L. Nhung, T. T. Phung, H. Nguyen, T. N. Le, T. A. Nguyen, T. D. Vo
This paper proposes a new load shedding method based on the application of a Dual Neural Network (NN). The combination of a Back-Propagation Neural Network (BPNN) and of Particle Swarm Optimization (PSO) aims to quickly predict and propose a load shedding strategy when a fault occurs in the microgrid (MG) system. The PSO algorithm has the ability to search and compare multiple points, so the proposed NN training method helps determine the link weights faster and stronger. As a result, the proposed method saves training time and achieves higher accuracy. The Analytic Hierarchy Process (AHP) algorithm is applied to rank the loads based on their importance factor. The results of the ratings of the loads serve as a basis for constructing the load shedding strategies of a NN combined with the PSO algorithm (ANN-PSO). The proposed load shedding method is tested on an IEEE 25-bus 8-generator MG power system. The simulation results show that the frequency recovery of the power system is positive. The proposed neural network adapts well to the simulated data of the system and achieves high performance in fault prediction.
{"title":"Load Shedding in Microgrids with Dual Neural Networks and AHP Algorithm","authors":"L. Nhung, T. T. Phung, H. Nguyen, T. N. Le, T. A. Nguyen, T. D. Vo","doi":"10.48084/etasr.4652","DOIUrl":"https://doi.org/10.48084/etasr.4652","url":null,"abstract":"This paper proposes a new load shedding method based on the application of a Dual Neural Network (NN). The combination of a Back-Propagation Neural Network (BPNN) and of Particle Swarm Optimization (PSO) aims to quickly predict and propose a load shedding strategy when a fault occurs in the microgrid (MG) system. The PSO algorithm has the ability to search and compare multiple points, so the proposed NN training method helps determine the link weights faster and stronger. As a result, the proposed method saves training time and achieves higher accuracy. The Analytic Hierarchy Process (AHP) algorithm is applied to rank the loads based on their importance factor. The results of the ratings of the loads serve as a basis for constructing the load shedding strategies of a NN combined with the PSO algorithm (ANN-PSO). The proposed load shedding method is tested on an IEEE 25-bus 8-generator MG power system. The simulation results show that the frequency recovery of the power system is positive. The proposed neural network adapts well to the simulated data of the system and achieves high performance in fault prediction.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89620980","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}
Covid-19 is a highly infectious disease that spreads extremely fast and is transmitted through indirect or direct contact. The scientists have categorized the Covid-19 cases into five different types: severe, critical, asymptomatic, moderate, and mild. Up to May 2021 more than 133.2 million peoples have been infected and almost 2.9 million people have lost their lives from Covid-19. To diagnose Covid-19, practitioners use RT-PCR tests that suffer from many False Positive (FP) and False Negative (FN) results while they take a long time. One solution to this is the conduction of a greater number of tests simultaneously to improve the True Positive (TP) ratio. However, CT-scan and X-ray images can also be used for early detection of Covid-19 related pneumonia. By the use of modern deep learning techniques, accuracy of more than 95% can be achieved. We used eight CNN (CovNet)-based deep learning models, namely ResNet 152 v2, InceptionResNet v2, Xception, Inception v3, ResNet 50, NASNetLarge, DenseNet 201, and VGG 16 for both X-rays and CT-scans to diagnose pneumonia. The achieved comparative results show that the proposed models are able to differentiate the Covid-19 positive cases.
{"title":"Automatic Diagnosis of Covid-19 Related Pneumonia from CXR and CT-Scan Images","authors":"N. Kumar, A. Hashmi, M. Gupta, A. Kundu","doi":"10.48084/etasr.4613","DOIUrl":"https://doi.org/10.48084/etasr.4613","url":null,"abstract":"Covid-19 is a highly infectious disease that spreads extremely fast and is transmitted through indirect or direct contact. The scientists have categorized the Covid-19 cases into five different types: severe, critical, asymptomatic, moderate, and mild. Up to May 2021 more than 133.2 million peoples have been infected and almost 2.9 million people have lost their lives from Covid-19. To diagnose Covid-19, practitioners use RT-PCR tests that suffer from many False Positive (FP) and False Negative (FN) results while they take a long time. One solution to this is the conduction of a greater number of tests simultaneously to improve the True Positive (TP) ratio. However, CT-scan and X-ray images can also be used for early detection of Covid-19 related pneumonia. By the use of modern deep learning techniques, accuracy of more than 95% can be achieved. We used eight CNN (CovNet)-based deep learning models, namely ResNet 152 v2, InceptionResNet v2, Xception, Inception v3, ResNet 50, NASNetLarge, DenseNet 201, and VGG 16 for both X-rays and CT-scans to diagnose pneumonia. The achieved comparative results show that the proposed models are able to differentiate the Covid-19 positive cases.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88404073","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}
This paper presents a new feature extraction technique for face recognition. The new model, called multi-descriptor, is based on the well-known method of local binary patterns. It involves many different neighborhoods of the central pixel. Its unique advantage is that this descriptor allows the use of different neighborhood sizes instead of only one point. This structure ensures reasonable effectiveness and also provides the possibility to obtain a different distribution of features. Based on the new descriptor, a face recognition model using the pairwise feature descriptor based on the proposed descriptor was developed in this work, and local binary patterns were created to investigate the similarity and dissimilarity between the two models. For both models, the training was done using the support vector machine method on different face databases to overcome face recognition problems such as camera distance, expression, large head size, and illumination variations. The proposed technique achieved perfect accuracy on almost all tested databases including the Extended Yale B and Grimace database.
{"title":"A Novel Feature Extraction Descriptor for Face Recognition","authors":"A. Salamh, H. Akyüz","doi":"10.48084/etasr.4624","DOIUrl":"https://doi.org/10.48084/etasr.4624","url":null,"abstract":"This paper presents a new feature extraction technique for face recognition. The new model, called multi-descriptor, is based on the well-known method of local binary patterns. It involves many different neighborhoods of the central pixel. Its unique advantage is that this descriptor allows the use of different neighborhood sizes instead of only one point. This structure ensures reasonable effectiveness and also provides the possibility to obtain a different distribution of features. Based on the new descriptor, a face recognition model using the pairwise feature descriptor based on the proposed descriptor was developed in this work, and local binary patterns were created to investigate the similarity and dissimilarity between the two models. For both models, the training was done using the support vector machine method on different face databases to overcome face recognition problems such as camera distance, expression, large head size, and illumination variations. The proposed technique achieved perfect accuracy on almost all tested databases including the Extended Yale B and Grimace database.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86495832","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}
This paper describes Agri-Snaps, an Internet of Things (IoT) agriculture monitoring system designed to improve farmers’ acceptance of using IoT technology in their farm field. Agri-Snaps consists of four dedicated sensor circuit modules that integrate magnetic pogo pin connectors for easier assembly with the controller circuit module. This work investigated how such a design can enable the farmers to understand how 1) to assemble, 2) self-troubleshoot, and 3) maintain the monitoring system independently without requiring expertise on the farm site. User-experience testing was conducted with ten participants to validate Agri-Snaps’s viability. The results showed that those participants positively rated Agri-Snaps as attractive, easy to understand and assemble, exciting, and innovative compared to the typical agriculture monitoring systems.
{"title":"Designing an IoT Agriculture Monitoring System for Improving Farmer’s Acceptance of Using IoT Technology","authors":"S. A. Anas, R. S. S. Singh, N. Kamarudin","doi":"10.48084/etasr.4667","DOIUrl":"https://doi.org/10.48084/etasr.4667","url":null,"abstract":"This paper describes Agri-Snaps, an Internet of Things (IoT) agriculture monitoring system designed to improve farmers’ acceptance of using IoT technology in their farm field. Agri-Snaps consists of four dedicated sensor circuit modules that integrate magnetic pogo pin connectors for easier assembly with the controller circuit module. This work investigated how such a design can enable the farmers to understand how 1) to assemble, 2) self-troubleshoot, and 3) maintain the monitoring system independently without requiring expertise on the farm site. User-experience testing was conducted with ten participants to validate Agri-Snaps’s viability. The results showed that those participants positively rated Agri-Snaps as attractive, easy to understand and assemble, exciting, and innovative compared to the typical agriculture monitoring systems.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88495594","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}
This paper analyzes the electromagnetic and thermal design of interior permanent magnet motors using filled slots and hairpin windings for electric vehicle applications. Two models of ∇ shape of the interior permanent magnet motors have been proposed to evaluate the temperature distribution and cogging torque performance. A narrow opening slot of the interior permanent magnet of 48 slots/8 poles with the filled winding has been designed to investigate the electromagnetic torque because the cogging torque depends on opening stator slots. A parallel–rectangle slot of the interior permanent magnet with the hairpin winding has been also implemented with finite element analysis to evaluate their performances. Normally, the slot opening of the interior permanent magnet stator equals the slot width, it is greater than the size of hairpin windings, and the cogging torque is increased significantly with a bigger slot opening. The main advantage of the hairpin winding design is the high slot fill factors. Hence, the lower the current density, the higher torque, and efficiency are, than the normal design with the same geometry parameters. To improve the cogging torque due to the wide slot opening, the step–skew rotor slices have been arranged to minimize the torque ripple with different skewing angles.
{"title":"Electromagnetic and Thermal Analysis of Interior Permanent Magnet Motors Using Filled Slots and Hairpin Windings","authors":"D. B. Minh, N. H. Phuong, V. D. Quoc, H. B. Duc","doi":"10.48084/etasr.4683","DOIUrl":"https://doi.org/10.48084/etasr.4683","url":null,"abstract":"This paper analyzes the electromagnetic and thermal design of interior permanent magnet motors using filled slots and hairpin windings for electric vehicle applications. Two models of ∇ shape of the interior permanent magnet motors have been proposed to evaluate the temperature distribution and cogging torque performance. A narrow opening slot of the interior permanent magnet of 48 slots/8 poles with the filled winding has been designed to investigate the electromagnetic torque because the cogging torque depends on opening stator slots. A parallel–rectangle slot of the interior permanent magnet with the hairpin winding has been also implemented with finite element analysis to evaluate their performances. Normally, the slot opening of the interior permanent magnet stator equals the slot width, it is greater than the size of hairpin windings, and the cogging torque is increased significantly with a bigger slot opening. The main advantage of the hairpin winding design is the high slot fill factors. Hence, the lower the current density, the higher torque, and efficiency are, than the normal design with the same geometry parameters. To improve the cogging torque due to the wide slot opening, the step–skew rotor slices have been arranged to minimize the torque ripple with different skewing angles.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77996595","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}
The smart grid is a new concept that has been developed during recent years to improve the intelligence and efficiency of electric power system management. Traditional electricity systems are combined and integrated with information technology, communication technology, and intelligent control technology in the smart grid. Demand Response (DR) refers to the changes in consumers' electricity consumption behavior in response to dynamic pricing or financial incentives. Based on the control manner, DR methods are classified as centralized or distributed. In distributed techniques, customers communicate with the other consumers and provide data to the power utility about the overall use. In this paper, we focus on the distributed approach of DR using the shifting method for a short-term horizon. To be more specific, three well-known solutions were studied: the Resource Allocation with Legitimate Claims, the Constrained Fair-Splitting Dispatch, and Real-Time Pricing. Finally, we compare the different techniques of DR distributed approaches based on the control mechanism.
{"title":"A Distributed Control Approach for Demand Response in Smart Grids","authors":"A. El Gharbi","doi":"10.48084/etasr.4634","DOIUrl":"https://doi.org/10.48084/etasr.4634","url":null,"abstract":"The smart grid is a new concept that has been developed during recent years to improve the intelligence and efficiency of electric power system management. Traditional electricity systems are combined and integrated with information technology, communication technology, and intelligent control technology in the smart grid. Demand Response (DR) refers to the changes in consumers' electricity consumption behavior in response to dynamic pricing or financial incentives. Based on the control manner, DR methods are classified as centralized or distributed. In distributed techniques, customers communicate with the other consumers and provide data to the power utility about the overall use. In this paper, we focus on the distributed approach of DR using the shifting method for a short-term horizon. To be more specific, three well-known solutions were studied: the Resource Allocation with Legitimate Claims, the Constrained Fair-Splitting Dispatch, and Real-Time Pricing. Finally, we compare the different techniques of DR distributed approaches based on the control mechanism.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83040472","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}
F. Rafi, G. H. Dars, C. Strong, K. Ansari, S. H. Ali
Extreme precipitation events are among the most severe weather hazards. Knowledge about the spatial patterns underlying such events in the Upper Indus Basin is limited because estimating precipitation is very challenging due to the data scarcity and the complex orography. Numerical weather prediction models can be applied at a fine resolution to overcome this issue. The Advanced Research Weather Research and Forecasting (WRF) model version 3.8.1 was applied over the Kabul River Basin to simulate the temperature and precipitation of monsoon season 2010, i.e., 1st May to 16th September 2010. We considered the May month as a spin-up period. The initial and boundary conditions were derived from the National Oceanic and Atmospheric Administration, Climate Forecast System Reanalysis data. The model was set up by using two-nested domains with increasing horizontal resolution moving inward from 15km on domain d01 to 5km on domain d02. The simulations were compared with TRMM 3B42, and station data collected from the Pakistan Meteorological Department and Water and the Power Development Authority using bias, percentage bias, root mean square error, and Pearson correlation. The results revealed that the simulated precipitation was improved from d01 to d02. However, the model showed mixed results with overestimation of precipitation at some stations and underestimations at others. Simulated precipitation generally agreed better with TRMM than with station data. Overall, the results indicate that the WRF model can be used to simulate heavy precipitation in complex terrain.
{"title":"An Evaluation of the Extreme Rainfall Event of 2010 over the Kabul River Basin using the WRF Model","authors":"F. Rafi, G. H. Dars, C. Strong, K. Ansari, S. H. Ali","doi":"10.48084/etasr.4587","DOIUrl":"https://doi.org/10.48084/etasr.4587","url":null,"abstract":"Extreme precipitation events are among the most severe weather hazards. Knowledge about the spatial patterns underlying such events in the Upper Indus Basin is limited because estimating precipitation is very challenging due to the data scarcity and the complex orography. Numerical weather prediction models can be applied at a fine resolution to overcome this issue. The Advanced Research Weather Research and Forecasting (WRF) model version 3.8.1 was applied over the Kabul River Basin to simulate the temperature and precipitation of monsoon season 2010, i.e., 1st May to 16th September 2010. We considered the May month as a spin-up period. The initial and boundary conditions were derived from the National Oceanic and Atmospheric Administration, Climate Forecast System Reanalysis data. The model was set up by using two-nested domains with increasing horizontal resolution moving inward from 15km on domain d01 to 5km on domain d02. The simulations were compared with TRMM 3B42, and station data collected from the Pakistan Meteorological Department and Water and the Power Development Authority using bias, percentage bias, root mean square error, and Pearson correlation. The results revealed that the simulated precipitation was improved from d01 to d02. However, the model showed mixed results with overestimation of precipitation at some stations and underestimations at others. Simulated precipitation generally agreed better with TRMM than with station data. Overall, the results indicate that the WRF model can be used to simulate heavy precipitation in complex terrain.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86041826","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}
A. Bashir, Ritwick Chaudhry, A. Qureshi, U. Memon, N. Bheel
This study presents the seepage patterns of earth-fill dams, using critical situations by employing the finite element approach. The Nai Gaj dam is 65km northwest of Dadu city in Sindh Province, Pakistan. In this study, the seepage through the main dam body and foundation is computed and simulated for different scenarios, i.e. maximum, normal, and minimum reservoir level. Seepage analysis was conducted by using the SEEP/W sub-program of GEO-SLOPE software. Dam design parameters and dam geometry data were used as input data to compute the unknown seepage. The seepage behavior of the Nai Gaj dam is shown in terms of net flow which consists of equipotential lines, streamlines, velocity vectors, and phreatic lines. The results show the seepage flux, maximum seepage, and exit gradient at different reservoir levels. The results show that the average flow rate at normal, maximum, and minimum reservoir levels are 1.49×10-7cumec/m, 3.38×10-7cumec/m, and 2.108×10-8cumec/m respectively. In addition, the overall stability of the side slope of the dam is discussed.
{"title":"Understanding the Seepage Behavior of Nai Gaj Dam through Numerical Analysis","authors":"A. Bashir, Ritwick Chaudhry, A. Qureshi, U. Memon, N. Bheel","doi":"10.48084/etasr.4560","DOIUrl":"https://doi.org/10.48084/etasr.4560","url":null,"abstract":"This study presents the seepage patterns of earth-fill dams, using critical situations by employing the finite element approach. The Nai Gaj dam is 65km northwest of Dadu city in Sindh Province, Pakistan. In this study, the seepage through the main dam body and foundation is computed and simulated for different scenarios, i.e. maximum, normal, and minimum reservoir level. Seepage analysis was conducted by using the SEEP/W sub-program of GEO-SLOPE software. Dam design parameters and dam geometry data were used as input data to compute the unknown seepage. The seepage behavior of the Nai Gaj dam is shown in terms of net flow which consists of equipotential lines, streamlines, velocity vectors, and phreatic lines. The results show the seepage flux, maximum seepage, and exit gradient at different reservoir levels. The results show that the average flow rate at normal, maximum, and minimum reservoir levels are 1.49×10-7cumec/m, 3.38×10-7cumec/m, and 2.108×10-8cumec/m respectively. In addition, the overall stability of the side slope of the dam is discussed.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84620036","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}
Urban building lands are considered a scarce resource, which forces us to rationalize their use and assignment. They play an important role in shaping the urban space with all its components and determine its characteristics. The impact on urban space depends on the legal nature of the land, the density of buildings, and the quality of social cohesion. Like all Algerian cities, the city of M'sila has experienced, since the '90s, an increasing demand for building plots, especially in the outskirts which are mostly private properties. This situation directly contributed to the spread of illegal constructions and as a result, districts lack basic living conditions. This phenomenon appeared in the peripheral district called La Rocade. In this paper, we will attempt to identify the impact of the legal nature of land properties, particularly private ones, on the proliferation of illegal constructions in the outskirts of the city of M'sila. We will try to find solutions and alternatives to limit or stop its spread and propose urban interventions to restructure this district and integrate it into the existing urban space.
{"title":"Illegal Construction Imposed by the Private Lands in Peripheral Urban Areas of M’sila, Algeria","authors":"E. Benkhaled, M. Mili, F. Oudina","doi":"10.48084/etasr.4703","DOIUrl":"https://doi.org/10.48084/etasr.4703","url":null,"abstract":"Urban building lands are considered a scarce resource, which forces us to rationalize their use and assignment. They play an important role in shaping the urban space with all its components and determine its characteristics. The impact on urban space depends on the legal nature of the land, the density of buildings, and the quality of social cohesion. Like all Algerian cities, the city of M'sila has experienced, since the '90s, an increasing demand for building plots, especially in the outskirts which are mostly private properties. This situation directly contributed to the spread of illegal constructions and as a result, districts lack basic living conditions. This phenomenon appeared in the peripheral district called La Rocade. In this paper, we will attempt to identify the impact of the legal nature of land properties, particularly private ones, on the proliferation of illegal constructions in the outskirts of the city of M'sila. We will try to find solutions and alternatives to limit or stop its spread and propose urban interventions to restructure this district and integrate it into the existing urban space.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81675203","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}
The excessive permanent deformation (rutting) in asphalt-concrete pavements resulting from frequent repetitions of heavy axle loads is studied in this paper. Rutting gradually develops with additional load applications and appears as longitudinal depressions in the wheel path. There are many causes of the rutting of asphalt roads, such as poor asphalt mixing and poor continuous aggregate gradation. All factors affecting the mixture resistance to permanent deformation must be discussed, and all must be properly considered to reduce the rutting propensity of asphalt-aggregate mixtures. In this study, several mixtures were produced with the most common techniques in rutting resistance (using the most effective additives for each mixture), and their performance was compared with the (conventional) mixture currently used in Iraq. The tests focused on the asphalt-concrete mixture for wearing courses. Different mixtures types were tried, namely, dense hot asphalt mixture (HMA) with two different asphalt contents (4.7% and 5.3%), Open-Grade Friction Course (OGFC) mixture, Stone Mastic Asphalt (SMA) mixture, and Beton Bitumineux a Module Eleve (BBME). The modifiers included natural Sisal Fibers (SFs), Carbon Fibers (CFs), and mineral filler (hydrated lime, HL). Marshall test was carried out to find stability and flow values. Rutting was evaluated by the repeated load test for cylindrical specimens under two temperatures (40°C and 60°C) to obtain the permanent deformation parameters. The parameters were used as input to the VESYS 5W software to evaluate the rut depth during different times of design life under 7×10^6 Equivalent Single Axle Loads (ESALs). The results of the selected mixtures were compared with the mixture designed in the laboratory dense gradation mix Job-Mix Formula (JMF)) within the limits of the Iraqi specification (SCRB,2003). Manipulation of the aggregate gradation that is customary in the implementation of the local mixture showed that the best performance regarding rutting resistance was exhibited by JMF, which decreased the rut depth at 40°C and 60°C by 21.63mm and 44.304mm respectively, in comparison with the conventional mixture. Changing the aggregate gradation of the local mixture gives better performance in rutting resistance without additives or changing the percentage of asphalt, at the same cost.
{"title":"The Possibility of Minimizing Rutting Distress in Asphalt Concrete Wearing Course","authors":"Hanady M. Abd Al Kareem, A. Albayati","doi":"10.48084/etasr.4669","DOIUrl":"https://doi.org/10.48084/etasr.4669","url":null,"abstract":"The excessive permanent deformation (rutting) in asphalt-concrete pavements resulting from frequent repetitions of heavy axle loads is studied in this paper. Rutting gradually develops with additional load applications and appears as longitudinal depressions in the wheel path. There are many causes of the rutting of asphalt roads, such as poor asphalt mixing and poor continuous aggregate gradation. All factors affecting the mixture resistance to permanent deformation must be discussed, and all must be properly considered to reduce the rutting propensity of asphalt-aggregate mixtures. In this study, several mixtures were produced with the most common techniques in rutting resistance (using the most effective additives for each mixture), and their performance was compared with the (conventional) mixture currently used in Iraq. The tests focused on the asphalt-concrete mixture for wearing courses. Different mixtures types were tried, namely, dense hot asphalt mixture (HMA) with two different asphalt contents (4.7% and 5.3%), Open-Grade Friction Course (OGFC) mixture, Stone Mastic Asphalt (SMA) mixture, and Beton Bitumineux a Module Eleve (BBME). The modifiers included natural Sisal Fibers (SFs), Carbon Fibers (CFs), and mineral filler (hydrated lime, HL). Marshall test was carried out to find stability and flow values. Rutting was evaluated by the repeated load test for cylindrical specimens under two temperatures (40°C and 60°C) to obtain the permanent deformation parameters. The parameters were used as input to the VESYS 5W software to evaluate the rut depth during different times of design life under 7×10^6 Equivalent Single Axle Loads (ESALs). The results of the selected mixtures were compared with the mixture designed in the laboratory dense gradation mix Job-Mix Formula (JMF)) within the limits of the Iraqi specification (SCRB,2003). Manipulation of the aggregate gradation that is customary in the implementation of the local mixture showed that the best performance regarding rutting resistance was exhibited by JMF, which decreased the rut depth at 40°C and 60°C by 21.63mm and 44.304mm respectively, in comparison with the conventional mixture. Changing the aggregate gradation of the local mixture gives better performance in rutting resistance without additives or changing the percentage of asphalt, at the same cost.","PeriodicalId":11826,"journal":{"name":"Engineering, Technology & Applied Science Research","volume":null,"pages":null},"PeriodicalIF":1.5,"publicationDate":"2022-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84123088","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}
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