Pub Date : 2022-08-01DOI: 10.5604/01.3001.0016.1193
M. H. Ibrahim, N. Ishak, N.Z. Mukhtar, M. Basir, N. Said, K. Mohamed, M. Awang
To statistically analyse sitting posture using anthropometrics data among college students in Malaysia. This study was conducted among 52 college students consisting of males and females. Data were analysed using a common statistical tool which is the Statistical Package of Sosial Science (SPSS). Preliminary analysis of data indicated that there are wider differences in standard deviation of eye sitting height compared to the previous study conducted. This study was conducted at only one higher learning institution/college located at East Cost of Malaysia. The larger value of standard deviation discovered as statistical analysis performed using combined data among male and female participants suggested that data should be segregated. Result obtained could be used as a preliminary guideline to design any related item in related to sitting posture.
{"title":"Preliminary statistical analysis of anthropometrics data in related to sitting posture among college students at east coast Malaysia","authors":"M. H. Ibrahim, N. Ishak, N.Z. Mukhtar, M. Basir, N. Said, K. Mohamed, M. Awang","doi":"10.5604/01.3001.0016.1193","DOIUrl":"https://doi.org/10.5604/01.3001.0016.1193","url":null,"abstract":"To statistically analyse sitting posture using anthropometrics data among college students in Malaysia.\u0000\u0000This study was conducted among 52 college students consisting of males and females. Data were analysed using a common statistical tool which is the Statistical Package of Sosial Science (SPSS).\u0000\u0000Preliminary analysis of data indicated that there are wider differences in standard deviation of eye sitting height compared to the previous study conducted.\u0000\u0000This study was conducted at only one higher learning institution/college located at East Cost of Malaysia.\u0000\u0000The larger value of standard deviation discovered as statistical analysis performed using combined data among male and female participants suggested that data should be segregated.\u0000\u0000Result obtained could be used as a preliminary guideline to design any related item in related to sitting posture.\u0000\u0000","PeriodicalId":8297,"journal":{"name":"Archives of materials science and engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42703317","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}
Pub Date : 2022-08-01DOI: 10.5604/01.3001.0016.1190
M. Al-Shablle, M. Al-Waily, E. Njim
Developing structural designs that offer superior vibration properties is still a major challenge, but they stay solid and lightweight simultaneously. Composite faces are frequently used in insulating constructions as an alternative to sheet metal roofs. Rubber overlays have been added to reduce waves' natural frequency and fade time. The mechanical properties and the natural frequency calculation of the materials that make up the composite structural panels designed for structural applications with the addition of rubber layers were studied in this study. The results showed the addition of rubber layers with SiO2 nanoparticles with a density of 1180 kg m3, and the optimal decrease (VF = 2.5%) is 38.5% in the natural frequency while at a density of 1210 kg/m3, it is 40.2% in the natural frequency. While the addition of rubber layers with Al2O3 nanoparticles shows a density of 1180 kg/m3, the optimum reduction (VF = 2.5%) is 41% in HF while at a density of 1210 kg/m3 36.8% in an NF 41% during a density of 1210 kg/m3 38.4%. Certain hypotheses were used to apply Kirchhoff's theory to solve the mathematical model of the structure. The work was carried out on the faces of nanocomposites made of SiO2/epoxy and Al2O3/epoxy with different densities and polylactic acid core. The inclusion of nanoparticles as a percentage of the fraction size ranges from 0% to 2.50%. This study's results shed light on the fundamental behaviour of the components that make up the sandwich in the presence of rubber layers.
{"title":"Analytical evaluation of the influence of adding rubber layers on free vibration of sandwich structure with presence of nano-reinforced composite skins","authors":"M. Al-Shablle, M. Al-Waily, E. Njim","doi":"10.5604/01.3001.0016.1190","DOIUrl":"https://doi.org/10.5604/01.3001.0016.1190","url":null,"abstract":"Developing structural designs that offer superior vibration properties is still a major challenge, but they stay solid and lightweight simultaneously. Composite faces are frequently used in insulating constructions as an alternative to sheet metal roofs. Rubber overlays have been added to reduce waves' natural frequency and fade time.\u0000\u0000The mechanical properties and the natural frequency calculation of the materials that make up the composite structural panels designed for structural applications with the addition of rubber layers were studied in this study.\u0000\u0000The results showed the addition of rubber layers with SiO2 nanoparticles with a density of 1180 kg m3, and the optimal decrease (VF = 2.5%) is 38.5% in the natural frequency while at a density of 1210 kg/m3, it is 40.2% in the natural frequency. While the addition of rubber layers with Al2O3 nanoparticles shows a density of 1180 kg/m3, the optimum reduction (VF = 2.5%) is 41% in HF while at a density of 1210 kg/m3 36.8% in an NF 41% during a density of 1210 kg/m3 38.4%.\u0000\u0000Certain hypotheses were used to apply Kirchhoff's theory to solve the mathematical model of the structure.\u0000\u0000The work was carried out on the faces of nanocomposites made of SiO2/epoxy and Al2O3/epoxy with different densities and polylactic acid core. The inclusion of nanoparticles as a percentage of the fraction size ranges from 0% to 2.50%.\u0000\u0000This study's results shed light on the fundamental behaviour of the components that make up the sandwich in the presence of rubber layers.\u0000\u0000","PeriodicalId":8297,"journal":{"name":"Archives of materials science and engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41687267","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}
Pub Date : 2022-08-01DOI: 10.5604/01.3001.0016.1191
A. Trostianchyn, I. Izonin, Z. Duriagina, R. Tkachenko, V. Kulyk, B. Havrysh
This paper aims to decide the Sm-Co alloy’s maximum energy product prediction task based on the boosting strategy of the ensemble of machine learning methods. This paper examines an ensemble-based approach to solving Sm-Co alloy’s maximum energy product prediction task. Because classical machine learning methods sometimes do not supply acceptable precision when solving the regression problem, the authors investigated the boosting ML model, namely Gradient Boosting. Building a boosting model based on several weak submodels, each of which considers the errors of the prior ones, provides substantial growth in the accuracy of the problem-solving. The obtained result is confirmed using an actual data set collected by the authors. This work demonstrates the high efficiency of applying the ensemble strategy of machine learning to the applied problem of materials science. The experiments determined the highest accuracy of solving the forecast task for the maximum energy product of Sm-Co alloy formed on the boosting model of machine learning in comparison with classical methods of machine learning. The boosting strategy of machine learning, in comparison with single algorithms of machine learning, requires much more computational and time resources to implement the learning process of the model. This work demonstrated the possibility of effectively solving Sm-Co alloy’s maximum energy product prediction task using machine learning. The studied boosting model of machine learning for solving the problem provides high accuracy of prediction, which reveals several advantages of their use in solving issues applied to computational material science. Furthermore, using the Orange modelling environment provides a simple and intuitive interface for using the researched methods. The proposed approach to the forecast significantly reduces the time and resource costs associated with studying expensive rare earth metals (REM)-based ferromagnetic materials. The authors have collected and formed a set of data on predicting the maximum energy product of the Sm-Co alloy. We used machine learning tools to solve the task. As a result, the most increased forecasting precision based on the boosting model is demonstrated compared to classical machine learning methods.
{"title":"Boosting-based model for solving Sm-Co alloy’s maximum energy product prediction task","authors":"A. Trostianchyn, I. Izonin, Z. Duriagina, R. Tkachenko, V. Kulyk, B. Havrysh","doi":"10.5604/01.3001.0016.1191","DOIUrl":"https://doi.org/10.5604/01.3001.0016.1191","url":null,"abstract":"This paper aims to decide the Sm-Co alloy’s maximum energy product prediction task based on the boosting strategy of the ensemble of machine learning methods.\u0000\u0000This paper examines an ensemble-based approach to solving Sm-Co alloy’s maximum energy product prediction task. Because classical machine learning methods sometimes do not supply acceptable precision when solving the regression problem, the authors investigated the boosting ML model, namely Gradient Boosting. Building a boosting model based on several weak submodels, each of which considers the errors of the prior ones, provides substantial growth in the accuracy of the problem-solving. The obtained result is confirmed using an actual data set collected by the authors.\u0000\u0000This work demonstrates the high efficiency of applying the ensemble strategy of machine learning to the applied problem of materials science. The experiments determined the highest accuracy of solving the forecast task for the maximum energy product of Sm-Co alloy formed on the boosting model of machine learning in comparison with classical methods of machine learning.\u0000\u0000The boosting strategy of machine learning, in comparison with single algorithms of machine learning, requires much more computational and time resources to implement the learning process of the model.\u0000\u0000This work demonstrated the possibility of effectively solving Sm-Co alloy’s maximum energy product prediction task using machine learning. The studied boosting model of machine learning for solving the problem provides high accuracy of prediction, which reveals several advantages of their use in solving issues applied to computational material science. Furthermore, using the Orange modelling environment provides a simple and intuitive interface for using the researched methods. The proposed approach to the forecast significantly reduces the time and resource costs associated with studying expensive rare earth metals (REM)-based ferromagnetic materials.\u0000\u0000The authors have collected and formed a set of data on predicting the maximum energy product of the Sm-Co alloy. We used machine learning tools to solve the task. As a result, the most increased forecasting precision based on the boosting model is demonstrated compared to classical machine learning methods.\u0000\u0000","PeriodicalId":8297,"journal":{"name":"Archives of materials science and engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46600469","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}
Pub Date : 2022-08-01DOI: 10.5604/01.3001.0016.1189
E. Abdeddine, A. Majid, Z. Beidouri, K. Zarbane
The aim of this paper is to investigate experimentally the effect of large vibration of a cantilever and a fully free rectangular plate made by a Fused Filament Fabrication process. Furthermore, this investigation attempts to compare our measurements and those obtained in the literature experimentally. For this purpose, a test rig was designed and manufactured for all experimental trials. The plate was excited randomly and harmonically at large displacement respectively, to obtain the linear and non-linear frequencies parameter. The non-linear dynamic behaviour of our structure at forced vibration is figured by exciting the plate at large displacement. The dependence of frequency and amplitude vibration are examined for the first, second, and third mode shapes. The non-linear dynamic behaviour of cantilever plates is compared with literature to illustrate the convergence of our results by using our specific mechanical properties, printing parameters, and process. Furthermore, the non-dimensional comparison is shown by 33.38%, 5.83%, and 20.58% for the first, second, and third mode shapes, respectively. Experimental tests will be performed on a 3D-printed metal plate to improve the present work. This work is intended to determine the dynamic proprieties of our parts in order to manufacture a safe and comfort machine. Actually, the dynamic behaviour of our 3D printing plates is compared with the obtained in the case of the isotropic plate for the aim to predict the convergence of both structures.
{"title":"Experimental investigation for non-linear vibrations of free supported and cantilever FFF rectangular plates","authors":"E. Abdeddine, A. Majid, Z. Beidouri, K. Zarbane","doi":"10.5604/01.3001.0016.1189","DOIUrl":"https://doi.org/10.5604/01.3001.0016.1189","url":null,"abstract":"The aim of this paper is to investigate experimentally the effect of large vibration of a cantilever and a fully free rectangular plate made by a Fused Filament Fabrication process. Furthermore, this investigation attempts to compare our measurements and those obtained in the literature experimentally.\u0000\u0000For this purpose, a test rig was designed and manufactured for all experimental trials. The plate was excited randomly and harmonically at large displacement respectively, to obtain the linear and non-linear frequencies parameter.\u0000\u0000The non-linear dynamic behaviour of our structure at forced vibration is figured by exciting the plate at large displacement. The dependence of frequency and amplitude vibration are examined for the first, second, and third mode shapes. The non-linear dynamic behaviour of cantilever plates is compared with literature to illustrate the convergence of our results by using our specific mechanical properties, printing parameters, and process. Furthermore, the non-dimensional comparison is shown by 33.38%, 5.83%, and 20.58% for the first, second, and third mode shapes, respectively.\u0000\u0000Experimental tests will be performed on a 3D-printed metal plate to improve the present work.\u0000\u0000This work is intended to determine the dynamic proprieties of our parts in order to manufacture a safe and comfort machine.\u0000\u0000Actually, the dynamic behaviour of our 3D printing plates is compared with the obtained in the case of the isotropic plate for the aim to predict the convergence of both structures.\u0000\u0000","PeriodicalId":8297,"journal":{"name":"Archives of materials science and engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47934820","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}
Pub Date : 2022-07-01DOI: 10.5604/01.3001.0016.0978
S. Ramadevi, S. Meenakshi
Nanotechnology is one of the highly evolving fields of research having immense potential in various fields of healthcare sectors. The very advent of nanotechnology lies in its ability to serve as a targeted drug delivery system. The introduction of a new branch namely bionanotechnology has further expanded the scope, especially in the diagnostics and treatment of various diseases. Probiotics being a natural source with a plethora of beneficial properties have been investigated actively in recent days. Probiotics administered into the digestive system have been shown to promote gut health by increasing the microbial balance in the gut. However, the bioavailability of such administered probiotics remains a major concern. These probiotics are protected through microencapsulation techniques, which encapsulate them in small capsules. Several nanoparticles with varied dimensions, forms, surfaces and composites have recently been investigated for probiotic microencapsulation. This has been used for various therapeutic applications, such as drug delivery. This review gives an insight on various materials and strategies used for probiotic encapsulation. The main aim of this review is to give a perception of the different types of methods of probiotic encapsulation. This review implies the significance of probiotics and subsequent active release in the gastrointestinal system. Different sections of this review paper, on the other hand, may offer up new opportunities for comprehensive research in the field of microencapsulation for boosting probiotic viability and also talks about the various encapsulating materials that has been employed. This review emphasizes more perceptions about the ongoing and imminent techniques for encapsulating probiotics.
{"title":"An epitome on encapsulation of probiotics","authors":"S. Ramadevi, S. Meenakshi","doi":"10.5604/01.3001.0016.0978","DOIUrl":"https://doi.org/10.5604/01.3001.0016.0978","url":null,"abstract":"Nanotechnology is one of the highly evolving fields of research having immense potential in various fields of healthcare sectors. The very advent of nanotechnology lies in its ability to serve as a targeted drug delivery system. The introduction of a new branch namely bionanotechnology has further expanded the scope, especially in the diagnostics and treatment of various diseases. Probiotics being a natural source with a plethora of beneficial properties have been investigated actively in recent days. Probiotics administered into the digestive system have been shown to promote gut health by increasing the microbial balance in the gut. However, the bioavailability of such administered probiotics remains a major concern. These probiotics are protected through microencapsulation techniques, which encapsulate them in small capsules. Several nanoparticles with varied dimensions, forms, surfaces and composites have recently been investigated for probiotic microencapsulation. This has been used for various therapeutic applications, such as drug delivery. This review gives an insight on various materials and strategies used for probiotic encapsulation.\u0000\u0000The main aim of this review is to give a perception of the different types of methods of probiotic encapsulation.\u0000\u0000This review implies the significance of probiotics and subsequent active release in the gastrointestinal system. Different sections of this review paper, on the other hand, may offer up new opportunities for comprehensive research in the field of microencapsulation for boosting probiotic viability and also talks about the various encapsulating materials that has been employed.\u0000\u0000This review emphasizes more perceptions about the ongoing and imminent techniques for encapsulating probiotics.\u0000\u0000","PeriodicalId":8297,"journal":{"name":"Archives of materials science and engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46404603","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}
Pub Date : 2022-07-01DOI: 10.5604/01.3001.0016.0972
A. A. Nayeeif, Z. K. Hamdan, Z. W. Metteb, F. A. Abdulla, N. A. Jebur
The first goal is to get rid of waste and reduce environmental pollution, and the other goal is to investigate the effect of these fibres on properties (resistance of composite materials for bending and tensile testing) of polyester and use them in applications. Also, The moisture environment effect on the properties of composite materials was studied. It uses natural fibres, which are considered waste, namely eggshell and sawdust with polyester. Several samples were prepared with different weight percentages (30% and 40%), and their mechanical properties were studied and immersed in water for 15 days. And studying the effect of water on these properties. It was found that it is possible to use these fibres (waste) with polyester and benefit from them. It was found that when adding fibres to polyester, the tensile strength decreases, but the bending increases the strength. Finally, it was found that when the samples are immersed in water, the material weakens, and its mechanical properties decrease. It can be noticed that adding natural fibres by 40% and 30% improved the mechanical properties of polyester in the bending test, where the bending test increased with increased volume fraction of fibre. It can be noticed that adding natural fibres by 40% and 30% decreased the mechanical properties (tensile strength) of polyester in a tensile test. When the natural composite materials were treated with water for 15 days, water decreased the mechanical properties in bending and tensile test. One of the limitations of this research that was found through the work is that when increasing the weight ratios of the fibres added to polyester leads to the failure of polyester, so we recommend using lower weight ratios of fibre. One of the limitations of this research that was found through the work is that when increasing the weight ratios of the fibres added to polyester leads to the failure of polyester, so we recommend using lower weight ratios of fibre.
{"title":"Natural filler based composite materials","authors":"A. A. Nayeeif, Z. K. Hamdan, Z. W. Metteb, F. A. Abdulla, N. A. Jebur","doi":"10.5604/01.3001.0016.0972","DOIUrl":"https://doi.org/10.5604/01.3001.0016.0972","url":null,"abstract":"The first goal is to get rid of waste and reduce environmental pollution, and the other goal is to investigate the effect of these fibres on properties (resistance of composite materials for bending and tensile testing) of polyester and use them in applications. Also, The moisture environment effect on the properties of composite materials was studied.\u0000\u0000It uses natural fibres, which are considered waste, namely eggshell and sawdust with polyester. Several samples were prepared with different weight percentages (30% and 40%), and their mechanical properties were studied and immersed in water for 15 days. And studying the effect of water on these properties. It was found that it is possible to use these fibres (waste) with polyester and benefit from them. It was found that when adding fibres to polyester, the tensile strength decreases, but the bending increases the strength. Finally, it was found that when the samples are immersed in water, the material weakens, and its mechanical properties decrease.\u0000\u0000It can be noticed that adding natural fibres by 40% and 30% improved the mechanical properties of polyester in the bending test, where the bending test increased with increased volume fraction of fibre. It can be noticed that adding natural fibres by 40% and 30% decreased the mechanical properties (tensile strength) of polyester in a tensile test. When the natural composite materials were treated with water for 15 days, water decreased the mechanical properties in bending and tensile test.\u0000\u0000One of the limitations of this research that was found through the work is that when increasing the weight ratios of the fibres added to polyester leads to the failure of polyester, so we recommend using lower weight ratios of fibre.\u0000\u0000One of the limitations of this research that was found through the work is that when increasing the weight ratios of the fibres added to polyester leads to the failure of polyester, so we recommend using lower weight ratios of fibre.\u0000\u0000","PeriodicalId":8297,"journal":{"name":"Archives of materials science and engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46219034","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}
Pub Date : 2022-07-01DOI: 10.5604/01.3001.0016.0975
A. Gupta, Y. Aggarwal, P. Aggarwal
Application of deep neural networks (DNN) and ensemble of ANN with bagging for estimating of factor of safety (FOS) of soil stability with a comparative performance analysis done for all techniques. 1000 cases with different geotechnical and similar Geometrical properties were collected and analysed using the Limit Equilibrium based Morgenstern-Price Method with input variables as the strength parameters of the soil layers, i.e., Su (Upper Clay), Su (Lower Clay), Su (Peat), angle of internal friction (φ), Su (Embankment) with the factor of safety (FOS) as output. The evaluation and comparison of the performance of predicted models with cross-validation having ten folds were made based on correlation-coefficient (CC), Nash-Sutcliffe-model efficiency-coefficient (NSE), root-mean-square-error (RMSE), mean-absolute-error (MAE) and scattering-index (S.I.). Sensitivity analysis was conducted for the effects of input variables on FOS of soil stability based on their importance. The results showed that these techniques have great capability and reflect that the proposed model by DNN can enhance performance of the model, surpassing ensemble in prediction. The Sensitivity analysis outcome demonstrated that Su (Lower Clay) significantly affected the factor of safety (FOS), trailed by Su (Peat). This paper sets sight on use of deep neural network (DNN) and ensemble of ANN with bagging for estimating of factor of safety (FOS) of soil stability. The current approach helps to understand the tangled relationship of various inputs to estimate the factor of safety of soil stability using DNN and ensemble of ANN with bagging. A dependable prediction tool is provided, which suggests that model can help scientists and engineers optimise FOS of soil stability. Recently, DNN and ensemble of ANN with bagging have been used in various civil engineering problems as reported by several studies and has also been observed to be outperforming the current prevalent modelling techniques. DNN can signify extremely changing and intricate high-dimensional functions in correlation to conventional neural networks. But on a detailed literature review, the application of these techniques to estimate factor of safety of soil stability has not been observed.
{"title":"Deep neural network and ANN ensemble for slope stability prediction","authors":"A. Gupta, Y. Aggarwal, P. Aggarwal","doi":"10.5604/01.3001.0016.0975","DOIUrl":"https://doi.org/10.5604/01.3001.0016.0975","url":null,"abstract":"Application of deep neural networks (DNN) and ensemble of ANN with bagging for estimating of factor of safety (FOS) of soil stability with a comparative performance analysis done for all techniques.\u0000\u00001000 cases with different geotechnical and similar Geometrical properties were collected and analysed using the Limit Equilibrium based Morgenstern-Price Method with input variables as the strength parameters of the soil layers, i.e., Su (Upper Clay), Su (Lower Clay), Su (Peat), angle of internal friction (φ), Su (Embankment) with the factor of safety (FOS) as output. The evaluation and comparison of the performance of predicted models with cross-validation having ten folds were made based on correlation-coefficient (CC), Nash-Sutcliffe-model efficiency-coefficient (NSE), root-mean-square-error (RMSE), mean-absolute-error (MAE) and scattering-index (S.I.). Sensitivity analysis was conducted for the effects of input variables on FOS of soil stability based on their importance.\u0000\u0000The results showed that these techniques have great capability and reflect that the proposed model by DNN can enhance performance of the model, surpassing ensemble in prediction. The Sensitivity analysis outcome demonstrated that Su (Lower Clay) significantly affected the factor of safety (FOS), trailed by Su (Peat).\u0000\u0000This paper sets sight on use of deep neural network (DNN) and ensemble of ANN with bagging for estimating of factor of safety (FOS) of soil stability. The current approach helps to understand the tangled relationship of various inputs to estimate the factor of safety of soil stability using DNN and ensemble of ANN with bagging.\u0000\u0000A dependable prediction tool is provided, which suggests that model can help scientists and engineers optimise FOS of soil stability.\u0000\u0000Recently, DNN and ensemble of ANN with bagging have been used in various civil engineering problems as reported by several studies and has also been observed to be outperforming the current prevalent modelling techniques. DNN can signify extremely changing and intricate high-dimensional functions in correlation to conventional neural networks. But on a detailed literature review, the application of these techniques to estimate factor of safety of soil stability has not been observed.\u0000\u0000","PeriodicalId":8297,"journal":{"name":"Archives of materials science and engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47313433","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}
Pub Date : 2022-07-01DOI: 10.5604/01.3001.0016.0976
M. Hassan, Z. Rashid, R. A. Sarhan
The study of cracks behaviour in a composite plate is of significant importance in the dynamics of the Mechanical parts in order to avoid design failures due to resonance or high amplitude vibrations. In this paper, a square glass-epoxy composite plate is adopted. The plate has four layers with symmetric and asymmetric lamination. Assuming the cracks are profound as defects. The results were obtained by using a numerical solution of mechanical APDL from ANSYS. It has been found for different boundary conditions that the rank of natural frequencies is decreased by increasing the crack ratio due to the reduction of the plate’s stiffness, whereas the crack direction has no mentioned effect for a small angle of rotation. The accuracy of results is verified by comparing a single case of the current work with other previous investigations. Evaluate the influence of the crack length ratio, angle of the crack rotation, boundary conditions and lamination angles on the natural frequencies of the square composite plate with glass-epoxy materials.
{"title":"Study the internal cracks effect on vibration of laminated composite square plates","authors":"M. Hassan, Z. Rashid, R. A. Sarhan","doi":"10.5604/01.3001.0016.0976","DOIUrl":"https://doi.org/10.5604/01.3001.0016.0976","url":null,"abstract":"The study of cracks behaviour in a composite plate is of significant importance in the dynamics of the Mechanical parts in order to avoid design failures due to resonance or high amplitude vibrations.\u0000\u0000In this paper, a square glass-epoxy composite plate is adopted. The plate has four layers with symmetric and asymmetric lamination. Assuming the cracks are profound as defects. The results were obtained by using a numerical solution of mechanical APDL from ANSYS.\u0000\u0000It has been found for different boundary conditions that the rank of natural frequencies is decreased by increasing the crack ratio due to the reduction of the plate’s stiffness, whereas the crack direction has no mentioned effect for a small angle of rotation.\u0000\u0000The accuracy of results is verified by comparing a single case of the current work with other previous investigations.\u0000\u0000Evaluate the influence of the crack length ratio, angle of the crack rotation, boundary conditions and lamination angles on the natural frequencies of the square composite plate with glass-epoxy materials.\u0000\u0000","PeriodicalId":8297,"journal":{"name":"Archives of materials science and engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42515031","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}
Pub Date : 2022-06-01DOI: 10.5604/01.3001.0016.0752
A. Dubey, A. Rasool
Deep learning is a predominant branch in machine learning, which is inspired by the operation of the human biological brain in processing information and capturing insights. Machine learning evolved to deep learning, which helps to reduce the involvement of an expert. In machine learning, the performance depends on what the expert extracts manner features, but deep neural networks are self-capable for extracting features. Deep learning performs well with a large amount of data than traditional machine learning algorithms, and also deep neural networks can give better results with different kinds of unstructured data. Deep learning is an inevitable approach in real-world applications such as computer vision where information from the visual world is extracted, in the field of natural language processing involving analyzing and understanding human languages in its meaningful way, in the medical area for diagnosing and detection, in the forecasting of weather and other natural processes, in field of cybersecurity to provide a continuous functioning for computer systems and network from attack or harm, in field of navigation and so on. Due to these advantages, deep learning algorithms are applied to a variety of complex tasks. With the help of deep learning, the tasks that had been said as unachievable can be solved. This paper describes the brief study of the real-world application problems domain with deep learning solutions.
{"title":"Usage of deep learning in recent applications","authors":"A. Dubey, A. Rasool","doi":"10.5604/01.3001.0016.0752","DOIUrl":"https://doi.org/10.5604/01.3001.0016.0752","url":null,"abstract":"Deep learning is a predominant branch in machine learning, which is inspired by the operation of the human biological brain in processing information and capturing insights. Machine learning evolved to deep learning, which helps to reduce the involvement of an expert. In machine learning, the performance depends on what the expert extracts manner features, but deep neural networks are self-capable for extracting features.\u0000\u0000Deep learning performs well with a large amount of data than traditional machine learning algorithms, and also deep neural networks can give better results with different kinds of unstructured data.\u0000\u0000Deep learning is an inevitable approach in real-world applications such as computer vision where information from the visual world is extracted, in the field of natural language processing involving analyzing and understanding human languages in its meaningful way, in the medical area for diagnosing and detection, in the forecasting of weather and other natural processes, in field of cybersecurity to provide a continuous functioning for computer systems and network from attack or harm, in field of navigation and so on.\u0000\u0000Due to these advantages, deep learning algorithms are applied to a variety of complex tasks. With the help of deep learning, the tasks that had been said as unachievable can be solved.\u0000\u0000This paper describes the brief study of the real-world application problems domain with deep learning solutions.\u0000\u0000","PeriodicalId":8297,"journal":{"name":"Archives of materials science and engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49081273","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}
Pub Date : 2022-06-01DOI: 10.5604/01.3001.0016.0755
Nagentrau Muniandy, N. H. Ibrahim, S. Jamian, A. L. M. Mohd Tobi
Present paper addresses the formulation of delamination-fretting wear failure predictive equation in HAp-Ti-6Al-4V interface of hip arthroplasty femoral stem component using multiple linear regression model. A finite element computational model utilising adaptive meshing algorithm via ABAQUS/Standard user subroutine UMESHMOTION is developed. The developed FE model is employed to examine effect of different HAp-Ti-6Al-4V interface mechanical and tribological properties on delamination-fretting wear behaviour. The FE result is utilised to formulate predictive equations for different stress ratio conditions using multiple linear regression analysis. Delamination-fretting wear predictive equations are successfully formulated with significant goodness of fit and reliability as a fast failure prediction tool in HAp coated hip arthroplasty. The robustness of predictive equations is validated as good agreement is noted with actual delamination-fretting wear results. The influence of different mechanical and tribological properties such as delamination length, normal loading, fatigue loading, bone elastic modulus and cycle number under different stress ratio on delamination-fretting wear failure is analysed to formulate failure predictive equations. The formulated predictive equation can serve as a fast delamination-fretting wear failure prediction tool in hip arthroplasty femoral stem component. Limited attempt is done to explore the potential of utilizing multiple linear regression model to predict failures in hip arthroplasty. Thus, present study attempt to formulate delamination-fretting wear failure predictive equation in HAp -Ti-6Al-4V interface of hip arthroplasty femoral stem component using multiple linear regression model.
{"title":"Formulating delamination-fretting wear failure predictive equation in HAp coated hip arthroplasty using multiple linear regression model","authors":"Nagentrau Muniandy, N. H. Ibrahim, S. Jamian, A. L. M. Mohd Tobi","doi":"10.5604/01.3001.0016.0755","DOIUrl":"https://doi.org/10.5604/01.3001.0016.0755","url":null,"abstract":"Present paper addresses the formulation of delamination-fretting wear failure predictive equation in HAp-Ti-6Al-4V interface of hip arthroplasty femoral stem component using multiple linear regression model.\u0000\u0000A finite element computational model utilising adaptive meshing algorithm via ABAQUS/Standard user subroutine UMESHMOTION is developed. The developed FE model is employed to examine effect of different HAp-Ti-6Al-4V interface mechanical and tribological properties on delamination-fretting wear behaviour. The FE result is utilised to formulate predictive equations for different stress ratio conditions using multiple linear regression analysis.\u0000\u0000Delamination-fretting wear predictive equations are successfully formulated with significant goodness of fit and reliability as a fast failure prediction tool in HAp coated hip arthroplasty. The robustness of predictive equations is validated as good agreement is noted with actual delamination-fretting wear results.\u0000\u0000The influence of different mechanical and tribological properties such as delamination length, normal loading, fatigue loading, bone elastic modulus and cycle number under different stress ratio on delamination-fretting wear failure is analysed to formulate failure predictive equations.\u0000\u0000The formulated predictive equation can serve as a fast delamination-fretting wear failure prediction tool in hip arthroplasty femoral stem component.\u0000\u0000Limited attempt is done to explore the potential of utilizing multiple linear regression model to predict failures in hip arthroplasty. Thus, present study attempt to formulate delamination-fretting wear failure predictive equation in HAp -Ti-6Al-4V interface of hip arthroplasty femoral stem component using multiple linear regression model.\u0000\u0000","PeriodicalId":8297,"journal":{"name":"Archives of materials science and engineering","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47289524","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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