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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 6536

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

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Related Special Issue

Published Papers (9 papers)

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Research

18 pages, 7320 KiB  
Article
Direct Tensile Test Method for Shotcrete
by Oleg V. Kabancev and Oleg A. Simakov
Buildings 2024, 14(12), 3713; https://doi.org/10.3390/buildings14123713 - 21 Nov 2024
Viewed by 167
Abstract
This study substantiates the need for direct tensile strength testing of shotcrete and fiber-reinforced shotcrete, rather than relying on indirect methods, to accurately reflect material performance under biaxial stress conditions when used for structural reinforcement. Experiments on field specimens confirmed that tensile strength [...] Read more.
This study substantiates the need for direct tensile strength testing of shotcrete and fiber-reinforced shotcrete, rather than relying on indirect methods, to accurately reflect material performance under biaxial stress conditions when used for structural reinforcement. Experiments on field specimens confirmed that tensile strength values derived through direct testing differ significantly from those calculated based on compressive strength. The study presents a new testing methodology with optimized specimen dimensions (32, 40, 50, and 82 mm diameter cylinders with length-to-diameter ratios of 3.0) to mitigate eccentricity effects, ensuring normal-section failure. Results show that tensile strength values for fiber-reinforced shotcrete with brass-coated fibers (13–15 mm length, 0.3–0.5 mm diameter, 30 kg/m3 dosage) reached 68 MPa, compared to 60 MPa for standard shotcrete, while basalt-fiber reinforcement (6 mm length, 1% by weight) resulted in 42 MPa. The initial modulus of elasticity for unreinforced shotcrete was 280 × 103 MPa, with fiber reinforcement slightly increasing this value to 287 × 103 MPa. The findings support a direct approach to testing, providing a foundation for developing predictive methodologies for fiber-reinforced shotcrete properties based on reinforcement type and dosage. These results are essential for applications such as seismic strengthening, where accurate tensile characteristics are critical for performance under dynamic loading. Full article
(This article belongs to the Special Issue Safety and Optimization of Building Structures—2nd Edition)
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20 pages, 5219 KiB  
Article
Self-Compacting Mixtures of Fair-Faced Concrete Based on GGBFS and a Multicomponent Chemical Admixture—Technological and Rheological Properties
by Oksana A. Larsen, Svetlana V. Samchenko, Olga V. Zemskova, Andrey V. Korshunov and Artyom A. Solodov
Buildings 2024, 14(11), 3545; https://doi.org/10.3390/buildings14113545 - 6 Nov 2024
Viewed by 459
Abstract
The use of superplasticizers in a self-compacting concrete mix without the addition of a foaming agent in practice leads to a well-known problem associated with increased air entrainment and promotes the formation of harmful large bubbles, high-void content, and ununiform appearance. This paper [...] Read more.
The use of superplasticizers in a self-compacting concrete mix without the addition of a foaming agent in practice leads to a well-known problem associated with increased air entrainment and promotes the formation of harmful large bubbles, high-void content, and ununiform appearance. This paper presents research on the properties of cement paste consisting of Ordinary Portland Cement (OPC), powder based on ground granulated blast furnace slag (GBBS), and superplasticizer. The methodology of this study was the estimation of flow diameter and flow time, as well as the evaluation of the rheological characteristics. The influence of ground granulated blast furnace slag and polycarboxylate plasticizer on the flowability and viscosity of cement paste was studied. The effect of superplasticizer (SP) based on polycarboxylate esters (PCE) anti-foaming agent (AFA) based on a glycol ester and air-entraining admixture (AEA) based on an amphoteric surfactant on flowability, viscosity, rheological properties and the strength of the cement paste was evaluated. It was found that the increase of slag content in cement paste (25%) with the presence of superplasticizer (0.64%) significantly changes the flowability and viscosity. It was stated that the addition of 0.04% anti-foaming agents increases flowability (20%) and reduces viscosity (44%) of cement paste. It was stated that the addition of small dosages of glycol ester-based anti-foaming agent (0.02 and 0.04%) significantly changes the rheological properties, decreases the shear yield stress by 2.1–2.8 times, the plastic viscosity by 2.4–2.6 times and apparent viscosity 1.6–2.5 times, improves the compressive strength at the age of 1 and 7 days by 2.5 and 1.4 times, respectively. The addition of air-entraining admixture led to a decrease in the plastic viscosity by 1.2–1.4 times. It was stated that the presence of air-entraining admixture assists in increasing the apparent viscosity by 1.7–2.4 times. It was shown that the presence of complex admixtures of various origins, purposes, and mechanisms of action would assist in predicting the behavior of concrete mixtures under the conditions of the building site and reduce the consumption of polycarboxylate esters due to the enhancing plasticizing effect of anti-foaming agent and air-entraining admixture. Full article
(This article belongs to the Special Issue Safety and Optimization of Building Structures—2nd Edition)
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13 pages, 3110 KiB  
Article
Computational Models of Dynamic Load Sources for Modeling of Construction Structures Operation Used in Monitoring of Technical Condition of Buildings and Structures
by Zhanna Gennadievna Mogilyuk, Alexander Alexandrovich Tereshin and German Valerievich Alekseev
Buildings 2024, 14(10), 3193; https://doi.org/10.3390/buildings14103193 - 7 Oct 2024
Viewed by 554
Abstract
This research aims to develop principles for assessing the impact of mega-cyclic vibrodynamic loads on the reliability of construction structures. The relevance of the reasons for the development and improvement of algorithms for numerical modeling of multicycle dynamic loads on building structures is [...] Read more.
This research aims to develop principles for assessing the impact of mega-cyclic vibrodynamic loads on the reliability of construction structures. The relevance of the reasons for the development and improvement of algorithms for numerical modeling of multicycle dynamic loads on building structures is due to the steadily increasing intensity of such loads on buildings and structures in megacities, as well as the acute practical problem of significant differences in the dynamic characteristics of buildings and structures obtained as a result of mathematical modeling and determined by experimental methods. The article presents research materials on computational equivalent models of dynamic load sources for numerical modeling of the behavior of construction structures under their influence, using the method of vibroacoustic analogies. The article examines models of sources of dynamic impact on construction sites. Algorithms and final formulas for computational modeling of the simplest sources of dynamic load are developed using the method of vibroacoustic analogies. The dynamic properties of the simplest dynamic load sources were analyzed. A significant difference between the computational models of real and ideal dynamic load sources. The article presents research and development results intended for calculating the distribution of dynamic loads on elements of construction structures in industrial and civil engineering projects located in areas with high levels of transport vibrodynamic impacts. An important property of the proposed computational equivalent models of sources of dynamic impact on building structures is the possibility of computational verification of critical elements, points, or nodes of load-bearing structures of buildings and structures under dynamic overloads. The position of these critical elements, points, and nodes of load-bearing structures under dynamic loads can differ significantly from their position determined using static and quasistatic computational modeling methods. Full article
(This article belongs to the Special Issue Safety and Optimization of Building Structures—2nd Edition)
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14 pages, 1619 KiB  
Article
Experimental Studies on Joints of Wooden Elements with Proposed “CM Insert”
by Alexander Tusnin, Linkov Nikolay and Klyukin Aleksandr
Buildings 2024, 14(10), 3179; https://doi.org/10.3390/buildings14103179 - 6 Oct 2024
Viewed by 608
Abstract
The article examines the results of testing a series of samples, where the joint operation of wooden elements is ensured by a composite material based on fiberglass. A method for ensuring joint operation is adopted according to the insert scheme on the contact [...] Read more.
The article examines the results of testing a series of samples, where the joint operation of wooden elements is ensured by a composite material based on fiberglass. A method for ensuring joint operation is adopted according to the insert scheme on the contact surfaces. The strength and deformation characteristics of the samples are obtained, and the calculated bearing capacity is established. Statistical processing of the obtained parameters is performed. Full article
(This article belongs to the Special Issue Safety and Optimization of Building Structures—2nd Edition)
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12 pages, 2072 KiB  
Article
Piezoelectric Gauge of Small Dynamic Bending Strains
by Nelly Rogacheva, Vladimir Sidorov and Yulia Zheglova
Buildings 2024, 14(8), 2447; https://doi.org/10.3390/buildings14082447 - 8 Aug 2024
Viewed by 634
Abstract
This paper is devoted to a new gauge of small dynamic bending deformations of structures. Unlike previously existing strain gauges that measure elongation or compression at a certain point on the surface of a deformable body, the proposed gauge measures the change in [...] Read more.
This paper is devoted to a new gauge of small dynamic bending deformations of structures. Unlike previously existing strain gauges that measure elongation or compression at a certain point on the surface of a deformable body, the proposed gauge measures the change in curvature at a point on the surface of a deformable body and does not respond to elongation–compression strains. The gauge is a layered bar made of piezoelectric and elastic materials. It functions using the direct piezoelectric effect. In order to competently study the deformed state of a structure at points on a surface, it is necessary to determine all components of the strain tensor. The gauges currently used measure only elongational or compressive strains, which does not provide a complete picture of the strain state. It is very important to complement these deformations with bending strains measured by the new gauge. Full article
(This article belongs to the Special Issue Safety and Optimization of Building Structures—2nd Edition)
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17 pages, 3161 KiB  
Article
Estimation of the Reduction Coefficient When Calculating the Seismic Resistance of a Reinforced Concrete Frame Building after a Fire
by Ashot Tamrazyan, Oleg Kabantsev, Tatiana Matseevich and Vladimir Chernik
Buildings 2024, 14(8), 2421; https://doi.org/10.3390/buildings14082421 - 6 Aug 2024
Cited by 1 | Viewed by 909
Abstract
The consequences of destructive earthquakes show that the problem of analyzing the response of reinforced concrete frames under seismic loads after a fire is relevant. The calculation models used for individual elements and buildings as a whole must take into account the nonlinear [...] Read more.
The consequences of destructive earthquakes show that the problem of analyzing the response of reinforced concrete frames under seismic loads after a fire is relevant. The calculation models used for individual elements and buildings as a whole must take into account the nonlinear properties of concrete and reinforcement. In the spectral calculation method, the nonlinear properties of materials are taken into account by introducing a reduction coefficient to the elastic spectrum. When determining the reduction coefficient, a common deformation criterion is based on the use of the plasticity coefficient. The seismic resistance of a three-span, five-story reinforced concrete frame under four different fire exposure options is considered. The residual strength and stiffness of frame elements after a fire is assessed by performing a thermal engineering calculation in the SOLIDWORKS software for a standard fire. For the central sections of the elements, the highest temperatures were obtained after heating—during the cooling stage. The reduction coefficient is estimated by performing a nonlinear static analysis of reinforced concrete frames in OpenSees and constructing load-bearing capacity curves. Fracture patterns and damage levels in plastic hinges are analyzed. Based on the numerical modeling of reinforced concrete frames after exposure to fire, it was revealed that the most dangerous scenario is the occurrence of a fire on the first floor of the building. Based on the obtained plasticity coefficients, reduction coefficients were determined in the range of 2.62 to 2.44. The influence of fire on the permissible damage coefficient of a reinforced concrete frame is assessed using the coefficient φK—the coefficient of additional damage after a fire, which is equal to the ratio of the reduction coefficients for the control and fire-damaged frames. Depending on the percentage of damaged structures on the first floor, the following values were obtained: 50% or less—φK = 1.09; 100%—φK = 1.17. The obtained coefficients are recommended to be used when assessing the seismic resistance of a reinforced concrete frame after a local fire. Full article
(This article belongs to the Special Issue Safety and Optimization of Building Structures—2nd Edition)
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21 pages, 6178 KiB  
Article
Using Machine Learning Technologies to Design Modular Buildings
by Alexander Romanovich Tusnin, Anatoly Victorovich Alekseytsev and Olga Tusnina
Buildings 2024, 14(7), 2213; https://doi.org/10.3390/buildings14072213 - 18 Jul 2024
Viewed by 841
Abstract
The article discusses a solution to the relevant task of analyzing and designing modular buildings made of blocks to be used in industrial and civil engineering. A block that represents a container is a combination of plate and beam systems. The criteria for [...] Read more.
The article discusses a solution to the relevant task of analyzing and designing modular buildings made of blocks to be used in industrial and civil engineering. A block that represents a container is a combination of plate and beam systems. The criteria for its failure include both the strength of the individual elements and the loss of stability in a corrugated web. Methods of engineering analysis are hardly applicable to this system. Numerical analysis based on the finite element method is time-consuming, and this fact limits the number of design options for modular buildings made of blocks. Adjustable machine learning models are proposed as a solution to these problems. Decision trees are made and clustered into a single ensemble depending on the values of the design parameters. Key parameters determining the structures of decision trees include design steel resistance values, types of loads and the number of loadings, and ranges of rolled sheet thickness values. An ensemble of such models is used to take into account the nonlinear strain of elements. Piecewise approximation of the dependencies between components of the stress–strain state is used for this purpose. Linear regression equations are subjected to feature binarization to improve the efficiency of nonlinearity projections. The identification of weight coefficients without laborious search optimization methods is a distinguishing characteristic of the proposed models of steel blocks for modular buildings. A modular building block is used to illustrate the effectiveness of the proposed models. Its purpose is to accommodate a gas compressor of a gas turbine power plant. These machine learning models can accurately spot the stress–strain state for different design parameters, in particular for different corrugated web thickness values. As a result, ensemble models predict the stress–strain state with the coefficient of determination equaling 0.88–0.92. Full article
(This article belongs to the Special Issue Safety and Optimization of Building Structures—2nd Edition)
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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
Cited by 2 | Viewed by 1017
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 778
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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