Building envelope trade-off method integrated with BIM-based framework for energy-efficient building envelope

Mohanta, Ashaprava; Das, Sutapa; Mohanty, Rabi Narayan

doi:10.1080/17452007.2021.1941741

Cited by 9 publications

(2 citation statements)

References 25 publications

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“…BIM, which emerged in the 1970s [12,13], is the creation and application of coordinated, reliable, and computable data for construction projects. Such data are often parametric and can be applied to rapid design generation, planning, decision-making, document creation, and cost estimation, among other related functions [14][15][16][17].…”

Section: Design and Application Of Intelligent Construction Quality I...mentioning

confidence: 99%

Design and Application of Intelligent Construction Quality Inspection System Based on BIM-RFID

Huo

Xie

et al. 2023

Advances in Civil Engineering

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Building information modeling (BIM) and radio-frequency identification (RFID) technologies can assist with problems in the construction quality inspection process, such as difficulties with the intelligent positioning of components, data replication, and insufficient feedback information during rework and maintenance. A novel technology BIM-FRID-integration is competent for multiparticipant information sharing in construction sector by collecting, transmitting and processing the quality defect information found in the construction process. In this study, an intelligent positioning inspection system to ensure building quality was developed using leading BIM software (Autodesk Revit in a Microsoft Visual Studio environment) and RFID handheld terminal devices. To verify the effectiveness of the framework proposed in this paper, the system was applied to a practical project, and its modeling, unique identifier (UID) components, and other information generation and export processes were analyzed. The results demonstrated that the BIM-RFID-integrated building quality intelligent inspection system proposed in this paper could realize the correlation and interaction between the BIM model and the entity component information as well as accurately locate any components with quality problems and provide quick feedback of quality inspection information and visual construction annotation disclosures.

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Section: Design and Application Of Intelligent Construction Quality I...mentioning

confidence: 99%

Design and Application of Intelligent Construction Quality Inspection System Based on BIM-RFID

Huo

Xie

et al. 2023

Advances in Civil Engineering

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“…In this context, damage manifests itself more as being detrimental to serviceability, including the energy characteristics of buildings. Therefore, the correct prediction of the intensity of damage, especially in the case of existing building structures, may turn out to be crucial in terms of effectively preventing the loss of thermal properties, especially in the case of energy-efficient construction [10] or passive [11].…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Methods in Damage Prediction of Masonry Development Exposed to the Industrial Environment of Mines

2022

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This paper presents the results of comparative studies on the implementation of machine learning methods in the damage intensity assessment of masonry buildings. The research was performed on existing residential buildings, subjected to negative impacts of the industrial environment induced by coal mining plants during their whole technical life cycle. The research was justified on the grounds of safety of use, as well as potential energy losses and CO2 emissions generated by the inefficient management of building materials resources resulting from poor planning of retrofitting. In this field, the research is in line with the global trends of large-scale retrofitting of existing buildings in European countries due to their thermal insulation parameters and seismic hazard. By combining this with the effects of material degradation throughout the technical lifecycle of buildings, the proposed methods allow for a more efficient approach to maintaining quality management of large groups of buildings, which is part of the sustainable development framework. Due to the multidimensionality of the undertaken problem and the necessity of mathematical representation of uncertainty, it was decided to implement a machine learning approach. The effectiveness of the following methods was analysed: probabilistic neural network, support vector machine, naive Bayes classification and Bayesian belief networks. The complexity of individual methods dictated the order of the adopted research horizon. Within such a research plan, both model parameters were learned, and model structure was extracted from the data, which was applied only to the approach based on Bayesian networks. The results of the conducted analyses were verified by assuming classification accuracy measures. Thus, a method was extracted that allows for the best realisation of the set research objective, which was to create a classification system to assess the intensity of damage to masonry buildings. The paper also presents in detail the characteristics of the described buildings, which were used as input variables, and assesses the effectiveness of the obtained results in terms of utilisation in practice.

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Towards an Action Plan to Improve the Role of Perforated Building Envelopes in Sustainable Design

Fawaz,

Megahed,

El-Mowafy

et al. 2024

Earth and Environmental Sciences Library

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Building envelope trade-off method integrated with BIM-based framework for energy-efficient building envelope

Cited by 9 publications

References 25 publications

Design and Application of Intelligent Construction Quality Inspection System Based on BIM-RFID

Design and Application of Intelligent Construction Quality Inspection System Based on BIM-RFID

Machine Learning Methods in Damage Prediction of Masonry Development Exposed to the Industrial Environment of Mines

Towards an Action Plan to Improve the Role of Perforated Building Envelopes in Sustainable Design

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