Scientometric Review of Cement-Less Ultra-High-Performance Concrete: Trends, Innovations, and Future Research Directions

This study presents a comprehensive scientometric review of cement-less ultra-high-performance concrete (UHPC) with the objective of identifying research trends, key contributors, dominant themes, and critical knowledge gaps in this emerging field. A systematic bibliometric analysis was conducted using the Scopus database, from which 59 peer-reviewed journal articles published between 2014 and 2024 were selected following rigorous screening criteria. Scientometric mapping was performed using VOSviewer to analyze publication trends, keyword co-occurrence, leading journals, influential authors, and active research regions. The findings reveal a sharp increase in research output after 2020, reflecting growing interest in geopolymer-based UHPC due to sustainability concerns. Existing studies predominantly focus on mechanical properties, particularly compressive strength and steel fiber reinforcement, while durability-related aspects such as corrosion resistance, fire performance, and long-term structural behavior remain underexplored. Higher sand-to-binder ratios (up to 0.8) were found to improve packing density and mechanical performance, achieving compressive strengths up to 160.7 MPa, while silica fume contents around 30% enhanced compressive strength by approximately 25% and fracture energy by nearly 50%. The novelty of this work lies in being the first dedicated scientometric assessment of cement-less UHPC, providing a quantitative overview of research evolution while systematically highlighting critical gaps and future research directions to support its effective structural application

Spatial Prediction of Soil Index Properties Using GIS and Empirical Bayesian Kriging

The purpose of this study is to assess the possible use of Empirical Bayesian Kriging (EBK) combined with Geographic Information Systems (GIS) to map and analyze geotechnical index properties in Thi Qar Province in southern Iraq. The aim of this objective is to describe the spatial variability of soil limits of the consistency and define areas with expansive soils, which may influence infrastructure development. Data on 550 boreholes and 862 observations per soil property, including Liquid Limit (LL), Plastic Limit (PL), and Plasticity Index (PI), were analyzed. To test the predictive accuracy of the EBK model and thus assure its statistical validation, RMSE, MSD, RMSSD, and correlation coefficients were used to test the model. The findings show that the LL was between 32% and 69%, the PL between 9% and 36%, and the PI between 1% and 39%, with most of the soils being CL and CH, which signifies moderate-high plasticity. The results indicate that there are good spatial patterns, and plasticity is more dense in the north and central areas. The originality of this work is the use of EBK to create detailed digital soil maps of a semi-arid area, where the available geotechnical data is sparse, which is used to form a dependable base to support engineering design, land-use planning, and regional geotechnical modelling

Evaluating AI-Based Video Analytics for Traffic Engineering: Accuracy, Calibration, and Practical Use

This paper examines the potential and reliability of AI-based video analytics for solving key traffic engineering problems. The objectives were to compare several commercially available tools for collecting traffic data and, through practical examples, to show that AI-processed data can be used for the development, calibration, and validation of traffic models. Four AI-based video analytics (StreetLogic Pro, DataFromSky, CVEDIA RT Studio, and Camlytics Single) were tested using field video recordings at a signalized intersection on an urban arterial in Split, Croatia. Detection accuracy, usability, and sensitivity to camera placement and recording conditions are analyzed, and selected microscopic parameters (saturation flow rate and control delay) were obtained and compared with values derived from HCM procedures. DataFromSky and CVEDIA RT Studio achieved 97–99% vehicle detection accuracy and provided detailed trajectory data suitable for scientific applications, while StreetLogic Pro achieved 100% accuracy for operational vehicle counting. AI-based estimates of saturation flow rate and control delay differed by less than 1% and 5%, respectively, from traditional field measurements. The main novelty of this research lies in its practical comparison of AI-based video analytics tools combined with a worked example of using AI-derived data to calibrate analytical models, providing practical guidance for researchers and practitioners in traffic engineering

Comparative Study of Crack Width Prediction Models for Reinforced Concrete Beams

Crack-width control is a critical serviceability limit state (SLS) requirement in reinforced concrete (RC) structures, as excessive cracking can compromise durability and accelerate reinforcement corrosion. This study evaluates the accuracy of crack width prediction models within major international design standards. An experimental investigation was conducted on a RC beam subjected to four-point bending, where crack propagation, beam deflections, and reinforcement stresses were monitored throughout the loading process. The measured crack widths were compared with analytical predictions from Eurocode 2 (EN 1992-1-1), DIN 1045-1, and ACI-based formulations. The results indicate that while all evaluated codes capture the general trend of increasing crack width with rising steel stresses under incremental loading, significant discrepancies exist in their predicted magnitudes. In general, it is Eurocode 2 that consistently provides the most conservative estimates, whereas DIN 1045-1 yields slightly lower but also consistent values of the same. Conversely, ACI-based approaches tend to underestimate crack widths at higher load levels. This study highlights the influence of modeling assumptions—specifically those related to bond-slip behavior, crack spacing, and tension stiffening—on the reliability of crack-width predictions. The results provide experimental evidence regarding the reliability and limitations of common predictive methods, contributing to a refined understanding of design rules for the serviceability of RC structures

A Correlated Random-Field Ising Model for Pore-Scale Hysteresis in Soil-Water Characteristic Curves

The soil–water characteristic curve (SWCC) plays a central role in the behavior of unsaturated soils, yet explaining its hysteresis directly from pore-scale mechanisms remains challenging. The objective of this study is to investigate how pore-size heterogeneity, spatial correlations, and cooperative dynamics contribute to hysteresis in SWCCs. In this study, a correlated Random-Field Ising Model (RFIM) combined with Monte Carlo simulations is developed to represent the pore space as a two-dimensional lattice with a bimodal distribution of pore volumes and a spatially correlated disorder field. Drainage processes are simulated without parametric curve fitting, enabling direct analysis of pore-scale switching dynamics. The results show that macropore fraction, pore-size heterogeneity, and the activation parameter \beta exert a strong control on drainage behavior. Low \beta values produce smooth and nearly reversible drainage, whereas higher \beta stabilizes metastable pore configurations and yields abrupt transitions accompanied by hysteresis. The divergence between number-based and volume-based saturation serves as a useful indicator of size-selective drainage and cooperative pore-scale events. The novelty of this work lies in providing a physically grounded and statistically dynamics to macroscopic hysteresis in SWCCs, offering insights beyond traditional phenomenological or uncorrelated pore-network approaches

Development of Knowledge Management Based on Safety Audit for Design-Build Contract in High-Rise Building Projects

Audits play a crucial role in construction safety management systems (CSMS) by identifying discrepancies and evaluating the effectiveness of safety implementation. Despite Indonesia’s rapid infrastructure development, audit practices remain insufficient to prevent construction accidents. This research aims to formulate a conceptual framework for maturing a knowledge management-based CSMS audit to enhance the effectiveness of safety management implementation in construction projects. The study employed a quantitative approach using the least square method to test the significance of safety audit indicators, supported by descriptive analysis involving expert evaluations on three different construction projects. The findings revealed that the most influential safety audit elements are construction safety operations, followed by mastery and contribution to construction safety, safety planning, safety performance evaluation, and safety support. Expert assessments confirmed a high level of applicability of the proposed framework. The novelty of this study lies in the integration of knowledge management principles into the CSMS audit process, offering a more mature and structured approach to improving safety performance. This framework provides a practical tool to strengthen audit effectiveness and support continuous improvement in construction safety management within the Indonesian infrastructure sector

Energy-Based Evaluation of Brittleness in Moderately Weathered Rocks Under Triaxial Compression

Moderately weathered rock masses are widely encountered in deep and long tunnels, where excavation-induced unloading–reloading and stress concentration strongly affect failure behavior, stability, and support design. To clarify their brittleness from an energy perspective, this study develops a unified three-dimensional numerical framework for the triaxial compression analysis of five typical moderately weathered rocks, namely granite, basalt, limestone, shale, and sandstone, with the Jinmen Tunnel of the Longchuan–Huaiji Expressway as the engineering background. A coupled damage–plasticity constitutive model is adopted, and its parameters are calibrated using laboratory triaxial test data. Model reliability is verified by the close agreement between simulated and measured stress–strain curves and failure patterns of moderately weathered granite. The external work is decomposed into total, elastic, and dissipated energy densities, and a normalized dissipated energy is introduced to describe damage evolution. Results show that the energy evolution is strongly lithology-dependent: granite and shale exhibit a clear transition to post-peak dissipation-dominated behavior, whereas basalt, limestone, and sandstone remain mainly controlled by elastic energy. Increasing confining pressure from 5 to 10 MPa expands the dissipation zone and reduces the energy-density brittleness index BED, indicating a ductilizing effect. The novelty lies in the unified energy-based framework, the normalized dissipated energy, and the newly proposed BED for brittleness evaluation

Properties of Cement Sand Brick Containing Shredded Paper as Partial Sand Replacement

Sand disposal causes significant environmental pollution. Effective sand mining is one of the alternative approaches to reduce sand disposal. Thus, this research investigates the properties of cement sand brick (CSB) containing shredded paper (SP) at various percentages, 0%, 10%, 20%, 30%, 40%, and 50%, as partial sand replacements. This research also investigates the mechanical and durability properties of CSB containing SP. The compressive, flexural, and splitting tensile strengths incline with 10 and 20% sand replacements with SP, respectively. 50% SP replacement shows the maximum influence on water absorption and efflorescence. The scanning electron microscope (SEM) elucidates that the emergence cracks are repaired, which improves the CSB’s strength by enhancing the bond connection between sodium hydroxide (Na(OH)2) and potassium-silicate-hydrogen (K-S-H) links. Some cement particles have been hydrated at 20% SP replacement, producing the highest strength. This study indicates that SP can be utilized as partial sand substitution in CSB at 10% and 20%, with significant improvements in strength and engineering properties, especially in building construction. Research on other types of SP that might yield stronger CSB is necessary for future research. Besides that, future studies shall investigate and observe the effects of CSB reactions with different percentages of SP usage

Hierarchical Learning-Based System Decomposition for Time-Dependent Structural System Reliability Assessment

Time-dependent reliability assessment of structural systems is challenging when degradation and multiple interacting failure modes govern failure. Under these conditions, the system limit state function (LSF) may be highly nonlinear, non-smooth, and available only implicitly through high-fidelity analysis. This paper proposes a system decomposition and hierarchical learning (DHL) framework to construct an evaluable surrogate system LSF for degradation-driven, time-variant reliability analysis. The structural system is decomposed into dominant failure modes and their connectivity. Artificial neural networks are trained hierarchically to learn the decomposed relationships. Mode-level surrogates approximate the LSF of each failure mode. A system-level surrogate then integrates the mode-level performance quantities and time to capture mode interaction and mechanism switching. The resulting surrogate is combined with Monte Carlo simulation and the probability density evolution method to compute time-dependent failure probabilities and, when required, the evolution of the system performance probability density. Two benchmark problems—a highly nonlinear parallel system and a rigid–plastic portal frame with correlated collapse mechanisms under degrading capacities—are used to evaluate the approach. DHL improves system-level surrogate fidelity relative to direct system-level ANN learning, with mean reliability prediction errors below 3.1% and 1.23% in the two benchmarks, respectively, while remaining compatible with both sampling-based and density-evolution propagation schemes

Effect of Mixing Sequence on Properties and Fibre Dispersion of Glass Fibre Reinforced Cementitious Mortar

Cementitious composites play a vital role in construction due to their favourable strength, durability, and workability. Nonetheless, these materials are susceptible to cracking. Although incorporating glass fibres has improved mechanical properties, achieving uniform fibre dispersion remains a significant challenge. The objective of this study was to examine the effect of mixing sequence on the engineering properties and fibre dispersion of glass fibre–reinforced cementitious mortars (GFRCMs). There were four mixing sequences including: four mixing sequences for glass fibre-reinforced cementitious mortars (GFRCMs): (i) S1(fibres were incorporated into dry mortar mixtures), (ii) S2 (fibres were incorporated into fresh mortar mixtures), (iii) S3 (fibres added alongside gradual water addition, (iv) S4 (fibres were included during incremental water additions). This study examined various properties in accordance with the American Society for Testing and Materials (ASTM) standard test methods, including compressive strength, hardened density, setting time, flowability, and flexural strength. Scanning electron microscopy and fibre-distance analysis were also employed to evaluate the fibre dispersion of the specimens. The results indicate that fibre addition reduced the flowability and shortened the setting time of the mortar, whereas improvements in hardened properties depended strongly on dispersion quality. The most uniform fibre distribution was observed in S4 (β = 0.685), resulting in maximum compressive and flexural strengths of 15.88 MPa and 10.39 MPa, respectively, at 28 days. The strong correlations observed between density and porosity (R² = 0.8035) and between density and compressive strength (R² = 0.8184) indicate that reduced void content and enhanced fibre distribution are key contributors to the observed performance gains. This work establishes relationships among mixing sequence, fibre dispersion, and key engineering properties to guide fibre-mixing processes in cementitious composites