U.Porto Journal of Engineering最新文献_第8页

Numerical Modeling for Prediction of Compression Index from Soil Index Properties in Jimma town, Ethiopia 埃塞俄比亚Jimma镇土壤指数特性预测压缩指数的数值模拟

U.Porto Journal of Engineering Pub Date : 2022-11-28 DOI: 10.24840/2183-6493_008.006_0008

Worku Firomsa, Fikadu Fufa, Yerosan Feyisa

{"title":"Numerical Modeling for Prediction of Compression Index from Soil Index Properties in Jimma town, Ethiopia","authors":"Worku Firomsa, Fikadu Fufa, Yerosan Feyisa","doi":"10.24840/2183-6493_008.006_0008","DOIUrl":"https://doi.org/10.24840/2183-6493_008.006_0008","url":null,"abstract":"In this study, correlations are developed to predict compression index (Cc) from index parameters so that one can be able to model Jimma soils with compression index using simple laboratory tests. Undisturbed and disturbed soil samples from twelve different locations in Jimma town were collected. Laboratory tests like specific gravity, grain size analysis, Atterberg limit, and one-dimensional consolidation test for a total of twenty-four test samples were conducted. From one-dimensional consolidation tests, compressibility soil parameters (Cc and Cs) are determined. From the results of limited tests, an indicative good correlation is observed between Cc and LL, PL, and PI. However, a Poor correlation is developed between Cc and PL when related to the other parameters. The developed correlations will be important inputs in modeling Jimma clay soils with regression model and Artificial neural networks (ANN) analysis using simple index tests. In addition, the results of this study can serve as a basis for further study of such correlations on different clay soils in the country. In this study, regression analysis was used to explore the significance of individual independent (index) soil properties. Regression model and correlation of compression index for liquid limit, plastic limit, and plasticity index were obtained from the linear regression analysis and ANN. This correlation will be helpful for geotechnical engineers in developing the coefficient of compression (Cc) value of expansive/clay soil from index properties. Finally, based on the general findings of the study, suitable recommendations have been forwarded.","PeriodicalId":36339,"journal":{"name":"U.Porto Journal of Engineering","volume":"57 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86115208","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: 6

Performance Evaluation of Feature Extraction Algorithms for Vehicle Shape Classification 车辆形状分类特征提取算法性能评价

U.Porto Journal of Engineering Pub Date : 2022-11-28 DOI: 10.24840/2183-6493_008.006_0005

Sunitha Patel, Srinath S

{"title":"Performance Evaluation of Feature Extraction Algorithms for Vehicle Shape Classification","authors":"Sunitha Patel, Srinath S","doi":"10.24840/2183-6493_008.006_0005","DOIUrl":"https://doi.org/10.24840/2183-6493_008.006_0005","url":null,"abstract":"Vehicle classification is a classic application of automotive image processing that is necessary for a variety of modern vehicle safety and comfort features. While machine learning-based solutions are effective in these fields and are currently employed extensively in various automotive applications. However, the most challenging aspect of automotive image processing with machine learning methods is gathering adequate quality and quantity datasets to develop such applications. Additionally, imbalanced datasets are common in multiclass automotive image processing, as is the case with the current topic of vehicle platoon management. The effectiveness of available handcrafted feature extractors and classifiers employed for vehicle class categorization varies greatly due to the effect of dataset imbalance. This study aims to examine how the performance of four prominent feature extractors alters when used with the imbalance dataset for vehicle shape classification. Also, the use of image augmentation techniques to increase the dataset size for three vehicle classes: car, bus, and truck, has been presented. Further, using the Support Vector Machine (SVM) classifier, experimental analysis was performed using feature extractors such as Histogram of Oriented Gradient (HOG), Scaled Invariant Feature Transform (SIFT), Speeded-Up Robust Feature (SURF), and Haar. Vehicle shape classification, which is an important characteristic in vehicle platoon management, has been evaluated using Receiver Operating Characteristic (ROC) for both the unbalanced dataset and the augmented dataset. The experimental results demonstrate that using the HOG feature extractor performs better when compared to SIFT, SURF, and HAAR feature extractors on the imbalance dataset. After using an image augmentation technique to add images, output performance improved significantly, with HOG output of 95%, SIFT output of 91%, SURF output of 91%, and HAAR output of 96%.","PeriodicalId":36339,"journal":{"name":"U.Porto Journal of Engineering","volume":"14 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81883940","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

Understanding the Trends in Welding of Copper and Steel 了解铜和钢焊接的发展趋势

U.Porto Journal of Engineering Pub Date : 2022-11-28 DOI: 10.24840/2183-6493_008.006_0004

P. Maji, R. Meitei, S. Ghosh

引用次数: 0

Investigation of Crack in Beam Structure using an Adaptive-Genetic Algorithm (AGA) 基于自适应遗传算法(AGA)的梁结构裂缝研究

U.Porto Journal of Engineering Pub Date : 2022-11-28 DOI: 10.24840/2183-6493_008.006_0009

S. Sahu, S. Jena

{"title":"Investigation of Crack in Beam Structure using an Adaptive-Genetic Algorithm (AGA)","authors":"S. Sahu, S. Jena","doi":"10.24840/2183-6493_008.006_0009","DOIUrl":"https://doi.org/10.24840/2183-6493_008.006_0009","url":null,"abstract":"Fault detection and continuous condition monitoring in structural and machine elements are very sensitive topics and gaining significant value as a current research area. Due to the continuous loading and unloading of these elements, fatigue occurs. For the above-mentioned reason, crack is initiated and propagated. The initiation of any type of crack changes the physical properties of the structural and machine elements, which directly affects the lifetime of the element. The presence of any discontinuity changes the physical properties of the element, which also changes elastic properties. These alterations in physical properties change the modal properties of the structural elements. These changes in the vibration criteria can be used for the identification and quantification of the damage. In this research work, the vibration parameters are combined with Artificial Intelligence (AI) to predict the damage location. Here the natural evolution-based Genetic Algorithm (GA) has been used for the training of vibration features (frequencies). It has been discovered that the original AI methods are sometimes not able to give the proper prediction of damage location as they may be trapped in the local optimum. So, to counteract this loophole and to make it more flexible so that it can adjust to the constraints of real-life problems, a data mining method using Regression Analysis (RA) has been proposed and the results have been compared.","PeriodicalId":36339,"journal":{"name":"U.Porto Journal of Engineering","volume":"15 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75476173","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

Characterizing Academic Engineering Research Groups 学术工程研究小组的特点

U.Porto Journal of Engineering Pub Date : 2022-11-28 DOI: 10.24840/2183-6493_008.006_0006

E. Marques, R. Carbas, L. D. Da Silva

{"title":"Characterizing Academic Engineering Research Groups","authors":"E. Marques, R. Carbas, L. D. Da Silva","doi":"10.24840/2183-6493_008.006_0006","DOIUrl":"https://doi.org/10.24840/2183-6493_008.006_0006","url":null,"abstract":"Academic research is a key activity of higher learning institutions, where the knowledge, skills and capabilities of the staff are directed towards scientific activities. The case of academic engineering research groups is quite particular, as they must perform academic research work but still consistently work with industrial partners in problem-solving research activities. Although they appear to be distinct, these aspects are interconnected and combining impactful research work and academic training is highly advantageous to group performance. This paper studies the operation of academic engineering research groups, starting with a literature review on the subject, followed by an analysis of a case study. The target of the case study is the Advanced Joining Processes Unit, part of the Institute of Science and Innovation in Mechanical and Industrial Engineering and the Faculty of Engineering of the University of Porto, a leading research unit in mechanical engineering, performing research on advanced joining processes. The main lesson drawn is that to achieve lasting success and significant impact on the scientific community and society, a research group must operate with clear and result-oriented leadership, able to provide a work environment with well-defined goals, and which is consistently working towards knowledge generation and dissemination.","PeriodicalId":36339,"journal":{"name":"U.Porto Journal of Engineering","volume":"5 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75349400","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

State of the Art Techniques to Advance Deep Networks for Semantic Segmentation 推进深度网络语义分割技术的最新进展

U.Porto Journal of Engineering Pub Date : 2022-11-28 DOI: 10.24840/2183-6493_008.006_0010

Aakanksha, Arushi Seth, Shanu Sharma

{"title":"State of the Art Techniques to Advance Deep Networks for Semantic Segmentation","authors":"Aakanksha, Arushi Seth, Shanu Sharma","doi":"10.24840/2183-6493_008.006_0010","DOIUrl":"https://doi.org/10.24840/2183-6493_008.006_0010","url":null,"abstract":"In recent times, the computer vision community has seen remarkable growth in the field of scene understanding. With such a wide prevalence of images, the importance of this field is growing rapidly along with the technologies involved in it. Semantic Segmentation is an important step in scene understanding which requires the assignment of each pixel in an image to a pre-defined class and achieving 100% accuracy is a challenging task, thereby making it an active research topic among researchers. In this paper, an extensive study and review of the existing Deep Learning (DL) based techniques used for Semantic Segmentation is carried out along with a summary of the datasets and evaluation metrics used for it. The study involved the meticulous selection of relevant research papers in the field of interest by search based on several defined keywords. The study begins with a general and broader focus on Semantic Segmentation as a problem and further narrows its focus on existing Deep Learning (DL) based approaches for this task. In addition to this, a summary of the traditional methods used for Semantic Segmentation is also presented. The contents of this study are organized to provide ease of access to the relevant literature available for the problem of Semantic Segmentation, with a concentrated focus on DL-based methods. Since the problem of scene understanding is being vastly explored by the computer vision community, especially with the help of Semantic Segmentation, we believe that this study will benefit active researchers in reviewing and studying the existing state-of-the-art, as well as advanced methods for the same.","PeriodicalId":36339,"journal":{"name":"U.Porto Journal of Engineering","volume":"81 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77559542","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: 1

Techno-Economical Planning of an Off-Grid Integrated Renewable Energy System 离网综合可再生能源系统的技术经济规划

U.Porto Journal of Engineering Pub Date : 2022-11-28 DOI: 10.24840/2183-6493_008.006_0015

Akanksha Sharma, H. Singh, R. Viral, N. Anwer

{"title":"Techno-Economical Planning of an Off-Grid Integrated Renewable Energy System","authors":"Akanksha Sharma, H. Singh, R. Viral, N. Anwer","doi":"10.24840/2183-6493_008.006_0015","DOIUrl":"https://doi.org/10.24840/2183-6493_008.006_0015","url":null,"abstract":"This paper focuses on reducing the LCOE (Levelized Cost of Energy), the unmet load, Net Present Cost (NPC) and the greenhouse gas emissions by the utilization of an optimized off-grid integrated renewable energy system. The LCOE has been reduced by 14.8% of that of DG and by 28.6 % of Diesel Generator (DG) with Battery System, whereas the NPC has been reduced by 14.7% of DG only system and by 28.7% of DG with Battery System. A comparison analysis has also been presented based on the performance of the proposed system and most recently published similar studies. To achieve these objectives, an optimization algorithm has been developed and simulated in Hybrid Optimization Model for Multiple Energy Resources (HOMER) software with different combinations of IRES, DG and battery systems. Similarly, intending to analyze the feasibility and performance in terms of the technical and economic aspects of the proposed system, HOMER is used. Based on the obtained results, broadly, it is examined that the proposed system decreases diesel consumption by around 8113 liters/year and the total emissions of greenhouse gas by about 21545 kg/year in the study area; thereby, it can be foreseen as a viable and sustainable option(s) for the development of more such systems in remote locations.","PeriodicalId":36339,"journal":{"name":"U.Porto Journal of Engineering","volume":"70 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85789272","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

Effects of Glass and Steel Fibers on Fresh and Hardened Properties of Self-Compacting Concrete 玻璃纤维和钢纤维对自密实混凝土新鲜和硬化性能的影响

U.Porto Journal of Engineering Pub Date : 2022-11-28 DOI: 10.24840/2183-6493_008.006_0003

B. Patel, Siddharth G. Shah, Vikunj Tilva, Rajan Lad

引用次数: 0

Raised Floor Systems with Ceramic Tiles 带有瓷砖的活动地板系统

U.Porto Journal of Engineering Pub Date : 2022-11-28 DOI: 10.24840/2183-6493_008.006_0002

Guilherme Farias Idalêncio, Djeisa Pasini, E. Angioletto, Augusto Wanderlind, Jorge Henrique Piva, Elaine Guglielmi Pavei Antunes

引用次数: 0

Vane Angle Influence on the Flow Pattern around a Circular Pier 叶片角对圆形桥墩周围流型的影响

U.Porto Journal of Engineering Pub Date : 2022-11-28 DOI: 10.24840/2183-6493_008.006_0014

T. Jabbar, Rafi M. Qasim, Bassam A. Mohammed

{"title":"Vane Angle Influence on the Flow Pattern around a Circular Pier","authors":"T. Jabbar, Rafi M. Qasim, Bassam A. Mohammed","doi":"10.24840/2183-6493_008.006_0014","DOIUrl":"https://doi.org/10.24840/2183-6493_008.006_0014","url":null,"abstract":"This paper intends to numerically analyze the hydrodynamic characteristics of the flow pattern that surrounds the circular pier near the vane angle. These include flow velocity, turbulent intensity, and pressure. A computational fluid dynamic is proposed to simulate the two-dimensional model by using the finite volume method, while the k - ε turbulence model is used to describe the turbulent model. The vane is located upstream of the pier, with its dimensions as function of the pier diameter. The distance between the vane and the pier center is equal to the pier diameter, the angle of the vane is put with a range from 60o to 180o, and the pier diameter is equal to 10 mm. The turbulent flow has a Reynolds number that varies from 20000 to 50000. The existence of the vane angle leads to two different processes, which are flow separation and flow dissipation, which have a direct effect on flow velocity, turbulent intensity, and pressure. From the current numerical results, the relationships between Reynolds number and average flow velocity, maximum flow velocity, turbulent intensity, and maximum turbulent intensity are more sensitive to flow separation and flow dissipation along the vane. Also, positive and negative pressure distributions have a higher influence on flow separation and flow dissipation.","PeriodicalId":36339,"journal":{"name":"U.Porto Journal of Engineering","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85874049","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