Generative AI design for building structures

Automation in Construction, Journal Year: 2023, Volume and Issue: 157, P. 105187 - 105187

Published: Nov. 11, 2023

Language: Английский

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Review of advanced road materials, structures, equipment, and detection technologies

Journal of Road Engineering, Journal Year: 2023, Volume and Issue: 3(4), P. 370 - 468

Published: Dec. 1, 2023

As a vital and integral component of transportation infrastructure, pavement has direct tangible impact on socio-economic sustainability. In recent years, an influx groundbreaking state-of-the-art materials, structures, equipment, detection technologies related to road engineering have continually progressively emerged, reshaping the landscape systems. There is pressing growing need for timely summarization current research status clear identification future directions in these advanced evolving technologies. Therefore, Journal Road Engineering undertaken significant initiative introducing comprehensive review paper with overarching theme "advanced technologies". This extensive insightful meticulously gathers synthesizes findings from 39 distinguished scholars, all whom are affiliated 19 renowned universities or institutions specializing diverse multidimensional field highway engineering. It covers state anticipates development four major interconnected domains engineering: structures performance evaluation, construction equipment technology, assessment

Language: Английский

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Application of CHATGPT in civil engineering

East African Journal of Engineering, Journal Year: 2023, Volume and Issue: 6(1), P. 104 - 112

Published: June 28, 2023

Artificial Intelligence, machine learning, and the Internet of Things (IoT) are changing way tasks accomplished. CHATGPT is a well-known conversational artificial intelligence (AI) system based on generative pre-trained transformer (GPT) architecture, launched by OpenAI. trained through reinforcement learning human feedback. There advantages to use in Civil engineering, including but not limited design planning: structural analysis simulation, code compliance regulations construction management, knowledge repository information retrieval, education, research. The limitation bias datasets used training, requirement sufficient input information, as well risk transparency issues, negative consequences if generating inaccurate content. other language models civil engineering requires careful consideration ensure bypassing expert consultation particular cases. Deep Learning would have positive impact rather than replacing expertise improving infrastructure development world solving challenges facing mankind

Language: Английский

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Low-Altitude Intelligent Transportation: system architecture, infrastructure, and key technologies

Journal of Industrial Information Integration, Journal Year: 2024, Volume and Issue: unknown, P. 100694 - 100694

Published: Sept. 1, 2024

Language: Английский

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State-of-the-art review on the use of AI-enhanced computational mechanics in geotechnical engineering

Artificial Intelligence Review, Journal Year: 2024, Volume and Issue: 57(8)

Published: July 5, 2024

Abstract Significant uncertainties can be found in the modelling of geotechnical materials. This attributed to complex behaviour soils and rocks amidst construction processes. Over past decades, field has increasingly embraced application artificial intelligence methodologies, thus recognising their suitability forecasting non-linear relationships intrinsic review offers a critical evaluation AI methodologies incorporated computational mechanics for engineering. The analysis categorises four pivotal areas: physical properties, mechanical constitutive models, other characteristics relevant Among various analysed, ANNs stand out as most commonly used strategy, while methods such SVMs, LSTMs, CNNs also see significant level application. widely algorithms are Artificial Neural Networks (ANN), Random Forest (RF), Support Vector Machines (SVM), representing 35%, 19%, 17% respectively. extensive is domain accounting 59%, followed by applications at 16%. efficacy intrinsically linked type datasets employed, selected model input. study outlines future research directions emphasising need integrate physically guided adaptive learning mechanisms enhance reliability adaptability addressing multi-scale multi-physics coupled problems geotechnics.

Language: Английский

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An analysis approach for building collapse accident using system thinking approach and SEA model

Smart Construction and Sustainable Cities, Journal Year: 2023, Volume and Issue: 1(1)

Published: Sept. 12, 2023

Abstract The frequent occurrence of building collapse accidents not only causes significant casualties, but also jeopardizes local economies. This paper adopts a combinatory assessment approach to showcase the lessons learned from recent in Changsha, China. proposed blends system thinking and strategic environmental (SEA) model. It delineates provide key leverage points for safety management. results show that primary are poor construction quality, illegal alterations, lack regulations enforcement. management rural housing Hunan Province achieved total score 4 out 30. was determined prevention measures abating these deleterious phenomena involve ensuring quality assurance/quality control, efficiently assessing risk, timely performing structural health monitoring. study is bound enhance understanding foster achievement sustainable cities communities.

Language: Английский

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A Systematic Review on Formwork Pressure Exerted by Self-Compacting Concrete: Parameters, Prediction Models, and Advances in Monitoring Technologies

Iranian Journal of Science and Technology Transactions of Civil Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 25, 2025

Language: Английский

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Multivariate engineering formulas discovery with knowledge‐based neural network

Computer-Aided Civil and Infrastructure Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 26, 2025

Abstract Multivariate engineering formulas are the foundation of various standards worldwide for constructing complex systems. Traditional formula discovery methods suffer from low efficiency, curse dimensionality, and physical interpretability. To address these limitations, this study proposes a knowledge‐based method efficiently generating multivariate directly data. The consists four components: (1) deep generative model considering dimensional homogeneity, (2) physics‐adaptive normalization multiple variables with different units, (3) feature merging algorithm grounded in dimensionality theory, (4) machine learning‐based data segmentation piecewise formulas. Experiments on two ground‐truth datasets demonstrate that our proposed improves accuracy generated by 35.6% (measured mean absolute error), compared to Eureqa program. Additionally, it enhances mechanistic interpretability results, both emerging physics‐informed neural network‐based equation methods. successfully capture implicit mechanisms experimental data, consistent theoretical analysis. Overall, holds great promise improving efficiency discovering interpretable generalizable formulas, facilitating transformation new techniques testing applications.

Language: Английский

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Designing a reliable machine learning system for accurately estimating the ultimate condition of FRP-confined concrete

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Sept. 3, 2024

Language: Английский

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Unlocking the Potential of Artificial Intelligence for Sustainable Water Management Focusing Operational Applications

Water, Journal Year: 2024, Volume and Issue: 16(22), P. 3328 - 3328

Published: Nov. 19, 2024

Assessing diverse parameters like water quality, quantity, and occurrence of hydrological extremes their management is crucial to perform efficient resource (WRM). A successful WRM strategy requires a three-pronged approach: monitoring historical data, predicting future trends, taking controlling measures manage risks ensure sustainability. Artificial intelligence (AI) techniques leverage these knowledge fields single theme. This review article focuses on the potential AI in two specific areas: supply-side demand-side measures. It includes investigation applications leak detection infrastructure maintenance, demand forecasting supply optimization, treatment desalination, quality pollution control, parameter calibration optimization applications, flood drought predictions, decision support systems. Finally, an overview selection appropriate suggested. The nature adoption investigated using Gartner hype cycle curve indicated that learning application has advanced different stages maturity, big data reach plateau productivity. also delineates pathways expedite integration AI-driven solutions harness transformative capabilities for protection global resources.

Language: Английский

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