Journal of Science and Technology in Civil Engineering (JSTCE) - HUCE

2026-06-25T08:06:40+00:00

Hydraulic conductivity estimation for ballasted railway tracks: A systematic review

2026-06-25T08:35:21+00:00

The hydraulic conductivity of railway ballast is a critical parameter governing track stability and longevity. It is severely compromised by ballast fouling, which accelerates water retention and embankment soil degradation. To address a historical decade scarcity of consolidated research, this systematic literature review synthesizes a comprehensive range of available evaluation methodologies across laboratory, field, and numerical paradigms. Following PRISMA guidelines, a systematic database search of Scopus (n = 49) and Web of Science (n = 106) yielded 155 original records. After duplicate removal, 123 records were screened, and 24 full-text reports were assessed for eligibility. Incorporating 2 additional papers from citation searching, a final dataset of 26 publications was selected for rigorous data extraction. The reviewed methodologies primarily comprise laboratory techniques (n = 19) and numerical simulations (n = 5). Synthesized findings demonstrate a substantial reduction in ballast drainage capacity with increasing fouling, a transition from non-linear to linear flow regimes
as aggregates degrade, and a significant structural dependence on fouling type and initial aggregate gradation.
Crucially, the review maps critical hydraulic parameters—specifically hydraulic conductivity, free surface dynamics, fluid flow behaviors, and permeability—across a global framework of international scientific interest, aligning findings with standards and guidelines from the USA, Australia, Europe, South Africa, Nigeria, and India. Ultimately, this study bridges a vital knowledge gap by positioning railway infrastructure as an integrated
filtering and retention facility functioning as a Nature-Based Solution (NBS). To advance the field, a numerical simulation framework is proposed to synthesize both established and emergent parameters, incorporating complex aggregate geometries and time-variant hydraulic conditions for future infrastructure design.

CFD modeling of mudflow impact on rigid barriers using the Herschel–Bulkley rheology

2026-06-29T02:03:20+00:00

This study employs a Computational Fluid Dynamics (CFD) approach to simulate the dynamics of nonNewtonian mud/debris flows impacting rigid barriers under flume-scale conditions. The flow is modeled using the Herschel–Bulkley rheology to capture both yield stress and shear-thinning behavior characteristics of mud materials. Numerical simulations are performed with OpenFOAM for 12 configurations varying in slope inclination (0◦ –15◦) and barrier position relative to the slope toe. The model is first validated against experimental data, showing good agreement in terms of pressure evolution and velocity profiles. The numerical results reveal that flow behavior is strongly governed by the interplay between gravitational acceleration, yield stress effects, and energy dissipation within the basal shear layer. Increasing the slope angle enhances the conversion of potential to kinetic energy, leading to higher impact velocities, larger runup heights, and greater impact forces. Conversely, increasing the distance between the slope toe and the barrier promotes viscous dissipation, thereby reducing the available impact energy. Notably, for the steepest slope (15◦), the effect of barrier distance becomes minor due to compensation between acceleration and front spreading. These findings provide new insights into energy conversion mechanisms and their implications for the design and placement of protective barriers in mud/debris flow prone areas.

Buckling analysis for plates using finite strip method based on refined Mindlin–Reissner plate theory

2026-06-25T08:37:00+00:00

This paper presents a three-nodal-line finite strip formulation based on the refined first-order shear deformation plate theory (RFSDT) for the buckling analysis of both thin and thick plates. The proposed finite strip model incorporates the effects of transverse shear deformation, which leads to a significant reduction in the critical buckling stress of plates. Closed-form expressions for the strip stiffness and geometric stiffness matrices are derived using the principle of minimum total potential energy. These matrices enable more efficient structural stress analysis while reducing computational cost. The buckling problem is formulated as an eigenvalue problem obtained from the assembled strip stiffness and geometric stiffness matrices, from which the critical buckling load factors are determined. The results obtained using the proposed finite strip are validated through comparisons with exact solutions and previously published studies. Furthermore, based on an extensive parametric study, practical formulas are proposed for predicting the critical buckling stress of isotropic simply supported plates subjected to uniaxial compression and in-plane bending. The proposed formulas exhibit high reliability, as indicated by low coefficients of variation and high coefficients of determination.

Workplace injury prevention in construction: A data-driven evaluation using WIPAS

2026-06-25T08:38:25+00:00

The construction industry continues to experience persistent workplace injuries despite increasing digitalisation efforts, highlighting the need for evidence-based approaches to safety analytics. This paper investigates how data-driven practices contribute to workplace injury prevention in South African construction and validates a context-specific instrument for assessing such practices. A quantitative survey of construction professionals from firms operating across three provinces was analysed using SPSS and confirmatory factor analysis (CFA) to validate the Workplace Injury Prevention Analytics Scale (WIPAS), alongside descriptive and reliability statistics. Confirmatory factor analysis demonstrated high reliability (Cronbach’s α = 0.937; ρ = 0.940) and acceptable model fit for the newly developed Workplace Injury Prevention Analytics Scale (WIPAS). Within the WIPAS measurement model, items related to predictive analytics and real-time monitoring exhibited the strongest factor loadings, indicating that these advanced capabilities are central indicators of analytics-driven injury prevention maturity in the sampled organisations. Descriptive results indicate that while organisations routinely collect and evaluate safety-related data, advanced capabilities, particularly predictive analytics and real-time monitoring, are inconsistently adopted. These findings highlight a maturity gap between foundational and advanced analytical practices and demonstrate the need for stronger managerial support, systematic employee training, and integrated data governance. This study indicates that, in the surveyed regional cluster of South African construction organisations, firms are already collecting and reviewing safety data but have not yet fully transitioned to advanced, predictive uses of analytics.

Greenhouse gas emissions mitigation in municipal solid waste collection systems

2026-06-25T08:39:06+00:00

Greenhouse gas (GHG) emissions from the collection and transfer operations are a significant component within any municipal solid waste (MSW) system. This has not been optimally studied in previous works. The present study aims to quantify current GHG emissions from the MSW collection system in the central area of Hanoi and to develop alternative operational scenarios for GHG mitigation. Operational data on wastecollection vehicles and the transfer station (TS) were obtained from waste collection company’s digital maps and reports. The United Nations Environment Programme’s Emission Quantification Tool (EQT) Version III was ultilized for GHG emissions. The research evaluates various collection scenarios while incorporating TS location to determine an optimal distance that aligns with cost and GHG emissions targets. In the study area, the waste collection and transportation system covers an average daily travel distance of 2,167.68 km, utilizing a fleet of vehicles with capacities ranging from 1 to 11 tonnes. As a result, the system generates approximately 28 kg CO2-eq per tonne of MSW. At present, the waste transfer process in the study area remains inefficient. The proposed TS achieves about a 21.5% reduction in GHG emissions relative to the existing facility. Two key factors contributing to emission reduction are the minimization of transport distance and the use of fuel efficient vehicle types. Among all scenarios, employing TS consistently proves to be a more effective option than direct transportation to the Nam Son Waste Treatment and Disposal Complex. TS should be located along the shortest route between the collection areas and the treatment complex, preferably as close to the collection areas as possible to minimize transportation distance and cost. These results give scientific proof to back MSW planning and optimization aimed at the net-zero emission goal in the MSW management field.

Target value design as a conditional tool system: How A3, CBA, and BIM enable value-driven decision-making in construction projects

2026-06-29T02:04:53+00:00

Target Value Design (TVD) is increasingly adopted in construction projects as a means of aligning design decisions with cost and value objectives. However, existing studies largely focus on philosophical principles, contractual arrangements, or isolated tool applications, providing limited insight into how value-driven decisions are operationalised in practice. This gap contributes to the widely observed variation in TVD outcomes across projects, even when similar tools are formally applied. The paper argues that such variation cannot be adequately explained by differences in technical competence or Lean maturity alone. Instead, it conceptualises TVD as a conditional tool system whose effectiveness depends on the decision environments in which its tools are embedded. The study adopts an interpretive analytical review based on a structured corpus of International Group for Lean Construction (IGLC) publications (1996–2025), complemented by practitioneroriented sources and documented project cases. It examines how core TVD tools - A3 reports, Choosing By Advantages (CBA), BIM-enabled dynamic cost modelling, and collaborative workshops supported by incentive mechanisms function not as standalone techniques, but as an interdependent decision-support system. The analysis shows that these tools derive their value-generating capacity from mutual reinforcement across cognitive, analytical, technical, and behavioural dimensions of decision-making. When governance conditions support early multi-actor engagement, shared decision authority, and value-based justification, the tool system enables iterative learning and proactive management of value under cost constraints. Conversely, under constraining governance regimes, the same tools tend to degrade into symbolic or compliance-oriented practices. By reframing TVD from a set of methods to a governance-sensitive decision infrastructure, this paper contributes to construction management research by clarifying why TVD does not transfer easily across contexts and by providing a basis for more nuanced evaluation of its application in practice.

Effect of recycled sugarcane bagasse as an internal curing additive on mechanical strength, abrasion resistance, and drying shrinkage of paving concrete

2026-06-25T08:41:07+00:00

The utilization of agricultural by-products in paving concrete (PC) has been increasingly explored as a strategy to reduce material-related environmental impacts in pavement construction. This study investigates the influence of recycled sugarcane bagasse (RSB), incorporated into PC at volume fractions ranging from 0 to 2.5 vol.%, on mechanical strength, abrasion resistance, and drying shrinkage behavior. Compressive, flexural, and splitting tensile strengths, surface abrasion loss, and drying shrinkage were evaluated up to 56 days in accordance with relevant Vietnamese standards. Test results indicate that increasing RSB content significantly affects concrete’s properties. At 56 days, the compressive strength of the control mixture reached 48.2 MPa, whereas the mixture containing 2.5 vol.% RSB exhibited a substantially reduced strength of 8.9 MPa. Surface abrasion loss increased progressively with RSB addition, rising from 0.42 g/cm² for the control mixture to 0.98 g/cm²at 2.5 vol.% RSB. A strong inverse linear relationship was observed between compressive strength and surface abrasion loss across all mixtures and curing ages (R² = 0.88), highlighting the dominant role of matrix compactness in controlling abrasion resistance. Drying shrinkage exhibited a non-monotonic response to RSB incorporation. Mixtures containing 0.5–1.0 vol.% RSB showed shrinkage comparable to or lower than that of the control mixture, whereas higher RSB contents resulted in increased shrinkage at later ages. Although higher RSB dosages caused a noticeable reduction in flexural performance, the mixture containing approximately 0.5 vol.% RSB satisfied the 28-day flexural strength, compressive strength, and surface abrasion requirements specified for level-IV road, while providing measurable shrinkage mitigation. Further mixture optimization is required to enable the use of higher RSB contents while maintaining adequate mechanical performance for pavement applications.

Generative AI adoption in civil engineering: A mini review of benefits, barriers, and risks

2026-06-25T08:41:28+00:00

Generative Artificial Intelligence (GenAI) is emerging as a transformative technology in civil engineering, offering new capabilities in design automation, project management, and real-time decision-making. This review aims to systematically examine the key benefits, barriers, and risks associated with GenAI adoption in the civil engineering domain. To do so, we employed the PRISMA methodology to conduct an in-depth analysis of twenty-two peer-reviewed documents retrieved from Google Scholar. The findings reveal ten key benefits, with design optimization and creativity, progress monitoring and reporting, and improved risk management standing out as the most prominent. In addition, thirteen critical barriers were identified, notably privacy and data ownership concerns, software integration challenges, and high upfront investment costs. Furthermore, ten distinct risks were outlined, including overreliance on AI, copyright issues, and bias in training data, which are the most severe risks. Finally, this study proposes eight promising research directions for future exploration, ranging from human-AI collaboration models to legal and ethical frameworks, data interoperability, and AI trust mechanisms, all of which are vital to supporting the safe and effective integration of GenAI in civil engineering practices.