Hasil untuk "Building construction"

Ling LE, Linhai LU, Xiaojun LI et al.

ObjectiveCompared with traditional concrete construction, the application of prefabricated assembly construction based on digital twin technology in urban rail transit station construction can effectively ensure component production quality, reduce environmental pollution and lower resource consumption. Therefore, an in-depth research on digital twin technology suitable for prefabricated assembly station construction should be conducted. MethodFirst, in station construction, the overall architecture featuring "4 horizontal + 4 vertical + N platforms" for the application of digital twin technologies, such as BIM (building information modeling) and IoT (Internet of things) is proposed. Second, the modeling process and methodology of BIM are presented. By adopting methods such as mathematical model separation, lightweight processing, and mathematical model association, the established BIM data are imported into the platform, and a technical workflow for uploading IoT monitoring data to the BIM platform is established. Finally, taking a certain underground prefabricated assembly superimposed station in the Phase I project of Jinan Urban Rail Transit Line 8 as a case study, the application effect of the digital twin technology for prefabricated assembly superimposed stations based on BIM+IoT integration is analyzed. Result & Conclusion The proposed digital twin technology shows good application effects in the case station, achieving design goals such as construction progress query, structural safety monitoring, quality management control, and process auxiliary design, and realizing data management interaction and sharing throughout the components full life cycle.

Suhyung Jang, Ghang Lee, Jaekun Lee et al.

Accurate representation of building semantics, encompassing both generic object types and specific subtypes, is essential for effective AI model training in the architecture, engineering, construction, and operation (AECO) industry. Conventional encoding methods (e.g., one-hot) often fail to convey the nuanced relationships among closely related subtypes, limiting AI's semantic comprehension. To address this limitation, this study proposes a novel training approach that employs large language model (LLM) embeddings (e.g., OpenAI GPT and Meta LLaMA) as encodings to preserve finer distinctions in building semantics. We evaluated the proposed method by training GraphSAGE models to classify 42 building object subtypes across five high-rise residential building information models (BIMs). Various embedding dimensions were tested, including original high-dimensional LLM embeddings (1,536, 3,072, or 4,096) and 1,024-dimensional compacted embeddings generated via the Matryoshka representation model. Experimental results demonstrated that LLM encodings outperformed the conventional one-hot baseline, with the llama-3 (compacted) embedding achieving a weighted average F1-score of 0.8766, compared to 0.8475 for one-hot encoding. The results underscore the promise of leveraging LLM-based encodings to enhance AI's ability to interpret complex, domain-specific building semantics. As the capabilities of LLMs and dimensionality reduction techniques continue to evolve, this approach holds considerable potential for broad application in semantic elaboration tasks throughout the AECO industry.

Philippa Boyd, Debs Harding

The uptake of generative artificial intelligence (GenAI) tools has implications for doctoral research and academic publication practices within both construction management and the wider academic context. Unless these implications are understood, GenAI tools have the potential to disrupt traditional relationships between doctoral researchers and their academic supervisors. Rather than exploring the technical competence and reach of GenAI tools, this study explores the nature of these challenges. GenAI is explored from both supervisor and doctoral perspectives for how its integration into doctoral research processes might shift relationships and affect practice. Informed by structuration theory, the research uses mixed methods to map shifts in agency and structure resulting from the adoption of GenAI tools. Findings highlight that the often-unacknowledged use of GenAI in doctoral research can confer undue agency on the technology that disrupts traditional relationships in an unacknowledged way. The rapid but often unacknowledged uptake of GenAI within doctoral research comes with a lack of consideration of the emotional support ascribed by students to the technology. It is concluded that GenAI tools should be openly incorporated into research and practice in a transparent, integrated approach. Practice relevance This research has relevance to the academic community both within the built environment disciplines and more general pedagogical implications. The identification of concerns over the reach and rapidity of GenAI adoption exposes potential changes to relationships and practices. Academics will be able to understand the shifts in relationships between stakeholders and the possible ramifications. The research exposes an unacknowledged proliferation of GenAI use in doctoral research and its underlying role in providing surrogate emotional support to doctoral students. By giving voice to stakeholders, this research exposes the lack of ethical frameworks around the use of GenAI and the need to consider its open and supported use, and its impact on developing the technical understandings and communication of doctoral researchers. The research uncovers some of the debates, concerns and possibilities that GenAI can bring to doctoral research practice, so that they can be intentionally addressed.

Émilie Savoie, J. P. Sapinski, Anne-Marie Laroche

This study investigates the preservation through adaptive reuse of derelict heritage buildings at risk of demolition in urban settings in New Brunswick, Canada. Despite the demonstrated benefits of adaptive reuse in balancing heritage preservation and contemporary urban needs, small cities face significant challenges: financial constraints, regulatory barriers and technical limitations. Using a multiple-case study approach, adaptive reuse projects in Moncton, Fredericton and Saint John are examined to identify key factors contributing to their success. Findings reveal that prioritising structural adaptability, cultural value and long-term sustainability over profit-driven redevelopment models is essential. Successful adaptive reuse projects rely on collaborative governance frameworks, phased financial strategies, early involvement of technical expertise and active community engagement. This approach is critical to overcoming challenges such as hazardous material management, regulatory barriers and funding limitations. This study demonstrates that adaptive reuse can transform neglected heritage buildings into functional spaces, contributing to urban regeneration, cultural preservation and sustainability, while offering a framework for future adaptive reuse initiatives in similar contexts. Practice relevance The findings highlight key implications for advancing adaptive reuse as a strategy for heritage preservation and sustainability. Prioritising building location, adaptability and cultural value over profit-driven approaches is essential to fostering adaptive reuse initiatives. Establishing clear governance frameworks can align public, private and community efforts, facilitating collaboration to overcome common challenges. Financial incentives, such as grants or tax relief, can address issues such as hazardous material management, while adaptive regulatory processes can streamline approvals. Addressing expertise shortages through targeted training programmes and cross-regional collaboration is particularly important for smaller regions. Additionally, integrating sustainability principles and promoting material reuse within adaptive reuse projects can enhance environmental performance and urban resilience. These measures demonstrate how adaptive reuse can revitalise neglected heritage buildings into functional, purposeful spaces that contribute to cultural continuity, community identity and sustainable urban development.

Hao Jin, Yike Yang, Xinxin Zhao et al.

The service status of rail, fasteners and track slabs is the key determinant of whether the ballastless track is ready for traffic after a fire. The track slab rail support bolt anchoring performance and the shoulder service performance damaged by fire were tested. Experiments of ballastless track slab concrete burned at different high temperatures were carried out to compare macro- and microstructural properties of the concrete under high-temperature burning to study the microstructure of hydration products after high-temperature burning and reveal the damage mechanism of the track slab concrete after a fire. The results show that the fire damage to the rail and fastener is mainly deformations, fractures and strength reduction. The degree of the fire damage of the mortar layer and base slab is much lower than that of the track slab. The main fire damage to the concrete is track and base slab cracks, spalling and gaps. The degree of the fire damage to the mortar layer and base slab is much lower than that of the track slab. The fire damage of the track slab concrete is mainly bursts, and the concrete cracks, spalling and deterioration occur layer by layer from the outside to inside. The shoulder injury is the most serious, the shear resistance is greatly reduced, the rail support is protected by the rail and fastener, the impact of the fire damage is small and the bolt anchoring performance was not decreased. The position of the track slab’s inside damage corresponds to the surface damage position. The steel bar inside the track slab is in good condition, and there is no obvious damage. The bulk expansion of the ballastless track concrete was caused by the expansion of aggregates under fire. When the expansion of aggregates is constrained by the shrinkage of hydration products, greater internal stress is generated, which is the main reason for the cracking or bursting of the ballastless track slab concrete under high temperatures.

Abdalwhab Abdalwhab, Ali Imran, Sina Heydarian et al.

The construction industry has long explored robotics and computer vision, yet their deployment on construction sites remains very limited. These technologies have the potential to revolutionize traditional workflows by enhancing accuracy, efficiency, and safety in construction management. Ground robots equipped with advanced vision systems could automate tasks such as monitoring mechanical, electrical, and plumbing (MEP) systems. The present research evaluates the applicability of open-vocabulary vision-language models compared to fine-tuned, lightweight, closed-set object detectors for detecting MEP components using a mobile ground robotic platform. A dataset collected with cameras mounted on a ground robot was manually annotated and analyzed to compare model performance. The results demonstrate that, despite the versatility of vision-language models, fine-tuned lightweight models still largely outperform them in specialized environments and for domain-specific tasks.

Simon Adamov, Joel Oskarsson, Leif Denby et al.

Machine learning is revolutionizing global weather forecasting, with models that efficiently produce highly accurate forecasts. Apart from global forecasting there is also a large value in high-resolution regional weather forecasts, focusing on accurate simulations of the atmosphere for a limited area. Initial attempts have been made to use machine learning for such limited area scenarios, but these experiments do not consider realistic forecasting settings and do not investigate the many design choices involved. We present a framework for building kilometer-scale machine learning limited area models with boundary conditions imposed through a flexible boundary forcing method. This enables boundary conditions defined either from reanalysis or operational forecast data. Our approach employs specialized graph constructions with rectangular and triangular meshes, along with multi-step rollout training strategies to improve temporal consistency. We perform systematic evaluation of different design choices, including the boundary width, graph construction and boundary forcing integration. Models are evaluated across both a Danish and a Swiss domain, two regions that exhibit different orographical characteristics. Verification is performed against both gridded analysis data and in-situ observations, including a case study for the storm Ciara in February 2020. Both models achieve skillful predictions across a wide range of variables, with our Swiss model outperforming the numerical weather prediction baseline for key surface variables. With their substantially lower computational cost, our findings demonstrate great potential for machine learning limited area models in the future of regional weather forecasting.

Alexander Dietz

In this thesis, a new approach for constructing subdivision algorithms for generalized quadratic and cubic B-spline subdivision for subdivision surfaces and volumes is presented. First, a catalog of quality criteria for these subdivision algorithms is developed, serving as a guideline for the construction process. The construction begins by generating the desired subdominant eigenvectors as the vertices of regular convex 3-polytopes for volumes using circle packings. Subsequently, these polytopes are utilized to construct a Colin-de-Verdiere-matrix for the generalized quadratic and a Colin-de-Verdiere-like matrix for the generalized cubic B-spline subdivision. These matrices are then adjusted using the matrix exponential to obtain subdivision matrices with the desired properties. All subdivision algorithms introduced in this paper empirically exhibit a subdominant eigenvalue of 1/2 with the desired algebraic and geometric multiplicity. For the quadratic case, this property can even be formally proven. Moreover, the corresponding eigenvectors form a convex polytope in the central region for the generalized quadratic B-spline subdivision algorithms, while for the generalized cubic B-spline subdivision algorithms, they represent the refinement of a convex polytope. Additionally, the constructed subdivision algorithms fulfill various other quality criteria, such as affine invariance and convex hull preservation and respecting all symmetries. Furthermore, it is demonstrated that the original Catmull-Clark algorithm is not suitable for generalization to volumetric subdivision and that the established subdivision algorithms [Baj+02] and [JM99] do not exhibit a suitable spectrum for several combinatorial configurations. Additionally, research approaches for the volumetric case are proposed, aiming to generalize from hexahedral to arbitrary structures.

Jing Liu, Jing Liu

The cracking of recycled aggregate concrete (RAC) is well known to promotes the chloride diffusion, accelerates the corrosion of reinforcement embedded in RAC. To reveal the mechanism of chloride diffusion in RAC under cracking, a multiphase mesoscopic model for chloride diffusion in RAC was proposed. It should be noted that RAC is regarded as eight-phase composite materials consisting of coarse aggregate, reinforcement, new and old mortar, new and old interface transition zones (ITZ), cracks, and damage zones. The effects of the width and depth of cracks and damage zones on chloride diffusion behavior in RAC after cracking were further investigated. The numerical simulation results show that the damage zones accelerate the chloride diffusion and exacerbates the accumulation effect of chloride at the crack tip. Compared to the crack depth, the crack width of RAC has a small effect on chloride diffusion behavior, especially, the crack width is less than 50 µm. More importantly, the chloride diffusion streamline generated by numerical simulation reveals the mechanism of cracks promoting chloride diffusion. The research in this paper provides new insights into the durability design of RAC by revealing the diffusion behavior of chloride ions in RAC.

Sergey Yu. Savin, Maria I. Stupak, Dmitry K. Mankov

The effect of service life of a reinforced concrete building frame on its robustness parameters in the case of sudden failure of the outermost column has been investigated. The reinforced concrete frame of a philharmonic hall was chosen as the study subject. In order to evaluate its robustness, a relative robustness index, which is related to the parameters of the failure load for a system with and without initial local failure, has been utilized. Quasi-static modeling using the finite element method taking into account physical and geometric nonlinearity was performed as a part of the study. The physical nonlinearity of concrete, considering long-term operation of the structure, was accounted for by modified bilinear constitutive models of the material. Such models differed for elements with different stress-strain states in long-term operation. The parameters of the constitutive models were obtained using the integral deformation modulus proposed by Bondarenko. This approach has been employed to analyze the deformations and forces in the elements of the load-bearing system in the scenario of the outermost column failure. The curves for the percentage of destroyed elements of the load-bearing structure versus the parameters of the failure load have been plotted for the models with and without initial local failure of the outermost column, as well as for short-term and long-term operation. It is shown that the values of the failure load parameter and the relative robustness index decrease when the service life of the structure is accounted for.

Liang Anqi, Zeng Shuang, Ren Jiahang et al.

To improve the comprehensive utilization of regional energy and promote low-carbon development, this study constructs an integrated energy system for typical areas, such as parks, including a new energy power generation system driven by photovoltaic and wind power, heating and cooling energy supply systems for ground-source/air-source heat pumps, water chillers, and energy storage equipment. TRNSYS? software is used to simulate and study the dynamic characteristics of the system under six climate conditions in Beijing, and the game theory is used for intelligent operation, which is then compared with the logic control method. The results show that the logic control method can meet the load demand but cannot realize the efficient operation of the heat pump unit and the charge and discharge balance of the energy storage device. The integrated energy system after optimization via game theory can not only realize flexible energy scheduling and distribution through electric-thermal coordination, but also save the entire energy consumption of the heat pump unit and achieve the goal of regional energy economic benefits. The research presented in this paper provides an important theoretical basis for the intelligent operation of heat pump systems in integrated electric-thermal cooperative grids.

Omrane Benjeddou, Gobinath Ravindran, Mohamed Abuelseoud Abdelzaher

A large amount of industrial solid waste is generated from industrial activities worldwide. One such waste is marble waste, a waste generated from quarries which is generated in larger amount which needs attention. It is proved that this waste has a significant impact both on the people health and on the environment. Hence, research works are directed towards addressing usage of waste marble power, the aim of this experimental investigation is to study the usability of sand obtained by crushing marble waste (MWS) on the mixing of lightweight concrete based on expanded perlite aggregate (EPA). First, the mechanical, chemical, and physical properties of marble waste sand and expanded perlite aggregate were determined after which different mixtures of concrete are prepared by varying the percentage of EPA (0, 20, 40, 60, 80, and 100%), in order to find the optimum mixture focussing on obtaining best hydraulic properties. Also, in this work, the thermal and acoustic properties (thermal conductivity, thermal diffusivity, specific heat capacity and sound reduction index at different frequencies) of the tested concrete samples were investigated. Results shows that it is possible to obtain thermal and acoustic insulation lightweight concrete by using sand obtained by crushing marble wastes. Also, addition of more than 20% of EPA aggregate in concrete, develops a thermal insulating lightweight concrete which possess capacity to store heat and produce better thermal performance. Concrete blend with a percentage of more than of 20% of EPA aggregate can be placed in the category of acoustic insulation lightweight concrete. In summary, cement based on MWs and EPA provides better workability and energy saving qualities, which are economical and environmentally beneficial and may result in decreased construction budget and improve a long-term raw materials sustainability.

Wan-Li Lao, Liang Chang, Xin-Fang Duan

Abstract Quantifying carbon dioxide (CO2) emissions from China’s wood and bamboo processing industry is associated with China’s emissions reduction targets, as well as mitigating global climate change. This study employed the Intergovernmental Panel on Climate Change Tier-2 methodology to investigate spatio-temporal evolution characteristics of carbon dioxide emission from the wood and bamboo processing industry in China from 2000 to 2019. The results showed that energy consumption reached a maximum value of 312,900.35 TJ in 2012. Energy consumption has been gradually transformed from raw coal to electricity and other clean energy. Energy intensity dropped from 1.39 TJ per million yuan of corrected production value in 2000 to 0.15 TJ per million yuan of corrected production value in 2019. Accordingly, CO2 emissions reached their peak value of 31,148.1 thousand tons of CO2 in 2012. Raw coal and electricity had profound impacts on CO2 emissions. The CO2 emission intensity declined from 140.04 tons CO2 per million yuan of corrected production value in 2000 to 19.62 tons CO2 per million yuan of corrected production value in 2019. We conclude that China’s wood and bamboo processing sector is a green, low-carbon industry. The spatial distribution pattern of CO2 emissions is highly consistent with the industrial spatial layout. Furthermore, several mitigation paths were put forward.

Zongyuan Mao, Jiaqi Jiang, Hao Guo et al.

This paper presents a novel design for uplift piles incorporating a composite-anchor system. The composite-anchor system consists of steel strands, a non-expansion grouting body, and a high-strength steel pile. The aim of this design is to enhance the mechanical performance, durability, and economic efficiency of uplift piles. To evaluate the performance of the new pile, three sets of full-scale load tests were conducted, focusing on their in situ capacity, deformation, and stress characteristics. Despite a significantly lower reinforcement ratio of 0.75% compared to conventional piles with a ratio of 3.84%, the new uplift piles exhibit an exceptional uplift bearing performance. The utilization of the lateral friction resistance of the lower pile body is significantly improved, leading to enhanced load distribution and stress transfer mechanisms. Furthermore, a numerical model was developed and validated against the experimental results, demonstrating its reliability in simulating the bearing characteristics of the new uplift piles. The multi-interface design of the composite-anchor system ensures the efficient transmission of internal forces induced by external uplift loads, resulting in an improved stress state within the pile body. Moreover, the multi-layer structure of the composite main bar enhances the durability of the uplift piles. In comparison to conventional piles, the new uplift pile design offers substantial advantages, including an 80% reduction in reinforcement ratio, a 65% reduction in reinforcement cage welding, a cost reduction of approximately 30%, and a shortened construction time by around 20%. These findings highlight the potential of the new composite-anchor-pile design to revolutionize the field of uplift pile applications, offering improved efficiency and effectiveness.

Ci-Jyun Liang, Thai-Hoa Le, Youngjib Ham et al.

Artificial intelligence (AI) and robotics research and implementation emerged in the architecture, engineering, and construction (AEC) industry to positively impact project efficiency and effectiveness concerns such as safety, productivity, and quality. This shift, however, warrants the need for ethical considerations of AI and robotics adoption due to its potential negative impacts on aspects such as job security, safety, and privacy. Nevertheless, this did not receive sufficient attention, particularly within the academic community. This research systematically reviews AI and robotics research through the lens of ethics in the AEC community for the past five years. It identifies nine key ethical issues namely job loss, data privacy, data security, data transparency, decision-making conflict, acceptance and trust, reliability and safety, fear of surveillance, and liability, by summarizing existing literature and filtering it further based on its AEC relevance. Furthermore, thirteen research topics along the process were identified based on existing AEC studies that had direct relevance to the theme of ethics in general and their parallels are further discussed. Finally, the current challenges and knowledge gaps are discussed and seven specific future research directions are recommended. This study not only signifies more stakeholder awareness of this important topic but also provides imminent steps towards safer and more efficient realization.