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Developing a reliable cost estimate at the early stage of construction projects is challenging due to inadequate project information. Most of the information during this stage is qualitative, posing additional challenges to achieving accurate cost estimates. Additionally, there is a lack of tools that use qualitative project information and forecast the budgets required for project completion. This research, therefore, aims to develop a model for setting project budgets (excluding land) during the pre-conceptual stage of residential buildings, where project information is mainly qualitative.

Due to the qualitative nature of project information at the pre-conception stage, a natural language processing model, DistilBERT (Distilled Bidirectional Encoder Representations from Transformers), was trained to predict the cost range of residential buildings at the pre-conception stage. The training and evaluation data included 63,899 building permit activity records (2021–2022) from the Victorian State Building Authority, Australia. The input data comprised the project description of each record, which included project location and basic material types (floor, frame, roofing, and external wall).

This research designed a novel tool for predicting the project budget based on preliminary project information. The model achieved 79% accuracy in classifying residential buildings into three cost_classes ($100,000-$300,000, $300,000-$500,000, $500,000-$1,200,000) and F1-scores of 0.85, 0.73, and 0.74, respectively. Additionally, the results show that the model learnt the contextual relationship between qualitative data like project location and cost.

The current model was developed using data from Victoria state in Australia; hence, it would not return relevant outcomes for other contexts. However, future studies can adopt the methods to develop similar models for their context.

This research is the first to leverage a deep learning model, DistilBERT, for cost estimation at the pre-conception stage using basic project information like location and material types. Therefore, the model would contribute to overcoming data limitations for cost estimation at the pre-conception stage. Residential building stakeholders, like clients, designers, and estimators, can use the model to forecast the project budget at the pre-conception stage to facilitate decision-making.

Prefabricated technology is gradually being applied to the construction of subway stations due to its characteristic of mechanization. However, the prefabricated subway station in China is in the initial stage of development, which is prone to construction safety issues. This study aims to evaluate the construction safety risks of prefabricated subway stations in China and formulate corresponding countermeasures to ensure construction safety.

A construction safety risk evaluation index system for the prefabricated subway station was established through literature research and the Delphi method. Furthermore, based on the structure entropy weight method, matter-element theory and evidence theory, a hybrid evaluation model is developed to evaluate the construction safety risks of prefabricated subway stations. The basic probability assignment (BPA) function is obtained using the matter-element theory, the index weight is calculated using the structure entropy weight method to modify the BPA function and the risk evaluation level is determined using the evidence theory. Finally, the reliability and applicability of the evaluation model are verified with a case study of a prefabricated subway station project in China.

The results indicate that the level of construction safety risks in the prefabricated subway station project is relatively low. Man risk, machine risk and method risk are the key factors affecting the overall risk of the project. The evaluation results of the first-level indexes are discussed, and targeted countermeasures are proposed. Therefore, management personnel can deeply understand the construction safety risks of prefabricated subway stations.

This research fills the research gap in the field of construction safety risk assessment of prefabricated subway stations. The methods for construction safety risk assessment are summarized to establish a reliable hybrid evaluation model, laying the foundation for future research. Moreover, the construction safety risk evaluation index system for prefabricated subway stations is proposed, which can be adopted to guide construction safety management.

This study aims to assess the efficacy of thermal analysis of concrete slabs by including different insulation materials using ANSYS. Regression equations were proposed to predict the thermal conductivity using concrete density. As these simulation and regression analyses are essential tools in designing the thermal insulation concretes with various densities, they sequentially reduce the associated time, effort and cost.

Two grades of concretes were taken for thermal analysis. They were designed by replacing the natural fine aggregates with thermal insulation aggregates: expanded polystyrene, exfoliated vermiculite and light expanded clay. Density, temperature difference, specific heat capacity, thermal conductivity and time were measured by conducting experiments. This data was used to simulate concrete slabs in ANSYS. Regression analysis was performed to obtain the relation between density and thermal conductivity. Finally, the quality of the predicted regression equations was assessed using root mean square error (RMSE), mean absolute error (MAE), integral absolute error (IAE) and normal efficiency (NE).

ANSYS analysis on concrete slabs accurately estimates the thermal behavior of concrete, with lesser error value ranges between 0.19 and 7.92%. Further, the developed regression equations proved accurate with lower values of RMSE (0.013 to 0.089), MAE (0.009 to 0.088); IAE (0.216 to 5.828%) and higher values of NE (94.16 to 99.97%).

The thermal analysis accurately simulates the experimental transfer of heat across the concrete slab. Obtained regression equations proved helpful while designing the thermal insulation concrete.

The purpose of this paper is to identify the key aspects of building defects performance cases in relation to the building components focusing on the government-owned buildings and to enhance government’s role to curb the building defects to reoccur.

The qualitative research method approach was adopted with a total of 5,243 specific building defects identified and accumulated from actual building projects and provided feedback on the defects associated with the Government of Malaysia’s owned buildings.

This paper statistically validates that building defects are a staid delinquent matter fronting the construction industry in Malaysia. This matter needs to be tacked by all the parties involved in the industry. This paper proposes a factual statistical statement that is proved to be a practical and suitable measurement in correcting building defects and preventing them from reoccurring.

Future research could focus on developing a defect performance measurement on real projects now focusing on private buildings as well.

The defects performance statistical measurement is anticipated to prove the problematic rate of defects occurrence on government-owned structures, as the key elements on the national defect preventive strategy which have to be taken into account.

The outcome of this paper is significant in its own right and serves as a platform for future research in this area.

The United Nations has demonstrated a commitment to preserving the ecosystem through its 2030 sustainable development goals agenda. One crucial objective of these goals is to promote a healthy ecosystem and discourage practices that harm it. Building materials production significantly contributes to the emissions of greenhouse gases. This poses a threat to the ecosystem and prompts a growing demand for sustainable building materials (SBMs). The purpose of this study is to investigate SBMs to determine their utilization in construction operations and the potential impact their application could have on construction productivity.

A systematic review of the existing literature in the field of SBMs was conducted for the study. The search strings used were “sustainable” AND (“building” OR “construction”) AND “materials” AND “productivity”. A total of 146 articles were obtained from the Scopus database and reviewed.

Bio-based, cementitious and phase change materials were the main categories of SBMs. Materials in these categories have the potential to substantially contribute to sustainability in the construction sector. However, challenges such as availability, cost, expertise, awareness, social acceptance and resistance to innovation must be addressed to promote the increased utilization of SBMs and enhance construction productivity.

Many studies have explored SBMs, but there is a dearth of studies that address productivity in the context of SBMs, which leaves a gap in understanding. This study addresses this gap by drawing on existing studies to determine the potential implications that using SBMs could have on construction productivity.

This study aims to provide a framework for assessing the technical condition of a house to determine its market value, including the identification of other price-setting factors and their statistical significance. Time on market (TOM) in relation to the technical condition of a house is also addressed.

The primary database contains 631 houses, and the initial asking price and selling price are examined. All the houses are located in the Brno–venkov district in the Czech Republic. Regression analysis was used to test the influence of price-setting factors. The standard ordinary least squares estimator and the maximum likelihood estimator were used in the frame of generalized linear models.

Using envelope components of houses separately, such as the façade condition, windows, roof, condition of interior and year of construction, brings better results than using a single factor for the technical condition. TOM was found to be 67 days lower for houses intended for demolition – as compared to new houses – and 18 days lower for houses to refurbishment.

To the best of the authors’ knowledge, this paper is original in the substitution of specific price-setting factors for factors relating to the technical condition of houses as well as in proposing the framework for professionals in the Czech Republic.

The study aims to identify and evaluate relevant criteria in the proposal and support of public administration policies for preventive maintenance comprised in a conservation approach to built heritage and aligned with local sustainable development of the historic center of the city of Sobral, in Brazil.

A novel multicriteria decision model adopting the Bayesian best-worst method is presented and its application and results are described. Though a systematic procedure, criteria were selected in order to protect the tangible and intangible values of cultural heritage, as well as its sustainable development. Then experts evaluate these criteria through an elicitation instrument.

The results show that for the decision problem over preventive maintenance, social contribution and historical record of built heritage are more important than its structural vulnerability, while architecture is less relevant. Due to the low restrictions, the subcriterion related to this property has the least influence. The weights can assist in the characterization of measures and policies for the protection of the built cultural heritage.

The use of a novel decision-making method in cultural heritage is an important initiative, given the frequent use of simple and inefficient methods. The identified and weighted criteria are important data to characterize the scenario and the topic. The results contribute to protection and development of the built heritage, encouraging the implementation of preventive conservation in the historic center, conferring to the public administration valuable information to support and propose initiatives.

In the event of a disaster, educational institutions like schools serve as lifeline buildings. Hence, it is crucial to safeguard these buildings for the communities that may depend on the school as a disaster shelter and aid center. Thus, this paper aims to conduct a multihazard risk assessment survey at 50 schools (with 246 building blocks) in Dehradun.

The past few decades have witnessed the impact of multihazard frequency in Uttarakhand, India, due to the geographical features of the Himalayas and its neo-tectonic mountain-building process. Dehradun is the capital of Uttarakhand state and comes under seismic zone IV, which is highly prone to earthquakes.

The hazard assessment is divided into two types of surveys: first, building-level surveys that include rapid visual screening, nonstructural risk assessment and fire safety audit, and second, campus-level surveys that include vulnerability analysis for earthquake, flood, industrial hazard, landslide and wind.

This paper will list several gaps and unrecognized practices in the region that increase the schools’ multihazard risk. The study’s outcome will help prioritize the planning of disaster awareness, retrofitting execution, future construction practices and decision-making to minimize the risk and prepare the school for the upcoming disasters.

Physical data were collected by the author to determine the multihazard risk analysis in 50 schools in the Dehradun District of Uttarakhand, India. The building- and campus-level surveys have been used to generate a database for the retrofit and renovation process for each individual school to use their budget fruitfully and in a planned way. The survey conducted is more effort and a more detailed risk evaluation which necessitates effectively mitigating and ensuring the potential safety of the region’s schools.

This study has assessed the thermal performance of locally fabricated bio-based building envelopes made of coconut and corn husk composite bricks to reduce building wall heat transmission load and energy consumption towards green building adaptation.

Samples of coconut fiber (coir) and corn husk fiber bricks were fabricated and tested for their thermophysical properties using the Transient Plane Source (TPS) 2500s instrument. A simulation was conducted using Dynamic Energy Response of Building - Lunds Tekniska Hogskola (DEROB-LTH) to determine indoor temperature variation over 24 h. The time lag and decrement factor, two important parameters in evaluating building envelopes, were also determined.

The time lag of the bio-based composite building envelope was found to be in the range of 4.2–4.6 h for 100 mm thickness block and 10.64–11.5 h for 200 mm thickness block. The decrement factor was also determined to be in the range of 0.87–0.88. The bio-based composite building envelopes were able to maintain the indoor temperature of the model from 25.4 to 27.4 °C, providing a closely stable indoor thermal comfort despite varying outdoor temperatures. The temperature variation in 24 h, was very stable for about 8 h before a degree increment, providing a comfortable indoor temperature for occupants and the need not to rely on air conditions and other mechanical forms of cooling. Potential energy savings also peaked at 529.14 kWh per year.

The findings of this study present opportunities to building developers and engineers in terms of selecting vernacular materials for building envelopes towards green building adaptation, energy savings, reduced construction costs and job creation.

This study presents for the first time, time lag and decrement factor for bio-based composite building envelopes for green building adaptation in hot climates, as found in Ghana.

Gourd fibres (GF) are a natural biodegradable fibre material with excellent mechanical properties and high tensile strength. The use of natural fibres in composite materials has gained popularity in recent years due to their various advantages, including renewability, low cost, low density and biodegradability. Gourd fibre is one such natural fibre that has been identified as a potential reinforcement material for composites. However, it has low surface energy and hydrophobic nature, which makes it difficult to bond with matrix materials such as polyester. To overcome this problem, chemically adapted gourd fibre has been proposed as a solution. Chemical treatment is one of the most widely used methods to improve the properties of natural fibres. This research evaluates the feasibility and effectiveness of incorporating chemically adapted gourd fibre into polyester composites for industrial fabrication. The purpose of this study is to examine the application of chemically modified GF in the production of polyester composite engineering materials.

This work aims to evaluate the effectiveness of chemically adapted gourd fibre in improving the adhesion of gourd fibre with polyester resin in composite fabrication by varying the GF from 5 to 20 wt.%. The study involves the preparation of chemically treated gourd fibre through surface modification using sodium hydroxide (NaOH), permanganate (KMnO₄) and acetic acid (CH₃COOH) coupling agents. The mechanical properties of the modified fibre and composites were investigated. It was then characterized using scanning electron microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR) to determine the changes in surface morphology and functional groups.

FTIR characterization showed that NaOH treatment caused cellulose depolymerization and caused a significant increase in the hydroxyl and carboxyl groups, showing improved surface functional groups; KMnO₄ treatment oxidized the fibre surface and caused the formation of surface oxide groups; and acetic acid treatment induced changes that primarily affected the ester and hydroxyl groups. SEM study showed that NaOH treatment changed the surface morphology of the gourd fibre, introduced voids and reduced hydrophilic tendencies. The tensile strength of the modified gourd fibres increased progressively as the concentration of the modification chemicals increased compared to the untreated fibres.

This work presents the designed composite with density, mechanical properties and microstructure, showing remarkable improvements in the engineering properties. An 181.5% improvement in tensile strength and a 56.63% increase in flexural strength were got over that of the unreinforced polyester. The findings from this work will contribute to the understanding of the potential of chemically adapted gourd fibre as a reinforcement material for composites and provide insights into the development of sustainable composite materials.