A. Saiyathibrahim, V. Jatti, P. Dhanapal, D. Mohan
Aluminium matrix composites (AMCs) exhibit promising mechanical properties that are required for the aeronautical and automotive industries. In the current research, A413 (eutectic AlSi) alloy is employed as matrix material, and nickel based trialuminide (Al3Ni) with primary Si particles as reinforcements to manufacture aluminium matrix composites through the stir casting process. A total of three varieties of composite alloys containing 3, 6, and 9 wt% of nickel were used to fabricate stir cast composites, and their microstructural features, along with mechanical properties, such as tensile strength, impact strength, and hardness, were evaluated. Furthermore, the dry sliding wear behavior for three different applied loads (10, 20, and 30 N) was studied. Scanning electron microscopy (SEM) revealed nucleation of Al3Ni nickel trialuminide and increase of primary Si phases as well as exhibited even dissemination of such reinforcements in α‐Al. The composite with the highest nickel content (9 wt%) had a microstructure that consisted of 31 vol% in‐situ Al3Ni intermetallic and 8.1 vol% primary Si particles. This composite demonstrated a maximum increase of 25.93% in hardness and 40.30% in tensile strength. The quality index values of composites with in‐situ reinforcements were higher compared to that of A413 alloy, which had the lowest quality index value of 248.83 MPa, representing a 9.91% decrease. The impact strength of the composite was found to be reduced by a maximum of 50% and showed a significant loss in ductility also when compared with A413 aluminium alloy. Wear resistance was found to be increased with the evolution of in‐situ reinforcements inside the matrix, whereas an increase in applied load resulted in a higher wear rate. The uniform dispersion and good interfacial bonding between the aluminium matrix and in‐situ reinforcements (nickel trialuminide and primary Si) are showing preeminent mechanical properties and can be a novel composite material for industrial applications.
{"title":"Development and characterization of in‐situ nickel aluminide reinforced Al‐Si matrix composites by stir casting","authors":"A. Saiyathibrahim, V. Jatti, P. Dhanapal, D. Mohan","doi":"10.1002/eng2.12966","DOIUrl":"https://doi.org/10.1002/eng2.12966","url":null,"abstract":"Aluminium matrix composites (AMCs) exhibit promising mechanical properties that are required for the aeronautical and automotive industries. In the current research, A413 (eutectic AlSi) alloy is employed as matrix material, and nickel based trialuminide (Al3Ni) with primary Si particles as reinforcements to manufacture aluminium matrix composites through the stir casting process. A total of three varieties of composite alloys containing 3, 6, and 9 wt% of nickel were used to fabricate stir cast composites, and their microstructural features, along with mechanical properties, such as tensile strength, impact strength, and hardness, were evaluated. Furthermore, the dry sliding wear behavior for three different applied loads (10, 20, and 30 N) was studied. Scanning electron microscopy (SEM) revealed nucleation of Al3Ni nickel trialuminide and increase of primary Si phases as well as exhibited even dissemination of such reinforcements in α‐Al. The composite with the highest nickel content (9 wt%) had a microstructure that consisted of 31 vol% in‐situ Al3Ni intermetallic and 8.1 vol% primary Si particles. This composite demonstrated a maximum increase of 25.93% in hardness and 40.30% in tensile strength. The quality index values of composites with in‐situ reinforcements were higher compared to that of A413 alloy, which had the lowest quality index value of 248.83 MPa, representing a 9.91% decrease. The impact strength of the composite was found to be reduced by a maximum of 50% and showed a significant loss in ductility also when compared with A413 aluminium alloy. Wear resistance was found to be increased with the evolution of in‐situ reinforcements inside the matrix, whereas an increase in applied load resulted in a higher wear rate. The uniform dispersion and good interfacial bonding between the aluminium matrix and in‐situ reinforcements (nickel trialuminide and primary Si) are showing preeminent mechanical properties and can be a novel composite material for industrial applications.","PeriodicalId":11735,"journal":{"name":"Engineering Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141803090","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}
Accurate cross‐language aspect‐level sentiment analysis methods can provide accurate decision support for social networks, e‐commerce platforms, and other platforms, thereby providing users with higher quality services. However, actual data is very complex and contains a large amount of redundant information. Existing methods face challenges in extracting semantic association information and deep emotional features when dealing with this complex data. To address these issues, an aspect‐level sentiment analysis model (called Multi‐XLNet‐RCNN) is proposed that integrates multi‐channel XLNet and RCNN. First, a multi‐channel XLNet (Multi XLNet) network model is used to perform autoregressive encoding operations on different languages, fully extracting contextual information from the text and better characterizing the ambiguity of the text. Then, in the RCNN module, the contextual features output by the BiGRU layer are concatenated with the pre trained input features to extract deeper emotional features. Finally, in response to the issue of inconsistent aspect‐level information in sentence features extracted from different language channels, a multi head attention mechanism based on aspect class interaction is utilized to obtain a text attention emotion representation for a given aspect, thereby improving the accuracy of aspect‐level emotion classification. The experiment uses the public English corpus provided by SemEval 2016 as the source language, and Chinese comment data on Dianping and JD E‐commerce platforms as the target language. The experimental results show that the proposed Multi XLNet‐RCNN sentiment analysis method can achieve accurate aspect‐level Sentiment analysis, and the accuracy rates on the two data sets of Dianping and Jingdong E‐commerce can be as high as 0.851 and 0.792, respectively, superior to other advanced comparison models. This model has good application value in cross‐language analysis of social networks and e‐commerce platforms.
{"title":"An AI based cross‐language aspect‐level sentiment analysis model using English corpus","authors":"Jing Chen, Li Pan","doi":"10.1002/eng2.12969","DOIUrl":"https://doi.org/10.1002/eng2.12969","url":null,"abstract":"Accurate cross‐language aspect‐level sentiment analysis methods can provide accurate decision support for social networks, e‐commerce platforms, and other platforms, thereby providing users with higher quality services. However, actual data is very complex and contains a large amount of redundant information. Existing methods face challenges in extracting semantic association information and deep emotional features when dealing with this complex data. To address these issues, an aspect‐level sentiment analysis model (called Multi‐XLNet‐RCNN) is proposed that integrates multi‐channel XLNet and RCNN. First, a multi‐channel XLNet (Multi XLNet) network model is used to perform autoregressive encoding operations on different languages, fully extracting contextual information from the text and better characterizing the ambiguity of the text. Then, in the RCNN module, the contextual features output by the BiGRU layer are concatenated with the pre trained input features to extract deeper emotional features. Finally, in response to the issue of inconsistent aspect‐level information in sentence features extracted from different language channels, a multi head attention mechanism based on aspect class interaction is utilized to obtain a text attention emotion representation for a given aspect, thereby improving the accuracy of aspect‐level emotion classification. The experiment uses the public English corpus provided by SemEval 2016 as the source language, and Chinese comment data on Dianping and JD E‐commerce platforms as the target language. The experimental results show that the proposed Multi XLNet‐RCNN sentiment analysis method can achieve accurate aspect‐level Sentiment analysis, and the accuracy rates on the two data sets of Dianping and Jingdong E‐commerce can be as high as 0.851 and 0.792, respectively, superior to other advanced comparison models. This model has good application value in cross‐language analysis of social networks and e‐commerce platforms.","PeriodicalId":11735,"journal":{"name":"Engineering Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141802443","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 investigates the effect of Leca‐filled barriers, both single and double‐walled trenches, on mitigating ground vibrations due to harmonic loads. A three‐dimensional finite element program, validated in comparison by aforementioned studies, was used alongside automated models created via Plaxis and Python integration. This approach facilitated the evaluation of trench effectiveness in both active and passive design scenarios. Our findings suggest that optimal trench dimensions for effective vibration reduction in active designs are a depth and width of approximately 1λr and 0.2λr, respectively. In passive designs, while trench depth becomes less significant, width plays a crucial role in both single and double‐wall systems. Additionally, a support vector machine algorithm was developed to forecast the performance of single‐wall trenches, showing a high correlation with numerical model outcomes. This underscores the algorithm's utility in predicting trench efficiency, highlighting the practical application of machine learning in geotechnical engineering.
{"title":"Evaluating ground vibration attenuation through leca‐filled trenches: A support vector machine approach","authors":"Mohsen Naghizadeh Rokni, Omid Tavasoli, Reza Esmaeilabadi, Amirpouya Saraf","doi":"10.1002/eng2.12960","DOIUrl":"https://doi.org/10.1002/eng2.12960","url":null,"abstract":"This paper investigates the effect of Leca‐filled barriers, both single and double‐walled trenches, on mitigating ground vibrations due to harmonic loads. A three‐dimensional finite element program, validated in comparison by aforementioned studies, was used alongside automated models created via Plaxis and Python integration. This approach facilitated the evaluation of trench effectiveness in both active and passive design scenarios. Our findings suggest that optimal trench dimensions for effective vibration reduction in active designs are a depth and width of approximately 1λr and 0.2λr, respectively. In passive designs, while trench depth becomes less significant, width plays a crucial role in both single and double‐wall systems. Additionally, a support vector machine algorithm was developed to forecast the performance of single‐wall trenches, showing a high correlation with numerical model outcomes. This underscores the algorithm's utility in predicting trench efficiency, highlighting the practical application of machine learning in geotechnical engineering.","PeriodicalId":11735,"journal":{"name":"Engineering Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141803564","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}
S. Koley, Parothidil Anjusree Krishnan, Amya Ranjan Ray, Artem Krasovsky
The purpose of this study is to analyze the hydrodynamic performance and efficiency of a dual‐chamber oscillating water column (OWC) device. For the Joint North Sea Wave Project (JONSWAP) incident waves spectrum, a two dimensional numerical wave tank is employed with nonlinear Reynolds averaged Navier–Stokes equations model along with the standard turbulence model. The free surface elevation is measured using the volume of fluid method. The numerical simulation demonstrates the streamline and velocity vector profiles throughout an entire pressure fluctuation cycle inside the chambers of the given OWC device. Further, investigation is carried out to analyze the impact of pressure drop and air flow rate through the orifice of the dual‐chamber OWC device on the power generation. Moreover, the power spectral density analysis of the free surface elevation is provided to know the variation of the parameters in the frequency domain. These results demonstrate that the effectiveness of the dual‐chamber OWC device is more near the significant wave height m.
本研究旨在分析双腔振荡水柱（OWC）装置的水动力性能和效率。针对联合北海波浪项目（JONSWAP）的入射波谱，采用了一个二维数值波浪槽，其中包含非线性雷诺平均纳维-斯托克斯方程模型和标准湍流模型。采用流体体积法测量了自由表面高程。数值模拟展示了给定 OWC 设备腔室内整个压力波动周期的流线和速度矢量剖面。此外，研究还分析了通过双腔 OWC 设备孔口的压降和空气流速对发电量的影响。此外，还提供了自由表面升高的功率谱密度分析，以了解参数在频域中的变化。这些结果表明，在显著波高 m 附近，双腔 OWC 装置的效果更好。
{"title":"Performance of dual‐chamber oscillating water column device under irregular incident waves using Reynolds averaged Navier–Stokes model","authors":"S. Koley, Parothidil Anjusree Krishnan, Amya Ranjan Ray, Artem Krasovsky","doi":"10.1002/eng2.12970","DOIUrl":"https://doi.org/10.1002/eng2.12970","url":null,"abstract":"The purpose of this study is to analyze the hydrodynamic performance and efficiency of a dual‐chamber oscillating water column (OWC) device. For the Joint North Sea Wave Project (JONSWAP) incident waves spectrum, a two dimensional numerical wave tank is employed with nonlinear Reynolds averaged Navier–Stokes equations model along with the standard turbulence model. The free surface elevation is measured using the volume of fluid method. The numerical simulation demonstrates the streamline and velocity vector profiles throughout an entire pressure fluctuation cycle inside the chambers of the given OWC device. Further, investigation is carried out to analyze the impact of pressure drop and air flow rate through the orifice of the dual‐chamber OWC device on the power generation. Moreover, the power spectral density analysis of the free surface elevation is provided to know the variation of the parameters in the frequency domain. These results demonstrate that the effectiveness of the dual‐chamber OWC device is more near the significant wave height m.","PeriodicalId":11735,"journal":{"name":"Engineering Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141816825","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}
Santanu Kumar Dash, S. Koley, Subhendu Paul, Rajdip Dey, Maheswaran S
In this present work, the performance of a two‐layered thick porous breakwater of trapezoidal structure is investigated under the action of irregular waves. To investigate the physical problem, the classical linear water wave theory has been taken into consideration. To analyze the effect of irregular waves on the multilayered structure, two unidirectional wave spectra, namely the Pierson–Moskowitz and JONSWAP spectra based on the frequency domains are considered. Three different sea states are taken to analyze the impact of irregular waves on the multilayered porous breakwater. The constant boundary element method is used to handle the aforementioned boundary value problem, which is considered one of the most efficient numerical tools for handling complex structured open sea problems. Several wave characteristics associated with the spectral density functions are demonstrated and analyzed for a variety of structural and spectral parameters. The findings suggest that the adoption of suitable porous material for the construction of these breakwaters can significantly enhance the energy dissipation and thereby minimize the wave force on the structure.
{"title":"Performance of multilayered porous breakwater under irregular waves having different wave spectrum","authors":"Santanu Kumar Dash, S. Koley, Subhendu Paul, Rajdip Dey, Maheswaran S","doi":"10.1002/eng2.12964","DOIUrl":"https://doi.org/10.1002/eng2.12964","url":null,"abstract":"In this present work, the performance of a two‐layered thick porous breakwater of trapezoidal structure is investigated under the action of irregular waves. To investigate the physical problem, the classical linear water wave theory has been taken into consideration. To analyze the effect of irregular waves on the multilayered structure, two unidirectional wave spectra, namely the Pierson–Moskowitz and JONSWAP spectra based on the frequency domains are considered. Three different sea states are taken to analyze the impact of irregular waves on the multilayered porous breakwater. The constant boundary element method is used to handle the aforementioned boundary value problem, which is considered one of the most efficient numerical tools for handling complex structured open sea problems. Several wave characteristics associated with the spectral density functions are demonstrated and analyzed for a variety of structural and spectral parameters. The findings suggest that the adoption of suitable porous material for the construction of these breakwaters can significantly enhance the energy dissipation and thereby minimize the wave force on the structure.","PeriodicalId":11735,"journal":{"name":"Engineering Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141827259","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 article examines the fire safety of rubber flooring used in an ice sports center in China. The fire characteristics and parameters of the rubber floor were determined through material fire tests. Subsequently, a fire safety analysis was conducted using the fire intrinsic safety method. Additionally, numerical simulation was employed to investigate fire and evacuation scenarios, particularly when the safety grade of the floor decoration materials falls below standard requirements. The results indicate that, under specific safety conditions, the ice sports center can utilize B1 grade rubber flooring in the required area while ensuring compliance with fire safety standards.
{"title":"Fire safety research of rubber floor covering in a China ice sports center","authors":"Tianchen Nan, Huayun Zhang, Dongli Wu","doi":"10.1002/eng2.12908","DOIUrl":"https://doi.org/10.1002/eng2.12908","url":null,"abstract":"This article examines the fire safety of rubber flooring used in an ice sports center in China. The fire characteristics and parameters of the rubber floor were determined through material fire tests. Subsequently, a fire safety analysis was conducted using the fire intrinsic safety method. Additionally, numerical simulation was employed to investigate fire and evacuation scenarios, particularly when the safety grade of the floor decoration materials falls below standard requirements. The results indicate that, under specific safety conditions, the ice sports center can utilize B1 grade rubber flooring in the required area while ensuring compliance with fire safety standards.","PeriodicalId":11735,"journal":{"name":"Engineering Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141109987","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}
Ali Esmaeilpour, Shaghayegh Shahiri Tabarestani, Alireza Niazi
Epilepsy is a brain disorder that causes patients to have multiple seizures. About 30% of patients with epilepsy are not treated with medication or surgery. The abnormal activity of brain before occurring of a seizure (about a few minutes before a seizure occurs) are known as the preictal area. Therefore, if we can predict this state, we can control possible seizures by using appropriate medications. In this study, we present a method for predicting epileptic seizures using electroencephalogram (EEG) signals. The method can identify the preictal region that occurs before the onset of seizures. In our proposed method, first the noise removal of EEG signals is performed, and then the necessary features are extracted using a convolution neural network. Finally, we use the feature vectors in order to train multiple classifiers, fully connected layer, random forest, and support vector machines with linear kernel. Additionally, we apply maximum voting, which is an ensemble method, to classify preictal segments from interictal ones. In this study, using EEG signals of patients from CHB‐MIT dataset, we were able to achieve sensitivity of 90.76%.
{"title":"Deep learning‐based seizure prediction using EEG signals: A comparative analysis of classification methods on the CHB‐MIT dataset","authors":"Ali Esmaeilpour, Shaghayegh Shahiri Tabarestani, Alireza Niazi","doi":"10.1002/eng2.12918","DOIUrl":"https://doi.org/10.1002/eng2.12918","url":null,"abstract":"Epilepsy is a brain disorder that causes patients to have multiple seizures. About 30% of patients with epilepsy are not treated with medication or surgery. The abnormal activity of brain before occurring of a seizure (about a few minutes before a seizure occurs) are known as the preictal area. Therefore, if we can predict this state, we can control possible seizures by using appropriate medications. In this study, we present a method for predicting epileptic seizures using electroencephalogram (EEG) signals. The method can identify the preictal region that occurs before the onset of seizures. In our proposed method, first the noise removal of EEG signals is performed, and then the necessary features are extracted using a convolution neural network. Finally, we use the feature vectors in order to train multiple classifiers, fully connected layer, random forest, and support vector machines with linear kernel. Additionally, we apply maximum voting, which is an ensemble method, to classify preictal segments from interictal ones. In this study, using EEG signals of patients from CHB‐MIT dataset, we were able to achieve sensitivity of 90.76%.","PeriodicalId":11735,"journal":{"name":"Engineering Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141124536","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}
Abdulaziz I. Albannai, Henry León‐Henao, Antonio J. Ramirez
Wire arc additive manufacturing (WAAM) is an efficient technique for producing medium to large‐size components, due to its accessibility and sustainability in fabricating large‐scale parts with high deposition rates, employing low‐cost and simple equipment, and achieving high material efficiency. Consequently, WAAM has garnered attention across various industrial sectors and experienced significant growth, particularly over the last decade, as it addresses and mitigates challenges within production markets. One of the primary limitations of WAAM is its thermal history during the process, which directly influences grain formation and microstructure heterogeneity in the resulting part. Understanding the thermal cycle of the WAAM process is thus crucial for process improvement. Typically, fabricating a part using WAAM results in a microstructure with three distinct zones along the build direction: an upper zone (thin surface layer) with fine grains, a middle zone dominated by undesirably long and large columnar grains covering more than 90% of the produced part, and a lower zone with smaller to intermediate columnar grains closer to the substrate material. These zones arise from variations in cooling rates, with the middle zone exhibiting the lowest cooling rate due to 2D conduction heat transfer. Consequently, producing a component with a microstructure comprising three different zones, with a high fraction of large and long columnar grains, significantly impacts the final mechanical properties. Therefore, controlling the size and formation of these grain zones plays a key role in improving WAAM. The aim of this work is to investigate the formation of undesired columnar grains in austenitic stainless steel 316L during WAAM and propose a simple hybrid technique by combining WAAM with a hot forging process (with or without interlayer cooling time). This approach targets the disruption of the solidification pattern of columnar grain growth during deposition progression and aims to enhance the microstructure of WAAM components.
{"title":"Preventing columnar grains growth during hybrid wire arc additive manufacturing of austenitic stainless steel 316L","authors":"Abdulaziz I. Albannai, Henry León‐Henao, Antonio J. Ramirez","doi":"10.1002/eng2.12914","DOIUrl":"https://doi.org/10.1002/eng2.12914","url":null,"abstract":"Wire arc additive manufacturing (WAAM) is an efficient technique for producing medium to large‐size components, due to its accessibility and sustainability in fabricating large‐scale parts with high deposition rates, employing low‐cost and simple equipment, and achieving high material efficiency. Consequently, WAAM has garnered attention across various industrial sectors and experienced significant growth, particularly over the last decade, as it addresses and mitigates challenges within production markets. One of the primary limitations of WAAM is its thermal history during the process, which directly influences grain formation and microstructure heterogeneity in the resulting part. Understanding the thermal cycle of the WAAM process is thus crucial for process improvement. Typically, fabricating a part using WAAM results in a microstructure with three distinct zones along the build direction: an upper zone (thin surface layer) with fine grains, a middle zone dominated by undesirably long and large columnar grains covering more than 90% of the produced part, and a lower zone with smaller to intermediate columnar grains closer to the substrate material. These zones arise from variations in cooling rates, with the middle zone exhibiting the lowest cooling rate due to 2D conduction heat transfer. Consequently, producing a component with a microstructure comprising three different zones, with a high fraction of large and long columnar grains, significantly impacts the final mechanical properties. Therefore, controlling the size and formation of these grain zones plays a key role in improving WAAM. The aim of this work is to investigate the formation of undesired columnar grains in austenitic stainless steel 316L during WAAM and propose a simple hybrid technique by combining WAAM with a hot forging process (with or without interlayer cooling time). This approach targets the disruption of the solidification pattern of columnar grain growth during deposition progression and aims to enhance the microstructure of WAAM components.","PeriodicalId":11735,"journal":{"name":"Engineering Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140971631","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}
Globally, the encouragement of using renewable fuels like biodiesel for diesel engines is driven by concerns over the fossil fuel depletion and harmful emissions. Additionally, the utilization of renewable fuel additives like diethyl ether has the potential to enhance fuel properties and boost engine performance. The aim of this paper was to construct a computer simulation using Ricardo Wave program in order to predict the performance and nitrogen oxides (NOx) emission of a diesel engine fuelled by a diesel‐biodiesel blend and a diethyl ether (DEE) as a fuel additive. The computer model was validated by comparing the simulation engine performance and NOx emission results against the corresponding experimental data for diesel, diesel‐biodiesel blend with 30% biodiesel proportion (B30), and two blends of diesel‐biodiesel‐DEE with DEE proportions of 5% and 10% on a volume basis. Also, the effect of varying the inlet air pressure on engine performance and NOx emission was compared for all investigated fuels. It was numerically demonstrated that using the DEE with an optimum proportion of 5% enhanced engine performance as it decreased engine fuel consumption by 5.9% and increased engine thermal efficiency by 9.6% compared to diesel fuel at engine full load condition. Also, a significant reduction of 20.5% in NOx emission resulted from the addition of DEE. Increasing the inlet air pressure increased engine power and decreased engine fuel consumption for all investigated fuels. Increasing the inlet air pressure from 1 to 3 bar increased engine brake thermal efficiency by almost 20% for all tested fuels. However, NOx emission increased slightly within a range from 1.7% to 7% for the different investigated fuels.
{"title":"A numerical investigation on enhancing the performance of a diesel engine fuelled with diesel‐biodiesel blend using a diethyl ether as an additive","authors":"Abdulkarim Youssef, Amr Ibrahim","doi":"10.1002/eng2.12915","DOIUrl":"https://doi.org/10.1002/eng2.12915","url":null,"abstract":"Globally, the encouragement of using renewable fuels like biodiesel for diesel engines is driven by concerns over the fossil fuel depletion and harmful emissions. Additionally, the utilization of renewable fuel additives like diethyl ether has the potential to enhance fuel properties and boost engine performance. The aim of this paper was to construct a computer simulation using Ricardo Wave program in order to predict the performance and nitrogen oxides (NOx) emission of a diesel engine fuelled by a diesel‐biodiesel blend and a diethyl ether (DEE) as a fuel additive. The computer model was validated by comparing the simulation engine performance and NOx emission results against the corresponding experimental data for diesel, diesel‐biodiesel blend with 30% biodiesel proportion (B30), and two blends of diesel‐biodiesel‐DEE with DEE proportions of 5% and 10% on a volume basis. Also, the effect of varying the inlet air pressure on engine performance and NOx emission was compared for all investigated fuels. It was numerically demonstrated that using the DEE with an optimum proportion of 5% enhanced engine performance as it decreased engine fuel consumption by 5.9% and increased engine thermal efficiency by 9.6% compared to diesel fuel at engine full load condition. Also, a significant reduction of 20.5% in NOx emission resulted from the addition of DEE. Increasing the inlet air pressure increased engine power and decreased engine fuel consumption for all investigated fuels. Increasing the inlet air pressure from 1 to 3 bar increased engine brake thermal efficiency by almost 20% for all tested fuels. However, NOx emission increased slightly within a range from 1.7% to 7% for the different investigated fuels.","PeriodicalId":11735,"journal":{"name":"Engineering Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140976044","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 goal was to evaluate the hysteretic performance of buckling‐resistant braces with low yield point steel LYP160, the monotonic tensile and cyclic loading tests of LYP160 test specimens were conducted and the cyclic constitutive relationship was obtained. According to the load–displacement curves of the specimens, the low‐yield point steel was characterized by good ductility and energy absorption ability. With consideration of the Chaboche model for the materials, the cyclic hardening parameters of low‐yield point steel were obtained. On this basis, the hysteretic properties of buckling‐resistant braces under cyclic loads were simulated and analyzed. After the analysis and comparison of buckling‐resistant braces specimens with isotropic core plate and segmented variable section core plate, it can be found that: when the conventional buckling‐resistant braces with an isotropic core plate were loaded to L/100, the lateral deformation of the buckling‐resistant brace (BRB) would reach 17 mm. Additionally, serious squeezing could be observed on the lateral restraining members. The conventional BRB would become ineffective due to the accumulation of deformation at both ends of the BRB. When the segmented buckling‐resistant brace was applied, the core plate with variable section would buckle first in the middle area, other parts could continue to consume energy thanks to the action of the limit plate. It would avoid the situation that other areas would be unable to consume energy after the core plate yields at one area first. Under the action of cyclic loads, no stiffness degradation was noted in the segmented buckling‐resistant brace. Segmented buckling‐resistant braces demonstrated superior ductility and energy dissipation capacity.
{"title":"Hysteretic behavior of the segmented buckling‐resistant braces with LYP160","authors":"Shuai Xu, Yuanhong Hu, Yuchao Yin, Chengxin Guo","doi":"10.1002/eng2.12916","DOIUrl":"https://doi.org/10.1002/eng2.12916","url":null,"abstract":"The goal was to evaluate the hysteretic performance of buckling‐resistant braces with low yield point steel LYP160, the monotonic tensile and cyclic loading tests of LYP160 test specimens were conducted and the cyclic constitutive relationship was obtained. According to the load–displacement curves of the specimens, the low‐yield point steel was characterized by good ductility and energy absorption ability. With consideration of the Chaboche model for the materials, the cyclic hardening parameters of low‐yield point steel were obtained. On this basis, the hysteretic properties of buckling‐resistant braces under cyclic loads were simulated and analyzed. After the analysis and comparison of buckling‐resistant braces specimens with isotropic core plate and segmented variable section core plate, it can be found that: when the conventional buckling‐resistant braces with an isotropic core plate were loaded to L/100, the lateral deformation of the buckling‐resistant brace (BRB) would reach 17 mm. Additionally, serious squeezing could be observed on the lateral restraining members. The conventional BRB would become ineffective due to the accumulation of deformation at both ends of the BRB. When the segmented buckling‐resistant brace was applied, the core plate with variable section would buckle first in the middle area, other parts could continue to consume energy thanks to the action of the limit plate. It would avoid the situation that other areas would be unable to consume energy after the core plate yields at one area first. Under the action of cyclic loads, no stiffness degradation was noted in the segmented buckling‐resistant brace. Segmented buckling‐resistant braces demonstrated superior ductility and energy dissipation capacity.","PeriodicalId":11735,"journal":{"name":"Engineering Reports","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140980577","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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