Engineering Research Express最新文献_第7页

Revolutionizing Waste from Household Plastics to Eco-Friendly Diesel Alternatives through Catalytic Degradation with Biogas Utilization 通过催化降解和沼气利用，将家用塑料废弃物改造成生态友好型柴油替代品

Engineering Research Express Pub Date : 2024-07-11 DOI: 10.1088/2631-8695/ad6234

nishanth jude roy j, Premkumar P, Mohamed Iqbal Shajahan, elangkathir velusamy

{"title":"Revolutionizing Waste from Household Plastics to Eco-Friendly Diesel Alternatives through Catalytic Degradation with Biogas Utilization","authors":"nishanth jude roy j, Premkumar P, Mohamed Iqbal Shajahan, elangkathir velusamy","doi":"10.1088/2631-8695/ad6234","DOIUrl":"https://doi.org/10.1088/2631-8695/ad6234","url":null,"abstract":"\u0000 The study addressed the critical environmental challenge of managing biodegradable and non-biodegradable household plastic waste by converting it into valuable hydrocarbons, thus combating plastic pollution and contributing to renewable energy goals. Through innovative methods, the research utilized catalytic degradation with fly ash as a catalyst and biogas from cow dung and kitchen waste as a sustainable heat source. Various catalyst-to-polymer (cat/pol) ratios (0.10, 0.15, and 0.20) were explored, with the 0.20 ratio achieving a remarkable 100% conversion rate. The resulting oil was segmented based on boiling points, with the C2 fraction showing promise as a diesel substitute, boasting high efficiency and lower emissions. Notably, C2 demonstrated optimal combustion qualities with a maximum brake thermal efficiency of 32.92%, low smoke density (48 HSU), and hydrocarbon emissions (1216 ppm), albeit with increased NOx emissions. Overall, the study highlights the potential of waste-to-energy processes in addressing plastic pollution, reducing fossil fuel dependence, and advancing sustainable energy solutions.","PeriodicalId":505725,"journal":{"name":"Engineering Research Express","volume":"65 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141655744","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}

引用次数: 0

Top three intelligent algorithms for OAM mode recognitions in optical communications 光通信 OAM 模式识别的三大智能算法

Engineering Research Express Pub Date : 2024-07-10 DOI: 10.1088/2631-8695/ad61bc

Binbin Wang, Xizheng Zhang, S. Shah, Badreddine Merabet, Aleksey Andreevich Kovalev, S. Stafeev, E. S. Kozlova, V. Kotlyar, Zhongyi Guo

{"title":"Top three intelligent algorithms for OAM mode recognitions in optical communications","authors":"Binbin Wang, Xizheng Zhang, S. Shah, Badreddine Merabet, Aleksey Andreevich Kovalev, S. Stafeev, E. S. Kozlova, V. Kotlyar, Zhongyi Guo","doi":"10.1088/2631-8695/ad61bc","DOIUrl":"https://doi.org/10.1088/2631-8695/ad61bc","url":null,"abstract":"\u0000 Vortex optical communication employing orbital angular momentum (OAM) has been a hot research field in recent years. Thanks to the orthogonality of the OAM, several multiplexing and modulation techniques have been developed that can effectively improve communication capacity. However, to achieve this, accurate mode recognition in the OAM-based free-space optical (FSO) communication system is essential. Generally, perturbations in the free space link significantly affect the transmission efficiency and distort the helical phase-front of OAM beams, which will result in intermodal crosstalk and poses a critical challenge in the recognition of OAM modes. To date, artificial intelligence (AI) technologies have been widely applied to address the aforementioned bottleneck of insufficient accuracy of existing techniques for OAM mode detection. Therefore, a review paper that discusses the recent developments and challenges of the most widely used AI algorithms for OAM mode recognition schemes, i.e., feedforward neural network (FNN), convolutional neural network (CNN), and diffractive deep neural networks (D2NN) is urgently required. By elaborating on the principles of these algorithms and analyzing recent reports, encompassing both experimental and simulated results, we established their profound importance in enhancing the accuracy of OAM mode recognition. Moreover, this work provides an outlook on the recent trends in this newly developed field and the critical challenges faced in effectively using AI for improving the reliability of the OAM-based FSO communication system in near future.","PeriodicalId":505725,"journal":{"name":"Engineering Research Express","volume":"22 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141659126","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}

引用次数: 0

Optimal path planning using bidirectional rapidly-exploring random tree star-dynamic window approach (BRRT*-DWA) with adaptive Monte Carlo localization (AMCL) 使用双向快速探索随机树星形动态窗口方法（BRRT*-DWA）和自适应蒙特卡罗定位（AMCL）进行最佳路径规划

Engineering Research Express Pub Date : 2024-07-10 DOI: 10.1088/2631-8695/ad61bd

Wubshet Ayalew, Muluken Menebo, Chala Merga, Lebsework Negash

{"title":"Optimal path planning using bidirectional rapidly-exploring random tree star-dynamic window approach (BRRT*-DWA) with adaptive Monte Carlo localization (AMCL)","authors":"Wubshet Ayalew, Muluken Menebo, Chala Merga, Lebsework Negash","doi":"10.1088/2631-8695/ad61bd","DOIUrl":"https://doi.org/10.1088/2631-8695/ad61bd","url":null,"abstract":"\u0000 Path planning is an important task for mobile service robots. Most of the available path-planning algorithms are applicable only in static environments. Achieving path planning becomes a difficult task in an unknown dynamic environment. To solve the problem of path planning in an unknown dynamic environment, this paper proposes a BRRT*- DWA algorithm with Adaptive Monte Carlo Localization. Bidirectional Rapidly-exploring Random Tree Star(BRRT*) is used to generate an optimal global path plan, Dynamic Window Approach(DWA) is a local planner and Adaptive Monte Carlo Localization(AMCL) is used as a localization technique. By using the map file of the unknown environment created by SLAM and LiDAR sensor, the robot can navigate while avoiding dynamic as well as static obstacles. In addition, the object identification algorithm YOLO was adopted, trained, and used for the robot to recognize objects and people. Results obtained from both simulation and experiment show the proposed method can achieve better performance in a dynamic environment compared with other state-of-the-art algorithms.","PeriodicalId":505725,"journal":{"name":"Engineering Research Express","volume":"20 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141661186","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}

引用次数: 0

Software Installation Threat Detection Based on Attention Mechanism and Improved Convolutional Neural Network in IOT Platform 基于注意力机制和改进型卷积神经网络的物联网平台软件安装威胁检测

Engineering Research Express Pub Date : 2024-07-09 DOI: 10.1088/2631-8695/ad612d

Chongwei Liu, Jinlong Pang

{"title":"Software Installation Threat Detection Based on Attention Mechanism and Improved Convolutional Neural Network in IOT Platform","authors":"Chongwei Liu, Jinlong Pang","doi":"10.1088/2631-8695/ad612d","DOIUrl":"https://doi.org/10.1088/2631-8695/ad612d","url":null,"abstract":"\u0000 With of the Internet of Things (IoT) developing and the network technique progressing, malware attacks continue to occur, seriously endangering the information and property security of Internet of Things device users. To ensure the security of the Internet of Things platform and improve the efficiency of malware and vulnerability detection, a software installation threat detection model based on attention mechanism and improved convolutional neural network is constructed. Firstly, the enhanced dynamic symbolic execution module and forward program slicing algorithm are used to extract dynamic features, and then the improved convolutional neural network is utilized to classify malware. In the existing software of IoT devices, the inlining correlation function is studied using the inlining strategy, and the weight between the target pixel and the global pixel is calculated using the attention mechanism, through which the logic and correlation between the triples are correlated. Then, deep residual network is used to detect software vulnerabilities. This enables threat detection before and after software installation. In comparison with the current popular vulnerability detection model experiments, the accuracy, recall rate, accuracy rate and running time of the constructed model in the process of vulnerability detection are 0.975, 0.970, 0.968 and 0.02s, respectively. Compared with other models, the research design model has better performance. This shows that this built model can effectively detect software installation threats, and has high detection accuracy and operation efficiency, which can provide strong support for the Internet of Things platform’s security protection.","PeriodicalId":505725,"journal":{"name":"Engineering Research Express","volume":"101 13","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141666289","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}

引用次数: 0

Heavy metal removal performance of capacitive deionization technology studied by machine learning 通过机器学习研究电容式去离子技术的重金属去除性能

Engineering Research Express Pub Date : 2024-07-09 DOI: 10.1088/2631-8695/ad612c

Xiao-min Dian, Jiayuan Hao, Zheng-Ao Zhang, Zhe Chen, Lei Yao

{"title":"Heavy metal removal performance of capacitive deionization technology studied by machine learning","authors":"Xiao-min Dian, Jiayuan Hao, Zheng-Ao Zhang, Zhe Chen, Lei Yao","doi":"10.1088/2631-8695/ad612c","DOIUrl":"https://doi.org/10.1088/2631-8695/ad612c","url":null,"abstract":"\u0000 Capacitive deionization (CDI) technology is utilized for efficient treatment of industrial wastewater, characterized by low energy consumption and environmental protection. In order to comprehend the correlation between key experimental parameters and the electrosorption capacity (EC) of heavy metals in CDI technology, this paper employs a genetic algorithm (GA) to optimize a backpropagation artificial neural network (BPANN) for predicting the EC of CDI technology for heavy metal ions, with the characteristics of electrode materials converted into numerical characteristics for further analysis. Compared to the BPANN, the optimized GABPANN model demonstrates superior predictive accuracy. It achieves automatic adjustment of the hidden layer structure, neuron count, and transfer functions. Furthermore, the grey relational analysis indicates that the electrode material and the initial pH value of the solution are pivotal in determining the EC of heavy metal ions. This underscores the efficacy of machine learning (ML) algorithms in forecasting the nonlinear dynamics of CDI systems and elucidates the influence of individual parameters on the efficacy of heavy metal removal.","PeriodicalId":505725,"journal":{"name":"Engineering Research Express","volume":"94 19","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141664098","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}

引用次数: 0

Physical properties of InxSey and CuInSe2 thin films with potential application in radiation detectors 具有辐射探测器应用潜力的 InxSey 和 CuInSe2 薄膜的物理特性

Engineering Research Express Pub Date : 2024-07-09 DOI: 10.1088/2631-8695/ad6123

Trinidad Molina-Mil, Jorge Sastré Hernández, Jorge Aguilar-Hernández, María de los Ángeles Hernández-Pérez, Carlos Vázquez-López, Gerardo S. Conteras-Puente

{"title":"Physical properties of InxSey and CuInSe2 thin films with potential application in radiation detectors","authors":"Trinidad Molina-Mil, Jorge Sastré Hernández, Jorge Aguilar-Hernández, María de los Ángeles Hernández-Pérez, Carlos Vázquez-López, Gerardo S. Conteras-Puente","doi":"10.1088/2631-8695/ad6123","DOIUrl":"https://doi.org/10.1088/2631-8695/ad6123","url":null,"abstract":"\u0000 A study of InxSey and CuInSe2 thin films processed by the thermal co-evaporation technique by evaluating its physical properties is carried out. Both InxSey as well as CuInSe2 thin films were synthesized by multi-source thermal co-evaporation technique, using Knudsen-type effusion cells. The optical, structural, electrical, and morphological properties of each film were analyzed in order to determine the feasibility at the formation of a p-CuInSe2/n-InxSey heterojunction. InxSey films exhibited bandgap values in the range of 2.4 - 2.7 eV which was determined by UV-Vis spectroscopic analysis. Vibrational modes associated to In2Se3 as well as Se are presented in the InxSey films according to Raman studies. The irregular morphology of the grains on the InxSey surface, with an average size of 380 nm are related to both In2Se3 and Se materials according to Raman spectroscopy and Scanning Electron Microscopy analysis. The InxSey thin films showed resistivity vales around 10-3 Ω∙cm. The Hackee´s Figure of Merit (FOMH) analysis supported the physical assumption that InxSey thin films are feasible to be used as window layer in a photovoltaic device because of the high values of FOMH obtained for samples processed at 300 °C. On the other hand, an influence on the morphology of the CuInSe2 films was observed when the films were synthetized at different substrate temperature. Uniform CuInSe2 films with agglomerated cauliflower-like grains with an average size of 1.8 μm were observed by SEM. The presence of binary phases within the CuInSe2 compound were detected through Raman and X-Ray characterization. Average crystallite size of 61 nm and microstrain around 2.5 x10-3 were estimated for the CuInSe2 films through X-Ray analysis. According to the physical properties analyzed the InxSey/CuInSe2 semiconductor bilayer can be a suitable candidate for application in photovoltaic devices as well as charged particle detector.","PeriodicalId":505725,"journal":{"name":"Engineering Research Express","volume":"25 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141664974","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}

引用次数: 0

IDENTIFICATION OF END-MILLING CHATTER BASED ON COMPREHENSIVE FEATURE FUSION 基于综合特征融合的立铣刀颤振识别

Engineering Research Express Pub Date : 2024-07-09 DOI: 10.1088/2631-8695/ad6121

Dialoke Ejiofor Matthew, Hongrui Cao, Jianghai Shi

引用次数: 0

Structural health monitoring of a swivel bridge for evaluating builder comfort under train-induced vibration 对旋转桥梁进行结构健康监测，以评估列车引起的振动对施工人员的影响

Engineering Research Express Pub Date : 2024-07-09 DOI: 10.1088/2631-8695/ad612f

Huaxi Lu, Yuting Deng, xiang Wang

引用次数: 0

Development of novel prototype of orange sorting machine 开发新型柑橘分拣机原型

Engineering Research Express Pub Date : 2024-07-09 DOI: 10.1088/2631-8695/ad6124

Tinh Nguyen Van, Ngoc-Kien Nguyen

引用次数: 0

Comparative Assessment of Thermal Oils and Water as Working Fluids in Parabolic Trough Collectors for Enhanced Solar Power Generation 抛物面槽式集热器中作为工作流体的导热油和水在增强太阳能发电方面的比较评估

Engineering Research Express Pub Date : 2024-07-09 DOI: 10.1088/2631-8695/ad6122

H. A. Jabbar, K. Alwan, D. Hachim, Ahmed Al-Manea, R. Al-Rbaihat, Ali Alahmer

{"title":"Comparative Assessment of Thermal Oils and Water as Working Fluids in Parabolic Trough Collectors for Enhanced Solar Power Generation","authors":"H. A. Jabbar, K. Alwan, D. Hachim, Ahmed Al-Manea, R. Al-Rbaihat, Ali Alahmer","doi":"10.1088/2631-8695/ad6122","DOIUrl":"https://doi.org/10.1088/2631-8695/ad6122","url":null,"abstract":"\u0000 Examining the thermal behavior of specific working fluids, namely Syltherm800 and TherminolVP-1, in parabolic trough collectors (PTCs) is imperative for enhancing power generation. This study addresses a crucial gap by conducting computational fluid dynamics simulations through COMSOL Multiphysics software and experimental tests to explore the advantages of utilizing thermal oils over water as a working fluid in PTCs. Experimental tests were performed on a water-based PTC in Iraq to validate the numerical model, considering various operating conditions such as input temperature (323.15-423.15 K) and mass flow rates (0.00926-0.0556 kg/s). Key parameters including output temperature, thermal efficiency, useful heat, and total heat losses were evaluated. The numerical model was validated against experimental data, showing good agreement with an overall discrepancy of 1.7% for the current experiments and 3.18% for literature results. The results indicated that Syltherm800, particularly with a high mass flow rate, outperformed TherminolVP-1 and water in terms of overall thermal performance. The optimal PTC thermal efficiency was achieved in July with a mass flow rate of 0.0556 kg/s and an input temperature of 348.15 K. The optimal range for PTC thermal efficiency over four months was between 50% and 70%. The endorsement of thermal oils in PTCs is supported by their low vapor pressure, superior thermal stability, and extended lifespan.","PeriodicalId":505725,"journal":{"name":"Engineering Research Express","volume":"55 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141663239","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}

引用次数: 0