Buildings

In this study, the multi-mode resource-constrained multi-project scheduling problems (MMRCMPSPs) considering supply management and sustainable approach in the construction industry under uncertain conditions have been investigated using evidence theory to mathematical modeling and solving by multi-objective optimization algorithms. In this regard, a multi-objective mathematical model has been proposed, in which the first objective function aims to maximize a weighted selection of projects based on economic, environmental, technical, social, organizational, and competitive factors; the second objective function is focused on maximizing profit, and the third objective function is aimed at minimizing the risk of supply management. Moreover, various components, such as interest rates, carbon penalties, and other implementation limitations and additional constraints, have also been considered in the modeling and mathematical relationships to improve the model’s performance and make it more relevant to real-world conditions and related issues, leading to better practical applications. In the mathematical modeling adopted, the processing time of project activities has been considered uncertain, and the evidence theory has been utilized. This method can provide a flexible and rational approach based on evidence and knowledge in the face of uncertainty. In addition, to solve the proposed multi-objective mathematical model, metaheuristic optimization algorithms, such as the differential evolution (DE) algorithm based on the Pareto archive, have been used, and for evaluating the results, the non-dominated sorting genetic algorithm II (NSGA-II) has also been employed. Furthermore, the results have been compared based on multi-objective evaluation criteria, such as quality metric (QM), spacing metric (SM), and diversity metric (DM). It is worth noting that to investigate the performance and application of the proposed model, multiple evaluations have been conducted on sample problems with different dimensions, as well as a case study on residential apartment construction projects by a contracting company. In this respect, the answers obtained from solving the model using the multi-objective DE algorithm were better and superior to the NSGA-II algorithm and had a more favorable performance. Generally, the results indicate that using the integrated multi-objective mathematical model in the present research for managing and scheduling multi-mode resource-constrained multi-project problems, especially in the construction industry, can lead to an optimal state consistent with the desired objectives and can significantly improve the progress and completion of projects. Full article

Taking the main beams of historical buildings as the engineering background, existing theoretical research results related to influencing structural factors were used along with numerical simulation and data fusion methods to examine their integrity. Thus, the application of multifactor data fusion in the safety assessment of the main beams of historical buildings was performed. On the basis of existing structural safety assessment methods, neural networks and rough set theory were combined and applied to the safety assessment of the main beams of historical buildings. The bearing capacity of the main beams was divided into five levels according to the degree to which they met current requirements. The safety assessment database established by a Kohonen neural network was clustered. Thus, the specific evaluation indices corresponding to the five types of safety levels were presented. The rough neural network algorithm, integrating the rough set and neural network, was applied for data fusion with this database. The attribute reduction function of the rough set was used to reduce the input dimension of the neural network, which was trained, underwent a learning process, and then used for predictions. The trained neural network was applied for the safety assessment of the main beams of historical buildings, and six specific attribute index values corresponding to the main beams were directly input to obtain the current safety statuses of the buildings. Corresponding management suggestions were also provided. Full article

The construction industry is increasingly focused on sustainability, with a particular emphasis on reducing the environmental impact of cement production. One approach to this problem is to use recycled materials and explore eco-friendly raw materials, such as alumino-silicate by-products like fly ash, which can be used as raw materials for geopolymer concrete. To enhance the ductility, failure mode, and toughness of the geopolymer, researchers have added crumb rubber processed from scrap tires as partial replacement to fine aggregate of the geopolymer. Therefore, this study aims to develop rubberized geopolymer concrete (RGC) by partially replacing the fine aggregate with crumb rubber (CR). To optimize the mechanical properties of RGC, response surface methodology (RSM) has been used to develop 13 mixes with different levels and proportions of CR (10–30% partial replacement of fine aggregate by volume) and sodium hydroxide molarity (10–14 M) as input variables. The results showed that the strength properties increased as the molarity of NaOH increased, while the opposite trend was observed with CR. The maximum values for compressive strength, flexural strength, and uniaxial tensile strength were found to be 25 MPa, 3.1 MPa, and 0.41 MPa, respectively. Response surface models of the mechanical strengths, which were validated using ANOVA with high R² values of 72–99%, have been developed. It has been found that using 10% CR with 14 M sodium hydroxide resulting in the best mechanical properties for RGC, which was validated with experimental tests. The result of the multi-objective optimization indicated that the optimum addition level for NaOH is 14 M, and the fine aggregate replacement level with CR is 10% in order to achieve a rubberized geopolymer suitable for structural applications. Full article

As urbanization continues to advance rapidly, the emergence of biophilic design offers a positive perspective to address the alienation between humans and nature, becoming a hot research topic in areas related to human living environments. Biophilic design, as a design concept inspired by nature, has positive significance in promoting the development of ecological diversity and improving human physical and mental health. This paper makes a comparative analysis of two of China’s residential communities in the same high-density environment through the main influencing factors of plot ratio, greening rate, external facades environments, and internal living space. Starting from the five senses of the human body, namely, sight, hearing, touch, smell, and taste, this paper aims to investigate the design of living spaces through the lens of biophilic design, and proposes a biophilic design model, along with strategies and recommendations tailored to high-density urban environments, in the hope of serving as a valuable reference and source of inspiration for future healthy dwelling design. Full article

Stability calculation is the main objective during the analysis of domes. To investigate the effects of the initial defect, geometric nonlinearity, and material nonlinearity on the stability performance of different dome structures, 60 m numerical models were built and optimized by an iterative force-finding APDL program. Then, linear buckling analysis, geometric nonlinear stability analysis, geometric nonlinear stability analysis with initial defects, and dual nonlinear analysis with initial defects were discussed to compare the stability performance of ridge-beam cable domes (RCDs), suspen-domes, and conventional cable domes via finite element analysis. The results show that the buckling loads all follow the order of initial defect + dual nonlinear analysis < initial defect + geometric nonlinear analysis < geometric nonlinear analysis < linear buckling. The addition of ridge beams improves the overall stability and transforms the instability modes from local concave instability to overall torsional buckling. The ultimate load amplification coefficients of the RCD are close to those of the suspen-dome, while the vertical displacements of the RCD are more than those of the conventional cable dome, so the RCD has sufficient stiffness to reduce local displacement. Under 2–3 load combinations, internal ridge beams change from a tensile-bending state to a compressive-bending state, causing the entire instability of the RCD afterwards. Full article

Despite the excellent ductility and energy absorption properties of engineered cementitious composites (ECCs), a low modulus of elasticity and excessive drying shrinkage remain some of its major disadvantages. With the current trend in the application of nanotechnology in cementitious composites research, the effect of graphene oxide (GO) on the properties of ECCs is yet to be fully investigated, despite its promising results in ordinary cement paste, mortar, and concrete. ECCs need extensive material tailoring to provide the required mechanical characteristics and controlled fracture size with strain-hardening behavior. Striking a balance between these crucial hardened aspects of ECC without compromising any desired properties is a challenge. Hence, the main aim of the study reported in this paper is to use the response surface methodology (RSM) multi-objective optimization technique to identify an appropriate GO content via the weight of cement and also the volume fraction of polyvinyl alcohol (PVA) fiber as input variables that positively impact ECCs’ properties. Using RSM’s central composite design (CCD), 13 mixtures of various combinations of the variables (GO: 0.05%, 0.065%, 0.08%; PVA: 1%, 1.5%, 2%) were developed. Six responses were studied, including compressive strength, direct tensile strength, tensile capacity, flexural strength, modulus of elasticity, Poisson’s ratio, and drying shrinkage. Moreover, the microstructural properties of the composites were assessed using field-emission scanning electron microscopy (FESEM) and mercury intrusion porosimetry (MIP). The outcomes revealed that all the properties of ECCs were significantly enhanced by adding an optimum amount of 0.05% GO and 1–1.5% PVA fiber volume fractions. A maximum increase in 30%, 35%, 49%, and 33.9% in the compressive strength, direct tensile strength, flexural strength, and modulus of elasticity, respectively, of the mixes with 0.05% GO addition was recorded. It is demonstrated that the use of 0.05% GO as a nanoscale particle can provide good outputs for the construction industry. Full article

A low stiffness makes long-span suspension bridges sensitive to loads, and this sensitivity is particularly significant for wind-induced nonlinear vibrations. In the present paper, nonlinear vibrations of suspension bridges under the combined effects of static and vortex-induced loads are explored using the nonlinear partial differential–integral equation that models the plane bending motion of suspension bridges. First, we discretized the differential–integral equation through the Galerkin method to obtain the nonlinear ordinary differential equation that describes the vortex-induced vibrations of the bridges at the first-order symmetric bending mode. Then, the approximate analytical solution of the ordinary differential equation was obtained using the multiple scales method. Finally, the analytical solution was applied to reveal the relationships between the vibration amplitude and other parameters, such as the static wind load, the frequency of dynamic load, structural stiffness, and damping. The results show that the static wind load slightly impacts the bridge’s vibrations if its influence on the natural frequency of bridges is ignored. However, the bridge’s vibrations are sensitive to the load frequency, structural stiffness, and damping. The vibration amplitude, as a result, may dramatically increase if the three parameters decrease. Full article

The paper focuses on the analysis of the values of the static modulus of deformation obtained by the application of the test procedure specified in the methodology for the diagnostics of the sub-ballast layers used for German railways (DIN 18 134) and the Railways of the Slovak Republic (Regulation TS4). The purpose of the study was to determine the correlation between the measured values of the static modulus of deformation according to the above-mentioned methodologies based on a series of experimental measurements on an experimental field built at a scale of 1:1. It also aimed to develop a numerical model characterising the behaviour of the loaded environment during the experimental measurements using the finite element method, which can subsequently be used for the design of the structural composition of the sub-ballast layers. For the purpose of the experimental measurements, a sub-ballast layer of 0/31.5 mm crushed aggregate of different design thicknesses was applied to the sub-ballast layers. A polynomial dependence with a high value of the reliability coefficient can be found between the results of the static modulus of deformation obtained using the mentioned measurement methodologies during the quality inspection of the implemented construction works. This dependence is valid for the specific boundary conditions of the experimental measurements performed (subsoil of clay with gravel admixture and the sub-ballast crushed aggregate layer of 0/31.5 mm dolomitic gravel). In the future, establishing correlation dependencies for other boundary conditions and structural material compositions can be considered. Full article

Nature is the major source and basis for architectural design. It is beyond human ability to create the same unlimited changes and dimensions. One of the key actors in minimizing negative impacts on nature and the environment is the architect. Due to the different uses of nature in architectural design and the interdisciplinarity between the approaches and aspects of nature, this study aimed to explore the contributions of nature-based strategies to the architectural design domain and identify the comprehensive relationship between nature and architecture. Through using logical argument, the nature-based strategies of architectural design were classified according to four categories of architectural design principles in a predicted model. For testing and validating the model, one strategy, which included nine nature-based approaches of architectural design with 23 aspects, was evaluated, and the scopes of the approaches were identified. VOSviewer was used for data analysis, and the survey questionnaire method was used for the focus group of architects to evaluate Erbil City’s architectural design. In this survey, 328 responses were received, which were ranked using the four-point Likert scale (most of the time, some of the time, seldom, and never), and the t-test from SPSS software was used to compare the approaches of the selected nature-based strategy. The passive design was the only approach with a positive value from the t-test (3.805) with a p-value of 0.000. Among these 23 evaluated aspects, natural ventilation received the highest mean value (1.91). Full article

In order to predict the settlement of self-compacting solidified soil in foundation pit backfilling, finite element software is used to study the influence of soil properties and the surrounding structural properties of the foundation pit on the settlement of backfilled self-compacting solidified soil based on a foundation pit project in the city of Nanjing. The degree of influence of various factors influencing settlement is considered, a grey relational grade analysis is conducted, and input layer parameters of the neural network are determined based on the results of the grey relational grade analysis. Based on the GA-BP neural network model, the settlement of soil is predicted using numerical simulation results. The results reveal that the settlement and structural disturbance of self-compacting solidified soil after backfilling are smaller than those of fine silty sand; self-compacting solidified soil significantly improves the engineering performance of excavated soil. In the grey relational grade analysis, the six influencing factors that have high correlation with soil settlement can be used as input layer parameters for the neural network model. Among them, the correlation degree between elastic modulus and soil settlement is the highest, reaching 0.8402. The correlation degrees of the remaining five influencing factors are above 0.5, and the values are close. The GA-BP neural network can improve the overfitting situation of a BP neural network trapped in local optima, with R² reaching 0.9999 and RMSE only 0.0018 mm, achieving high-precision prediction of settlement of self-compacting solidified soil. Full article

Precast prestressed concrete hollow-core slabs (HCUs) are structural elements with less self-weight, providing improved structural effectiveness in withstanding the straining action and allowing for a long span. This study investigated the additional strand slips and developed machine learning (ML) models for evaluating the final strand slips (Śf) of the precast HCUs. Two groups of HCUs, with nominal widths of 1.2 m and 0.55 m, were subjected to flexural loading conditions. One sample from each group was selected to form composite specimens by casting a concrete topping slab, and the restrain mechanism was attached at the ends of the additional HCU specimens. The experimental datasets used to train the ML models, including the support vector machine (SVM), multi-linear regression (MLR), and improved eliminate particle swamp optimization hybridized artificial neural network (IEPANN) models for the prediction of Śf. The efficacy of the IEPANN model compared to the nonlinear predictive models was evaluated, and the performances of the developed ML models were checked using the evaluation matrices. The results indicated that the prestressing strands with relatively higher initial strand slips may result in larger additional slips during flexural loading. The restraining mechanism and cast-in-place topping slab influenced the additional strand slip rate. The hybridized IEPANN model outperformed other classical models in estimating the additional slips with the R² values greater than 0.9 in the two modelling stages, indicating the efficacy of the IEPANN compared to the nonlinear predictive modes. Full article

Bridge vortex-induced vibration (VIV) refers to the vertical resonance phenomenon that occurs in a bridge when pulsating wind passes over it and causes vortices to detach. In recent years, VIV events have been observed in numerous long-span bridges, leading to fatigue damage to the bridge structure and posing risks to driving safety. The advancement of technologies such as structural health monitoring (SHM), machine learning, and big data has opened up new research avenues for the intelligent identification of VIV in bridges. Machine learning algorithms can accurately identify the VIV events from historical data accumulated by SHM systems, thus providing an effective method for VIV recognition. Nevertheless, the existing identification methods have limitations, particularly in their applicability to bridges lacking historical VIV data. This study introduces an adaptive VIV recognition method in the main girders of long-span suspension bridges based on Transfer Component Analysis (TCA). The method can accurately identify VIV patterns in real-time or in historical data, even when specific VIV data are not available for the target bridge. The proposed method exhibits suitability for multiple long-span bridges. Experimental validation is performed using the SHM datasets from two long-span suspension bridges. The results show that the proposed VIV identification method can recognize more VIV samples compared to the benchmark model. When using sensor 1 data of bridge B as the source domain to identify the VIV of the L-section of bridge A, the F1 score of the TCA-based method is 0.836, while the F1 score of the benchmark model is 0.165. In the other 11 cases, the F1 score of the proposed model is higher than 0.8, which demonstrates the method’s robust generalization capabilities. Full article

Additive Manufacturing (AM) of the Ti–6Al–4V alloy has gained significant importance across various industries, including biomedical, aerospace, cellular, and land vehicle applications, due to its numerous benefits. The certification of performance and reliability of AM materials, particularly for critical applications, heavily relies on evaluating fatigue strength. In this study, a numerical analysis based on the finite element method is presented to predict the High Cycle Fatigue (HCF) behavior of AM Ti–6Al–4V alloy. The investigation focuses on exploring the sensitivity of material fatigue life to surface roughness and Ultimate Tensile Strength (UTS). Uniaxial tensile and High Cycle Fatigue (HCF) tests were conducted on Ti–6Al–4V alloy samples extracted from rectangular walls manufactured using the Laser Metal Deposition (LMD) process. The walls were surface machined prior to sample extraction. Porosity and surface roughness measurements were performed on the samples. Numerical simulations of the HCF tests were carried out, considering various surface roughness ranges and UTS values. The numerical results were then compared to experimental data. The findings consistently demonstrated that higher surface roughness led to a shorter fatigue life, while higher UTS values resulted in a longer fatigue life. The numerical solutions aligned with the experimental results, indicating the efficacy of the finite element method in predicting the fatigue behavior of AM Ti–6Al–4V alloy. These insights contribute to a better understanding of the relationship between surface roughness, UTS, and fatigue life of Ti–6Al–4V alloys manufactured by AM. Full article

Unfortunately, most of the previous work studying the fracture toughness of fibrous composites has deliberately ignored bridging the fiber onto the pre-crack/notch surfaces by creating such a crack as a through-thickness crack (TTC). Furthermore, no standard specifications for measuring the fracture toughness of fibrous composites have considered the fiber bridging through the pre-notch. Only a few pieces of research, no more than fingers on one hand, have addressed this problem by creating an actual crack, i.e., a matrix crack (MC) instead of a TTC. The challenge these researchers face is the inability to calculate the fracture toughness directly through the stress intensity factor (SIF) relationship because there is no geometry correction factor equation, f(a/d), for an MC. The main objective of the present work is to calculate f(a/d) and ascertain a relationship between the SIF and crack mouth opening displacement (CMOD) for an MC numerically using 3-D finite element analysis. An experimental program was also conducted to measure the fracture toughness of three types of concrete beams: high-strength concrete (HSC) beams with a TTC, HSC beams with an MC, and fiber-reinforced concrete (FRC) beams with an MC. The results showed that FRC beams with an MC have the highest fracture toughness and, subsequently, the highest resistance to crack growth. The numerical results revealed a suggested relationship between the SIF and CMOD of FRC beams with an MC. This relation was used to predict the fracture toughness of FRC with an MC by the critical value of CMOD measured experimentally. Full article

Urban decline refers to the sustained deterioration of cities in terms of their economy, population, and social aspects. The outbreak of the Coronavirus Disease 2019 (COVID-19) pandemic in 2019 objectively affected the trajectory of this phenomenon. A comprehensive analysis of scientific research on urban decline and its practical implications was conducted using bibliometric methods, data acquired from 2019 to 2023 and the Web of Science. Since COVID-19, research on urban decline has been predominantly led by traditional developed countries such as the United States and England, with a high degree of regional collaboration. Keyword clusters have focused on urban regeneration, growth, decay, family planning, resource dependency theory, public art, etc. Keyword co-occurrence has focused on shrinking cities, gentrification policy, land use, etc. Based on previous analyses and the contemporary context, the intrinsic logic behind the urban decline in recent years can be summarized as inadequate economic development, lagging infrastructure construction, the siphoning effect of core regional cities, and unique institutional factors leading to specific urban decline patterns. Comprehensive urban recovery plans have been proposed, including reshaping urban spatial layouts and planning and strengthening strategies for social and economic revival, with correspondence-specific samples. Studying the impact of COVID-19 on urban decline from the perspectives of city development and strategies can help us better understand the repercussions of global health crises on cities, providing a more scientific basis for urban planning and management to build resilient, sustainable, and equitable cities. Full article

Determining the failure or failure mode of structures has long been a challenge for civil engineers. Traditional methods for analyzing structures are costly and complex. Plastic analysis, which involves combining pre-defined mechanisms, offers a less complex approach. However, as the number of potential mechanism combinations, or the search space, increases with the growing complexity of structural members, the effectiveness of this method diminishes. To address this issue, optimizers have been applied in the field of structural engineering to efficiently solve problems with large search spaces. Population-based meta-heuristic algorithms are widely used for their reduced dependency on input parameters. This research focuses on implementing the plastic theory of steel frames using MATLAB software, employing virtual work concepts and pre-defined mechanism combinations. A novel binary dolphin echolocation algorithm is proposed based on the principles of the primary algorithm. This algorithm is then utilized to optimize the plastic analysis method and determine the failure load factor and critical failure mode for sample frames. Additionally, the grey wolf optimizer and whale optimization algorithm are applied to optimize the problem, and the performance of all three algorithms is compared. The results demonstrate that the proposed algorithm yields accurate results with a minor margin of error compared to the other two algorithms. Full article

Research on the correlation between wind and block spatial form focuses mainly on hot and humid cities. However, cold regions are also experiencing high summer temperatures due to global climate change. Enhancing wind speed in blocks through urban spatial control improves comfort. Existing research cannot be directly applied to cold regions due to natural differences. Using Xi’an as an example, this study explores the impact of high-rise residential block spatial form on internal and external wind environments through field measurements and simulations. Optimal strategies for block planning and architectural design are identified to improve the wind environment. Results show that blocks with high buildings on the south and north sides and low buildings in the middle achieve a more comfortable internal wind environment. Gradually increasing building height from south to north has minimal impact on downwind blocks. Reducing the angle between the main facade and dominant wind direction enhances the residential area’s wind environment. Specific spatial planning and design strategies are summarized for early-stage decision-making. Full article

At present, dampers are widely used in the field of energy dissipation in engineering structures. However, when the displacement and velocity output of dampers are not significant under small and medium-sized earthquakes, it is difficult for a damper to fully exert its energy dissipation capacity. The use of toggle-brace mechanisms in the structure is an effective method to solve the above problems, and the effect of toggle-brace-viscous dampers (referred to as TBVDs) in the structure can be reflected by a magnification factor (referred to as M_f). Therefore, it is particularly important to study the calculation method for the M_f of TBVD. Domestic and foreign scholars have achieved certain results in the study of the calculation method for the M_f of TBVD, and the corresponding calculation formula for the M_f has been proposed. Given the existing research results, this article conducts the following work: analyzing the shortcomings of existing methods for calculating the M_f of TBVD, proposing an improved method for calculating the M_f of viscous dampers, comparing the accuracy of existing and improved algorithms, and analyzing the calculation results to provide practical suggestions for engineering applications. Full article

The use of vibro-centrifugation technology allows the manufacture of variotropic structures that are inhomogeneous in the annular section and have different characteristics along the section thickness. Hardening of the outer layers allows the structure to better resist bending conditions, however, the behavior of the variotropic column under central and eccentric compression remains unexplored. This article considers the problem of compression of hollow columns made of homogeneous concrete that is non-uniform in the annular section (variotropic), and is reinforced with steel reinforcing bars at different values of the load application eccentricity. Variotropic concrete obtained by vibro-centrifugation technology has a stronger outer part and a less durable inner part. The strength of a homogeneous column corresponds to the strength of the middle part of variotropic concrete. The problem was solved numerically in the ANSYS environment for a vertical column rigidly clamped at the bottom edge and loaded with eccentricity at the top edge. Three types of eccentricity are considered; e/r = 0, 0.16 and 0.32 (respectively 0 mm, 0.24 mm and 48 mm). The results of the solution in the form of stress fields, deformations and a pattern of crack development in a spatial setting are obtained. The results showed that for central compression, a homogeneous column has a better bearing capacity of 3.6% than a variotropic one. With the values of eccentricity e/r = 0.16 and 0.32, the variotropic column has a higher bearing capacity (by 5.5% and 6.2%) than the homogeneous one and better resists the development of cracks. The significance of the study lies in the practical application of the proposed approach, developed on a research basis, for non-trivial and complicated operating conditions of columns. This study influences the development of reinforced concrete structures and applies scientific findings to engineering practice. Full article