Open Engineering最新文献_第3页

A review of rutting in asphalt concrete pavement 沥青混凝土路面车辙研究综述

IF 1.7

Open Engineering Pub Date : 2023-01-01 DOI: 10.1515/eng-2022-0463

A. Albayati

{"title":"A review of rutting in asphalt concrete pavement","authors":"A. Albayati","doi":"10.1515/eng-2022-0463","DOIUrl":"https://doi.org/10.1515/eng-2022-0463","url":null,"abstract":"Abstract Undoubtedly, rutting in asphalt concrete pavement is considered a major dilemma in terms of pavement performance and safety faced by road users as well as the road authorities. Rutting is a bowl-shaped depression in the wheel paths that develop gradually with the increasing number of load applications. Heavy axle loadings besides the high pavement summer temperature enhance the problem of rutting. According to the AASHTO design equation for flexible pavements, a 1.1 in rut depth will reduce the present serviceability index of relatively new pavement, having no other distress, from 4.2 to 2.5. With this amount of drop in serviceability, the entire life of the pavement in effect has been lost. Therefore, it is crucial to look at the mechanism, possible reasons, as well as techniques, to reduce the rutting in order to offer long service life and safe roadways. To this end, the need has been arising for this research which deals mainly with a thorough review of the existing literature to highlight some key points for the researchers and pavement engineers related to rutting mechanism, measurement, and criteria, both intrinsic (mixture variables) and extrinsic (traffic and temperature) contributory factors to rutting, material characterization, test methods, and prediction methodologies, as well as possible ways to minimize the rutting distress in asphalt concrete pavement. So far, this research attempts to bridge the gap in the literature that frequently only addresses a single aspect of rutting by providing an in-depth review of rutting in asphalt concrete and thereby offers a complete comprehensive understanding of this major distress type.","PeriodicalId":19512,"journal":{"name":"Open Engineering","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42602419","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

Discharge coefficient and energy dissipation on stepped weir 阶梯堰的流量系数和消能

IF 1.7

Open Engineering Pub Date : 2023-01-01 DOI: 10.1515/eng-2022-0427

Samaa H. Hantoosh, M. Shamkhi

引用次数: 0

Architectural modeling of data warehouse and analytic business intelligence for Bedstead manufacturers Bedstead制造商的数据仓库和分析商业智能的架构建模

Open Engineering Pub Date : 2023-01-01 DOI: 10.1515/eng-2022-0508

Ford Lumban Gaol, Rezaka Ardho Siswanto, Tokuro Matsuo

引用次数: 0

A computational iterative design method for bend-twist deformation in composite ship propeller blades for thrusters 推进器用复合材料船用螺旋桨叶片弯扭变形的迭代设计方法

IF 1.7

Open Engineering Pub Date : 2023-01-01 DOI: 10.1515/eng-2022-0419

S. Ø. Rokvam, N. P. Vedvik, Lukas Mark, Eivind Rømcke, J. Ølnes, L. Savio, A. Echtermeyer

{"title":"A computational iterative design method for bend-twist deformation in composite ship propeller blades for thrusters","authors":"S. Ø. Rokvam, N. P. Vedvik, Lukas Mark, Eivind Rømcke, J. Ølnes, L. Savio, A. Echtermeyer","doi":"10.1515/eng-2022-0419","DOIUrl":"https://doi.org/10.1515/eng-2022-0419","url":null,"abstract":"Abstract This study investigates the feasibility of utilising common composite material layup techniques in ship propeller blade design to achieve an automatic pitch adjustment through bending-induced twist deformation. A comprehensive design approach, including various reinforcement materials and arrangements, was employed to attain the desired foil pitching, while minimising other undesirable deformation modes. The design process involved iterative computational analysis using finite element analysis and a deformation mode analysis based on foil shape parameters. The research showed that the proposed design approach effectively found options to improve the desired foil parameter pitch, while minimising undesirable deformation modes such as blade deflection and foil shape change. Furthermore, the proposed blade design was tested in thruster steering operational conditions and was found to have a pitch change well matched, potentially countering some changes in fluid flow. When compared to Kumar and Wurm’s design, which only focused on the angular orientation of glass reinforcement, the proposed design was found to outperform the twisting by achieving the same twist for a blade half the length. This study provides valuable insights into the utilisation of composite materials in ship propeller design and highlights the potential for further improvement through a composite engineering design approach.","PeriodicalId":19512,"journal":{"name":"Open Engineering","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43109353","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

The nonlinear analysis of reactive powder concrete effectiveness in shear for reinforced concrete deep beams 活性粉末混凝土深梁抗剪性能的非线性分析

IF 1.7

Open Engineering Pub Date : 2023-01-01 DOI: 10.1515/eng-2022-0412

A. Jaafar, M. M. Yussof, A. A. Azeez, T. M. Mezher, Abrahem A. Ali Blash

{"title":"The nonlinear analysis of reactive powder concrete effectiveness in shear for reinforced concrete deep beams","authors":"A. Jaafar, M. M. Yussof, A. A. Azeez, T. M. Mezher, Abrahem A. Ali Blash","doi":"10.1515/eng-2022-0412","DOIUrl":"https://doi.org/10.1515/eng-2022-0412","url":null,"abstract":"Abstract The aim of this article is to investigate the effect of using reactive powder concrete (RPC) for reinforcement concrete deep beams (CDBs) to study the shear effect by the numerical analysis. The method of finite element analysis model simulations using a program was used. The characteristics of RPC and the deep beam of reinforced concrete were obtained from previous scientific research. Non-linear analysis for two models of deep beams, one with RPC and the other without using it, was conducted to compare with experimental results from recent tests of deep concrete beams with RPC and loaded until failure. The data obtained from the specimens have many factors related to the effect of the strength and action of reinforcement CDBs such as shear load deflection, crack pattern, mode failure, and concrete strength. On the other hand, the mesh changing was investigated in terms of the maximum concrete strength and the running time by changing the mesh size to 50, 25, and 15. Models were simulated with a two-point load using a shear span-to-depth with an av/d ratio of 0.77. The difference in percentage deflection between the numerical and experimental models’ data was observed at 2.60 and 5.9% for concrete deep beam and RPC deep beam, respectively, and the maximum shear load was 2.27 and 5.40%. The importance of the outputs of this article lies in bridging the research gap of this new topic and identifying the shear behavior of deep beams reinforced with RPC due to the lack of research related to this topic. It was noted that the obtained data for finite element analysis are very consistent with the previous laboratory scientific research, while the error rate did not exceed 10%.","PeriodicalId":19512,"journal":{"name":"Open Engineering","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43139505","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

Compressive forces influence on the vibrations of double beams 压缩力对双梁振动的影响

IF 1.7

Open Engineering Pub Date : 2023-01-01 DOI: 10.1515/eng-2022-0408

Q. Atiyah, I. Abdulsahib

引用次数: 0

Rehabilitation of overload-damaged reinforced concrete columns using ultra-high-performance fiber-reinforced concrete 超高性能纤维增强混凝土修复超载损伤钢筋混凝土柱

IF 1.7

Open Engineering Pub Date : 2023-01-01 DOI: 10.1515/eng-2022-0437

H. Alasmari

{"title":"Rehabilitation of overload-damaged reinforced concrete columns using ultra-high-performance fiber-reinforced concrete","authors":"H. Alasmari","doi":"10.1515/eng-2022-0437","DOIUrl":"https://doi.org/10.1515/eng-2022-0437","url":null,"abstract":"Abstract One of the problems experienced by reinforced concrete (RC) structures, whether a mistake at the design phase or a change in building use, is an overload. The goal of this study is to determine whether ultra-high-performance fiber-reinforced concrete (UHPFRC) is effective in repairing damaged concrete columns utilizing 30 mm thin concrete jacketing made of different steel fibers at various contents with varied aspect ratios (28, 37, and 45). Nine pieces of 500 mm long RC column specimens with a cross-sectional size of 150 mm × 150 mm were cast as part of the experimental program. By loading these columns with roughly 90% of their actual ultimate axial load capacities, damage was caused, and the columns were subsequently strengthened and rebuilt using UHPFRC jacketing materials. The results demonstrated that when steel fiber content increased, so did the mechanical qualities, such as compressive and tensile strengths. Rehab materials that contained 0.5% steel fiber recovered 138% of their maximum load-bearing capacities, while materials that contained 1.5% steel fiber recovered 164% of their original capacities, which were roughly 1.38–1.64 times that of the unjacketed reference column. Additionally, it was observed that employing steel fiber in UHPFRC contents in these approaches resulted in the ultimate displacement being improved from 2.91 to 5.53 mm at 1.5% of steel fiber content, which is an increase of almost double that of control specimens.","PeriodicalId":19512,"journal":{"name":"Open Engineering","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43935238","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

Hybrid and cognitive digital twins for the process industry 加工行业的混合和认知数字双胞胎

IF 1.7

Open Engineering Pub Date : 2023-01-01 DOI: 10.1515/eng-2022-0418

S. T. Johansen, Perin Unal, Özlem Albayrak, E. Ikonen, Kasper Linnestad, Sudi Jawahery, Akhilesh K. Srivastava, Bjørn Tore Løvfall

{"title":"Hybrid and cognitive digital twins for the process industry","authors":"S. T. Johansen, Perin Unal, Özlem Albayrak, E. Ikonen, Kasper Linnestad, Sudi Jawahery, Akhilesh K. Srivastava, Bjørn Tore Løvfall","doi":"10.1515/eng-2022-0418","DOIUrl":"https://doi.org/10.1515/eng-2022-0418","url":null,"abstract":"Abstract In a Europe that is undergoing digital transformation, the COGNITWIN project is contributing to accelerate the transformation and introduce Industry 4.0 to the European process industries. The opportunities here can be illustrated by the SPIRE 2050 Vision document (https://www.spire2030.eu/sites/default/files/users/user85/Vision_Document_V6_Pages_Online_0.pdf), which states that “Digitalisation of process industries has a tremendous potential to dramatically accelerate change in resource management, process control and in the design and the deployment of disruptive new business models.” The process industries are characterized with harsh environments where sensors are either costly, not available, or may be subject to costly maintenance. The development of digital twins that can exploit the combinations of data-based and physics-based models is often found to be a preferred path to robust digital twins that can help cutting costs and reduce energy consumption. In this article, we present 5 out of 6 industrial pilots that are developed in the COGNITWIN project. We discuss the commonalities and differences between the selected approaches and give some ideas about how cognition can be incorporated into the digital twins. The aim of this article is to inspire similar projects in related industries.","PeriodicalId":19512,"journal":{"name":"Open Engineering","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44081429","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

Deep learning model for intrusion detection system utilizing convolution neural network 基于卷积神经网络的入侵检测系统深度学习模型

IF 1.7

Open Engineering Pub Date : 2023-01-01 DOI: 10.1515/eng-2022-0403

W. F. Kamil, Imad J. Mohammed

{"title":"Deep learning model for intrusion detection system utilizing convolution neural network","authors":"W. F. Kamil, Imad J. Mohammed","doi":"10.1515/eng-2022-0403","DOIUrl":"https://doi.org/10.1515/eng-2022-0403","url":null,"abstract":"Abstract An integral part of any reliable network security infrastructure is the intrusion detection system (IDS). Early attack detection can stop adversaries from further intruding on a network. Machine learning (ML) and deep learning (DL) techniques to automate intrusion threat detection at a scale never previously envisioned have snowballed during the past 10 years. Researchers, software engineers, and network professionals have been encouraged to reconsider the use of ML techniques, notably in cybersecurity. This article proposes a system for detecting intrusion with two approaches, the first utilizing a proposed hybrid convolutional neural network (CNN) and Dense layers. The second utilizes naïve Bayes (NB) ML techniques and compares the two approaches to determine the best detection accuracy. The preprocessing of network data is necessary. The suggested technique is evaluated using the UNSW-NB15 Dataset to create a reliable classifier and an effective IDS. The experimental results for the proposed CNN-dense classifier outperformed the ML and DL models. CNN has a 99.8% accuracy rate compared to previous studies. At the same time, the Gaussian naïve Bayes, which is considered the best among the ML-utilized classifiers, yielded an 83% accuracy rate.","PeriodicalId":19512,"journal":{"name":"Open Engineering","volume":" ","pages":""},"PeriodicalIF":1.7,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47080455","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

Numerical study of the fluid flow and heat transfer in a finned heat sink using Ansys Icepak 使用Ansys Icepak对翅片散热器中流体流动和传热的数值研究

IF 1.7

Open Engineering Pub Date : 2023-01-01 DOI: 10.1515/eng-2022-0440

S. Yaseen

引用次数: 0