Ke Li¹, Bendong Liu¹, Yulong Han², Yafeng Zhang³, Chunqi Yang¹, Dawei Yin², Yazhou Zhang³, Wantao Ding^4,*

FDMP-Fluid Dynamics & Materials Processing, Vol.21, No.11, pp. 2779-2793, 2025, DOI:10.32604/fdmp.2025.072671 - 01 December 2025

Abstract Traditional cement-based slurries are often constrained by excessive cement consumption, prolonged setting times, and limited controllability, which hinder their broader engineering applications. To overcome these challenges, this study focuses on optimizing ordinary cement-based slurry through the incorporation of targeted additives and rational adjustment of mix proportions, with the aim of developing a rapid-setting, early-strength cementitious system. In particular, a series of comparative and orthogonal experiments were conducted to systematically examine the evolution of the slurry’s macroscopic properties. In addition, the response surface methodology (RSM) was introduced to reveal the interaction mechanisms among key parameters, thereby… More >

Yassir M. Abbas^*, Abdulaziz Alsaif^*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1789-1819, 2025, DOI:10.32604/cmes.2025.073088 - 26 November 2025

Abstract The rapid advancement of three-dimensional printed concrete (3DPC) requires intelligent and interpretable frameworks to optimize mixture design for strength, printability, and sustainability. While machine learning (ML) models have improved predictive accuracy, their limited transparency has hindered their widespread adoption in materials engineering. To overcome this barrier, this study introduces a Random Forests ensemble learning model integrated with SHapley Additive exPlanations (SHAP) and Partial Dependence Plots (PDPs) to model and explain the compressive strength behavior of 3DPC mixtures. Unlike conventional “black-box” models, SHAP quantifies each variable’s contribution to predictions based on cooperative game theory, which enables… More >

Sandeerah Choudhary¹, Qaisar Abbas², Tallha Akram^3,*, Irshad Qureshi⁴, Mutlaq B. Aldajani², Hammad Salahuddin¹

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1755-1787, 2025, DOI:10.32604/cmes.2025.072200 - 26 November 2025

Abstract The increasing demand for sustainable construction practices has led to growing interest in recycled aggregate concrete (RAC) as an eco-friendly alternative to conventional concrete. However, predicting its compressive strength remains a challenge due to the variability in recycled materials and mix design parameters. This study presents a robust machine learning framework for predicting the compressive strength of recycled aggregate concrete using feedforward neural networks (FFNN), Random Forest (RF), and XGBoost. A literature-derived dataset of 502 samples was enriched via interpolation-based data augmentation and modeled using five distinct optimization techniques within MATLAB’s Neural Net Fitting module:… More >

Qi Feng^1,2, Weijie Hu¹, Lu Liu^3,*, Junhui Luo⁴

Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1589-1605, 2025, DOI:10.32604/sdhm.2025.072955 - 17 November 2025

Abstract Ultra-high performance fiber-reinforced concrete (UHPFRC) has received extensive attention from scholars and engineers due to its excellent mechanical properties and durability. However, there is a mutually restrictive relationship between the workability and mechanical properties of UHPFRC. Specifically, the addition of fibers will affect the workability of fresh UHPFRC, and the workability of fresh UHPFRC will also affect the dispersion and arrangement of fibers, thus significantly influencing the mechanical properties of hardened UHPFRC. This paper first analyzes the research status of UHPFRC and the relationship between its workability and mechanical properties. Subsequently, it outlines the test… More >

Yidong Xu¹, Weijie Zhuge^1,2, Jialei Wang¹, Xiaopeng Yu^3,*, Kan Wu⁴

Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1507-1527, 2025, DOI:10.32604/sdhm.2025.069021 - 17 November 2025

Abstract The performance of concrete can be affected by many factors, including the material composition, environmental conditions, and construction methods, and it is challenging to predict the performance evolution accurately. The rise of artificial intelligence provides a way to meet the above challenges. This article elaborates on research overview of artificial neural network (ANN) and its prediction for concrete strength, deformation, and durability. The focus is on the comparative analysis of the prediction accuracy for different types of neural networks. Numerous studies have shown that the prediction accuracy of ANN can meet the standards of the More >

Jian Xia^1,2, Xianzhong Hu¹, Yan Li¹, Wei Zhang^3,*

Structural Durability & Health Monitoring, Vol.19, No.6, pp. 1489-1506, 2025, DOI:10.32604/sdhm.2025.065997 - 17 November 2025

Abstract Incorporating microencapsulated phase change materials (MPCM) into mortar enhances building thermal energy storage for energy savings but severely degrades compressive strength by replacing sand and creating pores. This study innovatively addresses this critical limitation by introducing nano-silicon (NS) as a modifier to fill pores and promote hydration in MPCM mortar. Twenty-five mixes with varying NS content from 0 to 4 weight percent and different MPCM contents were comprehensively tested for flowability, compressive strength, thermal conductivity, thermal energy storage via Differential Scanning Calorimetry, and microstructure via Scanning Electron Microscopy. Key quantitative results showed MPCM reduced mortar… More >

Shinichiro Matsuguma^*

International Journal of Mental Health Promotion, Vol.27, No.10, pp. 1595-1609, 2025, DOI:10.32604/ijmhp.2025.068556 - 31 October 2025

Abstract Objectives: Character strengths use has been studied in WEIRD (Western, Educated, Industrialized, Rich, and Democratic) societies, where it is related to happiness, resilience, and reduced distress. However, this relationship in harsh living conditions remains unstudied. This study aims to examine the relationship between character strengths use and psychological well-being among slum dwellers in the Philippines, where harsh living conditions can create severe psychological challenges. Methods: A correlational analysis was conducted in a slum community in Cavite City, Philippines, with 120 participants completing self-report questionnaires, including the Strengths Use Scale (SUS), Flourishing Scale (FS), and Kessler… More >

Chenjun Ni, Kuo Tian^*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.3, pp. 1-1, 2025, DOI:10.32604/icces.2025.012069

Abstract The development of large-scale, high-precision aerospace structures has imposed increasingly stringent requirements on mechanical response monitoring during ground testing. Aiming at the long-standing limitations of mechanical response monitoring for ground tests in terms of accuracy and real-time performance, this study introduces an intelligent structural strength monitoring method using a dynamically evolving digital twin model.
First, a reduced-order modeling method that accounts for actual test deviations is established. By jointly sampling deviation and loading information as variables, a reduced-order model with full-field mechanical responses as output is constructed, enabling rapid updates to reflect the real test conditions.… More >

Weizheng Lu, Shuo Wang, Yang Chen, Jia Li^*, Qihong Fang^*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.3, pp. 1-1, 2025, DOI:10.32604/icces.2025.010711

Abstract The multi-principal elemental alloys (MPEAs) exhibit excellent combinations of mechanical properties and radiation-resistant, are considered potential candidates for aerospace industries and advanced reactors. However, the quantitative contribution of microstructure on the strengthening mechanism remains challenging at the micro-scale, which greatly limits the long-term application. To address this, we developed a hierarchical multiscale simulation framework that covers potential physical mechanisms to explore the hardening effects of chemical short-range order (CSRO) and irradiation defects in MPEA. Firstly, by combining atomic simulation, discrete dislocation dynamics, and crystal plasticity finite element method, a hierarchical cross-scale model covering heterostructure lattice… More >

Jia Liu, Yuwu Zhang^*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.2, pp. 1-1, 2025, DOI:10.32604/icces.2025.011553

Abstract The rigidity of the resin matrix is a critical factor affecting the impact resistance of composites [1]. However, the intrinsic relationship between resin matrix rigidity and ballistic performance remains insufficiently understood. To reveal the influence mechanisms of resin matrix rigidity on ballistic performance, this study compares the ballistic limits of PBO-140, PBO-200, Aramid III, and Aramid II fiber reinforced composites with resin matrices of different rigidities (epoxy resin, PX90, and PX30) through ballistic impact tests. The experimental results show that, the ballistic limit of composites with PX90 resin is higher than that of composites with… More >