Hasil untuk "Building construction"

Fei Yu, Norihito Nakatani, Yiling Hua et al.

By tracing the historical activities of the Japan-China Society of Architecture and Building Technology (JCSABT, 1973–2003), which was established in Japan in 1973, this study firstly provides an overview of the friendly exchange groups visiting China from Japan over a 30-year period. Drawing upon a systematic review of Nichi-Chu Kenchiku [Japan – China Architecture], the official journal of JCSABT, this study delineates the evolving professional concerns and focal themes of Japanese architects engaged in China. The focus gradually shifted from early concerns with the construction of socialist China to an interest in cultural heritage, particularly Chinese vernacular architecture, and later to friendly visits and international exchanges. These shifts reflect the dynamic interplay between political context, architectural evolution, and cultural exchange. The study concludes that beneath the surface of “friendly diplomacy,” China and Japan each pursued distinct agendas. China seeks to learn advanced techniques from Japan, while Japan, faced with pressing issues such as widening urban-rural disparities and environmental crises, endeavours to learn from China’s urban and rural development models. Above all,“architectural diplomacy” played a crucial role in fostering Sino – Japanese friendship. The interplay among state power, architecture, and socioeconomic forces collectively contributed to strengthening bilateral relations in Cold War era.

Yali Chen, Dan Huang, Z. Liu et al.

At present, the smart city offers the most desired state of urban development, encompassing, as it does, the concept of sustainable development. The creation of a smart city is closely associated with upgrading the construction industry to encompass many emerging concepts and technologies, such as Construction 4.0, with its roots in Industry 4.0, and the deployment of building information modeling (BIM) as an essential tool for the construction industry. Therefore, this paper aims to explore the current state of the art and development trajectory of the multidisciplinary integration of Construction 4.0, Industry 4.0, BIM, and sustainable construction in the context of the smart city. It is the first attempt in the literature to use both macro-quantitative analysis and micro-qualitative analysis methods to investigate this multidisciplinary research topic. By using the visual bibliometric tool, VOSviewer, and based on macro keyword co-occurrence, this paper is the first to reveal the five keyword-constructed schemes, research hotspots, and development trends of the smart city, Construction 4.0, Industry 4.0, BIM, and sustainable construction, from 2014 to 2021 (a period of eight years). Additionally, the top 11 productive subject areas have been identified with the help of VOSviewer software keyword-clustering analysis and application. Furthermore, the whole-building life cycle is considered as an aid to identifying research gaps and trends, providing suggestions for future research with the assistance of an upgraded version of BIM, namely, city information modeling (CIM) and the future integration of Industry 5.0 and Construction 5.0, or even of Industry Metaverse with Construction Metaverse.

Nan-Wei Wu

The purpose of this paper is to identify hybrid timber skeuomorph on the first empirical work of the Chinese Classical Style architecture carried out by a native Taiwanese architect, Chung-Yueh Li. The proportions, the composition and forms and numbers of tou-kung were therefore analyzed to compare the timber skeuomorph of the Ling-xiao Bao-dien of the Chih-nan Temple, other temple designs of Zu-Nan Hsieh, and early projects in the Chinese Classical Style architecture. The basis of the analysis was the research results on tou-kung published by the Society for Research in Chinese Architecture. The findings showed that the hybridized timber skeuomorph of the Ling-xiao Bao-dien of the Chih-nan Temple could be found both in the physical project and also in its design processes. The hybridity of the project showed the integration of northern tou-kung in the entire arrangement and the form of individual style with southern tou-kung in the proportions. This reflected the hybridity of the design processes: Li dominated the entire arrangement and forms of the project, whilst Hsieh was responsible for the proportions and forms of tou-kung. Study of this hybridization could further reveal the differences, dynamics and diversity of timber skeuomorphy.

Jaemin Kim, Seongwoong Shin, Seulki Lee et al.

Cracks in concrete structures, caused by aging, adjacent construction, and seismic activity, pose critical risks to structural integrity, durability, and serviceability. Traditional monitoring methods based solely on absolute thresholds are inadequate for detecting progressive crack growth at early stages. This study proposes a big data-driven anomaly detection model that combines absolute threshold evaluation with periodic trend analysis to enable both real-time monitoring and early anomaly identification. By incorporating relative comparisons, the model captures subtle variations within allowable limits, thereby enhancing sensitivity to incipient defects. Validation was conducted using approximately 2700 simulated datasets with an increase–hold–increase pattern and 470,000 real-world crack measurements. The model successfully detected four major anomalies, including abrupt shifts and cumulative deviations, and time series visualizations identified the exact onset of abnormal behavior. Through periodic fluctuation analysis and the Isolation Forest algorithm, the model effectively classified risk trends and supported proactive crack management. Rather than defining fixed labels or thresholds for the detected results, this study focused on verifying whether the analysis of detected crack data accurately reflected actual trends. To support interpretability and potential applicability, the detection outcomes were presented using quantitative descriptors such as anomaly count, anomaly score, and persistence. The proposed framework addresses the limitations of conventional digital monitoring by enabling early intervention below predefined thresholds. This data-driven approach contributes to structural health management by facilitating timely detection of potential risks and strengthening preventive maintenance strategies.

Dino Petrosa, Pamela Haverkamp, Jana Gerta Backes et al.

Abstract The construction sector significantly contributes to environmental issues and often relies on Life Cycle Assessment (LCA) for the quantification and optimization of its environmental impacts. One of the most time- and labour-intensive tasks in LCA is matching real elements (e.g., construction elements and materials) to suitable environmental datasets to get an idea of the element’s sustainability performance (emissions). In this regard, this study presents an open-access software tool that leverages artificial intelligence (AI) to support the matching process between construction elements in Building Information Modelling (BIM) with corresponding environmental datasets in a semi-automatic manner. Developed in Python and using the GPT-4o mini model from OpenAI for its matching mechanism, the tool demonstrates how AI-driven digital innovation can improve efficiency, reduce manual effort, and enhance early-stage environmental assessment in construction planning, while integrating sustainability data into BIM workflows. Through a series of use cases, the software’s ability to address key challenges in the integration of BIM and LCA tools is demonstrated, showcasing a high degree of automation and interoperability. Moreover, the accessible design of the tool allows use without extensive technical knowledge. The conducted validation tests confirmed the tool’s potential for accurate LCA matching, highlighting opportunities for AI to enhance sustainability workflows while offering BIM experts a better understanding of the challenges in sustainability assessment.

Neeraj Deshmukh, Felix Sefzig

In this article, we give a construction of the (un-)stable motivic homotopy category of an algebraic stack in the spirit of Morel-Voevodsky. We prove that this new construction agrees with the stable motivic homotopy category defined by Chowdhury and D'Angelo. As an application, we extend Bachmann's spectral rigidity theorem to algebraic stacks. Moreover, we extend the construction of the framed motivic homotopy category to algebraic stacks and prove Hoyois' Reconstruction Theorem in this setting. Finally, we discuss an extension of the formalism of cocomplete coefficient systems à la Drew-Gallauer to algebraic stacks.

Harm Derksen, Benjamin Lovitz

We present explicit quantum channels with strictly sub-additive minimum output Rényi entropy for all $p>1$, improving upon prior constructions which handled $p>2$. Our example is provided by explicit constructions of linear subspaces with high geometric measure of entanglement. This construction applies in both the bipartite and multipartite settings. As further applications, we use our construction to find entanglement witnesses with many highly negative eigenvalues, and to construct entangled mixed states that remain entangled after perturbation.

Douglas Mol Resende, José Maria Franco de Carvalho, Bárbara Oliveira Paiva et al.

Plastic is a widely consumed material with a high decomposition time, occupying significant space in landfills and dumps. Thus, strategies to reuse plastic waste are imperative for environmental benefit. Plastic waste is a promising eco-friendly building material for cement-based composites due to its reduced specific gravity and thermal conductivity. However, this waste reduces the composites’ mechanical strength. This work aims to produce and evaluate lightweight concretes made with only lightweight aggregates and mostly recycled plastic aggregates. Initially, an optimized dosage approach for lightweight concrete is presented. The mixture proportion of the lightweight concrete was based on the performance of mortars with the complete replacement of natural aggregate by recycled polyethylene terephthalate (PET) aggregates. The PET aggregates showed irregular shapes, impairing workability and providing lightweight concretes with around 18% water absorption and 21% void index. However, the concretes presented significantly low-unit weight, approximately 1200 kg/m³. This work presented a structural lightweight concrete (ACI 213-R) using only lightweight aggregates and mostly plastic waste aggregate, with a compressive strength of up to 17.6 MPa, a unit weight of 1282 kg/m³, and an efficiency factor of 12.3 MPa·cm³/g. The study shows that with an optimum dosage, reusing plastic waste in concrete is a viable alternative contributing to environmental sustainability.

Toni Utech, Henning Kruppa, Anya Vollpracht et al.

Biological materials found in nacre or glass sponges reveal specific layered organic and inorganic structures known for their fracture toughness caused by crack deflection and bridging. This work aims to bio-mimic the brick-and-mortar (BnM) structure from nacre and the layer-by-layer (LbL) structure from the glass sponge filaments to incorporate these effects into the contact zone of carbon fiber-reinforced concrete (CFRC) in order to prevent brittle composite failure. To build up BnM- and LbL-structure materials such as nanoclays, sodium water glass, and polymer dispersions were selected since they are well-established low-cost materials in building. Nanoclays were analyzed regarding their size, dispersibility and exfoliation. Montmorillonite (MMT) was used to be mixed with polymers to produce self-assembled BnM-structured films and coatings. Also, LbL-structures were formed by alternating layers of sodium water glass and polymer. Scanning electron microscopy and energy-dispersive X-ray spectroscopy were used to verify the morphology. The MMT-containing coatings demonstrated enhanced nucleation potential when exposed to cementitious eluate. Micromechanical pull-out tests on single carbon fibers with BnM- and LbL-coatings embedded in concrete demonstrate the potential to increase composite toughness. The successful implementation of the bio-inspired structures using affordable materials lays the groundwork for their scalability and integration into composite structures for building.

Liane Gabora, Joscha Bach

This paper is an invited layperson summary for The Academic of the paper referenced on the last page. We summarize how the formal framework of autocatalytic networks offers a means of modeling the origins of self-organizing, self-sustaining structures that are sufficiently complex to reproduce and evolve, be they organisms undergoing biological evolution, novelty-generating minds driving cultural evolution, or artificial intelligence networks such as large language models. The approach can be used to analyze and detect phase transitions in vastly complex networks that have proven intractable with other approaches, and suggests a promising avenue to building an autonomous, agentic AI self. It seems reasonable to expect that such an autocatalytic AI would possess creative agency akin to that of humans, and undergo psychologically healing -- i.e., therapeutic -- internal transformation through engagement in creative tasks. Moreover, creative tasks would be expected to help such an AI solidify its self-identity.

Ahmet Bahaddin Ersoz

The integration of Large Vision-Language Models (LVLMs) such as OpenAI's GPT-4 Vision into various sectors has marked a significant evolution in the field of artificial intelligence, particularly in the analysis and interpretation of visual data. This paper explores the practical application of GPT-4 Vision in the construction industry, focusing on its capabilities in monitoring and tracking the progress of construction projects. Utilizing high-resolution aerial imagery of construction sites, the study examines how GPT-4 Vision performs detailed scene analysis and tracks developmental changes over time. The findings demonstrate that while GPT-4 Vision is proficient in identifying construction stages, materials, and machinery, it faces challenges with precise object localization and segmentation. Despite these limitations, the potential for future advancements in this technology is considerable. This research not only highlights the current state and opportunities of using LVLMs in construction but also discusses future directions for enhancing the model's utility through domain-specific training and integration with other computer vision techniques and digital twins.

Sanghyeon Cho, Jungho Choi, Heeyoung Lee et al.

Abstract Composite rigid-frame bridges with steel girders have excellent structural performance, but behavioral inconsistency appears at the connection between the steel girder and concrete pier. In addition, composite rigid-frame bridges are challenging to construct owing to the need to connect different materials at the pier. Therefore, this study developed and demonstrated a composite rigid-frame bridge with a construction joint and anchors. The structural performance and composite behavior of the proposed construction joint were investigated by evaluating a direct connection between the girder and concrete prior to casting (Joint A), a plain construction joint (Joint B), and a construction joint with anchors (Joint C). Joints B and C exhibited 16.5% and 46.5% higher ultimate capacities, respectively, than did Joint A. Finite element analysis of Joint C was conducted, and its results were verified against the experimental results. Further, parameter analysis was performed to determine the effects of the steel girder strength and anchor diameter. The results indicated that the proposed construction joint with anchors exhibited excellent structural performance and composite behavior.

Vidhya Maney Surendran, Chandramathy Irulappan, Vijayalaxmi Jeyasingh et al.

This study aims to propose building envelope retrofit packages for existing naturally ventilated school buildings in the hot–humid climatic region of Chennai, India. Indoor thermal parameters were collected through field studies from nine sample classrooms of a selected school building in May 2019, between 9.00 am and 4.00 pm. The thermal performance assessment of the existing building was performed by examining the discomfort hours using the CBE thermal comfort tool. Envelope retrofit strategies gathered from the literature and building standards were applied and studied through simulation. The findings reveal the enormous potential to increase the thermal comfort of existing school buildings through envelope retrofit measures. The results demonstrate that the whole-building temperature can be reduced up to 3.2 °C in summer and up to 3.4 °C in winter. Implementing retrofit measures to the building envelopes of existing buildings will help school owners to increase the comfortable hours of whole buildings by up to 17%. In comparison, annual energy savings of up to 13% for the whole building can be made by enhancing the thermal performance of the building envelope. The findings will also help architects to optimise thermal performance and energy usage with minimal interventions.

Limeng Qiao, Yongchao Zheng, Peng Zhang et al.

This report introduces the 1st place winning solution for the Autonomous Driving Challenge 2023 - Online HD-map Construction. By delving into the vectorization pipeline, we elaborate an effective architecture, termed as MachMap, which formulates the task of HD-map construction as the point detection paradigm in the bird-eye-view space with an end-to-end manner. Firstly, we introduce a novel map-compaction scheme into our framework, leading to reducing the number of vectorized points by 93% without any expression performance degradation. Build upon the above process, we then follow the general query-based paradigm and propose a strong baseline with integrating a powerful CNN-based backbone like InternImage, a temporal-based instance decoder and a well-designed point-mask coupling head. Additionally, an extra optional ensemble stage is utilized to refine model predictions for better performance. Our MachMap-tiny with IN-1K initialization achieves a mAP of 79.1 on the Argoverse2 benchmark and the further improved MachMap-huge reaches the best mAP of 83.5, outperforming all the other online HD-map construction approaches on the final leaderboard with a distinct performance margin (> 9.8 mAP at least).

Maurice Funk, Simon Hosemann, Jean Christoph Jung et al.

We present a method for automatically constructing a concept hierarchy for a given domain by querying a large language model. We apply this method to various domains using OpenAI's GPT 3.5. Our experiments indicate that LLMs can be of considerable help for constructing concept hierarchies.

Mohamed Abdelhedi, Rateb Jabbar, Chedly Abbes

The COVID-19 pandemic has significantly impacted the construction sector, which is sensitive to economic cycles. In order to boost value and efficiency in this sector, the use of innovative exploration technologies such as ultrasonic and Artificial Intelligence techniques in building material research is becoming increasingly crucial. In this study, we developed two models for predicting the Los Angeles (LA) and Micro Deval (MDE) coefficients, two important geotechnical tests used to determine the quality of rock aggregates. These coefficients describe the resistance of aggregates to fragmentation and abrasion. The ultrasound velocity, porosity, and density of the rocks were determined and used as inputs to develop prediction models using multiple regression and an artificial neural network. These models may be used to assess the quality of rock aggregates at the exploration stage without the need for tedious laboratory analysis.

Limeng Wang, Xuemeng Liu, Yang Li et al.

In the operation of the integrated energy system (IES), considering further reducing carbon emissions, improving its energy utilization rate, and optimizing and improving the overall operation of IES, an optimal dispatching strategy of integrated energy system considering demand response under the stepped carbon trading mechanism is proposed. Firstly, from the perspective of demand response (DR), considering the synergistic complementarity and flexible conversion ability of multiple energy sources, the lateral time-shifting and vertical complementary alternative strategies of electricity-gas-heat are introduced and the DR model is constructed. Secondly, from the perspective of life cycle assessment, the initial quota model of carbon emission allowances is elaborated and revised. Then introduce a tiered carbon trading mechanism, which has a certain degree of constraint on the carbon emissions of IES. Finally, the sum of energy purchase cost, carbon emission transaction cost, equipment maintenance cost and demand response cost is minimized, and a low-carbon optimal scheduling model is constructed under the consideration of safety constraints. This model transforms the original problem into a mixed integer linear problem using Matlab software, and optimizes the model using the CPLEX solver. The example results show that considering the carbon trading cost and demand response under the tiered carbon trading mechanism, the total operating cost of IES is reduced by 5.69% and the carbon emission is reduced by 17.06%, which significantly improves the reliability, economy and low carbon performance of IES.