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Mass Timber Construction in the Workplace
Design of an Instant Vibration-Based Warning System and Its Operation during Relocation Works of Historic Facades
Current Developments and Future Directions in Energy-Efficient Buildings from the Perspective of Building Construction Materials and Enclosure Systems
Integrating Internet of Things (IoT) Approach to Post-Occupancy Evaluation (POE): An Experimental At-the-Moment Occupant Comfort Control System
Exploring the Spatially Heterogeneous Effects of Street-Level Perceived Qualities on Listed Real Estate Prices Using Geographically Weighted Regression (GWR) Modeling

Journal Description

Buildings

Buildings is an international, peer-reviewed, open access journal on building science, building engineering and architecture published monthly online by MDPI. The International Council for Research and Innovation in Building and Construction (CIB) is affiliated with Buildings and their members receive a discount on the article processing charges.

Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
High Visibility: indexed within Scopus, SCIE (Web of Science), Inspec, and other databases.
Journal Rank: JCR - Q2 (Engineering, Civil) / CiteScore - Q1 (Architecture)
Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 17.2 days after submission; acceptance to publication is undertaken in 3.6 days (median values for papers published in this journal in the first half of 2024).
Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
Companion Journal: Architecture.

Impact Factor: 3.1 (2023); 5-Year Impact Factor: 3.2 (2023)

Imprint Information Journal Flyer Open Access ISSN: 2075-5309

Latest Articles

19 pages, 704 KiB

Open AccessArticle

Research on Technological Innovation Capability of Yancheng Prefabricated Construction Industry Based on Patent Information Analysis

by Renyan Lu, Feiting Shi and Houchao Sun

Buildings 2024, 14(9), 2968; https://doi.org/10.3390/buildings14092968 (registering DOI) - 19 Sep 2024

In order to improve the innovation capabilities of Yancheng’s prefabricated construction industry, the Dawei Innojoy patent database was used to search the prefabricated construction technology patent literature data of Yancheng and other major cities in the Yangtze River Delta region from 2012 to [...] Read more.

In order to improve the innovation capabilities of Yancheng’s prefabricated construction industry, the Dawei Innojoy patent database was used to search the prefabricated construction technology patent literature data of Yancheng and other major cities in the Yangtze River Delta region from 2012 to 2022, and the prefabricated construction patents in Yancheng were analyzed from the number of patent applications. Analysis and research were conducted on trends, application type composition, applicants, technical fields, patent legal status, etc. At the same time, the prefabricated building technology innovation capability evaluation system was constructed, and the factor analysis method was used to compare and analyze the prefabricated building technology patent indicators of Yancheng and major cities in the Yangtze River Delta region. The results show that Yancheng has a small number of patent applications, a small proportion of invention patents, a low patent authorization rate, and a low patent conversion rate, and the industry-university-research chain needs to be opened up. Among the cities in the Yangtze River Delta, Yancheng’s comprehensive innovation ability in prefabricated building technology is medium to low, where it lags behind in terms of the scale and quality of technological innovation and ranks at the forefront of technological innovation operations. Based on this, the article puts forward countermeasures and suggestions for Yancheng’s prefabricated building technology patent applications from three levels, macro, meso, and micro, in order to achieve efficient innovation and promote the high-quality development of Yancheng’s new building industrialization. Full article

(This article belongs to the Topic 3D Computer Vision and Smart Building and City, 2nd Volume)

24 pages, 5948 KiB

Open AccessArticle

Predicting Main Characteristics of Reinforced Concrete Buildings Using Machine Learning

by Izzettin Alhalil and Muhammet Fethi Gullu

Buildings 2024, 14(9), 2967; https://doi.org/10.3390/buildings14092967 (registering DOI) - 19 Sep 2024

This paper presents a comprehensive study of five machine learning (ML) algorithms for predicting key characteristics of Reinforced Concrete (RC) structural systems. A novel dataset, ModRes, consisting of 9723 examples derived from modal and response spectrum analyses on masonry-infilled three-dimensional RC buildings, was [...] Read more.

This paper presents a comprehensive study of five machine learning (ML) algorithms for predicting key characteristics of Reinforced Concrete (RC) structural systems. A novel dataset, ModRes, consisting of 9723 examples derived from modal and response spectrum analyses on masonry-infilled three-dimensional RC buildings, was created for ML applications. The primary objective is to develop an ML model using five distinct algorithms from the literature, capable of concurrently predicting torsional irregularity, modal participating mass ratio (MPMR), and the fundamental period in a 3D environment, while accounting for the influence of infill walls. Additionally, the study aims to determine the applicability of pushover analysis (POA) without the need for extensive numerical modeling and analysis. This approach optimizes the preliminary design process with minimal computational effort, providing valuable insights into dynamic and torsional responses during seismic events. The Categorical Boosting algorithm demonstrated outstanding performance, achieving R² values of 0.977 for torsional irregularity, 0.997 for the fundamental period, and 0.923 for MPMR on the test dataset. It also successfully predicted POA applicability with an error rate of only 1.36%. This study highlights the practical application of ML algorithms, underscoring their effectiveness in structural engineering. Full article

(This article belongs to the Section Building Structures)

32 pages, 25612 KiB

Open AccessArticle

Numerical and Experimental Validation for Connecting Nature with Architecture by Mimicking Cranium into a Shell Roof

by Pennarasi Gunasekaran and P. R. Kannan Rajkumar

Buildings 2024, 14(9), 2966; https://doi.org/10.3390/buildings14092966 (registering DOI) - 19 Sep 2024

This study focuses on a structural element bio-mimicked from the human cranium (HC) into a shell element. As the HC is effective in resisting intracranial pressure developed by the brain, a water tank was considered to use a bio-mimicked shape of a shell [...] Read more.

This study focuses on a structural element bio-mimicked from the human cranium (HC) into a shell element. As the HC is effective in resisting intracranial pressure developed by the brain, a water tank was considered to use a bio-mimicked shape of a shell as a roof. An optimized numerical model was validated experimentally and compared with a conventional specimen. The structural behavior of the bio-mimicked specimen is similar and performs more efficiently than the conventional specimen in capacity ratio, crack formation, and load-carrying capacity. Methodology followed: A Computed Tomography (CT) scan of the HC was obtained in Digital Imaging and Communications in Medicine (DICOM) format for finite element analysis (FEA). From the geometric parameters of the HC, the radius of the curvature-to-thickness ratio was derived for the shell. The span and thickness of the shell under two criteria were considered. The spherical and circular shell behaviors were found to be similar to those of the HC, whereas the elliptical shell behavior was not. We studied the shape effect of the HC with the conventional slab and found that the HC shape has an impact on the behavior and is the most efficient. A bio-mimicked mono column was considered as a supporting column for the water tank and analyzed. Overall, adopting this bio-mimicking of the HC into the shell roof connects nature with sustainable architecture. Full article

(This article belongs to the Section Building Structures)

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25 pages, 3500 KiB

Open AccessArticle

A Co-Location Study of 87 Low-Cost Environmental Monitors: Assessing Outliers, Variability, and Uncertainty

by Sanyogita Manu and Adam Rysanek

Buildings 2024, 14(9), 2965; https://doi.org/10.3390/buildings14092965 - 19 Sep 2024

While field research in indoor air quality (IAQ) increasingly uses large numbers of low-cost sensors, detailed validation of each sensor is becoming infeasible, ignored, or undeclared. Questions remain about whether these sensors meet manufacturer or third-party specifications and whether their utility improves with [...] Read more.

While field research in indoor air quality (IAQ) increasingly uses large numbers of low-cost sensors, detailed validation of each sensor is becoming infeasible, ignored, or undeclared. Questions remain about whether these sensors meet manufacturer or third-party specifications and whether their utility improves with some validation, even under imperfect conditions. This study details the outcomes of a co-location experiment with 87 low-cost IAQ monitors, conducted with the objective of verifying their performance in measuring total volatile organic compounds (tVOCs), particulate matter 2.5 (PM_2.5), carbon dioxide (CO₂), temperature, and relative humidity. The monitors were installed next to professional-grade reference IAQ instruments in an office with controlled ventilation. A mixed validation methodology was used, involving outlier detection, uncertainty quantification, and performance metric calculations. Results showed that CO₂, temperature, and humidity sensors reliably met manufacturer specifications, while tVOC sensors had significant accuracy issues, deviating by up to 79% from reference measurements—substantially more than the stated uncertainty of ±20%. PM_2.5 sensors were more consistent but had an error margin of ±27%, compared to the stated ±15%. A total of 5 of the 87 sensors (5.7%) were outliers for at least one IAQ indicator. Despite the need for further long-term validation, this study highlights the importance of performing an experimental evaluation of low-cost IAQ monitors before field deployment. Full article

(This article belongs to the Section Building Energy, Physics, Environment, and Systems)

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18 pages, 9754 KiB

Open AccessArticle

Bridge Surface Defect Localization Based on Panoramic Image Generation and Deep Learning-Assisted Detection Method

by Tao Yin, Guodong Shen, Liang Yin and Guigang Shi

Buildings 2024, 14(9), 2964; https://doi.org/10.3390/buildings14092964 - 19 Sep 2024

Applying unmanned aerial vehicles (UAVs) and vision-based analysis methods to detect bridge surface damage significantly improves inspection efficiency, but the existing techniques have difficulty in accurately locating damage, making it difficult to use the results to assess a bridge’s degree of deterioration. Therefore, [...] Read more.

Applying unmanned aerial vehicles (UAVs) and vision-based analysis methods to detect bridge surface damage significantly improves inspection efficiency, but the existing techniques have difficulty in accurately locating damage, making it difficult to use the results to assess a bridge’s degree of deterioration. Therefore, this study proposes a method to generate panoramic bridge surface images using multi-view images captured by UAVs, in order to automatically identify and locate damage. The main contributions are as follows: (1) We propose a UAV-based image-capturing method for various bridge sections to collect close-range, multi-angle, and overlapping images of the surface; (2) we propose a 3D reconstruction method based on multi-view images to reconstruct a textured bridge model, through which an ultra-high resolution panoramic unfolded image of the bridge surface can be obtained by projecting from multiple angles; (3) we applied the Swin Transformer to optimize the YOLOv8 network and improve the detection accuracy of small-scale damages based on the established bridge damage dataset and employed sliding window segmentation to detect damage in the ultra-high resolution panoramic image. The proposed method was applied to detect surface damage on a three-span concrete bridge. The results indicate that this method automatically generates panoramic images of the bridge bottom, deck, and sides with hundreds of millions of pixels and recognizes damage in the panoramas. In addition, the damage detection accuracy reached 98.7%, which is improved by 13.6% when compared with the original network. Full article

(This article belongs to the Special Issue Intelligence Techniques Applied in Infrastructure, Engineering and Construction)

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23 pages, 3191 KiB

Open AccessArticle

An Investigation on Construction Project Development Planning Delays in South Africa

by Bedan Nyaga Githae, Hakim Hagir and Rebecca Alowo

Buildings 2024, 14(9), 2963; https://doi.org/10.3390/buildings14092963 - 19 Sep 2024

This article aims to determine the causes of the delays in South African construction project planning, discussing the centralised hierarchical planning system factors, multiple agencies/spheres of government regarding building-permit approval factors, and systems and spheres of government/multiple agencies for improving preconstruction project planning [...] Read more.

This article aims to determine the causes of the delays in South African construction project planning, discussing the centralised hierarchical planning system factors, multiple agencies/spheres of government regarding building-permit approval factors, and systems and spheres of government/multiple agencies for improving preconstruction project planning in South Africa. It also describes a one-stop centre as a framework for improving South African preconstruction planning. The nature of planning in South Africa is influenced by many legislative measures. The delays being experienced in the educational infrastructure project have attributed to the backlogs currently existing in the delivery of basic education infrastructure. This study was conducted using a quantitative research design technique to assess the secondary data findings through primary data gathered on about 106 construction industry operatives. The primary data collected from the 106 construction operatives focused on architects, engineers, surveyors, and contractors. The researchers conducted a pilot survey with experts/professionals before an industry-wide survey as a questionnaire pretest. The finalised questionnaire was used as a data-gathering technique in the quantitative study approach. A focus group discussion was held to validate the findings. The collected information was then subjected to quantitative analysis in SPSS Version: 29.0.2.0 to verify the veracity of the research. According to the findings, a one-stop centre would enhance systems and sectors of government/multiple agencies and prevent preconstruction project-planning delays in South Africa. A centralised hierarchical planning system is essential for reducing preconstruction-planning delays and multiple agencies/sectors of the government delaying building-permit approvals. The critical research contribution is in that expanding on what is already known about preconstruction project planning in South Africa, this study shows how crucial it is to identify and understand the factors that influence preconstruction project planning in that country. The limitation, however, is that, regarding South Africa, the available literature indicates that there is a problem with systems responsible for approving construction projects. In conclusion, by proposing a structure known as the one-stop centre (OSC) to address the issues that lead to delays in preconstruction project planning in South Africa, this study offers a significant contribution. Full article

(This article belongs to the Section Construction Management, and Computers & Digitization)

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15 pages, 2045 KiB

Open AccessArticle

An Urban Renewal Design Method Based on Carbon Emissions and Carbon Sink Calculations: A Case Study on an Environmental Improvement Project in the Suzhou Industrial Investment Science and Technology Park

by Liang Zhang, Yuqiu Cai, Sudan Song and Leilei Sun

Buildings 2024, 14(9), 2962; https://doi.org/10.3390/buildings14092962 - 19 Sep 2024

In the process of urban renewal, the high carbon emissions caused by pollution from construction waste and the consumption of materials and energy via “demolition and construction” present significant problems. Calculating carbon emissions and sinks is a prerequisite to carving out a low-carbon [...] Read more.

In the process of urban renewal, the high carbon emissions caused by pollution from construction waste and the consumption of materials and energy via “demolition and construction” present significant problems. Calculating carbon emissions and sinks is a prerequisite to carving out a low-carbon path via urban renewal. In this paper, we take an environmental improvement project in the Suzhou Industrial Investment Science and Technology Park as an example. Under the framework of the entire life cycle, we define the “renewal phase”, which includes “demolition” and “construction”, as the calculation boundary, and use the emission coefficient method as the primary calculation approach to assess carbon emissions and sinks. We construct a design-oriented carbon revenue and expenditure estimation system based on the BIM model. After its application in empirical cases, the results show the following: ① The building carbon emissions of Scheme A are 342 t higher than those of Scheme B, due to the fact that the “demolition and construction” works in the former increased by 6000 m² compared to the latter. ② The landscape carbon emissions of Scheme B are 269 t higher than those of Scheme A, due to the addition of a 2500 m² reinforced concrete overhead walking platform. ③ The annual carbon sink of Scheme A is six times higher than that of Scheme B, due to the fact that the number of trees and shrubs in the former is five-to-six times greater than in the latter. The number of trees planted plays a decisive role in enhancing the carbon sink benefit. ④ In the year during which the renewal project was implemented, the difference in carbon emissions between Scheme A and Scheme B was 72.9 t. By the 16th year, the difference in carbon emissions between the two schemes approached zero, and the carbon reduction advantages of Scheme A became more pronounced over the entire life cycle thereafter. Finally, this article summarizes four low-carbon design strategies for industrial park renewal projects: rational construction and demolition, three-dimensional parking, low-carbon materials, and plant carbon sequestration. In the context of inventory renewal, this article makes a significant contribution in terms of carbon footprint control and the “dual-carbon” goal. Full article

(This article belongs to the Section Building Energy, Physics, Environment, and Systems)

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17 pages, 8655 KiB

Open AccessArticle

Mechanical Performances of Concrete-Filled Steel Pipe Composite Segments in Complex Geological Conditions

by Xu Chang, Jiaqi Sun and Liqun Guo

Buildings 2024, 14(9), 2961; https://doi.org/10.3390/buildings14092961 - 19 Sep 2024

When shield tunnels are under complex geological conditions, tunnel damage, decreased structural performance, and shield tunnel deformation and destruction may occur. Therefore, a new type of composite segment and combined splicing joint were suggested and experimentally investigated in this study. According to the [...] Read more.

When shield tunnels are under complex geological conditions, tunnel damage, decreased structural performance, and shield tunnel deformation and destruction may occur. Therefore, a new type of composite segment and combined splicing joint were suggested and experimentally investigated in this study. According to the test results, the new composite segment effectively enhanced the load capacity of the segment, and the yield and ultimate loads of the segment were increased. Compared with the reference specimen, the ultimate load capacities of the proposed segments with different numbers were 23.8%, 50.0%, and 64.3% greater. Moreover, the combined splicing joint enhanced the initial bending stiffness and load capacity of the segment joint, reduced the opening displacement, and improved the rotational stiffness of the segment joint. The addition of a plug-in joint at the segment joint increased its load capacity by approximately 25%. A parametric study showed that the number and posit ion of the plug-in joint clearly affected the load capacity of the segment joint. In addition to the above test results, reasonable theoretical formulas for the new composite segment and combined splicing joint are given in this paper. Full article

(This article belongs to the Section Building Structures)

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22 pages, 45764 KiB

Open AccessArticle

Thermography Applied to the Adhesion Phenomenon of Mortars with Additions of Submerged Arc Welding (SAW) Slag

by Érica Sousa, Alef Santana, Millena Moura, João M. P. Q. Delgado and Romildo Berenguer

Buildings 2024, 14(9), 2960; https://doi.org/10.3390/buildings14092960 - 19 Sep 2024

In this work, the effects of the mixing water loss capacity of hydrated lime mortars with different dosages were analysed—type O (mix 1:2:9), type N (mix 1:1:6), and type M (mix 1:0.5:4.5), with additions of submerged arc welding (SAW) slag. Infrared thermography tests [...] Read more.

In this work, the effects of the mixing water loss capacity of hydrated lime mortars with different dosages were analysed—type O (mix 1:2:9), type N (mix 1:1:6), and type M (mix 1:0.5:4.5), with additions of submerged arc welding (SAW) slag. Infrared thermography tests and optical and scanning electronic microscopy analyses of the mortars were also carried out. The experimental results showed that the mortar samples with additions of SAW slag type M, using low-cost materials, proved to be in economic and technical terms (adhesion strength) the best solution, even more so if a spatter dash layer is used, a fact that increases the adhesion strength even more. Also, the infrared thermographic results revealed that the ability of the mortar paste to yield water to the ceramic substrate in the interface regions is a relevant factor in the adhesion of these coatings. Finally, the analyses by scanning electron microscopy and optical microscopy revealed that the ability to release water to the substrate is related to the hydration of the mortar and its anchoring capacity. Furthermore, the analyses carried out demonstrated that the adhesion of the mortars is influenced and increased with the application of a layer of splashes, as the pores of the substrate become more refined and better filled with the applied mortar. Full article

(This article belongs to the Section Building Materials, and Repair & Renovation)

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12 pages, 2001 KiB

Open AccessArticle

A Condition Assessment Tool for Steel Bridge Deck Pavement Systems Based on Data Balancing Methods and Machine Learning Algorithms

by Yazhou Wei, Rongqing Ji, Qingfu Li and Zongming Song

Buildings 2024, 14(9), 2959; https://doi.org/10.3390/buildings14092959 - 19 Sep 2024

The primary challenge in the operation of steel deck pavement systems lies in the inspection and assessment of their condition. Traditionally, manual inspection methods are employed. However, these approaches are not only time-consuming and labor-intensive but also prone to human error. As a [...] Read more.

The primary challenge in the operation of steel deck pavement systems lies in the inspection and assessment of their condition. Traditionally, manual inspection methods are employed. However, these approaches are not only time-consuming and labor-intensive but also prone to human error. As a result, integrating data-driven machine learning technologies into the evaluation of pavement systems presents a significant advantage in addressing these issues. This study proposes a decision-making tool for estimating the condition levels of steel bridge deck pavement systems by employing classification techniques. To address the issue of class imbalance in the dataset, the SMOTE algorithm is utilized. Additionally, seven different machine learning methods—Light Gradient Boosting Machine, Extreme Gradient Boosting, Random Forest, Adaptive Boosting, K-Nearest Neighbor, Multilayer Perceptron, and Logistic Regression—are applied for training. Comparative analysis reveals that the Light Gradient Boosting performs optimally, achieving classification accuracies of 0.841 and 0.929 on the original and synthetic datasets, respectively. Full article

(This article belongs to the Section Building Structures)

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22 pages, 5586 KiB

Open AccessArticle

Propagation Effect Analysis of Existing Cracks in Box Girder Bridges Based on the Criterion of Compound Crack Propagation

by Yong-Jian Chen, Xian-Cheng Huang, Shi-Zheng Chen, Li-Yuan Wang, Ji-Wei Zhong and Hui Cheng

Buildings 2024, 14(9), 2958; https://doi.org/10.3390/buildings14092958 - 19 Sep 2024

Cracking in concrete box girder bridges will have a significant impact on the safety and durability of the structure, and many box girder bridges which are in service have undergone varying degrees of cracking. Currently, the safety design of actual bridge projects place [...] Read more.

Cracking in concrete box girder bridges will have a significant impact on the safety and durability of the structure, and many box girder bridges which are in service have undergone varying degrees of cracking. Currently, the safety design of actual bridge projects place an emphasis on the stress or the load value of a cross section at the limit value specified in the code for safety control. This design method assumes that the member itself is of uniform and continuous material and is internally undamaged. However, the bridge structure is more or less cracked to varying degrees during the period from casting to construction to operation of the concrete members. In this paper, a finite element computational model of a three-span prestressed concrete box girder bridge with existing cracks is established based on the fracture mechanics theory, and the critical parameters of crack extension are introduced to evaluate the extension state of cracks. At the same time, the extended stability of the existing cracks of the box girder bridge is analyzed by considering the temperature effect, vehicle loading, and prestressing loss, and the sensitivity of crack extension under each working condition is investigated. The results show that, with the increase in crack length and depth, the crack expansion is promoted, but the effect is relatively small, and the maximum stress intensity factor is only 6.48 MPa mm^1/2. Under the multi-factor coupling effect, the cracks show a composite crack expansion dominated by type I cracks, the longitudinal cracks of the existing base plate are in a stable state, the maximum value of the crack expansion critical parameter of the vertical cracks of the webs reaches 1.087, and there is a tendency to expand locally. The maximum value of the critical parameter for crack extension of the vertical crack in the web plate reaches 1.087, and there is a tendency towards local expansion. The crack extension evaluation criteria proposed in this paper have a certain reference value for crack extension research on similar concrete box girder bridges and provide a scientific basis for the optimized design of similar bridges. Full article

(This article belongs to the Topic Condition Perception and Performance Evaluation of Engineering Structures)

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30 pages, 308 KiB

Open AccessArticle

A Survey and Research on the Use of Artificial Intelligence by Chinese Design-College Students

by Yang Song and Shaochen Wang

Buildings 2024, 14(9), 2957; https://doi.org/10.3390/buildings14092957 - 19 Sep 2024

The relationship between AI and design has attracted extensive academic attention and research, and the future relationship between AI and designers relies on current design students’ knowledge of AI, in addition to technological developments. To clarify the basic situation of Chinese design-college students’ [...] Read more.

The relationship between AI and design has attracted extensive academic attention and research, and the future relationship between AI and designers relies on current design students’ knowledge of AI, in addition to technological developments. To clarify the basic situation of Chinese design-college students’ use of AI software, the basic situation and status of using AI software to participate in design work, and the current relationship with AI, this study constructs a questionnaire on the status of the use of AI programs, with the help of the UTAUT model and the general program of design as a basis. The results of the research on 487 Chinese design-college students were analyzed by frequency analysis, descriptive statistics, etc., to clarify that currently more than 60% of design students have used AI programs, which are mainly used for data collection; providing ideas for design, e.g., when brainstorming; and conceptual ideas for design. Moreover, students generally believe that AI helps to improve personal skills and work efficiency, but the in-depth application and reliance on AI is relatively low; students hold anxiety about the development of AI, especially those who have not been exposed to AI. The education sector should focus on popularizing and deepening AI education, as well as helping students establish a correct concept of AI usage. Full article

(This article belongs to the Section Architectural Design, Urban Science, and Real Estate)

18 pages, 8423 KiB

Open AccessArticle

A Comparative Study of Machine Learning and Conventional Techniques in Predicting Compressive Strength of Concrete with Eggshell and Glass Powder Additives

by Yan Gao and Ruihan Ma

Buildings 2024, 14(9), 2956; https://doi.org/10.3390/buildings14092956 - 19 Sep 2024

Recent research has focused on assessing the effectiveness of response surface methodology (RSM), a non-machine learning technique, and artificial neural networks (ANN), a machine learning approach, for predicting concrete performance. This research aims to predict and simulate the compressive strength of concrete that [...] Read more.

Recent research has focused on assessing the effectiveness of response surface methodology (RSM), a non-machine learning technique, and artificial neural networks (ANN), a machine learning approach, for predicting concrete performance. This research aims to predict and simulate the compressive strength of concrete that replaces cement and fine aggregate with waste materials such as eggshell powder (ESP) and waste glass powder (WGP) for sustainable construction materials. In order to ensure concrete’s durability and structural integrity, a compressive strength evaluation is essential. Precise predictions maximize efficiency and advance sustainability, particularly when dealing with waste materials like ESP and WGP. The response surface methodology (RSM) and artificial neural network (ANN) techniques are used to accomplish this for practical applications in the built environment. A dataset comprising previously published research was used to assess ANN and RSM’s predictive and generalization abilities. To model and improve the model, ANN used seven independent variables, while three variables, cement, waste glass powder, and eggshell powder, improved the RSM. Both the ANN and RSM techniques are effective instruments for predicting compressive strength, according to the statistical results, which include mean squared error (MSE), determination coefficient (R²), and adjusted coefficient (R² adj). RSM was able to achieve the R² by 0.8729 and 0.7532 for compressive strength, while the accuracy of the results for ANN was 0.907 and 0.956 for compressive strength. Moreover, the correlation between ANN and RSM models and experimental data is high. The artificial neural network model, however, exhibits superior accuracy. Full article

(This article belongs to the Section Building Materials, and Repair & Renovation)

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12 pages, 4220 KiB

Open AccessArticle

Assessing the Reliability of Truss Structures Based on the Bound Method and Collectively Exhaustive Events

by Limei Zhang and Tao Yi

Buildings 2024, 14(9), 2955; https://doi.org/10.3390/buildings14092955 - 19 Sep 2024

Damage to long-span truss structures may cause structural deformation, load-capacity reduction, and even collapse. The design service life of truss structures is usually 50 years, so evaluating their reliability is of the utmost importance. Reliability considers the probability of failure as an analysis [...] Read more.

Damage to long-span truss structures may cause structural deformation, load-capacity reduction, and even collapse. The design service life of truss structures is usually 50 years, so evaluating their reliability is of the utmost importance. Reliability considers the probability of failure as an analysis index. In calculating the probability of structural failure, important components are first selected to form a failure path, and then the failure probability corresponding to the failure path is calculated. A truss structure has many important components and failure paths, so calculating this probability requires extensive and thorough work. As a result, we propose selecting the important components via the approximation method to reduce the influence of the threshold of approximation. Collectively exhaustive events were established using the differential equivalent recursive algorithm to calculate the probability of structural failure. This process was considerably simplified, and validity was verified via a reliability analysis involving a three-bar truss structure, a plane truss structure, and a square pyramid truss structure. This method is suitable for selecting important components of regular flat truss structures. Full article

(This article belongs to the Special Issue Advanced Analysis and Design for Steel Structure Stability)

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13 pages, 3555 KiB

Open AccessArticle

Optimizing Construction Spoil Reactivity for Cementitious Applications: Effects of Thermal Treatment and Alkaline Activation

by Kai Wang and Xiaoxiong Zha

Buildings 2024, 14(9), 2954; https://doi.org/10.3390/buildings14092954 - 19 Sep 2024

Construction spoil (CS), a prevalent type of construction and demolition waste, is characterized by high production volumes and substantial stockpiles. It contaminates water, soil, and air, and it can also trigger natural disasters such as landslides and debris flows. With the advent of [...] Read more.

Construction spoil (CS), a prevalent type of construction and demolition waste, is characterized by high production volumes and substantial stockpiles. It contaminates water, soil, and air, and it can also trigger natural disasters such as landslides and debris flows. With the advent of alkali activation technology, utilizing CS as a precursor for alkali-activated materials (AAMs) or supplementary cementitious materials (SCMs) presents a novel approach for managing this waste. Currently, the low reactivity of CS remains a significant constraint to its high-value-added resource utilization in the field of construction materials. Researchers have attempted various methods to enhance its reactivity, including grinding, calcination, and the addition of fluxing agents. However, there is no consensus on the optimal calcination temperature and alkali concentration, which significantly limits the large-scale application of CS. This study investigates the effects of the calcination temperature and alkali concentration on the mechanical properties of CS–cement mortar specimens and the ion dissolution performance of CS in alkali solutions. Mortar strength tests and ICP ion dissolution tests are conducted to quantitatively assess the reactivity of CS. The results indicate that, compared to uncalcined CS, the ion dissolution performance of calcined CS is significantly enhanced. The dissolution amounts of active aluminum, silicon, and calcium are increased by up to 420.06%, 195.81%, and 256.00%, respectively. The optimal calcination temperature for CS is determined to be 750 °C, and the most suitable alkali concentration is found to be 6 M. Furthermore, since the Al O bond is weaker and more easily broken than the Si O bond, the dissolution amount and release rate of active aluminum components in calcined CS are substantially higher than those of active silicon components. This finding indicates significant limitations in using CS solely as a precursor, emphasizing that an adequate supply of silicon and calcium sources is essential when preparing CS-dominated AAMs. Full article

(This article belongs to the Special Issue Research on the Performance of Traditional, New and Potential Building Materials: 2nd Edition)

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16 pages, 1242 KiB

Open AccessArticle

How Socially Sustainable Is the Institutional Care Environment in China: A Content Analysis of Media Reporting

by Kun Wang, Yongjian Ke and Shankar Sankaran

Buildings 2024, 14(9), 2953; https://doi.org/10.3390/buildings14092953 - 19 Sep 2024

The multiple changes in population, economy, and social structure have significantly impacted China’s traditional home-based elderly care and social welfare. The importance of institutional care is becoming increasingly prominent. One of the critical considerations for the development of institutional care is its social [...] Read more.

The multiple changes in population, economy, and social structure have significantly impacted China’s traditional home-based elderly care and social welfare. The importance of institutional care is becoming increasingly prominent. One of the critical considerations for the development of institutional care is its social sustainability, which pursues the realization of human well-being and aims to bring about good quality of life. However, this issue has not received due attention. The purpose of this paper is to investigate the social sustainability of the institutional care environment. Based on stakeholder theory and content analysis, this research identified and discussed the problems of the institutional care environment mentioned in the news coverage on eight major Chinese portal websites. The results indicate that seven of the eight problems that employees, the elderly, and their relatives encounter in providing and receiving elderly care services in the institutional environment are related to social sustainability. Employees’ health and safety is a concern; they lack education and training opportunities and have been unequally treated in the employment process. The elderly’s psychological, physical, and safety needs should also be further satisfied. Unequal access to institutional care and the inaccessibility of elderly care institutions is another problem that needs to be solved urgently. These findings will help government departments and investors become aware of the issues and implement countermeasures to create a successful, socially sustainable institutional care environment. They can also provide valuable insights for the elderly and their relatives in choosing appropriate elderly care institutions. Full article

(This article belongs to the Special Issue Human-Centric Space Design: Occupant Comfort, Wellbeing, and Post-occupancy Evaluation of Multi-Scale Built Environment)

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19 pages, 6967 KiB

Open AccessArticle

Study on Freeze–Thaw Resistance of Cement Concrete with Manufactured Sand Based on BP Neural Network

by Hengyu Wu and Qiju Gao

Buildings 2024, 14(9), 2952; https://doi.org/10.3390/buildings14092952 - 19 Sep 2024

In this study, experiments were conducted on the freeze–thaw performance of manufactured sand cement concrete with different sand ratios and fly ash contents. The research found that during 200 freeze–thaw cycles, as the fly ash content increased, the concrete exhibited a higher mass [...] Read more.

In this study, experiments were conducted on the freeze–thaw performance of manufactured sand cement concrete with different sand ratios and fly ash contents. The research found that during 200 freeze–thaw cycles, as the fly ash content increased, the concrete exhibited a higher mass loss rate and a decline in the relative dynamic modulus of elasticity. This was due to the lower activity of SiO₂ and Al₂O₃ in the fly ash, which reduced the hydration products. Incorporating an optimal amount of manufactured sand can increase the density of concrete, thereby improving its resistance to freeze–thaw cycles. However, when the content of manufactured sand was high, its large surface area could interfere with the hydration process and reduce strength, thereby diminishing the freeze–thaw resistance of the concrete. Given that studying the freeze–thaw resistance of manufactured sand concrete is time-consuming and influenced by many factors, a prediction model based on a BP (back propagation) neural network was developed to estimate the mass loss rate and the relative dynamic modulus of elasticity following freeze–thaw cycles. After validation, the model was found to be highly reliable and could serve as a foundation for mix design decisions and freeze–thaw performance prediction of manufactured sand cement concrete. Full article

(This article belongs to the Section Building Materials, and Repair & Renovation)

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17 pages, 10971 KiB

Open AccessArticle

Experimental Study on Reinforcement Properties of Tension-Resistant Reinforced Soil Retaining Wall

by Yantao Wang, Guangqing Yang, Lei Wang, Xujia Li and Guomu Jiao

Buildings 2024, 14(9), 2951; https://doi.org/10.3390/buildings14092951 - 18 Sep 2024

The tensioned reinforced soil retaining wall, a novel retaining structure, utilizes either anchors or geosynthetic materials as reinforcements that contribute to load-bearing and friction within the structure. This study aims to explore the tension distribution and strain patterns in the reinforcements, and their [...] Read more.

The tensioned reinforced soil retaining wall, a novel retaining structure, utilizes either anchors or geosynthetic materials as reinforcements that contribute to load-bearing and friction within the structure. This study aims to explore the tension distribution and strain patterns in the reinforcements, and their influence on the reinforced soil retaining walls. To this end, tensile, direct shear, and pullout tests were conducted on GeoStrap@5-50 geotextile strips and TGDG130HDPE geogrids to evaluate the tensile strength and interface strength between the reinforcement and the soil. The characteristics of the reinforcement–soil interface and the deformation behavior under stress were examined, with a comparative analysis of the technical merits of the two types of reinforcements. The results indicate that both the geotextile strips and geogrids enhanced the strength of the reinforced soil, primarily by increasing cohesion. The GeoStrap@5-50 geotextile strips exhibited superior tensile strength compared to the TGDG130HDPE geogrids; the reinforcement with the geotextile and geogrids both enhanced the cohesion of the standard sand, albeit with a slight decrease in the internal friction angle, by 4.6% and 3.1%, respectively, offering enhanced mechanical properties and economic value in reinforced soil retaining wall applications. Full article

(This article belongs to the Section Building Structures)

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20 pages, 6697 KiB

Open AccessArticle

Street Puppet Theatre Shows on the Façades of Commercial Buildings as a Novel Stimulator for Social Gatherings in Smart Cities

by Reza Askarizad, Mana Dastoum and Chiara Garau

Buildings 2024, 14(9), 2950; https://doi.org/10.3390/buildings14092950 - 18 Sep 2024

This study investigates the innovative use of street puppet theatre performances on the façades of commercial buildings to stimulate social gatherings in smart cities. This research investigates the impact of a unique musical puppet show held throughout the 2024 holiday season in the [...] Read more.

This study investigates the innovative use of street puppet theatre performances on the façades of commercial buildings to stimulate social gatherings in smart cities. This research investigates the impact of a unique musical puppet show held throughout the 2024 holiday season in the well-known shopping mall El Corte Inglés in Madrid, Spain. This study utilises both quantitative and qualitative methodologies, such as space syntax analysis and empirical observations. It uses the UCL Depthmap 10 software program to assess urban morphology and identify integrated and segregated areas. Observations and video recordings were conducted to analyse social gatherings and behaviours during the performances. The findings reveal that these performances attract diverse audiences and foster social engagement, transforming commercial façades into vibrant public spaces. The study concludes that such innovative uses of urban architecture can significantly enhance the sociability of detached and segregated urban spaces. The research demonstrates that this particular dynamic façade not only fosters social sustainability by creating lively urban spaces but also contributes to economic sustainability by attracting potential customers to commercial centres. This research advances the discourse on smart city development and public space utilisation, offering valuable insights for urban planners and policymakers on leveraging interactive urban façades to enhance public engagement and revitalise underutilised spaces. Full article

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20 pages, 11273 KiB

Open AccessArticle

Basic Mechanical Properties of Self-Compacting Concrete Prepared with Aeolian Sand and Recycled Coarse Aggregate

by Shiqi Zheng, Qing Liu, Fengxia Han, Shan Liu, Tong Han and Hao Yan

Buildings 2024, 14(9), 2949; https://doi.org/10.3390/buildings14092949 - 18 Sep 2024

To protect the environment and reduce the consumption of natural resources, this study investigated the performance of self-compacting concrete (SCC) utilizing aeolian sand (AS) as a replacement for fine aggregate and recycled coarse aggregate (RCA) as a replacement for natural coarse aggregate. Twelve [...] Read more.

To protect the environment and reduce the consumption of natural resources, this study investigated the performance of self-compacting concrete (SCC) utilizing aeolian sand (AS) as a replacement for fine aggregate and recycled coarse aggregate (RCA) as a replacement for natural coarse aggregate. Twelve mixing ratios were prepared, with AS replacement ratios at 0, 20%, 40%, and 60% and RCA replacement ratios at 0, 25%, and 50%. The evaluation primarily focused on workability, uniaxial compressive strength, split tensile strength, stress–strain curve, modulus of elasticity, and axial compressive strength. The results indicated that both AS and RCA can enhance the performance of SCC at appropriate replacement ratios, and a 20% AS and 50% RCA replacement ratio significantly improved the performance of SCC. In addition, the effects of AS and RCA replacements on SCC were evaluated by several performance indexes, which provides a basis for subsequent experimental studies and demonstrates the feasibility of incorporating AS and RCA into SCC. Full article

(This article belongs to the Special Issue Low-Carbon Concrete with Different Sources of Solid Waste)

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