Construction Sector Research Articles

Analytical Hierarchy Process for Construction Safety Management and Resource Allocation

The construction industry plays a crucial role in contributing to the economy and developing sustainable infrastructures. However, it is known as one of the most dangerous industrial domains. Over the years, special attention has been paid to developing models for managing and planning construction safety. Many research studies have been carried out to analyze the root causes of fatal accidents in construction sites to develop models for preventing them and mitigating their consequences. Root cause identification and analysis are essential for effective risk mitigation. However, implementing mitigation activities is usually limited to the project’s safety budget. The construction sector suffers from a lack of allocation of appropriate safety resources triggered by a dynamic and complex project environment. This study aims to address the gap in safety resource allocation through a comprehensive root cause analysis of construction work accidents. In this paper, we present a comprehensive review of work accident-related research, categorized according to the 5M model into five root factors: medium, mission, man, management, and machinery. A novel methodology for construction safety resource allocation is proposed to mitigate risks analyzed by the 5M model with the aid of advanced technological solutions. Safety resource allocation alternatives are formulated, and their priorities are established based on an analysis of structured criteria that integrate both risk and cost considerations. The Analytical Hierarchy Process (AHP) is employed to select the optimal alternative for safety resource allocation, with the objective of effective risk mitigation. The proposed model underwent validation through two different case studies. The findings indicate that risk aversion is a critical factor in the optimal allocation of safety resources. Furthermore, the results suggest that regulatory measures should prioritize the stimulation of risk motivation in the safety decision-making processes of construction firms.

Determinants of Foreign Direct Investment in the Construction Sector in Nepal

Determinants of Foreign Direct Investment in the Construction Sector in Nepal

HBIM MODELLING PROCESS FROM 3D POINT CLOUDS BY APPLYING ARTIFICIAL INTELLIGENCE ALGORITHMS IN CULTURAL HERITAGE

In the context of Cultural Heritage (CH), the widespread adoption of 3D point cloud technology, coupled with Artificial Intelligence (AI) algorithms, plays a pivotal role. These technologies facilitate the creation of as-built models by integrating Building Information Modelling (BIM) strategies, enhancing collaboration within the Architecture, Engineering, and Construction (AEC) sector. Leveraging computer vision, robotics, and remote sensing, 3D points clouds provide rich data. However, manual segmentation and classification are labor-intensive and error prone. Consequently, researchers increasingly turn to machine learning (ML) and deep learning (DL) techniques for automating these tasks. The transition from manual reconstruction to automated procedures is crucial. Despite progress, gaps remain, particularly in incorporating 3D point cloud segmentation into Historical Building Information Modelling (HBIM). The lack of conclusive evidence regarding automated derivation of parametric attributes from segmentation outcomes underscores the need for further exploration. Addressing this gap is essential for cultural asset documentation, conservation, and upkeep. By automating the segmentation and classification of 3D point clouds, efficient communication via a shared database becomes feasible. The article aims to review studies on semantically parsing and classifying 3D point clouds using AI algorithms, particularly within complex cultural heritage geometries, shedding light on potential benefits and barriers.

Key Factors Influencing Consumer Choices in Wood-Based Recycled Products for Circular Construction Sector

This article explores the integration of wood recycling and reuse practices within construction and reconstruction processes, as highlighted in a wood products questionnaire. The aim of this study is to understand how the Romanian consumers perceive the circular economy in order to adopt responsible consumption models. The working instrument consisted of a questionnaire. The questionnaire was applied to 60.7% urban respondents and 39.3% rural ones and consisted of 23 items. The response rate was 68.5% for certain items (257 responses). In the first part, the integration of wood recycling and reuse practices within construction and reconstruction processes is examined. Emerging recycling techniques and demolition processes, particularly incorporating reused, reconditioned, and recycled wood in the construction industry, are evaluated. The economic and environmental implications of these practices are also examined, contributing to the discussion of eco-design policies, and construction waste management and standards. In the second part, insights are provided into how Romanian consumers’ knowledge of CE principles, information about product characteristics, and attitudes influence the demand for recycled wood products. The study concludes with recommendations for better promotion strategies of wood-based recycled products, aiming to increase awareness of its long-term environmental and socio-economic benefits. Additionally, it suggests the need for providing more information on the environmental benefits of wood-based recycled products, and for a more active engagement of stakeholders in the transition to a circular economy. The results serve as a basis for a better understanding of Romanian consumers’ adoption of sustainable consumption behavior in agreement with circular economy concepts and SDGs. While the majority of respondents generally shows openness to an eco-friendly product, mere promotion of these principles may not suffice to change entrenched behaviors and purchasing habits.

Role of the Regulation Framework in Occupational Safety in Construction Excavation Works—A Survey Analysis in Turkey

The construction sector is known to have the highest risks of occupational accidents. A rationale for this high occurrence of occupational risks can be related to legislative requirements to enforce safe construction practices within this sector. Within the context of excavation works in Turkey, this study investigates the leading risks for any compliance shortfalls and ultimately presents recommendations to mitigate occupational accidents’ occurrences during excavation works in the construction sector. Based on a quantitative methodology, a closed-ended survey consisting of 35 questions and based on legislative requirements was applied to project managers in the construction industry, such as site supervisors, occupational safety experts, auditors, and control personnel. A sample size of 277 responses was found to have stability and validity through a reliability analysis and an exploratory factor analysis, and was used for testing statistical significance via cross-tabulation analysis and chi-square tests. The findings revealed that the major deviation of safety in excavation works from legislative requirements is executing works during adverse weather conditions. Moreover, it was also noteworthy that protective curtains did not surround the excavation sites, and most of the employees encountered ground slippage during excavation work. Therefore, the findings revealed preliminary research that will contribute positively to providing incentives for a focus on and development of relevant security and technical measures. It also provided information to protect the safety and welfare of the workers involved in excavation works. Finally, though these findings may be considered context-specific, this research can be used for comparative purposes for similar studies into the safety practices of excavation works in different countries, where generalized findings can be later derived to inform academia and practice.

Going beyond carbon: Influence of structural parameters on the environmental impacts of typical building structures

The construction sector has a large impact on the environment, be it climate change, biodiversity loss or resources depletion. Part of those impacts comes from construction materials, and more specifically, concrete and steel building structures. Early-stage design tools including environmental damage assessment are therefore required to achieve sustainable construction practices. This article presents a parametric approach aiming at studying the influence of early-stage structural parameters on the environmental impacts of a structure. The developed methodology combines parametric structural design with a multicriteria cradle-to-grave Life Cycle Assessment, applied to typical housing structures such as grid based beam column structures with a central core for lateral stability. Results show that span, number of levels and materials greatly influence the environmental impacts of considered structures. Climate change scores per floor area range from 80 kgCO2/m2 for short span timber structure to 215 kgCO2/m2 for long span steel buildings with few levels. Beams and slabs have the largest contribution in such impacts. Changing the production processes of materials is a way to reduce greenhouse gas emissions. However, decarbonizing steel production processes or reducing the cement content of concrete participate in burdenshifting with increased scores in several impact categories, such as carcinogenic toxicity or ozone depletion.

Defining quality by quantifying degradation in the mechanical recycling of polyethylene

Polyolefins have a multitude of uses across packaging, automotive and construction sectors. Their resistance to degradation during reprocessing enables recyclability, but variability in recycled polymer feedstocks renders it difficult to assure their manufacturing suitability. The lack of quality control methods has disabled circular economy pathways; product failure is costly, wasteful and time-intensive. Using rheology-simulated and extrusion-based recycling experiments, we explore the degradation pathways of high-density polyethylene (HDPE). Chain scission dominates during the initial degradation of HDPE, and increasing exposure to O2 shifts the dominant mechanism to long-chain branching. Importantly, extending this method to post-consumer recyclate (PCR), the results show potential as a methodology to assess recyclate quality to enable a circular plastics economy. In this study, we establish the validity of this rheology simulation to define a characteristic degradation parameter, relating it to the structural evolution under different environments defined for virgin HDPE and post-consumer recyclate (PCR).

Addressing the Difficulties and Opportunities to Bridge the Integration Gaps of Bio-Based Insulation Materials in the European Construction Sector: A Systematic Literature Review

Bio-based insulation materials (BbIMs) represent a potential alternative to conventional insulations, with their characteristics that favor a negative-carbon built environment. However, their use may face challenges that could prevent them from being used on a large scale in certain countries. The current study aims to provide focused insights into the practical difficulties and market opportunities for the application of BbIMs in Europe through a systematic literature review (SLR). The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were used as the basis for the conduct and reporting of this review. A keyword search was performed in Web of Science, Scopus, and ScienceDirect databases to select peer-reviewed English-language articles. HubMeta web tool was used to organize the selection process. The quantitative visualization of the literature was made by the Bibliometrix R package V4.1.4. Data were manually extracted and clustered in an Excel sheet. The review included 28 studies that have revealed interrelated insights. Difficulties range from regulatory and policy limitations and variability in performance, such as microbial growth and inconsistency in the behavior of materials under different conditions, to cost barriers. However, there are promising opportunities, including policy incentives and material performance benefits such as improved energy efficiency and indoor air quality. This research contributes to the literature by providing focused insights into the practical difficulties and market opportunities for the application of BbIMs in Europe. Research gaps and future perspectives point to the need for more field validation experiments, exploration of alternative production processes, and expanding life cycle assessment scopes to optimize their integration and performance. Stakeholders’ perceptions were made with a small sample in certain countries. Stakeholder perceptions were conducted with a small sample in some countries, so insights from stakeholders are needed to confirm or correct current findings.

Construction 4.0 implementation for performance improvement: an innovation management perspective

Purpose The emergence of Construction 4.0 technologies provides an impetus for radical change and rejuvenates the interest of stakeholders in addressing long-standing performance issues in the construction sector. However, construction firms struggle to implement Construction 4.0 technologies for performance measurement and improvement. Therefore, the purpose of this research is to develop a conceptual model of innovation management for implementing Construction 4.0 that guides and facilitates the strategic transformation of construction firms. Design/methodology/approach A conceptual model of innovation management is presented, and the findings are synthesised based on a literature review, 20 semi-structured interviews, two focus group discussions, three workshops, expert consultation and observations on three digitally-enabled projects. Data were inductively analysed using thematic analysis. Findings The analysis of empirical data revealed: (i) Four scenarios that could lead the industry to different futures, based on the extent of research and development, and the extent of integration/collaboration; (ii) Construction 4.0 capability stages for a sustained implementation route; (iii) Possible business model configurations derived from servitisation strategies; and (iv) Skills management challenges for organisations. Research limitations/implications First, the empirical data was only collected in the UK with its unique industry context, which may limit the applicability of the results. Second, most of the research data comes from the private sector, without the views of public sector organisations. Third, the model needs to be further validated with specific data-driven use cases to address productivity and sustainability issues. Practical implications Successful Construction 4.0 transformation requires a concerted effort of stakeholders, including those in the supply chain, technology companies, innovation networks and government. Although a stakeholder’s action would depend on others’ actions, each stakeholder should undertake action that can influence the factors within their control (such as the extent of collaboration and investment) and the outcomes. Originality/value The conceptual model brings together and establishes the relationships between the scenarios, Construction 4.0 capability stages, business models and skills management. It provides the first step that guides the fuzzy front-end of Construction 4.0 implementation, underpins the transformation to the desired future and builds long-term innovation capabilities.

Life cycle assessment and generative design: development of a national LCA tool for exterior walls

PurposeThe promotion of sustainable design is demanded globally. The life cycle assessment (LCA) proved its reliability in this mission, but the difficulty and time required to apply it discouraged designers. This research aims to integrate LCA into the building design process through a software tool, taking advantage of generative design features. This will facilitate decision-making by architects and construction professionals.Design/methodology/approachThe study develops the EGY-LCA (http://egy-lca.com/). This prototype tool suggests exterior wall design alternatives for residential buildings in Egypt, using the environmental impact indicators of LCA data and other criteria related to national codes, materials, construction methods and required thermal resistance. Within a generative design process, the algorithm tests every possible wall method with materials and thickness combinations for each layer in compliance with inputs. The paper begins by explaining the tool’s working method. Afterward, different sets of inputs are examined and the values of the resultant environmental impacts of several suggested wall solutions are statistically analyzed. The application demonstrates the importance of the generative design tool. Proposing several solutions based on a set of inputs facilitates the selection of sustainable choices and allows comparisons between alternatives.FindingsThe prototype experiment confirms the research hypothesis. Unlike the available LCA tools, architects can make decisions with limited LCA experience if the data and equations are integrated into a generative design tool. The prototype proves its applicability for exterior wall alternatives.Research limitations/implicationsThe prototype is the initial step toward a whole-building LCA tool. It includes limited LCA stages and materials for the external wall. Future research is required to expand this parametric tool concept to include all the building components. The framework in Section 5 proposes a visualization.Practical implicationsThe prototype tool: EGY-LCA (http://egy-lca.com/). The value added to the design and construction sectors through the uncomplicated LCA application is fostering sustainable design, generative design tools can achieve this.Originality/valueThe novelty of this work is that it is the first initiative offering a parametric LCA tool. It promotes the application of LCA at the design stage using generative design, which contributes to sustainable development.

Use of data science in the development of concrete based on construction and demolition waste: a brazilian view

The growth in urbanization and construction activity has led to a growing increase in construction and demolition waste and the extraction of natural resources, energy, and CO2. The projection is that these figures will expand even more in the coming years, making it worrying for a sustainable balance in construction, especially in the manufacture of concrete, which is one of the most consumed materials globally. In this context, recycled concrete has emerged as a sustainable alternative to traditional concrete. Concepts such as urban mining combined with data mining and machine learning techniques are emerging as alternatives that serve as a basis for producing recycled concrete with the required qualities. Therefore, this study aims to map the existing research in the areas of materials and technology, focusing on the recycling and reuse of construction and demolition waste (CDW) and the manufacture of recycled concrete. Surveying this research will provide guidance for future research and encourage more sustainable standards in the construction sector.

Heating Energy Performance Gap in Vulnerable Households: Identification and Impact of Associated Variables

Reducing energy consumption in the construction sector is urgently needed. In Chile, where income distribution is unequal and the cost of energy is high, energy demand is seriously affected, especially in vulnerable households. Hence, it is essential to establish public policies with more realistic energy-saving goals to address this situation. However, reliably predicting the energy performance of buildings remains a challenge. For this reason, this study aims to identify and evaluate the impact of the variables associated with energy performance in vulnerable households in Central-Southern Chile and propose values that would reduce the gap. A sensitivity analysis was conducted to achieve this, adjusting the energy performance parameters in a base model with data analyzed using local standards. In addition, field information was collected in 93 households to obtain the actual energy consumption. The main results show that the variables that most impacted performance were infiltration, COP, heating setpoints, and schedules, which generated a 60% difference between the theoretical and actual consumption.

Design, modelling and optimisation of ultra high-performance fibre reinforced concrete incorporating waste materials

The adoption of ultra-high-performance fibre-reinforced concrete (UHPFRC) in modern-day construction has gradually increased because of its high compressive and flexural strength at the early production ages. The UHPFRC's high initial cost discourages its production and widespread use. This cost can be reduced by incorporating waste materials in UHPFRC production. This study aims to design, model, and optimise a three-day heat-cured UHPFRC incorporating waste materials. To produce a sustainable UHPFRC mixture, this study combines rice husk ash (RHA) and recycled tire steel fibre (RTSF) as the primary waste components, with Portland limestone cement, river sand, superplasticizer, and water. The concrete is heat-cured in a hot water bath at 90 °C for 3 days, resulting in rapid strength development. A D-optimal mixture design technique was used to optimise the mix proportions, and mathematical models were developed to predict the compressive and flexural strengths. The non-significant lack-of-fit results and the high values of coefficient of determination (R2) revealed the accuracy of the models in predicting the compressive and flexural strengths of the UHPFRC. The low values of standard deviation (SD) and coefficient of variation (CV) confirmed the consistency and reliability of the prediction models. A numerical optimisation revealed that it is possible to design a UHPFRC mixture with a lower cement content of 38.29% of the UHPFRC mix, resulting in a compressive strength of 117.62 MPa and a flexural strength of 36.32 MPa. The study reveals that integrating RHA and RTSF into UHPFRC can yield high-performance properties, offering innovative solutions for resource scarcity and environmental sustainability in the construction sector.

A Influência de Brises e Cortinas na Eficiência Energética de Edifícios de Escritório

The construction sector is responsible for a significant portion of energy consumption and greenhouse gas emissions. In this sense, it is extremely important that initiatives are developed to reduce the energy consumption of buildings, contributing to the sustainability of these buildings. Among the alternatives for reducing energy consumption is the possibility of inserting shading devices into building windows. In this context, this work aims to analyze the influence of the use of shading devices on windows of an office building model geographically located in Passo Fundo - RS. To this end, 24 computer simulations were carried out using the Energy Plus software in a model of an office building considering its windows without any shading device and, subsequently, with the installation of two different types of sun shades and curtains that act according to the internal temperature of the building. environment and with a pre-defined agenda. Single and double glazing were also tested. The results revealed positive influences of shading devices in the office building, reducing electrical energy consumption by up to 4.64% in relation to the reference case. Therefore, the use of sunshades and curtains can help reduce energy consumption in the building, maintaining the thermal comfort of the environment.

Effect of Delay on Profitability of Building Construction Projects

In construction, delay could be defined as the time overrun either beyond completion date specified in a contract, or beyond the date that the parties agreed upon for delivery of a project. It is a project slipping over its planned schedule and is considered as common problem in construction projects. The Indian construction sector has acted as an engine of growth for the Indian economy for over the past five-decades and becoming a basic input for the socio-economic development of the country. Construction is the second largest economic activity after agriculture, and has contributed around 6 to 9% of India's GDP over the past five years while registering 8 to 10% growth per annum. This paper refers to study effect of delay in construction industry particularly in profitability or economic factors. Keywords: Construction, Delay, Profitability, GDP, Economic factor

Examining the Relationship Between Project Complexity and Project Success: The Moderating Role of Project Management Competencies in Ghana’s Construction Sector

ABSTRACT This study seeks to examine the relationship between project complexity and project success in construction projects in Ghana while assessing the moderating role of project management competencies (PMC). Using a quantitative cross-section research design, data was collected from 141 respondents in organizations that undertake construction projects in Ghana. Responses were analyzed using IBM SPSS (v.23.0) and Smart PLS 3.0. The results established a negative relationship between Technological, Organizational, and Environmental complexity and project success. Technological complexity was seen as the dimension of complexity that significantly affects the success outcomes of projects. PMC’s moderating influence was insignificant. The findings suggest that, for projects to have an increased success rate, organizations must thoroughly investigate the kind of project complexity expected to be present in the project, and this will inform decisions on the caliber of skills/competencies needed for a successful execution of the project.

The Relationship Between Sectoral Employment and Real Sector Economic Confidence: Fourier Causation Analysis

Purpose –In order to ensure economic growth in the short term and economic development in the long term, it is important to evaluate the events occurring in the political and economic order correctly and to meet the expectations. This study was created to evaluate the effectiveness of economic confidence on the relevant sectors on a sectoral basisDesign/Methodology/Approach –In this study, the relationship between the real sector economic confidence index and employment rates in industry, construction and services sectors will be analyzed. Turkey is selected as the sample and the data range subject to the analysis is determined as 2009:01-2023:08. In the study, the Fourier analysis method, which is among the new generation analysis methods, was applied, and Fractional Frequency Fourier Augmented Dickey Fuller Unit Root Test and Fourier Toda-Yamamoto Causality Test were applied.Findings –As a result of the application, a one-way causality relationship from the real sector economic confidence index to building and industry sector employment was determined. A recommendation should be made regarding the necessity of making political arrangements that will maintain the stability level of employment in the relevant sector.Discussion –In line with the data obtained in this study, the fact that real economic confidence has an effect on employment in the construction and industrial sectors, in addition to the fact that sectoral employment has no effect on the real economic confidence index, can be linked to the fact that sectoral leaders pursue a policy of contraction or expansion within the framework of expectations

Network-Based Modeling of Lean Implementation Strategies and Planning in Prefabricated Construction

Abstract: Prefabricated construction (PC) is increasingly promoted in the construction sector for its potential benefits, including reduced resource assumption and improved quality. Accordingly, Lean methods are popularly applied to PC projects for optimizing operational processes and enhancing their performance in line with strategic objectives. A key factor in effectively implementing Lean to improve strategic control is developing specific strategies and planning that consider their complex interactions. Thus, this paper aims to propose a quantitative network-based model by integrating Interpretive Structural Modeling (ISM) and Matrix Impact Cross-Reference Multiplication Applied to a Classification (MICMAC) under complex network theory to develop a Lean implementation framework for effective strategy formulation. Specifically, 17 Lean implementation strategies for PC in the context of the Chinese prefabrication industry were identified via an extensive literature review and expert interviews. Then, ISM-MICMAC quantitatively identifies the direct and indirect relationships among strategies, while subsequent analysis of Topological Structure Weight (TSW) and Structural Degree Weight (SDW), as complex network parameters, is used to evaluate the importance of each strategy. The findings show that the strategic planning for Lean implementation in PC consists of four levels, i.e., foundation, organizational, technical, and control. Selecting appropriate Lean tools and technologies is crucial for PC implementation, which must be built on a top-level management team and foster a Lean culture. Moreover, it involves building a standardized system of processes and activities, enhancing both internal and external collaboration, and continuously improving processes in response to changes. On one hand, this in-depth network-based analysis offers practical insights for PC stakeholders, particularly in China, on Lean implementation in line with PC performance and strategic control and objectives. On the other hand, the network-based model can be future-implemented globally. Additionally, this study expands the current body of knowledge on Lean in PC by exploring the interrelationships of Lean implementation strategies.

Predictive modeling of sustainable recycled materials for stone column construction

Climate change due to carbon dioxide emissions is one of the most significant global challenges. Sustainable recycled materials are recognized as a critical factor in mitigating climate change, representing a fundamental strategy for reducing gas emissions and preserving the environment. Promising sustainable recycled materials in construction, such as crushed asphalt, crushed concrete, crushed ceramic, and treated concrete offer numerous advantages, including reduced carbon dioxide (CO2)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{(CO}}_{2} )$$\\end{document} emissions, cost-effectiveness, increased strength, and enhanced mechanical properties. In this study, various machine learning techniques, including the support vector machine (SVM), multiple linear regression (MLR), gaussian process regression (GPR), and artificial neural network (ANN), are used to assess the effectiveness of sustainable recycled materials within stone columns. The MLR model was specifically utilized to predict the ultimate stress equation for these materials within stone columns. Forty-five constructed samples were used in developing the models. The effectiveness of each model was evaluated using various statistical assessment measures, including mean absolute error (MAE), absolute fraction of variation (R2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{R}}^{2}$$\\end{document}), and root mean square error (RMSE). The predictive model’s performance was validated using the k-fold cross-validation method. The ANN model with an R2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$${\ ext{R}}^{2}$$\\end{document} value of 0.962 and an RMSE value of 7.268 kPa, performed better compared to GPR, SVM and MLR models. In summary, the results of the study indicate that the MLR model, utilizing the identified input parameters, can accurately predict the ultimate stress for different sustainable recycled materials. Implementing such technologies within the construction sector can expedite and reduce the cost of assessing material characteristics and the influence of input parameters.

Evaluation of aerial thermography for measuring the thermal transmittance (U-value) of a building façade

In efforts to mitigate greenhouse gas emissions in the construction sector, policies promoting energy efficiency improvements in existing buildings are being implemented. Accurately assessing the impact of energy retrofit strategies requires precise determination of thermal envelope performance through energy audits. Aerial thermography, employing unmanned aerial vehicles (UAVs) equipped with infrared thermal cameras (IRT), is an underused method overcoming limitations in energy audits of large buildings or complexes. This approach offers an elevated perspective, providing an overview of the building’s thermal patterns, aiding in the identification of thermal envelope defects. By measuring temperature distribution, even in inaccessible envelope areas, the severity of identified defects can be estimated. Beyond detecting thermal bridges, air leaks, and moisture, aerial thermography is valid for estimating thermal transmittance (U-value) of enclosures. The aim of this research is to evaluate this method to calculate the U-value of the façade of an university building located in a Subtropical Mediterranean climate, during a typical full day in different seasons of the year. Concurrently with aerial thermography, the thermometric method (THM) was applied to compare results and refine the operational conditions during U-value measurement using different statistical indices and uncertainty analysis. The results demonstrated the validation of airborne thermography as a method for U-value calculation under specific meteorological and operational conditions, overcoming the common physical limitations of traditional building audit methods.