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Safety and Optimization of Building Structures—2nd Edition
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Safety and Optimization of Building Structures—2nd Edition

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Building Structures".

Deadline for manuscript submissions: 20 December 2024 | Viewed by 764

Special Issue Editor

Dr. Anatoly Alekseytsev

E-Mail Website
Guest Editor
Department of Reinforced Concrete and Stone Structures, Moscow State University of Civil Engineering, 129337 Moscow, Russia
Interests: structural optimization; mechanical safety; progressive collapse resistance, metaheuristic algorithms; reliability; optimal design; fire damage; corrosion effects; building material; AI algorithms
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Ensuring the safety of designed, erected, and operated load-bearing and enclosing building structures is the most important task of engineering, science, and practice of design and operation. An important aspect of this is the development of design and optimization methods. The goals of such optimization can be not only material consumption or costs but also the risks of accidents. The relevance of preventing risks of material and socio-economic losses is the main priority, and new modern scientific research and practice will allow us to advance in its solution. The most important factors here are the force and environmental impacts on structures, such as corrosion, high-temperature heating, mechanical shocks, seismic activity, etc. The main purpose of the Special Issue is to provide a platform for discussion of the main problems related to the mechanical, fire, and environmental safety of load-bearing and enclosing structures of buildings and assessment of their technical condition. In these conditions, it is important to consider the stages of the structure's life cycle, optimal design and calculation algorithms development to ensure sustainable evolution, and the required level of comfort of the environment of buildings.

Dr. Anatoly Alekseytsev
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. Buildings is an international peer-reviewed open access monthly 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

  • structural optimization
  • mechanical safety
  • progressive collapse resistance
  • fire safety
  • life cycle
  • metaheuristic algorithms
  • risk prevention
  • sustainable development
  • reliability
  • optimal design

Related Special Issue

Published Papers (2 papers)

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Research

27 pages, 11313 KiB  
Article
Progressive Collapse Behavior of a Precast Reinforced Concrete Frame System with Layered Beams
by Vitaly I. Kolchunov, Natalia V. Fedorova, Sergei Y. Savin and Pavel A. Kaydas
Buildings 2024, 14(6), 1776; https://doi.org/10.3390/buildings14061776 - 12 Jun 2024
Viewed by 282
Abstract
A possible way to improve the structural safety and robustness of precast building structures is to develop effective precast frame systems with layered beams, which combine prefabricated parts with cast-in situ ordinary concrete, high-performance concrete, fiber concrete, or FRP. The paper provides a [...] Read more.
A possible way to improve the structural safety and robustness of precast building structures is to develop effective precast frame systems with layered beams, which combine prefabricated parts with cast-in situ ordinary concrete, high-performance concrete, fiber concrete, or FRP. The paper provides a new type of precast reinforced concrete frame system with layered beams for rapidly erected multi-story buildings resistant to accidental actions. Using a combination of the variational method and two-level design schemes, a simplified analytical model has been developed for structural analysis of the precast reinforced concrete frame system, both for serviceable and ultimate limit states as well as for accidental actions. The proposed model allows for determining shear deformations and the formation and opening of longitudinal cracks in the intermediate contact zone between precast and monolithic parts of reinforced concrete structural elements of the frame, as well as the formation and opening of normal cracks because of the action of axial tensile force or bending moment in these elements. The design model was validated by comparing the calculated and experimental data obtained from testing scaled models of the precast reinforced concrete frame system with layered beams. The paper investigates and thoroughly analyzes the factors affecting the stiffness and bearing capacity of the intermediate contact zone, discusses the criteria for the formation of shear cracks along the contact zone of precast and monolithic concrete, and examines the change in the stiffness and dissipative properties of layered elements at different stages of their static–dynamic loading. The robustness of the experimental models of the structural system was not ensured under the specified load, section dimensions, and reinforcement scheme. Following an accidental action, longitudinal cracks were observed in the contact joint between the monolithic and prefabricated parts in the layered beams. This occurred almost simultaneously with the opening of normal cracks in adjacent sections. A comprehensive analysis of the results indicated a satisfactory degree of agreement between the proposed semi-analytical model and the test data. Full article
(This article belongs to the Special Issue Safety and Optimization of Building Structures—2nd Edition)
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25 pages, 5679 KiB  
Article
Load Identification in Steel Structural Systems Using Machine Learning Elements: Uniform Length Loads and Point Forces
by Alexander R. Tusnin, Anatoly V. Alekseytsev and Olga A. Tusnina
Buildings 2024, 14(6), 1711; https://doi.org/10.3390/buildings14061711 - 7 Jun 2024
Viewed by 269
Abstract
Actual load identification is a most important task solved in the course of (1) engineering inspections of steel structures, (2) the design of systems rising or restoring the bearing capacity of damaged structural frames, and (3) structural health monitoring. Actual load values are [...] Read more.
Actual load identification is a most important task solved in the course of (1) engineering inspections of steel structures, (2) the design of systems rising or restoring the bearing capacity of damaged structural frames, and (3) structural health monitoring. Actual load values are used to determine the stress–strain state (SSS) of a structure and accomplish various engineering objectives. Load identification can involve some uncertainty and require soft computing techniques. Towards this end, the article presents an integrated method combining basic provisions of structural mechanics, machine learning, and artificial neural networks. This method involves decomposing structures into primitives, using machine learning data to make projections, and assembling structures to make final projections for steel frame structures subjected to elastic strain. Final projections serve to identify parameters of point forces and loads distributed along the length of rods. The process of identification means checking the difference between (1) weight coefficient matrices applied to unit loads and (2) actual loads standardized using maximum load values. Cases of neural network training and parameters identification are provided for simple beams. The aim of this research is to enhance the reliability and durability of steel structures by predicting consequences of unfavorable load, including emergency impacts. The novelty of this study lies in the co-use of artificial intelligence elements and structural mechanics methods to predict load parameters using actual displacement curves of structures. This novel approach will enable engineering inspection teams to predict unfavorable load peaks, prevent emergency situations, and identify actual causes of emergencies triggered by excessive loading. Full article
(This article belongs to the Special Issue Safety and Optimization of Building Structures—2nd Edition)
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