Viewed by 182
Special Issue Editors
Interests: computational fluid and solid mechanics; finite element/meshless methods for modelling material behavior; modelling and experimental analysis of self-compacting concrete; computational fluid dynamics and solid mechanics with SPH method; application of modelling techniques for simulating advanced manufacturing processes; data-driven modelling of material characteristics and performance
Interests: finite element modelling (FEM); computational mechanics; simulation-driven materials design; fibre-reinforced and self-compacting concrete; explicit modelling of fibre reinforcement; X-ray CT-scan–assisted analysis; fracture and damage mechanics; mechanical and durability performance of cementitious materials; supplementary cementitious materials (SCMs) and low-carbon cements; experimental–computational integration in civil engineering
Interests: digital twin; structural health monitoring (SHM); ontology & semantic rule modelling; deep learning; BIM-based life-cycle management; physics-informed modelling; point cloud to FEM updating; automated maintenance strategy generation; IoT for intelligent infrastructure; green bridge design & carbon emission optimization
Special Issue Information
Dear Colleagues,
The traditional paradigms of the building and construction industry are undergoing a radical transformation driven by the integration of computational and data-driven modelling for materials, design and construction methodologies. This issue focuses on heuristic-based workflows to integrate digital pipelines that leverage high-performance computing and machine learning to optimize the built environment.
Core themes of this Special Issue
- Multiscale Material Modelling advances in computational mechanics for simulating material behaviour from the micro-scale to the structural level: It includes the "bottom-up" design of bespoke materials, such as carbon-sequestering concrete or high-performance composites, tailored for specific environmental stresses.
- Generative Design and Optimization by utilizing algorithmic frameworks exploring vast multidimensional design solution spaces: It includes computational methods prioritizing performance metrics—such as structural efficiency, thermal regulation, and material minimization—far beyond the capacity of manual iteration.
- Data-Driven Predictive Analytics through the use of artificial intelligence (AI) and machine learning (ML) to predict structural health, project timelines, and life-cycle costs: It also includes data-driven models augmenting traditional finite element analysis by providing real-time insights and reducing the "uncertainty gap" in complex construction environments.
Dr. Sivakumar Kulasegaram
Dr. Abdullah Alshahrani
Dr. Honghong Song
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 250 words) can be sent to the Editorial Office for assessment.
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.
Keywords
- physics-informed machine learning
- digital twins for infrastructure
- data-driven structural modelling
- AI-assisted structural optimization
- sustainable construction materials
- fibre-reinforced concrete
- experimental–numerical integration
- fracture and damage mechanics
- machine learning in civil engineering
- sustainable construction materials
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