Udaya Devadiga, Peter Fernandes, A. Buradi, Addisu Frinjo Emma
In order to improve the wear and frictional behavior of the aluminum metal matrix composites, carbon nanotube, and fly ash were added as reinforcements. Powder metallurgy technique was used to fabricate the hybrid metal matrix composites. Experimentations were carried out using pin on disc type wear test rig. The analyzed experimental results showed that, in comparison to the pure aluminum and mono reinforcement combination, the wear loss and coefficient of friction of hybrid metal matrix composites were greatly reduced. It was noted that compared to pure aluminum wear loss was decreased to 89.58%, 86.97%, 83.3% by adding 0.25, 0.5, 0.75 wt% carbon nanotube (CNT), respectively. By the addition of 4, 8 and 16 wt% FA to pure Al wear loss was decreased to 83.85%, 89.58%, and 78.12%, respectively. It was also noted that compared to Al/8 wt% FA mono reinforced composites, wear loss was decreased to 77%, 71.26%, and 53.22% with the addition of 0.25, 0.5, 0.75 wt% CNT, respectively. With the addition of 4, 8, 16 wt% FA, wear loss decreased to 81%, 88%, and 75% over Al/0.25 wt% CNT composites, respectively. The microstructural study of the worn‐out surfaces revealed low abrasive and adhesive wear by the presence of carbon nanotubes and fly ash in aluminum metal matrix. The reinforcing mechanisms of the wear and frictional properties were also discussed.
{"title":"Significance of addition of carbon nanotubes and fly ash on the wear and frictional performance of aluminum metal matrix composites","authors":"Udaya Devadiga, Peter Fernandes, A. Buradi, Addisu Frinjo Emma","doi":"10.1002/eng2.12865","DOIUrl":"https://doi.org/10.1002/eng2.12865","url":null,"abstract":"In order to improve the wear and frictional behavior of the aluminum metal matrix composites, carbon nanotube, and fly ash were added as reinforcements. Powder metallurgy technique was used to fabricate the hybrid metal matrix composites. Experimentations were carried out using pin on disc type wear test rig. The analyzed experimental results showed that, in comparison to the pure aluminum and mono reinforcement combination, the wear loss and coefficient of friction of hybrid metal matrix composites were greatly reduced. It was noted that compared to pure aluminum wear loss was decreased to 89.58%, 86.97%, 83.3% by adding 0.25, 0.5, 0.75 wt% carbon nanotube (CNT), respectively. By the addition of 4, 8 and 16 wt% FA to pure Al wear loss was decreased to 83.85%, 89.58%, and 78.12%, respectively. It was also noted that compared to Al/8 wt% FA mono reinforced composites, wear loss was decreased to 77%, 71.26%, and 53.22% with the addition of 0.25, 0.5, 0.75 wt% CNT, respectively. With the addition of 4, 8, 16 wt% FA, wear loss decreased to 81%, 88%, and 75% over Al/0.25 wt% CNT composites, respectively. The microstructural study of the worn‐out surfaces revealed low abrasive and adhesive wear by the presence of carbon nanotubes and fly ash in aluminum metal matrix. The reinforcing mechanisms of the wear and frictional properties were also discussed.","PeriodicalId":11735,"journal":{"name":"Engineering Reports","volume":"14 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139838472","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}
Georgia de Souza Assumpção, Carolina Maia dos Santos, Daniele de Lima Campello, Leonardo Silva de Lima, Alexandre de Carvalho Castro
The paper analyzes how to improve the teaching of Operational Research, focusing on distance learning courses where professors and students are separated through space and time. This case study was done in a public Industrial Engineering undergraduate course, and the work structure is divided into three main parts: an exploratory‐descriptive documentary analysis, application of free software, and evaluation of learning. The authors showed the feasibility of using the SageMath tool in the teaching‐learning process. The study revealed the importance of developing alternative solutions to educational realities marked by economic and financial constraints, where structure teaching with free software is a ruling factor once Engineering education is not a similar global event everywhere. Distance learning is a phenomenon that has been growing over the last 20 years in Brazil, but this was one of the first experiences with the use of SageMath. So, it can serve as a reference for countries with socioeconomic conditions similar to Brazil. Also, this case study can help other professors to enhance their teaching in a distance learning context even in scarcity scenarios of educational resources. The software implementation would be justified in part of the groups studied.
{"title":"A proposal of teaching operational research in online contexts: An experience with SageMath in Brazil","authors":"Georgia de Souza Assumpção, Carolina Maia dos Santos, Daniele de Lima Campello, Leonardo Silva de Lima, Alexandre de Carvalho Castro","doi":"10.1002/eng2.12863","DOIUrl":"https://doi.org/10.1002/eng2.12863","url":null,"abstract":"The paper analyzes how to improve the teaching of Operational Research, focusing on distance learning courses where professors and students are separated through space and time. This case study was done in a public Industrial Engineering undergraduate course, and the work structure is divided into three main parts: an exploratory‐descriptive documentary analysis, application of free software, and evaluation of learning. The authors showed the feasibility of using the SageMath tool in the teaching‐learning process. The study revealed the importance of developing alternative solutions to educational realities marked by economic and financial constraints, where structure teaching with free software is a ruling factor once Engineering education is not a similar global event everywhere. Distance learning is a phenomenon that has been growing over the last 20 years in Brazil, but this was one of the first experiences with the use of SageMath. So, it can serve as a reference for countries with socioeconomic conditions similar to Brazil. Also, this case study can help other professors to enhance their teaching in a distance learning context even in scarcity scenarios of educational resources. The software implementation would be justified in part of the groups studied.","PeriodicalId":11735,"journal":{"name":"Engineering Reports","volume":"123 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139780897","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 biochemical pathway for propionic acid (PA) production is an interesting alternative that can include the utilization of biomass as feedstock. This study evaluated the utilization of Agave bagasse (AB), a lignocellulosic residue, to produce PA by Propionibacterium acidipropinici in batch systems (125 mL‐hermetic bottles and 1000 mL‐bioreactor). The process included a steam explosion pretreatment at 142°C for 15 min and enzymatic hydrolysis, where solid loading (2.75% and 5% in pretreatment and 2.5%, 3.75%, and 5% in enzymatic hydrolysis) was evaluated. Furthermore, the enzymatic concentrations of 18.3 filter paper unit (FPU)/gAB (1×) of Cellic® CTec2 and 1.5× and 3× were tested. The yields of total carbohydrates (TC) obtained at the two solid loadings tested in the pretreatment were statistically similar, but the 3x enzymatic concentration enhanced the yields of TC, glucose, and xylose (0.23 ± 0.01, 0.15 ± 0.01 and 0.03 ± 0.01 g/gAB, respectively). The hydrolysates obtained under these conditions were evaluated as carbon sources for PA production, obtaining a productivity of 0.069 ± 0.006 g/L h and a yield product/substrate of 0.44 gPA/gTC. The control of pH in the culture reduced the fermentation time in the bioreactor by 52% compared with the hermetic bottles without pH control. The potential of hydrolysates as carbon sources for PA production was evidenced, as approximately 50% of the initial carbon was converted to this product. The observed yield product/substrate was similar to those reported from hydrolysates of diverse biomass types, pretreatments, or enzymatic cocktails and the same or related microorganisms. However, the system studied has advantages, such as not requiring the addition of chemical or detoxification stage, and lower temperature and time compared to other pretreatments.
{"title":"Propionic acid production by Propionibacterium acidipropionici CDBB‐B‐1981 from enzymatic hydrolysates of Agave bagasse pretreated by steam explosion","authors":"Veronica Duran‐Cruz, Sergio Hernández, I. Ortíz","doi":"10.1002/eng2.12858","DOIUrl":"https://doi.org/10.1002/eng2.12858","url":null,"abstract":"The biochemical pathway for propionic acid (PA) production is an interesting alternative that can include the utilization of biomass as feedstock. This study evaluated the utilization of Agave bagasse (AB), a lignocellulosic residue, to produce PA by Propionibacterium acidipropinici in batch systems (125 mL‐hermetic bottles and 1000 mL‐bioreactor). The process included a steam explosion pretreatment at 142°C for 15 min and enzymatic hydrolysis, where solid loading (2.75% and 5% in pretreatment and 2.5%, 3.75%, and 5% in enzymatic hydrolysis) was evaluated. Furthermore, the enzymatic concentrations of 18.3 filter paper unit (FPU)/gAB (1×) of Cellic® CTec2 and 1.5× and 3× were tested. The yields of total carbohydrates (TC) obtained at the two solid loadings tested in the pretreatment were statistically similar, but the 3x enzymatic concentration enhanced the yields of TC, glucose, and xylose (0.23 ± 0.01, 0.15 ± 0.01 and 0.03 ± 0.01 g/gAB, respectively). The hydrolysates obtained under these conditions were evaluated as carbon sources for PA production, obtaining a productivity of 0.069 ± 0.006 g/L h and a yield product/substrate of 0.44 gPA/gTC. The control of pH in the culture reduced the fermentation time in the bioreactor by 52% compared with the hermetic bottles without pH control. The potential of hydrolysates as carbon sources for PA production was evidenced, as approximately 50% of the initial carbon was converted to this product. The observed yield product/substrate was similar to those reported from hydrolysates of diverse biomass types, pretreatments, or enzymatic cocktails and the same or related microorganisms. However, the system studied has advantages, such as not requiring the addition of chemical or detoxification stage, and lower temperature and time compared to other pretreatments.","PeriodicalId":11735,"journal":{"name":"Engineering Reports","volume":"5 9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139781797","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 frequency‐domain reflection (FDR) has been demonstrated to be a trustworthy technique in solving the defect location of power cable by field experiments. However, the location spectrum of the FDR requires manual window smoothing and can be disturbed by spurious peaks. Aiming at these shortcomings of FDR, a new method of cable defect location based on Burg power spectral (BPS) is introduced in this paper. The idea of this method is to use linear difference variance to fit the distribution of reflection coefficient spectrum and build an auto‐regressive (AR) model. The Burg algorithm is employed to estimate the coefficients model and calculate the power distribution of the AR model. Then, the cable defects will be located by BPS with high precision and resolution. In this method, the fast Fourier transform (FFT) with windowed function is replaced by an AR model without windowed function. This suppressed the impact of spurious peaks or spectrum leakage in FFT on the localization defects, and the localization resolution is higher. Finally, we validate the feasibility and effectiveness of BPS through experiments conducted on a 500 m laboratory cable and a 9.6 km submarine cable.
通过现场实验证明，频域反射（FDR）是解决电力电缆缺陷定位问题的可靠技术。然而，频域反射仪的定位频谱需要人工窗口平滑处理，而且会受到杂散峰值的干扰。针对 FDR 的这些缺点，本文介绍了一种基于伯格功率谱（BPS）的电缆缺陷定位新方法。该方法的理念是利用线性差分方差拟合反射系数频谱的分布，并建立一个自动回归（AR）模型。采用 Burg 算法估计系数模型并计算 AR 模型的功率分布。然后，通过高精度和高分辨率的 BPS 定位电缆缺陷。在这种方法中，有窗函数的快速傅立叶变换（FFT）被无窗函数的 AR 模型所取代。这就抑制了 FFT 中的杂散峰值或频谱泄漏对定位缺陷的影响，而且定位分辨率更高。最后，我们通过在 500 米实验室电缆和 9.6 千米海底电缆上进行的实验验证了 BPS 的可行性和有效性。
{"title":"A defect location method for power cable based on Burg power spectral","authors":"Zhirong Tang, Kaihua Zhou, Yun Li, P. Meng","doi":"10.1002/eng2.12859","DOIUrl":"https://doi.org/10.1002/eng2.12859","url":null,"abstract":"The frequency‐domain reflection (FDR) has been demonstrated to be a trustworthy technique in solving the defect location of power cable by field experiments. However, the location spectrum of the FDR requires manual window smoothing and can be disturbed by spurious peaks. Aiming at these shortcomings of FDR, a new method of cable defect location based on Burg power spectral (BPS) is introduced in this paper. The idea of this method is to use linear difference variance to fit the distribution of reflection coefficient spectrum and build an auto‐regressive (AR) model. The Burg algorithm is employed to estimate the coefficients model and calculate the power distribution of the AR model. Then, the cable defects will be located by BPS with high precision and resolution. In this method, the fast Fourier transform (FFT) with windowed function is replaced by an AR model without windowed function. This suppressed the impact of spurious peaks or spectrum leakage in FFT on the localization defects, and the localization resolution is higher. Finally, we validate the feasibility and effectiveness of BPS through experiments conducted on a 500 m laboratory cable and a 9.6 km submarine cable.","PeriodicalId":11735,"journal":{"name":"Engineering Reports","volume":"12 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139853716","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}
Hailong Xu, Li Huang, Wen Zhang, Jing Liang, Xuanqiao Gao, Jianfeng Li
Textures in molybdenum‐rhenium (Mo‐Re) alloys are inevitable during thermal fabrication. [110] and [100] are common orientations in Mo‐Re alloys and effect mechanical responses. However, orientation dependence of mechanical responses in Mo‐Re alloys is not quite clear yet. To clarity this problem, micro‐pillar compression tests are conducted in grains with orientation [100] and [110] separately. Orientation‐dependent compressive properties are found in Mo‐14Re and Mo‐42Re (wt.%), but are not found in Mo and Mo‐5Re, which may be attributed to activated multi‐slip planes as increased Re. Solid solution effect of Re not only relies on orientations, but also on Re contents. Softening effect occurs in both [100] and [110] Mo‐5Re. while, strong strengthening effect happens in [110] Mo‐14Re and Mo‐42Re. Our research clarifies that Mo‐Re alloys with [110] orientation/texture could be preferred to obtain good strengthening effect.
钼-铼（Mo-Re）合金的纹理在热加工过程中不可避免。[110]和[100]是 Mo-Re 合金中常见的取向，会影响机械响应。然而，Mo-Re 合金中机械响应的取向依赖性尚不十分明确。为了澄清这一问题，我们分别对取向为 [100] 和 [110] 的晶粒进行了微柱压缩试验。在 Mo-14Re 和 Mo-42Re（重量百分比）中发现了与取向相关的压缩特性，但在 Mo 和 Mo-5Re 中却没有发现，这可能是由于 Re 增加时激活了多滑移平面。Re 的固溶效应不仅取决于取向，还取决于 Re 的含量。[100]和[110]Mo-5Re中都出现了软化效应，而[110]Mo-14Re和Mo-42Re中则出现了强烈的强化效应。我们的研究表明，要获得良好的强化效果，应优先选择具有[110]取向/质地的 Mo-Re 合金。
{"title":"Orientation‐dependent mechanical responses in molybdenum‐rhenium alloys evaluated via micro‐pillars","authors":"Hailong Xu, Li Huang, Wen Zhang, Jing Liang, Xuanqiao Gao, Jianfeng Li","doi":"10.1002/eng2.12829","DOIUrl":"https://doi.org/10.1002/eng2.12829","url":null,"abstract":"Textures in molybdenum‐rhenium (Mo‐Re) alloys are inevitable during thermal fabrication. [110] and [100] are common orientations in Mo‐Re alloys and effect mechanical responses. However, orientation dependence of mechanical responses in Mo‐Re alloys is not quite clear yet. To clarity this problem, micro‐pillar compression tests are conducted in grains with orientation [100] and [110] separately. Orientation‐dependent compressive properties are found in Mo‐14Re and Mo‐42Re (wt.%), but are not found in Mo and Mo‐5Re, which may be attributed to activated multi‐slip planes as increased Re. Solid solution effect of Re not only relies on orientations, but also on Re contents. Softening effect occurs in both [100] and [110] Mo‐5Re. while, strong strengthening effect happens in [110] Mo‐14Re and Mo‐42Re. Our research clarifies that Mo‐Re alloys with [110] orientation/texture could be preferred to obtain good strengthening effect.","PeriodicalId":11735,"journal":{"name":"Engineering Reports","volume":"412 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139860198","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}
Muhammad Shalahuddin, W. Sunindyo, Mohammad Ridwan Effendi, K. Surendro
Modelers often create diverse system dynamics models for the same issue, depending on their viewpoints, which can decrease stakeholder assurance. Validating system dynamics may enhance stakeholder confidence. This study suggests using fuzzy‐set qualitative comparative analysis (fsQCA) as a technique based on a set theory approach to validate the causal connections between entities in causal loop diagram (CLD) models. This case study analyzed the issue of Indonesian mobile network operators with limited sample data, utilizing the fsQCA method to test causal connections between entities in the CLD model that require validation. Following the creation of the CLD model through the system dynamics methodology, fsQCA was employed to enhance the previously formed model. The fsQCA method fuses qualitative comparative analysis (QCA) with fuzzy set theory, permitting partial membership, and can identify causal links among entities in the CLD model. It assists in testing causal relationships using limited sample data and boosts stakeholder confidence in the CLD model.
{"title":"Fuzzy‐set qualitative comparative analysis (fsQCA) for validating causal relationships in system dynamics models","authors":"Muhammad Shalahuddin, W. Sunindyo, Mohammad Ridwan Effendi, K. Surendro","doi":"10.1002/eng2.12855","DOIUrl":"https://doi.org/10.1002/eng2.12855","url":null,"abstract":"Modelers often create diverse system dynamics models for the same issue, depending on their viewpoints, which can decrease stakeholder assurance. Validating system dynamics may enhance stakeholder confidence. This study suggests using fuzzy‐set qualitative comparative analysis (fsQCA) as a technique based on a set theory approach to validate the causal connections between entities in causal loop diagram (CLD) models. This case study analyzed the issue of Indonesian mobile network operators with limited sample data, utilizing the fsQCA method to test causal connections between entities in the CLD model that require validation. Following the creation of the CLD model through the system dynamics methodology, fsQCA was employed to enhance the previously formed model. The fsQCA method fuses qualitative comparative analysis (QCA) with fuzzy set theory, permitting partial membership, and can identify causal links among entities in the CLD model. It assists in testing causal relationships using limited sample data and boosts stakeholder confidence in the CLD model.","PeriodicalId":11735,"journal":{"name":"Engineering Reports","volume":"2008 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139807189","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}
To address the problem that the whale optimization algorithm tends to fall into the local optimum and fails to maintain a balance between exploration and exploitation, an elitist whale optimization algorithm with the nonlinear parameter (EWOANP) is proposed in this paper. An elitist strategy based on the random Cauchy mutation is used in the shrinking encircling mechanism to increase the chance of escaping the local optimum. Cleverly, the strategy is to generate mutation solutions based on the random Cauchy mutation, after which the better population is selected to proceed to the next iteration. Then, a nonlinear parameter is used in the logarithmic spiral mechanism to balance exploration and exploitation. Various numerical optimization experiments are performed based on the IEEE CEC2020 benchmark suite and compared with eleven other algorithms. The results show that EWOANP outperforms most competitors in numerical optimization. Finally, the backpropagation neural network is optimized by EWOANP to build a prediction model for the sulfur content in the molten iron. The experimental results based on production data indicate that the proposed prediction model has a relatively small fluctuation in errors. Compared to the other seven competitors, the proposed model has a better prediction performance with and =0.916619.
{"title":"An elitist whale optimization algorithm with the nonlinear parameter: Algorithm and application","authors":"Yajing Zhang, Guoxu Zhang","doi":"10.1002/eng2.12857","DOIUrl":"https://doi.org/10.1002/eng2.12857","url":null,"abstract":"To address the problem that the whale optimization algorithm tends to fall into the local optimum and fails to maintain a balance between exploration and exploitation, an elitist whale optimization algorithm with the nonlinear parameter (EWOANP) is proposed in this paper. An elitist strategy based on the random Cauchy mutation is used in the shrinking encircling mechanism to increase the chance of escaping the local optimum. Cleverly, the strategy is to generate mutation solutions based on the random Cauchy mutation, after which the better population is selected to proceed to the next iteration. Then, a nonlinear parameter is used in the logarithmic spiral mechanism to balance exploration and exploitation. Various numerical optimization experiments are performed based on the IEEE CEC2020 benchmark suite and compared with eleven other algorithms. The results show that EWOANP outperforms most competitors in numerical optimization. Finally, the backpropagation neural network is optimized by EWOANP to build a prediction model for the sulfur content in the molten iron. The experimental results based on production data indicate that the proposed prediction model has a relatively small fluctuation in errors. Compared to the other seven competitors, the proposed model has a better prediction performance with and =0.916619.","PeriodicalId":11735,"journal":{"name":"Engineering Reports","volume":"21 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139867114","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. Karaca, Mert Guney, A. Agibayeva, Nurlan Otesh, M. Kulimbet, Natalya Glushkova, Yuefang Chang, Akira Sekikawa, K. Davletov
The present study introduces a concentration estimation model for indoor inhalable fine particles (PM2.5) during cooking activities in typical Kazakh houses, which are generally poorly ventilated with high emission levels. The aim of the present work is to identify factors influencing PM2.5 concentrations during cooking and elucidate the mechanisms underlying the build‐up and reduction of PM2.5 concentrations. These are achieved through a methodology that combines PM2.5 sampling, monitoring, and modeling to predict household PM2.5 levels and estimate daily concentrations. Specifically, USEPA's IAQX v1.1 was employed to simulate the one‐zone concept (kitchen) for concentrations related to cooking activities in several households. The results reveal that PM2.5 concentrations varied between 13 and 266 μg/m3 during cooking activities. Factors such as kitchen size, air exchange characteristics, and the type of food and cooking style were identified as important, influencing the observed concentrations. The model accurately captured concentration trends (R > 0.9). However, certain predictions tended to overestimate the measurements, attributing to inaccuracies in selecting air exchange and emission rates. Cooking activities contributed to household air pollutant (HAP) PM2.5 levels ranging from 9% to 94%. Notably, during the non‐heating period of the year (corresponding to the warmer half of the year), the impact of cooking became more significant and was identified as a major contributor to indoor PM2.5 concentrations. Conversely, during the heating period (i.e., the colder part of the year), outdoor PM levels and household ventilation practices played primary roles in regulating indoor air concentrations. This present study presents one of the initial efforts to assess household air pollutants in Central Asia, providing foundation and insights into the indoor air quality of Kazakh houses, where the understanding of indoor air quality remains limited. Future research recommendations include developing advanced models that account for individual activity patterns and specific house types for improved accuracy and representativeness.
{"title":"Indoor air quality in Kazakh households: Evaluating PM2.5 levels generated by cooking activities","authors":"F. Karaca, Mert Guney, A. Agibayeva, Nurlan Otesh, M. Kulimbet, Natalya Glushkova, Yuefang Chang, Akira Sekikawa, K. Davletov","doi":"10.1002/eng2.12845","DOIUrl":"https://doi.org/10.1002/eng2.12845","url":null,"abstract":"The present study introduces a concentration estimation model for indoor inhalable fine particles (PM2.5) during cooking activities in typical Kazakh houses, which are generally poorly ventilated with high emission levels. The aim of the present work is to identify factors influencing PM2.5 concentrations during cooking and elucidate the mechanisms underlying the build‐up and reduction of PM2.5 concentrations. These are achieved through a methodology that combines PM2.5 sampling, monitoring, and modeling to predict household PM2.5 levels and estimate daily concentrations. Specifically, USEPA's IAQX v1.1 was employed to simulate the one‐zone concept (kitchen) for concentrations related to cooking activities in several households. The results reveal that PM2.5 concentrations varied between 13 and 266 μg/m3 during cooking activities. Factors such as kitchen size, air exchange characteristics, and the type of food and cooking style were identified as important, influencing the observed concentrations. The model accurately captured concentration trends (R > 0.9). However, certain predictions tended to overestimate the measurements, attributing to inaccuracies in selecting air exchange and emission rates. Cooking activities contributed to household air pollutant (HAP) PM2.5 levels ranging from 9% to 94%. Notably, during the non‐heating period of the year (corresponding to the warmer half of the year), the impact of cooking became more significant and was identified as a major contributor to indoor PM2.5 concentrations. Conversely, during the heating period (i.e., the colder part of the year), outdoor PM levels and household ventilation practices played primary roles in regulating indoor air concentrations. This present study presents one of the initial efforts to assess household air pollutants in Central Asia, providing foundation and insights into the indoor air quality of Kazakh houses, where the understanding of indoor air quality remains limited. Future research recommendations include developing advanced models that account for individual activity patterns and specific house types for improved accuracy and representativeness.","PeriodicalId":11735,"journal":{"name":"Engineering Reports","volume":"26 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139869015","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 work proposes the use of an unmanned aerial vehicle (UAV) with an autopilot to identify the defects present in municipal sewerage pipes. The framework also includes an effective autopilot control mechanism that can direct the flight path of a UAV within a sewer line. Both of these breakthroughs have been addressed throughout this work. The UAV's camera proved useful throughout a sewage inspection, providing important contextual data that helped analyze the sewerage line's internal condition. A plethora of information useful for understanding the sewerage line's inner functioning and extracting interior visual details can be obtained from camera‐recorded sewerage imagery if a defect is present. In the case of sewerage inspections, nevertheless, the impact of a false negative is significantly higher than that of a false positive. One of the trickiest parts of the procedure is identifying defective sewerage pipelines and false negatives. In order to get rid of the false negative outcome or false positive outcome, a guided image filter (GIF) is implemented in this proposed method during the pre‐processing stage. Afterwards, the algorithms Gabor transform (GT) and stroke width transform (SWT) were used to obtain the features of the UAV‐captured surveillance image. The UAV camera's sewerage image is then classified as “defective” or “not defective” using the obtained features by a Weighted Naive Bayes Classifier (WNBC). Next, images of the sewerage lines captured by the UAV are analyzed using speed‐up robust features (SURF) and deep learning to identify different types of defects. As a result, the proposed methodology achieved more favorable outcomes than prior existing approaches in terms of the following metrics: mean PSNR (71.854), mean MSE (0.0618), mean RMSE (0.2485), mean SSIM (98.71%), mean accuracy (98.372), mean specificity (97.837%), mean precision (93.296%), mean recall (94.255%), mean F1‐score (93.773%), and mean processing time (35.43 min).
{"title":"Autopilot control unmanned aerial vehicle system for sewage defect detection using deep learning","authors":"B. Pandey, Digvijay Pandey, S. K. Sahani","doi":"10.1002/eng2.12852","DOIUrl":"https://doi.org/10.1002/eng2.12852","url":null,"abstract":"This work proposes the use of an unmanned aerial vehicle (UAV) with an autopilot to identify the defects present in municipal sewerage pipes. The framework also includes an effective autopilot control mechanism that can direct the flight path of a UAV within a sewer line. Both of these breakthroughs have been addressed throughout this work. The UAV's camera proved useful throughout a sewage inspection, providing important contextual data that helped analyze the sewerage line's internal condition. A plethora of information useful for understanding the sewerage line's inner functioning and extracting interior visual details can be obtained from camera‐recorded sewerage imagery if a defect is present. In the case of sewerage inspections, nevertheless, the impact of a false negative is significantly higher than that of a false positive. One of the trickiest parts of the procedure is identifying defective sewerage pipelines and false negatives. In order to get rid of the false negative outcome or false positive outcome, a guided image filter (GIF) is implemented in this proposed method during the pre‐processing stage. Afterwards, the algorithms Gabor transform (GT) and stroke width transform (SWT) were used to obtain the features of the UAV‐captured surveillance image. The UAV camera's sewerage image is then classified as “defective” or “not defective” using the obtained features by a Weighted Naive Bayes Classifier (WNBC). Next, images of the sewerage lines captured by the UAV are analyzed using speed‐up robust features (SURF) and deep learning to identify different types of defects. As a result, the proposed methodology achieved more favorable outcomes than prior existing approaches in terms of the following metrics: mean PSNR (71.854), mean MSE (0.0618), mean RMSE (0.2485), mean SSIM (98.71%), mean accuracy (98.372), mean specificity (97.837%), mean precision (93.296%), mean recall (94.255%), mean F1‐score (93.773%), and mean processing time (35.43 min).","PeriodicalId":11735,"journal":{"name":"Engineering Reports","volume":"39 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140488599","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}
In recent years, penetration testing (pen‐testing) has emerged as a crucial process for evaluating the security level of network infrastructures by simulating real‐world cyber‐attacks. Automating pen‐testing through reinforcement learning (RL) facilitates more frequent assessments, minimizes human effort, and enhances scalability. However, real‐world pen‐testing tasks often involve incomplete knowledge of the target network system. Effectively managing the intrinsic uncertainties via partially observable Markov decision processes (POMDPs) constitutes a persistent challenge within the realm of pen‐testing. Furthermore, RL agents are compelled to formulate intricate strategies to contend with the challenges posed by partially observable environments, thereby engendering augmented computational and temporal expenditures. To address these issues, this study introduces EPPTA (efficient POMDP‐driven penetration testing agent), an agent built on an asynchronous RL framework, designed for conducting pen‐testing tasks within partially observable environments. We incorporate an implicit belief module in EPPTA, grounded on the belief update formula of the traditional POMDP model, which represents the agent's probabilistic estimation of the current environment state. Furthermore, by integrating the algorithm with the high‐performance RL framework, sample factory, EPPTA significantly reduces convergence time compared to existing pen‐testing methods, resulting in an approximately 20‐fold acceleration. Empirical results across various pen‐testing scenarios validate EPPTA's superior task reward performance and enhanced scalability, providing substantial support for efficient and advanced evaluation of network infrastructure security.
{"title":"EPPTA: Efficient partially observable reinforcement learning agent for penetration testing applications","authors":"Zegang Li, Qian Zhang, Guangwen Yang","doi":"10.1002/eng2.12818","DOIUrl":"https://doi.org/10.1002/eng2.12818","url":null,"abstract":"In recent years, penetration testing (pen‐testing) has emerged as a crucial process for evaluating the security level of network infrastructures by simulating real‐world cyber‐attacks. Automating pen‐testing through reinforcement learning (RL) facilitates more frequent assessments, minimizes human effort, and enhances scalability. However, real‐world pen‐testing tasks often involve incomplete knowledge of the target network system. Effectively managing the intrinsic uncertainties via partially observable Markov decision processes (POMDPs) constitutes a persistent challenge within the realm of pen‐testing. Furthermore, RL agents are compelled to formulate intricate strategies to contend with the challenges posed by partially observable environments, thereby engendering augmented computational and temporal expenditures. To address these issues, this study introduces EPPTA (efficient POMDP‐driven penetration testing agent), an agent built on an asynchronous RL framework, designed for conducting pen‐testing tasks within partially observable environments. We incorporate an implicit belief module in EPPTA, grounded on the belief update formula of the traditional POMDP model, which represents the agent's probabilistic estimation of the current environment state. Furthermore, by integrating the algorithm with the high‐performance RL framework, sample factory, EPPTA significantly reduces convergence time compared to existing pen‐testing methods, resulting in an approximately 20‐fold acceleration. Empirical results across various pen‐testing scenarios validate EPPTA's superior task reward performance and enhanced scalability, providing substantial support for efficient and advanced evaluation of network infrastructure security.","PeriodicalId":11735,"journal":{"name":"Engineering Reports","volume":"62 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138999089","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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