Journals Published by Vilnius Tech
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Quality and reliability of IFC/BIM models for public educational facilities construction projects via clash detection
Get PDFThis study investigates the reliability of monodiscipline IFC/BIM models in public construction projects of educational facilities through advanced clash detection and quantitative analysis. Data were collected from BIM models of two kindergartens and a school in Vilnius, Lithuania, representing different design disciplines. A mixed-methods approach was employed to analyse the number, types, and geometric characteristics of detected clashes. The research introduces innovative metrics, such as the Relative Quality Coefficient (RQC), Relative Uncertainty Coefficient (RUC), and Modified Relative Quality Coefficient (MRQC), to assess model quality and reliability quantitatively. The findings reveal a direct relationship between model complexity, clash detection precision, and the number of identified clashes, underscoring the importance of enhanced quality control measures in IFC/BIM models for public procurement. The study concludes that the implementation of these novel metrics can enhance the reliability of IFC/BIM models, thereby optimizing the design and construction process
Optimal time-based and cost-based contracts in construction projects under asymmetric information
Get PDFA project owner (principal) delegates a project to a contractor (agent). Because the contractor has construction experience, he has private information about the project’s expected completion time. Besides, the contractor can exert an unobservable effort to shorten the completion time. Under an asymmetric information setting, we provide the optimal time-based contract and the optimal cost-based contract, both of which consists of one payment scheme. Additionally, we consider a menu of time-based contracts that consists of a series of contracts. By comparing three contracts, we demonstrate that the owner has a preference for the menu of time-based contracts over the other two. The pooling time-based contract is superior to the pooling cost-based contract. We also find that the social welfare under the pooling time-based contract is lower than under the menu of time-based contracts if the daily operating cost is low but it may be higher than under the menu of time-based contracts if the daily operating cost is high. For the pooling cost-based contract, whether it is better than the previous two contracts depend greatly on the proportion of cost borne by the contractor and the daily operating cost
Evaluating complexity of construction precast component: empirical study in Taiwan
Get PDFCompanies in the construction precast industry usually face lack of skilled manpower, overtime working, and complexity of manpower allocation. The objective of this research is to identify the complexity of precast components using Swarm-Inspired Projection (SIP) algorithm. After conducting a comprehensive literature review regarding precast production, clustering, classification, cost management, manpower allocation, and optimization, expertise from field/head-quarter supervision leads the way to SIP algorithm that drives collected data converted to certain clusters. Data collection was carried out to gather over 90% precast construction data in Taiwan for the recent decade. A total of 1,015,840 datasets were collected and then 772,212 datasets were taken into computation SIP algorithm after data filtering. Evaluation and comparison of models reveal SIP’s remarkable efficiency, halving processing time while delivering superior results. The study identifies four complexity tiers linked to the manufacturing of building precast elements. Significant variations exist among these tiers, with workload increments of 18.22%, 11.71%, and 30.08% between Level 1 and 2, Level 2 and 3, and Level 3 and 4, respectively
Prediction of sewage pipeline construction duration by introducing machine learning and deep learning approaches
Get PDFEstablishing project costs in construction is crucial for project success, typically done through regression methods for prediction. While these methods are common, novel regression methods are less practiced in construction management. This study explores both traditional and modern regression techniques, analyzing data from 83 sewage pipeline projects in South Korea. The study implemented state-of-the-art frameworks, including hyperparameter optimization and k-fold cross-validation, to evaluate statistic, machine learning and deep learning based regression models using R2 score, RMSE, MAE, and MSE. Results revealed that performance metrics don’t always align with predictive accuracy. For instance, the random forest regressor achieved the best R2 score of 0.847 but ranked fifth in prediction accuracy. Moreover, polynomial regression outperformed novel methods with a 98.790% accuracy across the validation dataset
Integrating LINE BOT and Building Information Model to develop construction information management system
Get PDFIn the lifecycle of construction projects, the participation of various specialized members often leads to challenges in recording or retrieving information in real time. This can result in missing data or inaccurate project control decisions, due to the inability to access essential information swiftly and accurately. Recognizing the ubiquitous use of instant messaging platforms on mobile phones and the widespread adoption of Building Information Modeling (BIM) for information storage and management, this research proposes an innovative integration of chatbots with BIM to establish a robust construction information management system. Utilizing “LINE”, a popular communication software, as the foundation, this study develops four specialized chatbots (LINE BOTs) tailored for different phases of construction projects, namely design, construction, and maintenance. These chatbots employ a rule-based and conversational approach to aid construction personnel in real-time recording and retrieval of project information. During the maintenance phase, users can also access relevant equipment objects through the BIM model using mobile smart devices, further improving maintenance efficiency. Moreover, the chatbots are equipped with a string-matching mechanism to enhance the precision of data recording and retrieval processes. The effectiveness of this system is demonstrated through a case study on a public construction project
Exploring the use of in-house sodium silicate from agro-industrial by-products in pervious geopolymer concrete
Get PDFThe extraction of in-house sodium silicate (IHS) as an alternative to commercial silicate in geopolymer pervious concrete (GPC) is the focus of this research. The IHS was developed from rice husk ash (RHA) and treated palm oil fuel ash (TPOFA) using the hydrothermal method. Class F Fly Ash (FA) and Ground Granulated Blast Furnace Slag (GGBS) were used as precursors in a 70:30 ratio. Steel slag aggregate (SSA) was used to wholly replace the conventional aggregates. Palm kernel shell biochar (PKS-BC) at various weight percentages between 1 and 5% was used to replace coarse aggregates (CA). GPC specimens were prepared using 10 M sodium hydroxide (NaOH) and one of the SS: commercial SS, RHA-based IHS, and a ‘Hybrid SS’ (commercial SS: TPOFA-based IHS – 50:50). The findings revealed that due to the toughness, surface roughness, and shape of the SSA, the compressive strength of SSA-based GPC specimens produced higher strength compared to crushed granite aggregate (CGA)-based GPC. ‘Hybrid SS’ and RHA-based IHS yielded slightly higher compressive strengths in GPC specimens compared to commercial SS-based GPC specimens. This finding proved that the appropriate ratio of silica source with NaOH facilitates the development of SS in the development of GPC
Sustainable design of recycled concrete using shape optimization and carbon dioxide emission based on LCA
Get PDFSwitching from waste concrete disposal to recycling is urgently needed to enhance resource efficiency and reduce carbon emissions. This paper proposes a sustainable design framework for recycled concrete, incorporating shape optimization and carbon dioxide (CO2) emission analysis using life cycle assessment (LCA). Using recycled concrete in infrastructure projects, this paper develops a carbon dioxide emissions accounting model based on LCA. Two water-cement ratios (WCR) and four recycled concrete aggregate replacement rates (RCARR) were tested on two natural aggregate concrete (NAC) and six recycled aggregate concrete (RAC) samples. Furthermore, four shapes options for the RAC structural member were designed, optimized, and compared. The G35 Expressway slope projects were used as a case study. The results showed that the regular hexagonal RAC structural member was selected for the project, achieving a carbon reduction rate of about 9%. The study also found that 1) life cycle carbon emission decreases with the increase of WCR and RCARR, respectively; 2) compared to NAC, the key processes of carbon emission reduction of RAC include the raw material acquisition and transportation stage as well as the carbonization absorption stage; 3) there is a transport distance threshold, beyond which the life cycle CO2 emissions of RAC exceed those of NAC
How can data manipulation matter in predicting the failure risk? Evidence from Romanian companies
Get PDFRecent fraud scandals have raised concerns about the reliability of financial data disclosed in financial statements. The main purpose of this article is to investigate how financial data manipulation affects company failure risk. The research sample comprises 63 non-financial Romanian companies listed on the Bucharest Stock Exchange between 2015 and 2020. Three types of statistical methods were used to determine and consolidate the results. The results partially support the strand in literature according to which there is a correlation between manipulated data and failure risk. More specifically, the findings indicate that there is no statistically significant correlation between the Beneish Model and the Altman Z-score. However, after a more in-depth investigation taking into account the specific elements that indicate the existence of customized data in financial data, it was discovered that, among the eight Beneish model component variables, days\u27 sales in a receivable index, sales growth index, and total accruals to total assets have a significant impact on the measurement of bankruptcy risk. This study constitutes an important contribution to the body of knowledge because it focuses not only on the relationship between the risk of failure and financial statement manipulation, but it examines also the significance of financial manipulation indicators in predicting the likelihood of bankruptcy. Our findings are valuable to decision makers seeking a deeper understanding of the reality behind financial data presented in financial statements
Multi-criteria hybrid model of region assessment in the context of sustainable tourism
Get PDFThe main goal of the research was to develop a multi-criteria hybrid model for evaluating the region in the context of sustainable tourism, based on the example of the countries of the Visegrad Group. The research uses the mathematical apparatus of expert evaluation, theory of fuzzy sets, fuzzy logic, and multi-criteria evaluation of alternatives. For the first time, an expert method for assessing the level of sustainability of tourism in the region was developed, which was tested on the data of four groups of environmental criteria and sociocultural aspects. For the first time, a multi-criteria model for evaluating the region in the context of sustainable tourism was developed, based on the matrix multiplication method, which derives normalised estimates of regions by groups of sustainable tourism criteria. For the first time, a hybrid model of regional assessment in the context of sustainable tourism has been developed, aggregating the expert level of sustainable tourism development and the normalised estimates of regions by groups of sustainable tourism criteria. As a result, a ranking of regions in the context of sustainable tourism is being built for further decision-making by stakeholders of the new data-driven era. The multi-criteria hybrid model was verified and tested on real data from 2343 respondents of participants of the tourist movement in the V4 countries. The study outcomes will be very useful for policymakers, strategies and action plans, for agencies, national and international organisations, and other entities in the tourism system. They will support the development of a national and international comparative platform and strategic planning processes in the tourism sector aimed at the sector sustainability and the country’s economy
Terminal value problem for the system of fractional differential equations with additional restrictions
Get PDFThis paper deals with the study of terminal value problem for the system of fractional differential equations with Caputo derivative. Additional conditions are imposed on the solutions of this problem in the form of a linear vector functional. Using the theory of pseudo-inverse matrices, we obtain the necessary and sufficient conditions for the solvability and the general form of the solution of this boundary-value problem. In the one-dimensional case, the obtained results are generalized to the case of a multi-point boundary-value problem. The issue of obtaining similar results for the terminal value problem for the system of fractional differential equations with tempered and Ψ–tempered fractional derivatives of Caputo type is considered