Pub Date : 2024-06-03DOI: 10.1177/09544089241259665
Ilangovan Arun, Igor Velkavrh, Uma Rani R, Sivakumar Annamalai, Yuvaraj C
Electric discharge alloying presents an alternate coating process for improving mechanical properties through physical and metallurgical modification. Ti-6Al-4 V is a titanium alloy used in aerospace industry and biomechanical applications but has limitations in terms of wear resistance. Alloying with nickel could provide improvements in terms of wear and other tribological properties. Nickel as an alloying element provides pseudo-elastic behaviour (such as two-way shape memory effect) by changing α-Ti to β-Ti. After coating process, surface hardness of the samples increased up to 684 HV0.5 while in the cross-section, it ranged up to 580 HV0.5. Due to porosity, areas with hardness below the base material hardness value of 260 HV0.5 were measured as well. At the lowest load, coefficient of friction had a value of 1.1 while at higher loads it decreased down to 0.8 compared with alloyed layer with average values of 0.3 to 0.7. Wear resistance properties of titanium were improved as well. Specific wear rate under 40 N was 1.0 × 10−5 N/mm2 showing higher wear resistance with minimal ploughing.
{"title":"Electrical discharge shape memory alloying of Ti-6Al-4V: Mechanisms and mechanical properties","authors":"Ilangovan Arun, Igor Velkavrh, Uma Rani R, Sivakumar Annamalai, Yuvaraj C","doi":"10.1177/09544089241259665","DOIUrl":"https://doi.org/10.1177/09544089241259665","url":null,"abstract":"Electric discharge alloying presents an alternate coating process for improving mechanical properties through physical and metallurgical modification. Ti-6Al-4 V is a titanium alloy used in aerospace industry and biomechanical applications but has limitations in terms of wear resistance. Alloying with nickel could provide improvements in terms of wear and other tribological properties. Nickel as an alloying element provides pseudo-elastic behaviour (such as two-way shape memory effect) by changing α-Ti to β-Ti. After coating process, surface hardness of the samples increased up to 684 HV0.5 while in the cross-section, it ranged up to 580 HV0.5. Due to porosity, areas with hardness below the base material hardness value of 260 HV0.5 were measured as well. At the lowest load, coefficient of friction had a value of 1.1 while at higher loads it decreased down to 0.8 compared with alloyed layer with average values of 0.3 to 0.7. Wear resistance properties of titanium were improved as well. Specific wear rate under 40 N was 1.0 × 10−5 N/mm2 showing higher wear resistance with minimal ploughing.","PeriodicalId":20552,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141269604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-03DOI: 10.1177/09544089241258376
B. Balaji, V. B. Alur, Ajmeera Suresh, P. S. Ranjit
The scarcity and rising costs of fossil fuels, coupled with increasing pollution levels, have prompted the exploration of innovative biofuel blends. While binary and ternary fuels have been studied extensively in proportions of 5–20%, replacing up to 30–40% of fossil fuel dependency without significant engine modifications remains a challenge. One potential solution is to investigate an optimal quaternary blend (QB) through experimental methods. This study investigates the impact of increased injection pressure (IOP) and quaternary fuel blends on a common rail direct injection (CRDI) engine's performance and emissions. Different blends, including diesel fuel, vegetable oil, mahua methyl ester and normal-butanol, were tested to replace 30–40% of diesel and enhance combustion, reduce exhaust emissions and improve overall performance. Experiments used a 1-cylinder CRDI engine at high IOPs (400, 500, 600 and 700 bar). Results at 600 bar IOP showed that the optimal blend, QB3–QB4, increased brake thermal efficiency (BTE) by 9% and reduced brake-specific fuel consumption (BSFC) by approximately 11% compared to other blends. Emissions at 600 bar included a 16% reduction in hydrocarbons (HC) and a 24% decrease in carbon monoxide (CO) at full load. However, nitrogen oxide (NOx) emissions slightly increased with higher IOP. Significantly employing the QB3–QB4 blend at 600 bar improved control over HC, CO and smoke emissions. Overall, performance was enhanced and comparable to conventional diesel fuel, with only a minor increase in NOx emissions.
{"title":"Impact of injection pressure on the performance, emissions, and combustion of a common rail direct injection engine fueled with quaternary blends","authors":"B. Balaji, V. B. Alur, Ajmeera Suresh, P. S. Ranjit","doi":"10.1177/09544089241258376","DOIUrl":"https://doi.org/10.1177/09544089241258376","url":null,"abstract":"The scarcity and rising costs of fossil fuels, coupled with increasing pollution levels, have prompted the exploration of innovative biofuel blends. While binary and ternary fuels have been studied extensively in proportions of 5–20%, replacing up to 30–40% of fossil fuel dependency without significant engine modifications remains a challenge. One potential solution is to investigate an optimal quaternary blend (QB) through experimental methods. This study investigates the impact of increased injection pressure (IOP) and quaternary fuel blends on a common rail direct injection (CRDI) engine's performance and emissions. Different blends, including diesel fuel, vegetable oil, mahua methyl ester and normal-butanol, were tested to replace 30–40% of diesel and enhance combustion, reduce exhaust emissions and improve overall performance. Experiments used a 1-cylinder CRDI engine at high IOPs (400, 500, 600 and 700 bar). Results at 600 bar IOP showed that the optimal blend, QB3–QB4, increased brake thermal efficiency (BTE) by 9% and reduced brake-specific fuel consumption (BSFC) by approximately 11% compared to other blends. Emissions at 600 bar included a 16% reduction in hydrocarbons (HC) and a 24% decrease in carbon monoxide (CO) at full load. However, nitrogen oxide (NOx) emissions slightly increased with higher IOP. Significantly employing the QB3–QB4 blend at 600 bar improved control over HC, CO and smoke emissions. Overall, performance was enhanced and comparable to conventional diesel fuel, with only a minor increase in NOx emissions.","PeriodicalId":20552,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141270837","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-03DOI: 10.1177/09544089241257899
Mustafa Göktaş, B. Demir, M. Elitas
Fatigue, corrosion, and fatigue damage models are best addressed to improve and understand the service performance of materials, particularly automotive steel. This study is an attempt to experimentally and finite element investigates plain bending fatigue performance and damage model of DP 1000 sheet steel resistance spot welding (RSW) joints in 3% NaCl aqueous corrosive treatment. RSW applications were carried out using different weld currents. The joint samples were then subjected to optical image analysis, tensile shear, and fatigue tests (3% NaCl-aqueous and normal atmosphere). A proper damage model of RSW junctions was developed and corrected by numeric analysis. Besides, RSW nugget formation, tensile shear, and plain bending fatigue tests were also applied. Consequence, fatigue behavior, tensile load carrying capacity, and effective fracture behavior of resistance spot welded joint specimens were evaluated. Results showed that a corrosive environment negatively affected fatigue performance. With the developed model, it was observed that the fatigue life of the samples decreased by 30–35% in the fatigue tests performed in the corrosive environment. Experimental and numerical analysis results of plain bending were compatible.
{"title":"An investigation on bending fatigue in a corrosive environment of dual-phase 1000 sheet steel RSW joints and damage model via experiment and numeric analysis","authors":"Mustafa Göktaş, B. Demir, M. Elitas","doi":"10.1177/09544089241257899","DOIUrl":"https://doi.org/10.1177/09544089241257899","url":null,"abstract":"Fatigue, corrosion, and fatigue damage models are best addressed to improve and understand the service performance of materials, particularly automotive steel. This study is an attempt to experimentally and finite element investigates plain bending fatigue performance and damage model of DP 1000 sheet steel resistance spot welding (RSW) joints in 3% NaCl aqueous corrosive treatment. RSW applications were carried out using different weld currents. The joint samples were then subjected to optical image analysis, tensile shear, and fatigue tests (3% NaCl-aqueous and normal atmosphere). A proper damage model of RSW junctions was developed and corrected by numeric analysis. Besides, RSW nugget formation, tensile shear, and plain bending fatigue tests were also applied. Consequence, fatigue behavior, tensile load carrying capacity, and effective fracture behavior of resistance spot welded joint specimens were evaluated. Results showed that a corrosive environment negatively affected fatigue performance. With the developed model, it was observed that the fatigue life of the samples decreased by 30–35% in the fatigue tests performed in the corrosive environment. Experimental and numerical analysis results of plain bending were compatible.","PeriodicalId":20552,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141269274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-06-03DOI: 10.1177/09544089241258839
S. Davu, Ramesh Tejavathu, Suresh Kumar Tummala
High energy supply is critical, particularly in developing countries, to maintain lifestyles as the world's population and technological-economic metropolis grow. Solar photovoltaic cells have been used as an alternative to generate renewable, sustainable, and green energy for the past two decades. In general, the materials employed in the photoanode part are critical to manufacturing high-efficiency solar cells with 14–18% efficiency. A simple and successful method has been discovered for creating a film composed of graphene sheets and 99.8% pure anatase titanium oxide (TiO2) nanoparticles. After sensitization, the films were tested as photoelectrodes for dye-sensitized solar cells. The experimental results show that using an optimized graphene material considerably improves the power conversion efficiency of the cells, resulting in a 45% increase in short-circuit current density ( JSC). This study uses capsician as a bonding agent to enhance the current density of a graphene–TiO2 based semi-organic solar cell. The mechanical and electrical properties of the cell are investigated using a scanning electron microscope, energy dispersive X-ray, and Corescan.
随着世界人口和技术经济大都市的增长，能源供应对维持生活方式至关重要，尤其是在发展中国家。在过去二十年里，太阳能光伏电池一直被用作生产可再生、可持续和绿色能源的替代品。一般来说，光阳极部分所使用的材料对于制造效率为 14-18% 的高效太阳能电池至关重要。目前已经发现了一种简单而成功的方法，用于制造由石墨烯片和纯度为 99.8% 的锐钛型氧化钛（TiO2）纳米颗粒组成的薄膜。经过敏化处理后，这些薄膜被测试用作染料敏化太阳能电池的光电极。实验结果表明，使用优化的石墨烯材料可大大提高电池的功率转换效率，使短路电流密度（JSC）提高 45%。本研究使用胶囊剂作为结合剂，以提高基于石墨烯-二氧化钛的半有机太阳能电池的电流密度。使用扫描电子显微镜、能量色散 X 射线和 Corescan 对电池的机械和电气性能进行了研究。
{"title":"Characterization of graphene–TiO2-deposited semi-organic solar cell","authors":"S. Davu, Ramesh Tejavathu, Suresh Kumar Tummala","doi":"10.1177/09544089241258839","DOIUrl":"https://doi.org/10.1177/09544089241258839","url":null,"abstract":"High energy supply is critical, particularly in developing countries, to maintain lifestyles as the world's population and technological-economic metropolis grow. Solar photovoltaic cells have been used as an alternative to generate renewable, sustainable, and green energy for the past two decades. In general, the materials employed in the photoanode part are critical to manufacturing high-efficiency solar cells with 14–18% efficiency. A simple and successful method has been discovered for creating a film composed of graphene sheets and 99.8% pure anatase titanium oxide (TiO2) nanoparticles. After sensitization, the films were tested as photoelectrodes for dye-sensitized solar cells. The experimental results show that using an optimized graphene material considerably improves the power conversion efficiency of the cells, resulting in a 45% increase in short-circuit current density ( JSC). This study uses capsician as a bonding agent to enhance the current density of a graphene–TiO2 based semi-organic solar cell. The mechanical and electrical properties of the cell are investigated using a scanning electron microscope, energy dispersive X-ray, and Corescan.","PeriodicalId":20552,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141272146","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anomalous sound detection (ASD) is an important technology in the fourth industrial revolution, which can monitor the abnormal state of machine by identifying whether the sound of the machine is normal or not. However, in practical applications where there are few anomalous sound samples from machines, achieving effective ASD is still a challenge. In this paper, an unsupervised ASD algorithm based on adversarial autoencoder with attention mechanism is proposed. Different from the traditional reconstruction-based ASD model, in order to make the features learned by the model more representative, complex sound timing signals are converted into Gammatone spectrogram with richer features through filtering. Then the spectrogram is used as the input of the convolutional autoencoder. At the same time, the attention mechanism is introduced in the encoder to enhance adaptive learning of the normal patterns. Then the discriminator is used in the generative adversarial network to perform adversarial learning with the improved convolutional autoencoder to improve the reconstruction ability of the model for normal samples. Experimental results demonstrate that the proposed algorithm significantly outperforms commonly used industry methods for anomaly detection and exhibits advantages over other deep learning approaches in terms of system complexity.
{"title":"Unsupervised anomalous sound detection method based on Gammatone spectrogram and adversarial autoencoder with attention mechanism","authors":"Hao Yan, Xianbiao Zhan, Zhenghao Wu, Junkai Cheng, Liang Wen, Xisheng Jia","doi":"10.1177/09544089241258027","DOIUrl":"https://doi.org/10.1177/09544089241258027","url":null,"abstract":"Anomalous sound detection (ASD) is an important technology in the fourth industrial revolution, which can monitor the abnormal state of machine by identifying whether the sound of the machine is normal or not. However, in practical applications where there are few anomalous sound samples from machines, achieving effective ASD is still a challenge. In this paper, an unsupervised ASD algorithm based on adversarial autoencoder with attention mechanism is proposed. Different from the traditional reconstruction-based ASD model, in order to make the features learned by the model more representative, complex sound timing signals are converted into Gammatone spectrogram with richer features through filtering. Then the spectrogram is used as the input of the convolutional autoencoder. At the same time, the attention mechanism is introduced in the encoder to enhance adaptive learning of the normal patterns. Then the discriminator is used in the generative adversarial network to perform adversarial learning with the improved convolutional autoencoder to improve the reconstruction ability of the model for normal samples. Experimental results demonstrate that the proposed algorithm significantly outperforms commonly used industry methods for anomaly detection and exhibits advantages over other deep learning approaches in terms of system complexity.","PeriodicalId":20552,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141273084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-31DOI: 10.1177/09544089241253083
Himanshu Mahesh Shukla, Mahendra M. Gupta
Productivity plays a pivotal role in profitability and success of business. In this study, the wood cutting activity in Indian sawmills is selected. This study replicates the novel approach by integrating spherical fuzzy DEMATEL (Decision Making Trial and Evaluation Laboratory) and artificial neural networks (ANN) to improve the wood cutting productivity in Indian sawmills. The measure of betterness is selected as net productivity rate (NPR), a time-based labor productivity measure. The methodology unfolds in two crucial steps. First, SF-DEMATEL is employed to unearth influential factors affecting wood cutting, delving into their interrelationships through fuzzy logic. This process provides relationships between key determinants and their interconnected dynamics. Secondly, an ANN, a machine learning algorithm, is harnessed to predict wood cutting performance based on these identified factors. The ANN is trained using historical or simulation data, paving the way for predictions under diverse scenarios. The novelty of this approach lies in its holistic precision. The results showcase that lifting index and log weight emerge as primary influencers on productivity, with NPR, occupational risk index, and perceived exertion ranking lower. In the grand tapestry of factors, the study unveils universal driving forces, such as the weight of the log and lifting index. The ANN model, attaining a remarkable RMSE = 0.0478 and R2 = 0.9783 for training set and for training data and RMSE = 0.0487 and R2 = 0.9727 for testing data. This contributes to the comprehensive ranking comparison of factors derived from both Fuzzy DEMATEL and ANN. In summation, the fusion of Fuzzy DEMATEL and ANN unravels the intricacies of wood cutting dynamics. By identifying key factors and predicting performance, this approach provides a transformative gateway to enhance wood cutting quality and efficiency, thereby elevating the overall productivity of the woodworking industry.
生产率对企业的盈利和成功起着举足轻重的作用。本研究选择了印度锯木厂的木材切割活动。本研究通过整合球形模糊 DEMATEL（决策试验和评估实验室）和人工神经网络（ANN），复制了一种新方法，以提高印度锯木厂的木材切割生产率。更好的衡量标准是净生产率（NPR），这是一种基于时间的劳动生产率衡量标准。该方法分为两个关键步骤。首先，采用 SF-DEMATEL 来发掘影响木材切割的因素，通过模糊逻辑深入研究这些因素之间的相互关系。这一过程提供了关键决定因素之间的关系及其相互关联的动态。其次，利用机器学习算法 ANN，根据这些确定的因素预测木材切割性能。使用历史数据或模拟数据对 ANN 进行训练，为在不同情况下进行预测铺平道路。这种方法的新颖之处在于其整体精确性。研究结果表明，提升指数和原木重量是影响生产率的主要因素，而全国人口普查指数、职业风险指数和体力消耗指数则排名靠后。在众多因素中，研究揭示了普遍的驱动力，如原木重量和提升指数。ANN 模型在训练集和训练数据中的 RMSE = 0.0478 和 R2 = 0.9783，以及在测试数据中的 RMSE = 0.0487 和 R2 = 0.9727，均达到了很高的水平。这有助于对模糊 DEMATEL 和 ANN 得出的因子进行综合排名比较。总之，模糊 DEMATEL 和 ANN 的融合揭示了木材切割动态的复杂性。通过识别关键因素和预测性能，该方法为提高木材切割质量和效率提供了一个变革性途径，从而提升了木材加工行业的整体生产力。
{"title":"A comprehensive approach to enhance wood cutting productivity: Integration of spherical fuzzy DEMATEL and artificial neural networks","authors":"Himanshu Mahesh Shukla, Mahendra M. Gupta","doi":"10.1177/09544089241253083","DOIUrl":"https://doi.org/10.1177/09544089241253083","url":null,"abstract":"Productivity plays a pivotal role in profitability and success of business. In this study, the wood cutting activity in Indian sawmills is selected. This study replicates the novel approach by integrating spherical fuzzy DEMATEL (Decision Making Trial and Evaluation Laboratory) and artificial neural networks (ANN) to improve the wood cutting productivity in Indian sawmills. The measure of betterness is selected as net productivity rate (NPR), a time-based labor productivity measure. The methodology unfolds in two crucial steps. First, SF-DEMATEL is employed to unearth influential factors affecting wood cutting, delving into their interrelationships through fuzzy logic. This process provides relationships between key determinants and their interconnected dynamics. Secondly, an ANN, a machine learning algorithm, is harnessed to predict wood cutting performance based on these identified factors. The ANN is trained using historical or simulation data, paving the way for predictions under diverse scenarios. The novelty of this approach lies in its holistic precision. The results showcase that lifting index and log weight emerge as primary influencers on productivity, with NPR, occupational risk index, and perceived exertion ranking lower. In the grand tapestry of factors, the study unveils universal driving forces, such as the weight of the log and lifting index. The ANN model, attaining a remarkable RMSE = 0.0478 and R<jats:sup>2</jats:sup> = 0.9783 for training set and for training data and RMSE = 0.0487 and R<jats:sup>2</jats:sup> = 0.9727 for testing data. This contributes to the comprehensive ranking comparison of factors derived from both Fuzzy DEMATEL and ANN. In summation, the fusion of Fuzzy DEMATEL and ANN unravels the intricacies of wood cutting dynamics. By identifying key factors and predicting performance, this approach provides a transformative gateway to enhance wood cutting quality and efficiency, thereby elevating the overall productivity of the woodworking industry.","PeriodicalId":20552,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141194469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this study, an erosion model of silicon carbide ceramics and YW3 was established by combining experimental and numerical simulation data. This model can be applied for the prediction of erosion in natural gas equipment and transportation systems and also provides ideas for the establishment of erosion models. The erosion model was established by using quartz sand, brown corundum, and glass beads as abrasive materials, and then the accuracy of the erosion model was confirmed by numerical simulations. The results showed that when the abrasive was quartz sand, brown corundum, or glass beads, the erosion angle at which the maximum erosion of silicon carbide and YW3 occurred was related to the type of abrasive. When the abrasive was quartz sand, brown corundum, and glass beads, the velocity index n of silicon carbide was 3.24, 3.66, and 3.32, respectively, and the model constant k was 4.1959 × 10−11, 3.6436 × 10−11, and 4.1838 × 10−11, respectively. The velocity index n of YW3 was 2.29, 2.41, and 1.87, respectively, and the model constant k was 2.6176 × 10−7, 3.0017 × 10−7, and 3.1040 × 10−7, respectively. When the test results were compared with the numerical simulation results, the maximum error for silicon carbide was 6.59%, 7.71%, and 9.25%, respectively, and the maximum error for YW3 was 8.78%, 9.51%, and 5.97%, respectively. Finally, the erosion model of silicon carbide ceramics and YW3 was established via a large number of experiments and numerical simulations. When the target material and abrasive material are the same, it can be directly used for erosion prediction and structure optimization of natural gas equipment. Meanwhile, this paper provides a new idea for the establishment of gas–solid two-phase erosion model, and when the abrasive material and target material change, a new erosion model can be established according to the idea of this paper.
{"title":"Erosion model of silicon carbide ceramics and YW3","authors":"Chunyu Feng, Zhen Wang, Yuelong Liu, Xuefeng Deng, Pei Xiong","doi":"10.1177/09544089241255926","DOIUrl":"https://doi.org/10.1177/09544089241255926","url":null,"abstract":"In this study, an erosion model of silicon carbide ceramics and YW3 was established by combining experimental and numerical simulation data. This model can be applied for the prediction of erosion in natural gas equipment and transportation systems and also provides ideas for the establishment of erosion models. The erosion model was established by using quartz sand, brown corundum, and glass beads as abrasive materials, and then the accuracy of the erosion model was confirmed by numerical simulations. The results showed that when the abrasive was quartz sand, brown corundum, or glass beads, the erosion angle at which the maximum erosion of silicon carbide and YW3 occurred was related to the type of abrasive. When the abrasive was quartz sand, brown corundum, and glass beads, the velocity index n of silicon carbide was 3.24, 3.66, and 3.32, respectively, and the model constant k was 4.1959 × 10<jats:sup>−11</jats:sup>, 3.6436 × 10<jats:sup>−11</jats:sup>, and 4.1838 × 10<jats:sup>−11</jats:sup>, respectively. The velocity index n of YW3 was 2.29, 2.41, and 1.87, respectively, and the model constant k was 2.6176 × 10<jats:sup>−7</jats:sup>, 3.0017 × 10<jats:sup>−7</jats:sup>, and 3.1040 × 10<jats:sup>−7</jats:sup>, respectively. When the test results were compared with the numerical simulation results, the maximum error for silicon carbide was 6.59%, 7.71%, and 9.25%, respectively, and the maximum error for YW3 was 8.78%, 9.51%, and 5.97%, respectively. Finally, the erosion model of silicon carbide ceramics and YW3 was established via a large number of experiments and numerical simulations. When the target material and abrasive material are the same, it can be directly used for erosion prediction and structure optimization of natural gas equipment. Meanwhile, this paper provides a new idea for the establishment of gas–solid two-phase erosion model, and when the abrasive material and target material change, a new erosion model can be established according to the idea of this paper.","PeriodicalId":20552,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141194437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-29DOI: 10.1177/09544089241258065
Jun Xiao, Maofei Geng
For the analysis of gas pulsation characteristics in the pipeline systems of low density polyethylene (LDPE) hyper compressors, a time-domain calculation method for compressor pipeline gas pulsation based on real gas properties is proposed. First the thermophysical property tables are prepared with gas state parameters as independent and dependent variables. Then one-dimensional unsteady flow equations and characteristic equations for pipeline flow are established based on real gas properties. After setting pipeline parameters and boundary conditions, the flow equations are discretized using a two-step method at the inner points of the pipeline. The characteristic equations are discretized using the trapezoidal integration method at the boundary points. Thus, the time-domain solving of pulsating flow field in the pipeline is realized. A self-developed numerical code was used to conduct the time-domain calculation and analysis of gas pulsation in the discharge pipeline of a two-stage hyper compressor. The calculated pressure pulsation curves based on real gas properties are in good agreement with experimental data, with a maximum difference lower than 4% of the local average pressure, which is smaller than the difference between the results calculated based on the plane wave theory and the measured data. The analysis of gas pulsation characteristics shows that the pressure pulsation in the main pipeline is mainly contributed by the fundamental and second harmonics. The pressure pulsation in the safety valve branch is higher than that in the main pipeline, and the harmonic components falling into the acoustic resonance frequency range of this branch have significant amplitudes. The acoustic resonance frequency of the branch pipeline is not affected by the main pipeline. Pressure pulsation varies with changes in rotational speed and back pressure, and the pulsation level is more significantly affected by rotational speed compared to back pressure. The renovation scheme of connecting the safety valve branch and expansion tube in series can effectively reduce the pressure pulsation levels of the main pipeline and branch pipeline.
{"title":"Analyses of gas pulsation characteristics in the discharge pipeline of a hyper compressor","authors":"Jun Xiao, Maofei Geng","doi":"10.1177/09544089241258065","DOIUrl":"https://doi.org/10.1177/09544089241258065","url":null,"abstract":"For the analysis of gas pulsation characteristics in the pipeline systems of low density polyethylene (LDPE) hyper compressors, a time-domain calculation method for compressor pipeline gas pulsation based on real gas properties is proposed. First the thermophysical property tables are prepared with gas state parameters as independent and dependent variables. Then one-dimensional unsteady flow equations and characteristic equations for pipeline flow are established based on real gas properties. After setting pipeline parameters and boundary conditions, the flow equations are discretized using a two-step method at the inner points of the pipeline. The characteristic equations are discretized using the trapezoidal integration method at the boundary points. Thus, the time-domain solving of pulsating flow field in the pipeline is realized. A self-developed numerical code was used to conduct the time-domain calculation and analysis of gas pulsation in the discharge pipeline of a two-stage hyper compressor. The calculated pressure pulsation curves based on real gas properties are in good agreement with experimental data, with a maximum difference lower than 4% of the local average pressure, which is smaller than the difference between the results calculated based on the plane wave theory and the measured data. The analysis of gas pulsation characteristics shows that the pressure pulsation in the main pipeline is mainly contributed by the fundamental and second harmonics. The pressure pulsation in the safety valve branch is higher than that in the main pipeline, and the harmonic components falling into the acoustic resonance frequency range of this branch have significant amplitudes. The acoustic resonance frequency of the branch pipeline is not affected by the main pipeline. Pressure pulsation varies with changes in rotational speed and back pressure, and the pulsation level is more significantly affected by rotational speed compared to back pressure. The renovation scheme of connecting the safety valve branch and expansion tube in series can effectively reduce the pressure pulsation levels of the main pipeline and branch pipeline.","PeriodicalId":20552,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141194441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-05-29DOI: 10.1177/09544089241255931
Prakash Kumar, Binay Kumar
This research delves into the tribological performance of hybrid aluminum metal matrix composites (HAMMCs) incorporating zirconium diboride (ZrB2) particles and fly ash as reinforcing agents. The study employs a linear reciprocating wear test to investigate the impact of dry sliding wear on these HAMMCs under ambient and elevated temperatures. Wear mechanisms are discerned through field emission scanning electron microscopy. Optimization of wear test parameters, coefficient of friction (COF), and wear rate is achieved using the genetic algorithm. Additionally, artificial neural network (ANN) and multiple linear regression analysis are employed to formulate a predictive model for wear, estimating specific wear rate and COF under various testing conditions. The ANN predictions exhibit a deviation ranging from 0% to 1.39% from the experimental values, indicating the model's effectiveness in understanding and predicting wear behavior in the study of HAMMC.
{"title":"Synergistic approach to tribological characterization of hybrid aluminum metal matrix composites with ZrB2 and fly ash: Experimental and predictive insights","authors":"Prakash Kumar, Binay Kumar","doi":"10.1177/09544089241255931","DOIUrl":"https://doi.org/10.1177/09544089241255931","url":null,"abstract":"This research delves into the tribological performance of hybrid aluminum metal matrix composites (HAMMCs) incorporating zirconium diboride (ZrB<jats:sub>2</jats:sub>) particles and fly ash as reinforcing agents. The study employs a linear reciprocating wear test to investigate the impact of dry sliding wear on these HAMMCs under ambient and elevated temperatures. Wear mechanisms are discerned through field emission scanning electron microscopy. Optimization of wear test parameters, coefficient of friction (COF), and wear rate is achieved using the genetic algorithm. Additionally, artificial neural network (ANN) and multiple linear regression analysis are employed to formulate a predictive model for wear, estimating specific wear rate and COF under various testing conditions. The ANN predictions exhibit a deviation ranging from 0% to 1.39% from the experimental values, indicating the model's effectiveness in understanding and predicting wear behavior in the study of HAMMC.","PeriodicalId":20552,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141194467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Al-Si-Mg aluminum alloys exhibit excellent machinability as heat-treatable strengthened aluminum alloys. Heat treatment has a great influence on the microstructure and mechanical properties of Al-Si-Mg aluminum alloys. In this study, the ZL114A aluminum alloy wire was used to fabricate the Al-Si-Mg thin-walled component based on the wire-arc additive manufacturing process of metal inert-gas welding. The microstructure and mechanical properties of the ZL114A aluminum alloy components were investigated in both the as-deposited and heat treated at different solution temperatures. The results indicated that the microstructure of as-deposited ZL114A aluminum alloys consisted mainly of dendrites. The dendritic morphology disappeared after solid solution treatment (ST) at different temperatures, and the eutectic Si phase appeared coarsened and spheroidized. Numerous β″ phases were observed to have precipitated within the grains by transmission electron microscopy. The tensile properties of the alloy were improved due to precipitation strengthening of the β″ phase and spheroidization of the eutectic silicon phase. After the solid ST at 540 °C for 9 h and artificial aging treatment at 170 °C for 8 h, the yield strength and ultimate tensile strength of the alloy reached the maximum values of 344 and 377 MPa, respectively.
铝硅镁铝合金作为一种可热处理的强化铝合金，具有出色的机械加工性能。热处理对 Al-Si-Mg 铝合金的微观结构和机械性能有很大影响。本研究使用 ZL114A 铝合金线材，基于金属惰性气体焊接的线弧快速成型制造工艺，制造了铝-硅-镁薄壁部件。研究了 ZL114A 铝合金部件在敷镀和不同固溶温度下热处理时的微观结构和机械性能。结果表明，未轧制的 ZL114A 铝合金的微观结构主要由树枝状晶组成。在不同温度下进行固溶处理（ST）后，树枝状形态消失，共晶硅相出现粗化和球化。透射电子显微镜观察到晶粒内析出了大量的 β″ 相。由于β″相的沉淀强化和共晶硅相的球化，合金的拉伸性能得到了改善。在 540 °C 下固态 ST 9 小时和 170 °C 下人工时效处理 8 小时后，合金的屈服强度和极限抗拉强度分别达到了 344 和 377 兆帕的最大值。
{"title":"Effects of solution temperature on microstructure and mechanical properties of Al-Si-Mg aluminum alloy fabricated by wire-arc additive manufacturing","authors":"Guoqing Chen, Zhanwei Zhang, Yuanzheng Zhao, Xuming Guo","doi":"10.1177/09544089241257792","DOIUrl":"https://doi.org/10.1177/09544089241257792","url":null,"abstract":"Al-Si-Mg aluminum alloys exhibit excellent machinability as heat-treatable strengthened aluminum alloys. Heat treatment has a great influence on the microstructure and mechanical properties of Al-Si-Mg aluminum alloys. In this study, the ZL114A aluminum alloy wire was used to fabricate the Al-Si-Mg thin-walled component based on the wire-arc additive manufacturing process of metal inert-gas welding. The microstructure and mechanical properties of the ZL114A aluminum alloy components were investigated in both the as-deposited and heat treated at different solution temperatures. The results indicated that the microstructure of as-deposited ZL114A aluminum alloys consisted mainly of dendrites. The dendritic morphology disappeared after solid solution treatment (ST) at different temperatures, and the eutectic Si phase appeared coarsened and spheroidized. Numerous β″ phases were observed to have precipitated within the grains by transmission electron microscopy. The tensile properties of the alloy were improved due to precipitation strengthening of the β″ phase and spheroidization of the eutectic silicon phase. After the solid ST at 540 °C for 9 h and artificial aging treatment at 170 °C for 8 h, the yield strength and ultimate tensile strength of the alloy reached the maximum values of 344 and 377 MPa, respectively.","PeriodicalId":20552,"journal":{"name":"Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering","volume":null,"pages":null},"PeriodicalIF":2.4,"publicationDate":"2024-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141194285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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