AI-Based Holistic Structural Analysis and Designs

Dear Colleagues,

Artificial neural network (ANN)-based designs are receiving attentions from many researchers around the world recently. ANNs demonstrate a learning and memory capability similar to that of the human brain, and we can use this extraordinary capability when designing structural systems. ANNs are developed to map inputs into outputs based on large structural design datasets for engineering applications rather than being based on structural mechanics or knowledge. This Special Issue invites papers investigating holistic structural designs with engineering applications based on ANNs. During designs, cost of materials and manufacture of concrete beam and columns can be also optimized, while considering constraints according to design codes and engineer’s needs. Large datasets are generated based on structural mechanics-based software to train ANNs to optimize objective functions.

The proposed Special Issue will cover all areas related to holistic structural designs using ANNs that can solve structural engineering problems in general and design specific structural systems in particular. This Special Issue will also include AI-based optimizations of single objective function and multiple objective functions for Perato curve under given constraining conditions. Columns can be optimized subject to single and multiple loads while they are optimized based on multiple objective functions. The optimizations can utilize equality and inequality constraints to consider local design codes considering any design requirement. Optimal designs are not simple especially when multiple objective functions are to be considered, such as cost, CO2 emissions, structural weights, etc., at the same time. A resilient design capable of finding balanced structures beyond human efficiency will be demonstrated via this Special Issue.

Topics to be covered by the Special Issue but not limited to the following topics:

• Holistic designs for reinforced beams and columns using artificial neural networks
• Holistic designs for steel beams and columns using artificial neural networks
• Holistic designs for hybrid beams and columns using artificial neural networks
• Use of artificial neural networks to design hybrid structures
• Use of artificial neural networks to design precast frames
• Use of artificial neural networks to design prestressed structures
• AI-based holistic designs of buildings and bridges
• AI-based holistic designs of offsite modular constructions
• AI-based optimizations of single objective functions
• AI-based optimizations of multiple objective functions for Perato curve
• AI-based optimizations of multiple objective functions subject to single and multiple loads

Prof. Dr. Won-Kee Hong
Guest Editor

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. Materials 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.

• AI-based holistic designs for RC structures
• AI-based holistic designs for hybrid structures
• AI-based holistic designs for precast frames
• AI-based holistic designs for prestressed structures
• AI-based holistic designs for steel structure
• AI-based holistic designs for buildings and bridges
• AI-based holistic designs for offsite modular constructions
• AI-based optimizations of single objective functions
• AI-based optimizations of multiple objective functions
• Perato frontier
• AI-based optimizations subject to single and multiple loads