Results in Engineering最新文献

{"title":"Investigating age-related muscle force adaptations in males and females during sit-to-walk transition motion using EMG-informed modeling","authors":"Zakia Hussain ,&nbsp;Alpha Agape Gopalai ,&nbsp;Siti Anom Ahmad ,&nbsp;Mazatulfazura Sf Binti Salim ,&nbsp;Darwin Gouwanda ,&nbsp;Pei-Lee Teh","doi":"10.1016/j.rineng.2025.104660","DOIUrl":"10.1016/j.rineng.2025.104660","url":null,"abstract":"<div><h3>Background</h3><div>The sit-to-walk (STW) transition is essential for mobility but deteriorates with age due to declining muscle strength, balance, and postural control. This study hypothesizes that age- and sex-related variations in muscle forces during STW lead to altered muscle recruitment strategies, reflecting compensatory mechanisms. When these compensations are no longer adequate, mobility limitations may occur.</div></div><div><h3>Methods</h3><div>This study involved 65 healthy adults (32 males and 33 females) from three age groups. Motion capture and surface electromyography (sEMG) data were used to develop an EMG-informed neuromusculoskeletal model for estimating muscle forces. Age and sex-related variations in muscle forces were analyzed using Generalized Linear Mixed Modeling (GLMM).</div></div><div><h3>Results</h3><div>The findings reveal consistent recruitment of primary STW muscles across all age-sex subgroups. The <em>vasti, gluteus maximus, gluteus medius, dorsiflexors,</em> and <em>soleus</em> generated the highest average muscle forces during STW. However, older adults consistently generated lower forces in these muscles during rising (except for the <em>soleus</em>). Despite this, phase durations were like other groups, with increased ankle plantarflexor (except <em>gastrocnemius</em>) and hip abductors (<em>gluteus medius</em>) forces to support gait transition. These findings indicate compensation in healthy aging involves variations in muscle force production rather than altered muscle recruitment strategies. Moreover, females exhibited more pronounced age-related muscle force changes than males during gait initiation.</div></div><div><h3>Conclusion</h3><div>Significant age- and sex-specific variations in muscle forces across STW phases highlight the need for biomechanically informed interventions to preserve muscle health and reduce functional decline. Targeted interventions should focus on strengthening STW muscles and not just knee extensors to enhance mobility. For example, exercises like Tai Chi, known to improve dynamic stability during gait initiation, can benefit females across age groups.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"26 ","pages":"Article 104660"},"PeriodicalIF":6.0,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Flow boiling of HFE-7100 over graphene coated sintered porous copper surfaces in a minichannel","authors":"Tayfun Guler ,&nbsp;Vahid Ebrahimpour Ahmadi ,&nbsp;Ilker Alagozoglu ,&nbsp;Saifa Amin ,&nbsp;Ahmet Muhtar Apak ,&nbsp;Alper Apak ,&nbsp;Murat Parlak ,&nbsp;Umur Tastan ,&nbsp;Ismet Inonu Kaya ,&nbsp;Ali Sadaghiani ,&nbsp;Ali Koşar","doi":"10.1016/j.rineng.2025.104653","DOIUrl":"10.1016/j.rineng.2025.104653","url":null,"abstract":"<div><div>High power dense electronic devices demand efficient heat removal and thermal management. Phase change heat transfer with the application of graphene coating offers superior heat dissipation. In this study, the effects of sintered copper powders and monolayer graphene coating on flow boiling of HFE-7100 were investigated for a minichannel. Bare copper surface and surfaces with additional sintered layers of thicknesses of 0.5 mm, 1.0 mm, and 2.0 mm were compared in terms of flow boiling heat transfer. Additionally, graphene coatings were applied to each surface, and the effects of graphene coating on flow boiling heat transfer were assessed at atmospheric pressure. The experiments were conducted at different heating fluxes and two different mass fluxes (120 kg/m²s and 180 kg/m²s) for each surface. Novec HFE-7100, a dielectric fluid having a high potential for the use in electronics cooling applications, was used as the working fluid in flow boiling experiments. The results indicated that the sintered layer improved the flow boiling heat transfer performance. The sintered layer thickness of 0.5 mm offered the best heat transfer performance with an enhancement up to 145 % relative to the bare surface at high heat fluxes. It was also observed that graphene coatings further enhanced the heat transfer performance of the sintered surfaces up to 34 %. When 0.5 mm sinter thickness and graphene coating were combined, the maximum heat transfer enhancement was recorded as 227 % compared to the bare surface. In the light of high-speed camera images, flow boiling characteristics and effects of graphene coating on flow patterns were displayed. Accordingly, the graphene coating increased the nucleation site density, improved the stability of bubble formation and led to HTC enhancement for the sintered surfaces.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"26 ","pages":"Article 104653"},"PeriodicalIF":6.0,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686446","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Estimating and parametrically improving the microstructure, hardness, and wear resistance of SiC-CeO2 reinforcements on hot rolled Al7075 hybrid composites","authors":"Ravi Kumar M ,&nbsp;Vijay Kumar S ,&nbsp;C.Durga Prasad ,&nbsp;G Sridevi ,&nbsp;Aprameya C R ,&nbsp;Ashish Kumar ,&nbsp;Saravana Bavan ,&nbsp;Adem Abdirkadir Aden","doi":"10.1016/j.rineng.2025.104634","DOIUrl":"10.1016/j.rineng.2025.104634","url":null,"abstract":"<div><div>This research employed stir casting to fabricate hybrid aluminum matrix composites (MMC) by mixing different weight proportions of silicon carbide (SiC) with a fixed weight percentage of cerium oxide (CeO₂) and adding it to Al7075 alloy. Hot rolling process was carried out for the developed hybrid composites and mechanical and wear behavior were studied. The effect of wear parameters like applied load (N), sliding distance (m) and wt. % of SiC were studied using statistical approach. The obtained results indicate that, significant improvement was obtained in the grain refinements with minimum porous structures. Similarly, increases of toughness (80–120 KJ/m2), tensile strength (115–136 N/mm2) and hardness (55–71 VHN) with increasing in 0–6 wt. % of SiC reinforcements were obtained. The statistical analysis results indicate that, SiC reinforcements significantly influence the wear resistance of the hybrid composites followed by applied load and sliding distance. Lastly, a feed-forward &amp; backward propagation neural network employing the Levenberg-Marquardt algorithm was used to study COF &amp; wear loss based on three input parameters. For both combinations, the coefficient of correlation was found to be 0.9516 &amp; 0.9956 for training &amp; 0.9907 &amp; 0.9736 for testing, with a confidence interval of 95 %. The mean square error performance achieved was 1.6010^-5 &amp; 1.3210^-5, respectively.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"26 ","pages":"Article 104634"},"PeriodicalIF":6.0,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686051","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Utilizing voting classifiers for enhanced analysis and diagnosis of cardiac conditions","authors":"Mohamed S. Elgendy ,&nbsp;Hossam El-Din Moustafa ,&nbsp;Hala B. Nafea ,&nbsp;Warda M. Shaban","doi":"10.1016/j.rineng.2025.104636","DOIUrl":"10.1016/j.rineng.2025.104636","url":null,"abstract":"<div><div>Identifying heart disease based on initial symptoms poses a considerable difficulty in the modern era. Untimely diagnosis may lead to fatality. An accurate decision support system is essential for timely identification of heart diseases. The model proposed is named Heart Disease Prediction Model (HDPM) and comprises three primary components; which are; (i) data collection and preprocessing, (ii) feature selection, and (iii) Disease Prediction. In the first part, the used heart disease dataset is preprocessed and the heart disease features are extracted. Then, these extracted features are fed to the second part (i.e. feature selection). This paper presents a novel approach to feature selection using the Sand Cat Swarm Optimization (SCSO) algorithm. An enhanced methodology has been implemented in the SCSO system to improve its effectiveness in identifying and categorizing the most crucial and impactful features for predicting and classifying patients with heart disease. The proposed methodology is called Dynamic SCSO (DSCSO). DSCSO is combination method between SCSO and Dynamic Opposite Learning (DOL). Ultimately, the chosen features are inputted into the voting classifiers to arrive at the ultimate determination. The proposed voting classifiers is based on using multiple classifiers which are, Logistic Regression (LR), Naïve Bayes (NB), Random Forest (RF), Extreme Gradient Boost (EGB), Decision Tree (DT), and Support Vector Machine (SVM). At the end, the proposed model (i.e., HDPM) trained and tested using heart disease data and it performs well.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"26 ","pages":"Article 104636"},"PeriodicalIF":6.0,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From waste to worth: Assessing the feasibility of sodium aluminate as an activator for transforming steel slag modified waste foundry sand into a valuable resource","authors":"Felicia Magedi ,&nbsp;Joseph Nseke ,&nbsp;Samarjeet Siwal ,&nbsp;Wolfram Schmidt ,&nbsp;Ali Ghamari ,&nbsp;Thabo Falayi ,&nbsp;Thandiwe Sithole","doi":"10.1016/j.rineng.2025.104554","DOIUrl":"10.1016/j.rineng.2025.104554","url":null,"abstract":"<div><div>Steel industries and foundries worldwide produce substantial amounts of waste, such as slag and waste foundry sand, which pose significant environmental hazards if not managed properly. This study explores the utilization of basic oxygen furnace slag (BOFS) and green waste foundry sand (GWFS) as raw materials for synthesizing alkali-activated materials (AAMs) using sodium aluminate (NaAlO₂) as an alkaline activator. The research investigates various mix designs of BOFS and GWFS in different proportions 100:0, 85:15, 70:30, 55:45, and 50:50 to determine the optimal combination for maximum strength. The curing conditions, including temperature and time, were varied, with temperatures ranging from 40 °C to 80 °C and curing time from 1 to 6 days. The AAM formulated using 50% BOFS and 50% GWFS, cured at 80 °C with an alkaline activator concentration of 8 M, achieved the highest compressive strength of 14.25 MPa. X-ray diffraction (XRD) analysis revealed the formation of calcium silicate hydrate (C-S-H) and calcium aluminium silicate hydrate (C-A-S-H) phases, which are critical in the strength development of AAMs. Additionally, scanning electron microscopy (SEM) results demonstrated that BOFS-GWFS specimens exhibited enhanced structural densification and compaction as the concentration of sodium aluminate increased. The Toxicity Characteristic Leaching Procedure (TCLP) confirmed that metals were effectively immobilized within the AAM matrix, indicating that these materials pose minimal environmental risks. Moreover, the environmental footprint of the synthesized monolith is sufficiently low, allowing it to be safely used alongside standard masonry bricks in compliance with the specifications outlined in ASTM C34–03 and ASTM C62–10.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"26 ","pages":"Article 104554"},"PeriodicalIF":6.0,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"P-DETR: A transformer-based algorithm for pipeline structure detection","authors":"Ibrahim Akinjobi Aromoye,&nbsp;Lo Hai Hiung,&nbsp;Patrick Sebastian","doi":"10.1016/j.rineng.2025.104652","DOIUrl":"10.1016/j.rineng.2025.104652","url":null,"abstract":"<div><div>Pipelines are essential transportation infrastructure for oil and gas, but they are vulnerable to defects such as cracks, joint failure, and corrosion due to extreme weather conditions. These defects can result in oil and gas leakage, which prompts environmental and economic damages. Hence, regular inspection of pipelines is necessary. The industry has increasingly relied on using drones for pipeline inspections, though the inspection is still done manually by the drone operator or offline via recorded video footage from the drone. This paper proposes using the Pipe Detection Transformer (P-DETR), a novel transformer-based model designed for pipeline detection and potential integration with aerial robots or drones to enable autonomous pipeline inspection. P-DETR introduces significant improvements to the original Detection Transformer (DETR) framework to enhance its detection performance, particularly for small-sized pipes - a key limitation of the baseline DETR. The major contribution is a Feature Normalization and Transformation (FNT) module, which fuses multiple layers of the convolutional backbone to provide a focused representation of small-sized features before processing by the transformer module. Experimental results validate the superiority of P-DETR, achieving an overall mAP of 55 %, a 3 AP improvement over DETR, and significantly increasing precision for small-sized pipe detection by 8.6 AP (from 1.9 to 10.5). Additionally, precision improvements for medium- and large-sized pipes were 10.8 AP (from 10.8 to 21.6) and 2.2AP (from 64.4 to 66.6), respectively, with an overall recall of 73.9 %, a 4 AP improved performance over DETR. The results from extensive experiments highlight the superior performance of the proposed P-DETR model over the original DETR, UP-DETR, R-DETR, Skip-DETR, and other standard object detection models, including YOLOv3 and SSD.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"26 ","pages":"Article 104652"},"PeriodicalIF":6.0,"publicationDate":"2025-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparison of thermal characteristics and cooling performance of crude palm oil and mineral oil as electrical insulators","authors":"Muhamad Mustangin ,&nbsp;Bambang Purwantana ,&nbsp;Chusnul Hidayat ,&nbsp;Radi","doi":"10.1016/j.rineng.2025.104547","DOIUrl":"10.1016/j.rineng.2025.104547","url":null,"abstract":"<div><div>Crude Palm Oil (CPO) has the potential to be an environmentally friendly renewable insulator, one of which functions as a coolant. This study evaluated and compared thermal characteristics between Mineral Oil (MO) and CPO, such as specific heat, thermal conductivity, and heat distribution. The data analysis used ANOVA, Response Surface Methodology, and dimensionless analysis. Specific heat was measured by heating CPO, MO, and water to 100 °C, while thermal conductivity was assessed using a two-point observation method under steady-state heating conditions. Forced convection experiments were conducted with varying mass flow rates and air velocity. As a result, CPO had a higher specific heat and thermal conductivity than MO. Moreover, CPO produced a lower cooling temperature on average, but MO produced a lower temperature for all data and lower power. Also, CPO was more sensitive to mass flow rate changes, while MO was more responsive to air velocity. The optimization for CPO was an air velocity of 2.35 m s^-1 and mass flow rate of 0.37 g s^-1, resulting in a temperature of 56.90 °C and power of 6.82 W. Besides, CPO showed a Nusselt number range of 10.5–12.0 and a heat transfer coefficient of 370–410 W/m² °C, indicating relatively high thermal efficiency. The correlation between the predicted heat transfer coefficient and experimental observations was strong (R² = 0.99). The Nusselt number showed a proportional increase with the Prandtl number, with a correlation of R² = 0.95. These results suggest that CPO could be a more effective insulator with better cooling performance than MO.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"26 ","pages":"Article 104547"},"PeriodicalIF":6.0,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644359","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Understanding forest fragmentation dynamics and identifying drivers for forest cover loss using random forest models to develop effective forest management strategies in North-East India","authors":"Soumik Mahapatra ,&nbsp;Bishal Kumar Majhi ,&nbsp;Mriganka Shekhar Sarkar ,&nbsp;Debajit Datta ,&nbsp;Arun Pratap Mishra ,&nbsp;Upaka Rathnayake","doi":"10.1016/j.rineng.2025.104640","DOIUrl":"10.1016/j.rineng.2025.104640","url":null,"abstract":"<div><div>Deforestation poses a significant conservation challenge on a global scale, endangering both plant life and the interconnected animal communities reliant upon it. This loss is primarily propelled by anthropogenic activities, emphasizing the need for meticulous monitoring tools tailored to the intricacies of regional socio-political and cultural dynamics influencing forest loss within specific regions. This study utilized advanced remote sensing technologies, employing <em>Landsat</em> imagery on the Google Earth Engine platform, to generate detailed Land Use and Land Cover (LULC) classifications spanning three decades (1991–2021), revealing significant landscape changes over time. Forest fragmentation patterns and loss were analyzed using spatial metrics derived from FRAGSTATS to assess ecological impacts. Furthermore, spatial and non-spatial Random Forest regression techniques were employed to identify key drivers of forest loss within the landscape. The assessment of deforestation identifies a significant ∼9% reduction, particularly in the plains of Assam, Manipur, and Meghalaya, with substantial changes in AREA, PERIM, and SHAPE (p <em>&lt;</em> 0.05). Landscape fragmentation analysis revealed the susceptibility of peripheral forest zones and forest perforation to rapid deforestration. Human population density, forest-to-population ratio, and mean temperature emerged as key drivers of forest loss, with elevated temperatures augmenting forest fire risks. Conversely, rugged terrain and high rainfall negatively impacted forest loss in less inaccessible areas of the region. Our study underscores the urgent need for evidence-based conservation strategies and sustainable land use practices in the North East Indian Region. By integrating remote sensing and modeling techniques, our approach offers a template for regional analysis worldwide, informing policy-making and ground-based management efforts to safeguard terrestrial forest ecosystems.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"26 ","pages":"Article 104640"},"PeriodicalIF":6.0,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Error prediction for machining thin-walled blade with Kriging model","authors":"Jinhua Zhou ,&nbsp;Sitong Qian ,&nbsp;Tong Han ,&nbsp;Rui Zhang ,&nbsp;Junxue Ren","doi":"10.1016/j.rineng.2025.104645","DOIUrl":"10.1016/j.rineng.2025.104645","url":null,"abstract":"<div><div>Compressor blades are the key components of aero-engines, and their machining accuracy is critical to aero-engine performance. However, the choice of machining parameters during machining compressor blade has a direct impact on the position error and torsion error, which in turn affects the aero-engine performance. The conventional methodology for investigating mechanisms on machining error is frequently both time-consuming and labour-intensive. The agent-based modelling approach is trained on a limited set of experimental data in order to obtain an approximate mathematical model of the real process. This approach has the advantages of low modelling cost, convenient operation, and high computational efficiency. Accordingly, this paper employs the agent model to construct prediction models for the position error and torsion error of compressor blades. Firstly, experiments were designed to be conducted on compressor blades under different working conditions in order to obtain the position error and torsion error data of compressor blades. Then, based on the superiority of the agent model, the Kriging models are constructed to establish prediction models for the position error and torsion error of compressor blades. Finally, the influence of machining parameters on the position error and torsion error of compressor blades is analysed. The prediction accuracies of the established models are all greater than 0.85, which can provide strong support for the optimization of the machining process of compressor blades.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"26 ","pages":"Article 104645"},"PeriodicalIF":6.0,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143686038","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Double-Diffusive flow and heat transfer of nano-encapsulated phase change materials in a circular cavity with partial porous region under magnetic influence","authors":"Mohammed Azeez Alomari ,&nbsp;Ahmed M. Hassan ,&nbsp;Abdellatif M. Sadeq ,&nbsp;Faris Alqurashi ,&nbsp;Mujtaba A. Flayyih","doi":"10.1016/j.rineng.2025.104646","DOIUrl":"10.1016/j.rineng.2025.104646","url":null,"abstract":"<div><div>A numerical investigation of double-diffusive natural convection and magnetohydrodynamics (MHD) in a circular cavity containing nano-encapsulated phase change materials (NEPCM) with a partial porous medium under magnetic field influence has been conducted. The governing equations were discretized using the Galerkin finite element method, and the resulting nonlinear system was solved through the Newton-Raphson iteration technique with PARDISO solver. The study examined the effects of key parameters including Rayleigh (Ra) number (10³-10⁵), Hartmann (Ha) number (0–61), Darcy (Da) number (10⁻⁵-10⁻¹), Lewis (Le) number (0.1–10), buoyancy ratio (2–6), nanoparticle volume fraction (0–0.05), and fusion temperature (0.1–0.9). Results show that increasing nanoparticle concentration from 0 to 0.05 enhances heat transfer (Nusselt number, Nu) by 128 % while reducing mass transfer (Sherwood number, Sh) by 10.3 % at Ra = 10⁵. The magnetic field demonstrates a significant suppressive effect, with Ha increasing from 0 to 61 reducing both Nu and Sh by approximately 55 % and 57 % respectively. An optimal fusion temperature of 0.6 was identified for heat transfer enhancement, while mass transfer showed minimal sensitivity to fusion temperature variations. The study reveals that proper selection of operating parameters, particularly Da and Le numbers, can improve system performance by up to 218 % in mass transfer and 158 % in heat transfer, providing valuable insights for the design of thermal energy storage systems incorporating NEPCM and porous media.</div></div>","PeriodicalId":36919,"journal":{"name":"Results in Engineering","volume":"26 ","pages":"Article 104646"},"PeriodicalIF":6.0,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}