Engineering Research Express最新文献

{"title":"Shot peening effects on Cr-Mo-V steel: a comprehensive study of microstructure, surface roughness, residual stress, and mechanical behavior","authors":"S Sarveswara Reddy, K Durga Rajesh, A K Maiti and Durga Venkatesh Janaki","doi":"10.1088/2631-8695/ad777f","DOIUrl":"https://doi.org/10.1088/2631-8695/ad777f","url":null,"abstract":"This study presents a comprehensive study of the microstructure, mechanical characteristics, and surface roughness of Cr-Mo-V low alloy steels and a detailed investigation of the overall impact of shot peening (SP). The microstructure was examined using the optical and scanning electron microscope, showing a significant grain size decrease after shot peening. Evaluations of mechanical characteristics, such as microhardness and tensile strength, showed a noteworthy rise, suggesting enhanced material strength. Studies using fragmentography shed more light on changed fracture tendencies. X-ray diffraction technique (XRD) was used to measure residual stress distribution, and the outcomes displayed an increase after SP, which suggests that internal stresses were created. Surface roughness measurements also showed a noticeable decline, indicating better surface quality. The transformational effects of shot peening on Cr-Mo-V low alloy steels were highlighted by comparative investigations with base metals, providing insights into enhancing material performance for various engineering applications.","PeriodicalId":11753,"journal":{"name":"Engineering Research Express","volume":"23 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A comprehensive machine learning framework with particle swarm optimization for improved polycystic ovary syndrome (PCOS) diagnosis","authors":"Ankur Kumar, Jaspreet Singh and Asim Ali Khan","doi":"10.1088/2631-8695/ad76f9","DOIUrl":"https://doi.org/10.1088/2631-8695/ad76f9","url":null,"abstract":"Polycystic Ovary Syndrome (PCOS) is a hormonal disorder primarily affecting women of reproductive age, characterized by irregular menstrual cycles, elevated male hormones, and ovarian cysts. Early detection and treatment are crucial to prevent long-term complications. This research utilizes clinical data from Kaggle to develop a non-invasive PCOS diagnostic system. The authors conducted comprehensive data preprocessing, feature engineering, and exploratory data analysis (EDA). The refined dataset was incorporated into various default machine learning (ML) algorithms, including LR, LDA, GNB, SVM, XGB, DT, AB, RF, and KNN, for PCOS classification with varying train test ratios 70:30 to 80:20. To further enhance the model’s performance, the authors hybridized all the ML models with Particle Swarm Optimization (PSO). Remarkably, the proposed LR+PSO model achieved the highest accuracy at 96.30%, demonstrating exceptional proficiency with an 80:20 train-test ratio. It significantly improved sensitivity to 94.44%, indicating enhanced detection of positive cases, all while maintaining the highest specificity at 97.22% and precision at 94.44% compared to other models. These results highlight a substantial improvement in integrated models, emphasizing the potential of this novel approach to enhance PCOS diagnosis in terms of accuracy and efficiency, ultimately benefiting individuals with PCOS in their treatment journey.","PeriodicalId":11753,"journal":{"name":"Engineering Research Express","volume":"30 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Defect prediction and performance optimization of A413 vertical centrifugal castings through FEA-based simulation","authors":"Kamar Mazloum, Ameen Al Njjar and Amit Sata","doi":"10.1088/2631-8695/ad7668","DOIUrl":"https://doi.org/10.1088/2631-8695/ad7668","url":null,"abstract":"This study benefits from advanced simulation based on finite element analysis, where finite element analysis possesses robust numerical algorithms to confront critical industrial challenges, including prediction and optimization techniques. The primary goal is to predict the location and quantity of shrinkage porosity and air entrainment, and to mitigate them by optimizing key casting process factors while considering the geometric effects. Virtual experiments designed through the Taguchi method, with three parameters (aspect ratio, pouring temperature, and mold rotation speed) at five levels each, were conducted using the finite element analysis software ProCAST. Post-experimentation, comprehensive data analyses, including signal-to-noise ratio and response surface methods, were employed to determine optimal conditions. Additionally, a sophisticated regression model was developed to clarify the complex relationship between key parameters and defect aspects. Optimal conditions to reduce shrinkage porosity were identified within parameter ranges of (50–75) rpm, (750–800) °C, and (1.75–2) aspect ratio. Similarly, optimal parameters to reduce air entrainment were identified as 150 rpm, 800 °C, and (1) aspect ratio.","PeriodicalId":11753,"journal":{"name":"Engineering Research Express","volume":"58 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and functional testing of battery management system algorithm for an electric bicycle using hardware in the loop testbench","authors":"M Siddharth and Rammohan A","doi":"10.1088/2631-8695/ad7559","DOIUrl":"https://doi.org/10.1088/2631-8695/ad7559","url":null,"abstract":"An embedded Battery Management System (BMS) ensures the effective functionality and longevity of the vehicle battery systems. Testing the BMS using the Hardware in Loop (HIL) approach effectively increases safety and reduces product development time in the manufacturing sector. This research aims to develop an efficient battery management system with two-level protection for electric bicycles and test its functionality in the HIL configuration. The bicycle traction model and battery management system were first developed using a model-based design. Further, the model is tested and validated using battery emulators in the HIL methodology. The battery management system receives input data, such as current, voltage, and temperature, and monitors these parameters. The first level of protection involves the vehicle user receiving the warning when the monitoring parameters values exceed the given first safety threshold. As per the second safety threshold values, the BMS trips off the charging or discharging process when the voltage is 51V, the charge current is 5A, the discharge current is -5A and the IC temperature is 80 degrees. Also, BMS balances the cells in 3.84 min using passive balancing. Additionally, the BMS delivers a controlled current of 2.5A for safe battery charging. This methodology increases safety by reducing the potential risks of testing the BMS algorithms in the actual electric bicycle.","PeriodicalId":11753,"journal":{"name":"Engineering Research Express","volume":"34 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning and design of experiments for optimizing laser-engraved micro fresnel lens mould","authors":"Subir Datta and Arjyajyoti Goswami","doi":"10.1088/2631-8695/ad7193","DOIUrl":"https://doi.org/10.1088/2631-8695/ad7193","url":null,"abstract":"This research examines the application of Laser Engraving to produce micro Fresnel Lenses on aluminum plates, a novel application of this non-conventional machining method. The research explores the effects of the scan speed, laser power with number of cycles on the roundness deviation using a L9 orthogonal array. Multiple analytical methods, including the Taguchi method, Random Forest Algorithm with sensitivity analysis, are employed to optimize process and predict the outcomes. In this study, a thorough analysis of the fabrication of a micro Fresnel lens on Aluminum plate (10 mm × 10 mm × 2 mm) using fiber laser of wavelength 1064 nm is presented. The study finds that laser power has most significant effect on the roundness deviation, followed by the number of the cycles and scan speed. Scan Speed ranges from 500 to 700 mm s−1, the Power ranges from 25 to 35 Watts, and the Number of Cycles ranges from 100 to 200. Optimal conditions are identified as 700 mm/s scan speed, 25 W power, and 100 cycles. Microscopic analysis confirms roundness deviation under these conditions. Comparisons between analytical approaches and experimental results reveal that both the Taguchi method and Random Forest Algorithm align closely with experimental outcomes, with the Random Forest Algorithm showing slightly higher accuracy (6.18 percentage points closer to experimental results). This research addresses a gap in comparative studies evaluating traditional statistical methods against modern machine learning algorithms for process optimization in laser machining. It combines knowledge from optics, materials science, and laser machining, utilizing advanced methods and technologies that have only recently become accessible. The findings provide valuable insights for future applications of micro Fresnel lenses on aluminum plates and contribute to the understanding of laser engraving processes for precision optical components. Between the Random Forest Algorithm and the Taguchi method, Random Forest Algorithm fits more closely to the experimental result. Random Forest Algorithm prediction is closer to experimental result by about 6.18 percentage points compared to the Taguchi method prediction.","PeriodicalId":11753,"journal":{"name":"Engineering Research Express","volume":"38 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189597","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel dual-band defected ground structure wearable microstrip patch antenna for breast tumor detection in biomedical applications","authors":"Sonam Gour, Amit Rathi and Pallav Rawal","doi":"10.1088/2631-8695/ad766a","DOIUrl":"https://doi.org/10.1088/2631-8695/ad766a","url":null,"abstract":"This paper presents a dual-band, low-profile wearable antenna for detecting breast tumors in biomedical applications. The antenna is designed on the FR4 substrate with an optimized dimension of 32 × 27.5 × 0.61 mm3. The compact rectangular patch is miniaturized by cutting the rectangular slots on the front side. The partial ground structure is used for moving the resonance frequency in the ISM band region and for giving the tripping result of the return loss. A breast phantom is created between the transmitter and receiver for detecting the tumor in the phantom model. The different sizes and positions of the tumor in the breast phantom provide different values of the return loss. The final optimized design of the antenna is operated at 2.43 GHz and 3.32 GHz with −35 and −24 return losses respectively. It has been observed from the simulated and measured results that the antenna has a negligible difference between the reflected coefficient, radiation pattern and gain. Afterward, the antenna is also checked for biocompatibility, which represents its good performance. The on-body analysis of the antenna represents a minor variation in the results. The Specific Absorption Ratio (SAR) value of the antenna is in the acceptable range as defined for the wearable device. It is a promising compact wearable antenna that can be used in biomedical applications.","PeriodicalId":11753,"journal":{"name":"Engineering Research Express","volume":"66 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Static and dynamic analyses and multi-objective optimization of wafer thinning machine’s design variables","authors":"Guijiu Xie, Wenbin Zhang, Dongge He, Zhongbo Yi, Zhu Liu, Shibo Wang and Yan Wang","doi":"10.1088/2631-8695/ad74c9","DOIUrl":"https://doi.org/10.1088/2631-8695/ad74c9","url":null,"abstract":"In order to meeting the physical strength, heat dissipation and dimensional requirements of chips, the wafer surface needs to be thinned by wafer thinning machines. In the design of wafer thinning machine, the analysis and optimization of castings is an important and complex issue. In this study, the multi-objective optimization of wafer thinning machine’ s design variables are executed due to static and dynamic analyses. According to the analysis results, the design quality, amplitude and equivalent stress of the casting are optimized. The inner diameter of the ring, the height of the ring, the height of the middle groove, and the height of the groove on both sides are selected as the main design variables of the optimization. The results show that the static deformation of the optimized cast structure is 8% lower than the original structure, the overall mass is 4% lower, the operating frequency is 3.5% lower, higher stability, smaller mass and amplitude are obtained after optimization. The research has a great significance for the wafer thinning machines design, and provides theoretical guidance for the development of other lithography equipments.","PeriodicalId":11753,"journal":{"name":"Engineering Research Express","volume":"13 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization and tribological behavior of carbon nano tubes blended with POE oil","authors":"K Veera Raghavulu, V Mahidhar Reddy, N Govindha Rasu, S P Jani, U Sudhakar, S S Godara, Ashish Kumar, Alok Bhadauria, Kirtanjot Kaur and V Revathi","doi":"10.1088/2631-8695/ad7229","DOIUrl":"https://doi.org/10.1088/2631-8695/ad7229","url":null,"abstract":"Over the past two decades, nano additive lubricants have become essential in manufacturing as lubricating agents. Our study examines the impact of three process parameters—carbon nanotube (CNT) (volume concentration,%), sliding velocity (m/s), and applied load (N)—on the tribological performance of polyolester oil blended with carbon nanotubes. By employing the robust Taguchi L9 orthogonal array as the design of experiment, the current study made an attempt to identify the best combination of these three factors parameters to achieve the least coefficient of friction (COF) while the study also conducted ANOVA and multivariate linear regression to determine the significant factor that determines the least COF. For this study, POE oil and varying concentrations of CNTs (such as 0.05, 0.075 and 0.1 volume concentration%) were used. For this study, the characterization of the CNTs was performed using TEM, SEM and XRD methods while its stability was validated through Zeta potential value i.e., 0.075 volume concentration% CNT concentration achieved 35 mV zeta potential value. The Taguchi L9 orthogonal array outcomes found the least COF i.e., 0.0359 was achieved from 0.075 volume concentration % of CNT with a sliding speed of 3.6 m s−1 at 50 N load. The ANOVA outcomes confirmed the major contribution (91%) of the CNT concentration towards influencing the COF outcomes. The contour plots confirmed that optimal COF can be achieved when using 0.075 volume concentration% CNT with load ranged from 75 N to 125 N and sliding velocities between 1.2 m s−1 and 3.0 m s−1. The outcomes establish that when POE oil is supplemented with CNTs, it can achieve superior performance as the nanolubricant mitigates the coefficient of friction (COF), eventually enhancing the tribological performance. Future researchers can focus on employing Taguch-grey relational analysis, artificial intelligence and machine learning models to find the optimal process parameters for other lubricants and nanoadditives.","PeriodicalId":11753,"journal":{"name":"Engineering Research Express","volume":"8 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189598","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SM-GMVAE: an intelligent model for defect quantification evaluation based on few ultrasonic signals","authors":"Zhifeng Li, Xiaojian Liu, Runchen Li, Shaoheng Song, Weihua Liu and Yaqin Song","doi":"10.1088/2631-8695/ad7669","DOIUrl":"https://doi.org/10.1088/2631-8695/ad7669","url":null,"abstract":"The conventional defect quantification evaluation approaches based on machine learning requires massive amounts of labelled defect signals, which is expensive and time-consuming works. This paper proposed a novel Similarity Metric Gaussian Mixture Variational Auto-Encoder (SM-GMVAE) model, which enables quantify defect with few labelled defect signals. The SM-GMVAE model is designed based on few-shot learning, which includes two modules: feature extraction (FE) module and similarity metric (SM) module. The FE module is designed to extract the feature of defect signal via the Variational Auto-Encoder (VAE). The SM module is used to measure the similarity of two defect signals based on the Gaussian Mixture Model (GMM). Moreover, sparse filtering techniques are used to enhance the sparsity of the features in the SM module. To validate proposed model, some specimens with four various depth defects are designed and fabricated for ultrasonic non-destructive testing experiments. A dataset with defects of different depths is established to compare proposed model with other methods. Our method obtains state-of-the-art experimental results with few labelled defect signals. Different from many published papers, our model is trained with few labelled data, which is more close to engineering practical application than other evaluation model trained using large numbers of labelled data. In other words, the developed approach can realize more complex defect evaluation tasks (such as: size, location, shapes, etc) at very low data labelling cost.","PeriodicalId":11753,"journal":{"name":"Engineering Research Express","volume":"102 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189367","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Fabrication of solution-processed flexible resistive gas sensors based on carbon-quantum-dots decorating mesoporous ZnO fibres for room temperature sensing","authors":"A G Martinez-Lopez, Y Avalos-Grajales, S A Hernandez, S Carmona-Tellez and J C Tinoco","doi":"10.1088/2631-8695/ad7441","DOIUrl":"https://doi.org/10.1088/2631-8695/ad7441","url":null,"abstract":"In recent years, the gas sensor technology has experimented an interesting growth due to the device improvements driven by nanostructured semiconductor films. Nanostructured sensors have enabled the possibility of reducing the operation temperature at room temperature levels, which implies a significant reduction on the power consumption, as well as the possibility to develop sensors over flexible substrates. Therefore, in this work, the fabrication of flexible gas sensors using solution-processing technologies is presented. Nanostructured ZnO mesoporous fibres decorated with Carbon-Quantum-Dots has been used as active layer, and the electrical response, measured as the ratio between the resistance at the target gas respect the resistance in air, is presented. Furthermore, interdigitated electrode configuration has been used for device fabrication with finger spacing of 0.2, 0.4 and 0.6 mm. A maximum response of 0.016 was achieved.","PeriodicalId":11753,"journal":{"name":"Engineering Research Express","volume":"394 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142189428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}