Local Construction Research Articles

Post-Construction Defects in Multi-Unit Australian Dwellings: An Analysis of the Defect Type, Causes, Risks, and Impacts

Due to the rising prices of houses and rent, apartment buildings have become the preferred and most utilized dwellings in Australia. However, there have been cases of serious defects in multi-unit dwellings (apartment buildings), posing various risks to and reducing potential residents’ confidence in such dwellings. To address this issue, the current study investigated the types, causes, risk severity, and impacts of defects on residents in mid- to high-rise multi-unit dwellings in Australia. The study utilized a mixed approach involving quantitative (online questionnaire) and qualitative (interviews) methods. Data were collected from 104 apartment building residents in Brisbane, Queensland, Australia, with support from interviews with six experienced local construction professionals. The results revealed that there are 11 key defects present in local apartment buildings, with waterproofing, internal finishes, and structural issues being the most frequently reported. Residents typically report these defects to building owners, agents, and managers, who take more than three months, on average, to rectify them, adding to the residents’ psychological issues and their inability to use the property as intended. The reasons for the delayed rectification of defects include non-responsive owners, agents, and building management teams, scheduling conflicts, litigation, and high costs. The interviewed professionals acknowledged the presence of defects and identified the reliance on Design and Construct (D&C) and fixed price contracts, lack of public awareness, and absence of a system to capture builders’ reputation, as well as a manipulative quality check system, as key reasons for defects. This study addresses the defect concerns in multi-unit Australian dwellings (apartments) and expects to spark a much-needed debate around reforms in the construction sector to address these issues and minimize their risks and impact on residents.

Architectural Heritage Preservation for Rural Revitalization: Typical Case of Traditional Village Retrofitting in China

With the massive urbanization and industrialization in China, the paradox between fast modernization and cultural preservation arouses challenges on new insight into green construction and sustainable development strategies throughout the nation. Particularly, how to strike a balanced cultural–modern rural revitalization has become a research priority, especially for cultural and historical villages in relatively under developed western regions. In this paper, taking Gaotunzi Village, a traditional ethnic village in western high-altitude plateau as an illustrative example, the typical green design manner and optimization strategy are proposed for cultural and architectural heritage preservation. The detailed architecture and structure design is conducted for both old temple retrofitting and new museum construction, with consideration for retaining traditional building colors, styles, and materials. Moreover, land use planning is demonstrated for local public space and services upgrading. The overall design strategy has been taken into practice for the local renovation construction program. The preliminary results indicate that this green retrofitting idea and approach are quite locally feasible for sustainable rural revitalization with local heritage conservation, including traditional wooden buildings, Buddhism belief, Tibetan icons, and ethnic symbolic culture preservation and promotion. This work can provide a typical design reference and application prototype for rural construction and modernization with local heritage preservation considerations, especially for those traditional villages in developing countries.

The techno-economics of transmitting heat at high temperatures in insulated pipes over large distances

This study reports a systematic techno-economic assessment of the cost-optimal transmission for air as the heat transfer fluid at temperatures of up to 1200 °C, at scales of 1 to 1000 MW and at distances of up to 10 km. It employs a steady state heat transfer analysis, with energy balances, to assess the effect of scale, temperature and insulation on the heat losses and efficiency of the thermal transmission system, following by a techno-economic assessment. The sensitivity of the Levelised Cost of Heat, LCOHtr, to variations in thermal scale, operating temperature, distance, refractory and insulation thickness, ratio of the thickness of refractory and insulation, cost of any supplementary heat and lifetime is reported. The results show that LCOHtr decreases with an increase in thermal scale, as expected. The role of insulation is much more complex, since increasing the thickness of thermal barrier increases both cost and efficiency of the transmission, requiring an economic optimum to be determined for each of the various conditions assessed. Parameters are also coupled because a higher cost of supplied energy/ heat justifies the use of more insulation material. For a large GW scale thermal system, we estimate that it is possible to achieve a minimum overall LCOHtr,min of 0.16–0.36 USD/GJ/km of the length of the thermal transmission system, excluding additional location-specific costs such as land-access and local construction costs. These estimated costs are sufficiently attractive to justify ongoing development of systems to transport renewable heat to industry from sources such as concentrated solar thermal energy.

Building typology classification using convolutional neural networks utilizing multiple ground-level image process for city-scale rapid seismic vulnerability assessment

Several studies have focused on generating seismic vulnerability maps for earthquake-prone areas, particularly in Indonesia. Building typologies are a key factor in determining vulnerability to earthquakes. However, conducting large-scale field surveys to determine the spatial distribution of building typologies in a city is uneconomical. This paper explores the use of a convolutional neural network (CNN) to automatically detect building typologies from diverse regions in Indonesia, utilizing both conventional and automated building image acquisition processes. In this study, datasets from three distinct image acquisition methods are trained with four unique CNN architectures to identify the best-performing model to classify building typologies. The sample size effect on CNN performance is also investigated. The results showed that randomly sampled Google Street View (GSV) images are the most effective dataset for the CNN model, achieving an f1-score of 84.33%. Among the network architectures tested, MobileNet demonstrated superior performance on the majority of evaluated datasets. As the sample size increases by about 350% in the dataset, there is a positive correlation with up to 2.3% f1-score improvement. Using the best-performing CNN model, two building vulnerability models were employed to assess the spatial distribution of building damage in the urban area of Bandung, considering a hypothetical scenario of an M7 earthquake. Incorporating local construction data, one of the generated maps estimated that approximately 55% of buildings in Bandung would experience moderate to severe structural damage. This study showcases the potential of CNN models in automating regional seismic assessments and providing valuable insights for comprehensive seismic mitigation strategies.

Field Investigation of Water Infiltration into a Three-Layer Capillary Barrier Landfill Cover System Using Local Soils and Construction Waste

In response to the rapid urban expansion and the burgeoning number of landfill sites, managing water infiltration in these areas has become a critical challenge, especially in cities like Shenzhen, Hong Kong, and Singapore where traditional cover materials such as silt, clayey gravel, and sand are scarce. A three-layer (silt/gravelly sand/clay) capillary barrier cover system has been proposed to address this issue in humid climates. As an alternative to scarce traditional materials, using local soils and construction waste (CW) for this system presents a viable solution. However, the real-world performance of this adapted three-layer system, constructed with local soils and CW under natural rainfall conditions, remains to be fully evaluated. This paper presents a field test evaluating the water infiltration behavior of a three-layer capillary barrier landfill cover system under natural conditions. The tri-layered system is comprised of a 0.6 m loose local unscreened soil layer, covered by a 0.4 m CW layer and topped by a 0.8 m heavily compacted local screened soil layer. Monitoring findings reveal that, during the wet season, infiltration through the top two layers was staved off until the third rainfall, after which these layers retained moisture until 15 September 2016. The fluctuation in pore water pressure in the topmost layers showed each rainfall was contingent not only on the day’s precipitation but also the hydraulic state. Beyond the hydraulic state’s influence, a deeper tensiometer showed resulted in a diminished correlation between the surge in pore water pressure and daily rainfall. This declining correlation with depth can be attributed to the capillary effect and the reduced permeability of the screened soil layer. Rainfall patterns significantly affect percolation, with the combination of a short-duration, intense rainfall and prolonged weak rainfall resulting in a marked increase in percolation. In the foundational screened soil layer, the pore water pressure remained relatively low, with the cumulative percolation over six months (June to December) registering approximately 10 mm. These findings suggest a promising performance of the three-layer capillary barrier cover system, integrating local soils and CW, in the year of the study conducted in a humid environment.

The current situation of Russia’s GNSS continuous operating reference station network and thinking on future development

The GNSS (Global Navigation Satellite Systems) continuous operating reference station network not only provides a reliable technical foundation and data support for achieving high-precision navigation and positioning services, but also can be integrated with other Earth observation systems (such as laser ranging, gravity measurement, etc.) to improve the accuracy and stability of Earth observation data. It is used to establish regional and global coordinate frameworks and provide data to support scientific research such as seismology, geo-tectonics, and oceanography. This article first systematically introduces the construction, development history and current situation of the Russian GNSS continuous operating reference station network, and then carefully analyzes the construction, operation, and application status and existing problems of the Russian reference station network. Finally, after careful consideration, it discusses the problems and challenges faced in the planning of reference station network construction, equipment localization, and national unified reference station network construction, and provides some suggestions and ideas.

Utilizing advanced machine learning approaches to assess the seismic fragility of non-engineered masonry structures

Seismic fragility assessment provides a substantial tool for assessing the seismic resilience of these buildings. However, using traditional numerical methods to derive fragility curves poses significant challenges. These methods often overlook the diverse range of buildings found in different regions, as they rely on standardized assumptions and parameters. Consequently, they may not accurately capture the seismic response of various building types. Alternatively, extensive data collection becomes essential to address this knowledge gap by understanding local construction techniques and identifying the relevant parameters. This data is crucial for developing reliable analytical approaches that can accurately derive fragility curves. To overcome these challenges, this research employs four Machine Learning (ML) techniques, namely Support Vector Regression (SVR), Stochastic Gradient Descent (SGD), Random Forest (RF), and Linear Regression (LR), to derive fragility curves for probability of collapse in terms of Peak Ground Acceleration (PGA). To achieve the research objective, a comprehensive input/output dataset consisting of on-site data collected from 646 masonry walls in Malawi is used. Adopted ML models are trained and tested using the entire dataset and then again using only the most highly correlated features. The study includes a comparative analysis of the efficiency and accuracy of each ML approach and the influence of the data used in the analyses. Random Forest (RF) technique emerges as the most efficient ML approach for deriving fragility curves for the surveyed dataset in terms of achieved lowest values for evaluation metrics of the ML methods. This technique scored the lowest Mean Absolute Percentage Error (MAPE) of 16.8 %, and the lowest Root Mean Square Error (RMSE) of 0.0547. These results highlight the potential of ML techniques, particularly RF, in derivation of fragility curves with proper levels of accuracy.

A Study on Sustainable Design of Traditional Tujia Village Architecture in Southwest Hubei, China

The rapid urbanization in China in the past four decades has significantly affected traditional villages, resulting in a series of problems such as limited space, damaged style, weak sense of place, and loss of skills. This paper aims to establish a new paradigm for the sustainable development of village architecture in the Tujia ethnic area of southwestern Hubei province in order to address the issues of development and renovation of village architecture in this region. To achieve this goal, first, through field investigations and records of typical villages in the Tujia ethnic area of southwestern Hubei province, the characteristics of Tujia ethnic villages and the real challenges faced by village architecture are summarized. Secondly, the Delphi method is used to conduct expert interviews, construct a multi-level evaluation index system for sustainable development, and use the analytic hierarchy process to determine the weights of each index. Based on this, four design paradigms for sustainable development are proposed, including flexible layout, integrated interface composition, localized housing construction, and modular unit construction. These four paradigms cover the entire design stage from function to form, and from overall scene to structure. At the same time, multiple modular options are provided for each stage. Compared to the traditional experience-based construction model, the comprehensive benefits and promotability are greatly improved. Therefore, the research findings provide a reference for the sustainable development of traditional village architecture in other ethnic areas of China.

Ceramic Properties of Three Specimens of Alluvial Clays Used in Local Constructions from Mbouda Clay Deposit, West Cameroon

Ceramic Properties of Three Specimens of Alluvial Clays Used in Local Constructions from Mbouda Clay Deposit, West Cameroon

Effects of pyrolysis bio-oil derived from palm kernel shell on modified bitumen properties

Economical and environmental friendly materials that able to replace petroleum based binder has become an urgent demand in road industry. Bio oil from palm oil waste is relatively more economical and has the potential to used as bitumen replacement as bio asphalt. The performance of bio asphalt derived from different source and process to produce bio oils are varies. Hence, this study aims to investigate the effects of palm kernel shell bio-oil in terms of physical properties, the chemical functional group, and the morphology. The bitumen properties were evaluated by the conventional physical tests, Fourier Transform Infrared Spectroscopy, and Scanning Electron Microscopy. The palm kernel shell bio-oil was added into the bitumen by weight of bitumen at 0%, 2%, 3%, 5%, 10%, 15%, and 20% and blended using mechanical stirrer. From the conventional physical test, it was found that bio-oil modified bitumen increased in penetration and ductility with decreased softening point. This indicate that direct addition of bio oil soften the modified bitumen. The change of the functional group in FTIR is significantly influenced by the increasing content of bio-oil. The morphology of the modified bitumen showed inhomogenous surface with noticeable wrinkles as the bio oil content increase. Based on the physicochemical evaluation, 3% bio oil replacement passed all the physical tests requirement with less changes in FTIR result. Therefore, 3% bio oil content is proposed for further tests for direct inclusion of bio oil into bitumen for local road construction utilization.

BIM implementation in the middle east construction: Evaluating the prospects and challenges

This research explores the potential benefits and challenges associated with the implementation of Building Information Modelling (BIM), a rapidly evolving global trend, within the construction industry of the Middle East. The study is underpinned by a comprehensive literature review on the global and Middle Eastern usage of BIM. A methodical empirical survey was employed to collect quantitative data, comparing the perspectives of Clients, Contractors, and Consultants. Key impediments to BIM adoption in the Middle East were identified as a scarcity of BIM-skilled subcontractors, the lack of industry standards, substantial initial costs, and organizational structures that do not support BIM. On the other hand, the advantages of BIM include improved construction planning, enhanced project quality, an elevated organizational image, and streamlined communication. The study provides crucial recommendations for local governments, policymakers, construction companies, and stakeholders to encourage comprehensive BIM adoption and its utilization in construction projects, while also discussing the practical implications of the findings.

Construction Disputes Causes and Resolution Methods: A Case Study from a Developing Country

The increasing complexity of the construction industry, characterised by diverse multidisciplinary project teams, various stakeholders, distinctive site conditions and uncertainties, can contribute to an antagonistic environment, which may result in disputes arising between the contractual parties. Identifying the most common causes of disputes is important for an efficient contract management process. This study aims to help project stakeholders incorporate consolidative contract management strategies before commencing a new project by identifying the most common causes of construction disputes in Jordanian construction projects. Key causative factors of disputes were analysed through a literature review, a questionnaire survey and a case study analysis of construction projects in Jordan. The results revealed that the main factors leading to disputes in Jordan are incomplete technical drawings/specifications, variations initiated by the owner/consultant (additive/ deductive) and errors and omissions in the contract documents. Moreover, the results show that the most popular methods of dispute resolution in the Jordanian construction industry are negotiation and arbitration. The findings can enable local and international construction stakeholders to initiate contract management strategies before commencing projects. More effective planning can help to reduce the negative impacts of known causes of disputes.

Effect of rice husk ash on soil stabilization at Dinajpur City

Understanding local conditions is crucial for applying soil stabilization principles from other regions to a specific country for effective and sustainable stabilization methods. This investigative study delves into the suitability of locally available Rice Husk Ash (RHA) for incorporation into local building construction practices at Dinajpur, Bangladesh, aiming to minimize the volume of waste disposed of in the environment, thereby mitigating environmental pollution. Conventional soil stabilization techniques are becoming increasingly expensive due to the rising costs of stabilizing agents such as cement. Replacing a portion of the stabilizing agent with RHA could potentially reduce the cost of stabilization while also minimizing environmental harm. RHA comprises 85-90% silica, making it an excellent substitute for silica in soil stabilization. Silica is recognized as an effective binding agent alongside cement. The soil sample selected for this research is a highly plastic clay (CH), which necessitates significant strength enhancement. Three soil samples were stabilized with varying percentages of RHA and a minimal amount of cement. Observations were made to assess the changes in soil properties, including Maximum Dry Density (MDD), Optimum Moisture Content (OMC), and Unconfined Compressive Strength (UCS). The results obtained indicate that increasing RHA content leads to an increase in MDD but a decrease in OMC. Additionally, the UCS of the soil exhibits substantial improvement to up to 88% with increasing RHA content up to 10%. Based on the observed maximum strength enhancement, a 10% RHA content combined with 6% cement is recommended as the optimal combination for practical applications.

The Real-Time Local Surface Model Construction Method of Unknown-Model Workpieces for Robotic Polishing

The Real-Time Local Surface Model Construction Method of Unknown-Model Workpieces for Robotic Polishing

Designing and presenting a conceptual model of technology transfer for the provision of technological products in the localization and internal construction of oil and gas industry equipment

Technology transfer in the oil and gas industry plays a vital role in improving domestic capabilities and reducing dependence on imports. This article deals with the design and presentation of a conceptual model for technology transfer in order to provide technological products and localization of equipment in this industry. The documents obtained from the searches were used to identify the most important challenges of technology transfer. In the next step, in order to validate the identified critical challenges, ten experts were interviewed and their qualitative judgments about the identified challenges were collected. Among these ten experts, seven experts were from the industry and three experts were from university professors of technology management. Also, in the expert interview stage, in addition to validating the challenges identified based on the literature, a number of new challenges faced by the country's oil and gas industries regarding technology transfer And the first purchases of technological products face them; was identified In the next step, the weights of each of the identified challenges were calculated based on the subject literature and expert interviews, with the design of special questionnaires for pairwise comparisons and the multi-criteria decision-making method of Analytical Hierarchy (AHP). The results of the research show that the use of this model can help to improve the localization process and promote the industrial capabilities of the country in the field of oil and gas. Also, suggestions have been made to facilitate and accelerate the technology transfer process and increase its effectiveness.

Appraisal of Alternative Dispute Resolution Methods Used in Construction Industry of Abeokuta Ogun State.

The construction industry is a vital component of economic development in Abeokuta, Ogun State, Nigeria, characterized by its dynamic and complex nature. With the increase in construction activities, disputes are inevitable, often leading to project delays, cost overruns, and strained relationships among stakeholders. To address these challenges, alternative dispute resolution (ADR) methods have gained popularity as effective mechanisms for resolving disputes in the construction industry. This research paper aims to provide a comprehensive appraisal of the ADR methods used in the construction industry in Abeokuta, Ogun State. The study employs a qualitative research methodology with the aid of focus group discussion strategy employing various stakeholders, including construction professionals, legal experts, government officials, and project owners. The research investigates the types and frequency of disputes encountered in construction projects, explores the awareness and utilization of ADR methods, and evaluates the effectiveness and efficiency of these methods in resolving disputes. The research highlights the need for increased awareness and education about ADR methods among construction professionals in Abeokuta. It underscores the importance of establishing an ADR framework tailored to the specific needs and challenges of the local construction industry. Furthermore, the study suggests that a more structured and standardized approach to ADR could lead to more efficient and timelier dispute resolution, ultimately benefiting the construction industry's stakeholders.

The impact of migration processes on the construction sector of Kyrgyzstan: Problems and strategies of public administration

This article examines the impact of migration on the construction industry of Kyrgyzstan, and also analyzes the main problems faced by government agencies in managing this process. Aspects such as labor instability, increasing demand for housing resources, changes in urban infrastructure and sociocultural changes are discussed. Possible solutions are proposed for the effective management of migration flows in the construction sector, including improving mechanisms for regulating labor migration, developing programs to support local construction companies and creating conditions for improving the skills of local personnel. In conclusion, a conclusion is drawn about the need for an integrated approach to managing migration processes, taking into account their impact on various aspects of the economy and society of Kyrgyzstan.

LiDAR-SLAM loop closure detection based on multi-scale point cloud feature transformer

Loop closure detection is an important part of simultaneous localization and mapping (SLAM), used to detect and correct map and trajectory drift issues caused by accumulated errors. For the LiDAR-SLAM system, the sparsity and disorder of point clouds make position recognition based on 3D point clouds more challenging. In recent years, many deep learning-based closed-loop detection algorithms have been proposed. However, due to the sparsity of point clouds, current deep learning algorithms often convert point clouds into histograms or depth maps and then process them using deep learning algorithms, undoubtedly causing information loss. In this paper, we propose a closed-loop detection method based on multi-scale point cloud features transformer, which introduces multi-scale point cloud feature extraction and transformer global context modeling. We use voxel sparse convolution to obtain features of original point clouds at different resolutions and establish contextual relationships between features at different resolutions using the transformer network to achieve multi-scale feature fusion, and then obtain global descriptors. The obtained global descriptors can be used not only for closed-loop detection but also for front-end registration to address the challenges of point cloud processing in the SLAM system, especially in enhancing global modeling capabilities and reducing information loss. Our method directly processes point cloud data and integrates multi-scale point cloud feature information, which can better adapt to the characteristics of LiDAR-SLAM systems, improving the accuracy and robustness of localization and map construction, thus having broad application prospects in the field of measurement. We evaluated our method on multiple sequences of the KITTI and KITTI-360 datasets, each containing more than 5000 frames of point clouds, and extensively evaluated on a self-collected dataset of over 3.6 km. The experimental results show that our method achieves an accuracy of over 80% on multiple datasets and demonstrates superior performance in different environments.

STUDY OF TRANSFORMATION OF JHAROKHA WINDOW FORM IN LAHORE

The traditional architecture of any area embodies its true character, deeply rooted in the history, geography, and culture of that region. It does not only satisfy the functional requirements but also stems from local construction techniques and materials available. Traditional architecture faces the problem of its coexistence with modern technological development everywhere. The built heritage which stands in Lahore over centuries is encroached by modern and efficient techniques. The present paper specifically focuses on the development of Jharokha windows (Bay windows) in Lahore. The Jharokha window that was used in the Indian sub-continent during and after the Mughal period was the solution to the climatic conditions of the region. This research will investigate the old Jharokha window form and how with technology and advancement it starts losing its original form. The change in Jharokha form will be studied by the existing examples from different time periods available in the city of Lahore.

IRGWP: An international network of key players for a better understanding and industrial developments in wood protection and preservation

IRGWP: An international network of key players for a better understanding and industrial developments in wood protection and preservation