Yanzhao Yang¹, Xiaowen Song², Zhiying Deng^2,*, Jianyang Yu³

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.1, 2026, DOI:10.32604/fdmp.2026.074345 - 06 February 2026

Abstract In this study, a Gaussian Process Regression (GPR) surrogate model coupled with a Bayesian optimization algorithm was employed for the single-objective design optimization of fan-shaped film cooling holes on a concave wall. Fan-shaped holes, commonly used in gas turbines and aerospace applications, flare toward the exit to form a protective cooling film over hot surfaces, enhancing thermal protection compared to cylindrical holes. An initial hole configuration was used to improve adiabatic cooling efficiency. Design variables included the hole injection angle, forward expansion angle, lateral expansion angle, and aperture ratio, while the objective function was the More >

Wonkyu Yi, Jongseok Park^*

Phyton-International Journal of Experimental Botany, Vol.95, No.1, 2026, DOI:10.32604/phyton.2026.073450 - 30 January 2026

Abstract Understanding plant responses under low-pressure conditions is important for developing closed cultivation systems that simulate space environments. This study aimed to assess the effects of different pressure levels on growth, photosynthesis, and secondary metabolite accumulation in red leaf lettuce (Lactuca sativa L. var. ‘Super Caesar’s Red’). Plants were cultivated for three weeks in sealed chambers under 101 kPa (atmospheric pressure), 66 kPa (moderate low pressure), and 33 kPa (severe low pressure). Growth analysis showed that leaf length and leaf area decreased significantly with reduced pressure, while chlorophyll content and SPAD values increased gradually. Photosynthetic measurements indicated More >

Mohammad Shokouhifar^1,*, Fakhrosadat Fanian², Mehdi Hosseinzadeh^3,4,*, Aseel Smerat^5,6, Kamal M. Othman⁷, Abdulfattah Noorwali⁷, Esam Y. O. Zafar⁷

CMES-Computer Modeling in Engineering & Sciences, Vol.146, No.1, 2026, DOI:10.32604/cmes.2026.073789 - 29 January 2026

Abstract Wireless Sensor Networks (WSNs) have become foundational in numerous real-world applications, ranging from environmental monitoring and industrial automation to healthcare systems and smart city development. As these networks continue to grow in scale and complexity, the need for energy-efficient, scalable, and robust communication protocols becomes more critical than ever. Metaheuristic algorithms have shown significant promise in addressing these challenges, offering flexible and effective solutions for optimizing WSN performance. Among them, the Grey Wolf Optimizer (GWO) algorithm has attracted growing attention due to its simplicity, fast convergence, and strong global search capabilities. Accordingly, this survey provides… More >

Abdulrazzak Akroot¹, Kayser Aziz Ameen², Haitham M. Ibrahim³, Hasanain A. Abdul Wahhab^3,*, Miqdam T. Chaichan⁴

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.073702 - 27 January 2026

Abstract Improving energy efficiency and lowering negative environmental impact through waste heat recovery (WHR) is a critical step toward sustainable cement manufacturing. This study analyzes advanced cogeneration systems for recovering waste heat from the Fallujah White Cement Plant in Iraq. The novelty of this work lies in its direct application and comparative thermodynamic analysis of three distinct cogeneration cycles—the Organic Rankine Cycle, the Single-Flash Steam Cycle, and the Dual-Pressure Steam Cycle—within the Iraqi cement industry, a context that has not been widely studied. The main objective is to evaluate and compare these models to determine the… More > Graphic Abstract

Lei Zhao¹, Lihui Ma², Junwen Chen³, Pan Zhang², Jiang Bian^4,*, Dong Sun²

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.070290 - 27 January 2026

Abstract Shock waves in the nozzle during supersonic separation under different conditions can disrupt the flow field’s thermodynamic equilibrium. While it contributes to the recovery of pressure energy, it also leads to the dissipation of mechanical energy. This study aimed to investigate the effects of changes in back pressure on the shock wave position and its subsequent impact on the refrigeration performance of nozzles. A mathematical model for the supersonic gas in a nozzle was established and evaluated via experiments. The results show that when the back pressure is less than 0.2 MPa, no shock wave… More >

Zujun Ding, Shuaichao Wu, Chenliang Ji, Xinyu Feng, Yuanyuan Shi, Baolian Liu, Wan Chen, Qiuchan Bai, Hengrui Zhou, Hui Huang, Jie Ji^*

Energy Engineering, Vol.123, No.2, 2026, DOI:10.32604/ee.2025.068106 - 27 January 2026

Abstract In the quest to enhance energy efficiency and reduce environmental impact in the transportation sector, the recovery of waste heat from diesel engines has become a critical area of focus. This study provided an exhaustive thermodynamic analysis optimizing Organic Rankine Cycle (ORC) systems for waste heat recovery from diesel engines. The study assessed the performance of five candidate working fluids—R11, R123, R113, R245fa, and R141b—under a range of operating conditions, specifically varying overheat temperatures and evaporation pressures. The results indicated that the choice of working fluid substantially influences the system’s exergetic efficiency, net output power,… More >

Yunpeng Wen^1,*, Bingyang Ke², Junrong Ding³

Chalcogenide Letters, Vol.23, No.1, 2026, DOI:10.32604/cl.2026.076587 - 26 January 2026

Abstract This study reports an active learning (AL)-guided strategy to optimize the sulfurization–selenization processing conditions of Sb₂(S,Se)₃ thin-film photovoltaic absorbers for enhanced power conversion efficiency (PCE). By coupling Gaussian process modeling with iterative experimental feedback, we explored 20 targeted annealing conditions across the full compositional spectrum (x = 0–1) and identified an optimal S/(S + Se) ratio of 0.40 (x = 0.60), which yielded a band gap (Eg) of ~1.34 eV, close to the theoretical Shockley–Queisser optimum. The optimized process employed a controlled two-step 420°C anneal with sequential H₂Se→H₂S exposure, which produced large plate-like grains (300–500 nm)… More >

Abla Guechi¹, Djohra Dekhil², Abdelhak Nouri^2,*

Chalcogenide Letters, Vol.23, No.1, 2026, DOI:10.32604/cl.2026.076586 - 26 January 2026

Abstract This work uses numerical modeling in SCAPS-1D to examine the efficiency analysis of a solar cell based on SnS. The power conversion efficiency (PCE) is limited to 24.5% because of incomplete photon absorption in the absorber layer (SnS) and carrier recombination. To increase the absorption window, facilitate charge mobility, and suppress bulk recombination at the rear contact, the absorbent film was divided up into three sublayers with graded band gaps of 1.1 eV, 1.2 eV, and 1.3 eV. Furthermore, the sublayers’ linear gradient doping improved charge collection while simultaneously lowering recombination at the interface. A… More >

Anis Zarrad¹, Thomas Armstrong², Jaber Jemai^3,*

CMC-Computers, Materials & Continua, Vol.86, No.3, 2026, DOI:10.32604/cmc.2025.072768 - 12 January 2026

Abstract Test case prioritization and ranking play a crucial role in software testing by improving fault detection efficiency and ensuring software reliability. While prioritization selects the most relevant test cases for optimal coverage, ranking further refines their execution order to detect critical faults earlier. This study investigates machine learning techniques to enhance both prioritization and ranking, contributing to more effective and efficient testing processes. We first employ advanced feature engineering alongside ensemble models, including Gradient Boosted, Support Vector Machines, Random Forests, and Naive Bayes classifiers to optimize test case prioritization, achieving an accuracy score of 0.98847… More >

Supriya Wadekar^1,*, Shailendra Mittal¹, Ganesh Wakte², Rajshree Shinde²

Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.071761 - 27 December 2025

Abstract Rapid evolutions of the Internet of Electric Vehicles (IoEVs) are reshaping and modernizing transport systems, yet challenges remain in energy efficiency, better battery aging, and grid stability. Typical charging methods allow for EVs to be charged without thought being given to the condition of the battery or the grid demand, thus increasing energy costs and battery aging. This study proposes a smart charging station with an AI-powered Battery Management System (BMS), developed and simulated in MATLAB/Simulink, to increase optimality in energy flow, battery health, and impractical scheduling within the IoEV environment. The system operates through… More >