This research proposes control method to balance and stabilize an inverted pendulum. A robust control was analyzed and adjusted to the model output with real time feedback. The feedback was obtained using state space equation of the feedback controller. A linear quadratic regulator (LQR) model tuning and control was applied to the inverted pendulum using internet of things (IoT). The system's conditions and performance could be monitored and controlled via personal computer (PC) and mobile phone. Finally, the inverted pendulum was able to be controlled using the LQR controller and the IoT communication developed will monitor to check the all conditions and performance results as well as help the inverted pendulum improved various operations of IoT control is discussed.
{"title":"System design for inverted pendulum using LQR control via IoT","authors":"D. Maneetham, Petrus Sutyasadi","doi":"10.1051/smdo/2020007","DOIUrl":"https://doi.org/10.1051/smdo/2020007","url":null,"abstract":"This research proposes control method to balance and stabilize an inverted pendulum. A robust control was analyzed and adjusted to the model output with real time feedback. The feedback was obtained using state space equation of the feedback controller. A linear quadratic regulator (LQR) model tuning and control was applied to the inverted pendulum using internet of things (IoT). The system's conditions and performance could be monitored and controlled via personal computer (PC) and mobile phone. Finally, the inverted pendulum was able to be controlled using the LQR controller and the IoT communication developed will monitor to check the all conditions and performance results as well as help the inverted pendulum improved various operations of IoT control is discussed.","PeriodicalId":37601,"journal":{"name":"International Journal for Simulation and Multidisciplinary Design Optimization","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1051/smdo/2020007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58002393","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 take advantage of the physical principles of determining parameters, such as frequency stability, noise and also alignment of optical signals, it is necessary to control complex systems. This work allows explaining it through various concrete cases such as the determination of phase noise of microwave oscillators, the control of the temperature of the manufacturing process of optical components. We also discuss the estimation of the uncertainty associated with the measurement results, as it is fundamental to control the error range.
{"title":"Frequency and temperature control for complex system engineering in optoelectronics and electronics: an overview","authors":"P. Salzenstein","doi":"10.1051/smdo/2020001","DOIUrl":"https://doi.org/10.1051/smdo/2020001","url":null,"abstract":"To take advantage of the physical principles of determining parameters, such as frequency stability, noise and also alignment of optical signals, it is necessary to control complex systems. This work allows explaining it through various concrete cases such as the determination of phase noise of microwave oscillators, the control of the temperature of the manufacturing process of optical components. We also discuss the estimation of the uncertainty associated with the measurement results, as it is fundamental to control the error range.","PeriodicalId":37601,"journal":{"name":"International Journal for Simulation and Multidisciplinary Design Optimization","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1051/smdo/2020001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58001800","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}
H. Abubakar, Shamsul Rijal Muhammad Sabri, Sagir Abdu Masanawa, Surajo Yusuf
Election algorithm (EA) is a novel metaheuristics optimization model motivated by phenomena of the socio-political mechanism of presidential election conducted in many countries. The capability and robustness EA in finding an optimal solution to optimization has been proven by various researchers. In this paper, modified version of EA has been utilized in accelerating the searching capacity of Hopfield neural network (HNN) learning phase for optimal random-kSAT logical representation (HNN-R2SATEA). The utility of the proposed approach has been contrasted with the current standard exhaustive search algorithm (HNN-R2SATES) and the newly developed algorithm HNN-R2SATICA. From the analysis obtained, it has been clearly shown that the proposed hybrid computational model HNN-R2SATEA outperformed other existing model in terms of global minima ratio (Zm), mean absolute error (MAE), Bayesian information criterion (BIC) and execution time (ET). The finding portrays that the MEA algorithm surpassed the other two algorithms for optimal random-kSAT logical representation.
{"title":"Modified election algorithm in hopfield neural network for optimal random k satisfiability representation","authors":"H. Abubakar, Shamsul Rijal Muhammad Sabri, Sagir Abdu Masanawa, Surajo Yusuf","doi":"10.1051/smdo/2020008","DOIUrl":"https://doi.org/10.1051/smdo/2020008","url":null,"abstract":"Election algorithm (EA) is a novel metaheuristics optimization model motivated by phenomena of the socio-political mechanism of presidential election conducted in many countries. The capability and robustness EA in finding an optimal solution to optimization has been proven by various researchers. In this paper, modified version of EA has been utilized in accelerating the searching capacity of Hopfield neural network (HNN) learning phase for optimal random-kSAT logical representation (HNN-R2SATEA). The utility of the proposed approach has been contrasted with the current standard exhaustive search algorithm (HNN-R2SATES) and the newly developed algorithm HNN-R2SATICA. From the analysis obtained, it has been clearly shown that the proposed hybrid computational model HNN-R2SATEA outperformed other existing model in terms of global minima ratio (Zm), mean absolute error (MAE), Bayesian information criterion (BIC) and execution time (ET). The finding portrays that the MEA algorithm surpassed the other two algorithms for optimal random-kSAT logical representation.","PeriodicalId":37601,"journal":{"name":"International Journal for Simulation and Multidisciplinary Design Optimization","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58001984","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ali Tesfaye Kebede, E. Balasubramanian, A. Praveen, Lade Rohit, K. Arvind
Traditionally solid propellants are manufactured using casting and molding techniques. The effective burning rate of solid propellants is strongly depended on its cross section and geometry. The preparation of mold and mandrel for the manufacturability of various geometric profiles are tedious, time consuming, increases the cost and more human efforts are needed. In order to mitigate these issues, a disruptive technology called additive manufacturing (AM) is in the verge of development. Although the method is effective, additional study must be conducted to improve the flow characteristics of slurries for the high solid loading and there is a huge necessity to reduce the prolonged curing time. The present study focuses on preliminary investigations of extrusion of high viscosity slurry using a pneumatically driven extrusion system. The slurry was prepared with a 80 wt.% solid loading of NaCl having particle sizes of 45 µm and 150 µm, 15.6 wt.% HTPB, 2.2 wt.% TDI, 2.2 wt.% DOA and 0.03 wt.% of ferric acrylacetonate. The slurry was extruded with an aid of pneumatically controlled extruder and each layer was formed. Formed by extruding the slurry using 1.65 mm internal diameter nozzle. Infrared (IR) heater was utilized to transfer the radiational energy for partial curing of each layer and thereby adhesion of other layer was guaranteed. Simulation is performed to determine the temperature distribution using ANSYS platform for comparing the curing temperature of the printed part top surface. Preliminary experiments confirm that extrusion of slurry and heating of each layer can be effectively achieved with the proposed 3D printing technique. Three tensile specimens were produced in accordance with ASTMD 412-C and their corresponding mechanical properties are evaluated. The printed parts have the tensile strength of 0.7 MPa, elongation of 4.85 % and modulus of elasticity of 18.5 MPa which are comparable with the properties of conventional casted part.
{"title":"Preliminary investigations on extrusion of high viscosity slurry using direct writing technique","authors":"Ali Tesfaye Kebede, E. Balasubramanian, A. Praveen, Lade Rohit, K. Arvind","doi":"10.1051/smdo/2020012","DOIUrl":"https://doi.org/10.1051/smdo/2020012","url":null,"abstract":"Traditionally solid propellants are manufactured using casting and molding techniques. The effective burning rate of solid propellants is strongly depended on its cross section and geometry. The preparation of mold and mandrel for the manufacturability of various geometric profiles are tedious, time consuming, increases the cost and more human efforts are needed. In order to mitigate these issues, a disruptive technology called additive manufacturing (AM) is in the verge of development. Although the method is effective, additional study must be conducted to improve the flow characteristics of slurries for the high solid loading and there is a huge necessity to reduce the prolonged curing time. The present study focuses on preliminary investigations of extrusion of high viscosity slurry using a pneumatically driven extrusion system. The slurry was prepared with a 80 wt.% solid loading of NaCl having particle sizes of 45 µm and 150 µm, 15.6 wt.% HTPB, 2.2 wt.% TDI, 2.2 wt.% DOA and 0.03 wt.% of ferric acrylacetonate. The slurry was extruded with an aid of pneumatically controlled extruder and each layer was formed. Formed by extruding the slurry using 1.65 mm internal diameter nozzle. Infrared (IR) heater was utilized to transfer the radiational energy for partial curing of each layer and thereby adhesion of other layer was guaranteed. Simulation is performed to determine the temperature distribution using ANSYS platform for comparing the curing temperature of the printed part top surface. Preliminary experiments confirm that extrusion of slurry and heating of each layer can be effectively achieved with the proposed 3D printing technique. Three tensile specimens were produced in accordance with ASTMD 412-C and their corresponding mechanical properties are evaluated. The printed parts have the tensile strength of 0.7 MPa, elongation of 4.85 % and modulus of elasticity of 18.5 MPa which are comparable with the properties of conventional casted part.","PeriodicalId":37601,"journal":{"name":"International Journal for Simulation and Multidisciplinary Design Optimization","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1051/smdo/2020012","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58002187","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 present work combines ergonomics with the posture prediction in the assembly process to avoid musculoskeletal issues of human operator. For improved productivity the operator should be in a better work environment and in sound health. The purpose of this paper is to provide a different perspective to avoid ergonomic risk factors in manual assembly. Here, a human is modeled as 20-DOF as modeled in robotic analysis and simulated in a virtual environment. In the present study, two objective cost functions i.e. joint discomfort function and energy expenditure function have been employed for evaluating the optimized posture. For posture prediction, a combined multi-objective optimization (MOO) method is used and the objective cost functions are minimized i.e. less joint discomfort and less energy in MOO method required to do the manual assembly operation and consequently, the results are compared and finally the movements are tested using REBA technique.
{"title":"Posture prediction and optimization for a manual assembly operation involving lifting of weights","authors":"Biswaranjan Rout, R. R. Dash, D. Dhupal","doi":"10.1051/smdo/2019020","DOIUrl":"https://doi.org/10.1051/smdo/2019020","url":null,"abstract":"The present work combines ergonomics with the posture prediction in the assembly process to avoid musculoskeletal issues of human operator. For improved productivity the operator should be in a better work environment and in sound health. The purpose of this paper is to provide a different perspective to avoid ergonomic risk factors in manual assembly. Here, a human is modeled as 20-DOF as modeled in robotic analysis and simulated in a virtual environment. In the present study, two objective cost functions i.e. joint discomfort function and energy expenditure function have been employed for evaluating the optimized posture. For posture prediction, a combined multi-objective optimization (MOO) method is used and the objective cost functions are minimized i.e. less joint discomfort and less energy in MOO method required to do the manual assembly operation and consequently, the results are compared and finally the movements are tested using REBA technique.","PeriodicalId":37601,"journal":{"name":"International Journal for Simulation and Multidisciplinary Design Optimization","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1051/smdo/2019020","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58001552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
S. Patil, Venkatesh M. Mudaliar, P. Kamat, S. Gite
A chatbot is a software that can reproduce a discussion portraying a specific dimension of articulation among people and machines utilizing Natural Human Language. With the advent of AI, chatbots have developed from being minor guideline-based models to progressively modern models. A striking highlight of the current chatbot frameworks is their capacity to maintain and support explicit highlights and settings of the discussions empowering them to have human interaction in real-time surroundings. The paper presents a detailed database concerning the models utilized to deal with the learning of long haul conditions in a chatbot. The paper proposes a novel crossbreed Long Short Term Memory based Ensemble model to retain the information in specific situations. The proposed model uses a characterized number of Long Short Term Memory Networks as a significant aspect of its working as one to create the aggregate forecast class for the information inquiry and conversation. We found that both of the ensemble methods LSTM and GRU work well in different dataset environments and the ensemble technique is an effective one in chatbot applications.
{"title":"LSTM based Ensemble Network to enhance the learning of long-term dependencies in chatbot","authors":"S. Patil, Venkatesh M. Mudaliar, P. Kamat, S. Gite","doi":"10.1051/smdo/2020019","DOIUrl":"https://doi.org/10.1051/smdo/2020019","url":null,"abstract":"A chatbot is a software that can reproduce a discussion portraying a specific dimension of articulation among people and machines utilizing Natural Human Language. With the advent of AI, chatbots have developed from being minor guideline-based models to progressively modern models. A striking highlight of the current chatbot frameworks is their capacity to maintain and support explicit highlights and settings of the discussions empowering them to have human interaction in real-time surroundings. The paper presents a detailed database concerning the models utilized to deal with the learning of long haul conditions in a chatbot. The paper proposes a novel crossbreed Long Short Term Memory based Ensemble model to retain the information in specific situations. The proposed model uses a characterized number of Long Short Term Memory Networks as a significant aspect of its working as one to create the aggregate forecast class for the information inquiry and conversation. We found that both of the ensemble methods LSTM and GRU work well in different dataset environments and the ensemble technique is an effective one in chatbot applications.","PeriodicalId":37601,"journal":{"name":"International Journal for Simulation and Multidisciplinary Design Optimization","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1051/smdo/2020019","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58002153","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}
By setting two vortex tubes in hot cascade type Vortex tube manner, can achieve two cooling points for spot cooling applications with the single input. These cooling points play a vital role to cool tools in machining operations. The present work aims to optimize the output parameters such as outlet temperature, Coefficient of Performance (COP). Based on the literature, the performance of this vortex tube mainly depends on its input parameters such as air inlet pressure, length to diameter ratio, and the number of nozzles. In the present work, the above input parameters have been experimented on this vortex tube, based on the Taguchi L18 array. The optimal condition for both temperatures, COP at hot and cold outlets was calculated using grey relational analysis (GRA). The obtained experimental results were analyzed using the ANOVA approach. Also for multi responses, 1st and 2nd order predicted mathematical models developed by using Minitab 18 software and its accuracy checked. The achieved results are at first spot cooling point temperature 294.9 K, COPc1 as 0.0203, second spot cooling point temperature 284.2 K, and COPc2 as 0.1628. This work proved that for solving multi-attribute decision-making problems, grey relational analysis methodology was efficient.
{"title":"Multi-attribute decision making parametric optimization in two-stage hot cascade vortex tube through grey relational analysis","authors":"R. Madhu Kumar, N. Sudheer, K. Babu","doi":"10.1051/smdo/2020015","DOIUrl":"https://doi.org/10.1051/smdo/2020015","url":null,"abstract":"By setting two vortex tubes in hot cascade type Vortex tube manner, can achieve two cooling points for spot cooling applications with the single input. These cooling points play a vital role to cool tools in machining operations. The present work aims to optimize the output parameters such as outlet temperature, Coefficient of Performance (COP). Based on the literature, the performance of this vortex tube mainly depends on its input parameters such as air inlet pressure, length to diameter ratio, and the number of nozzles. In the present work, the above input parameters have been experimented on this vortex tube, based on the Taguchi L18 array. The optimal condition for both temperatures, COP at hot and cold outlets was calculated using grey relational analysis (GRA). The obtained experimental results were analyzed using the ANOVA approach. Also for multi responses, 1st and 2nd order predicted mathematical models developed by using Minitab 18 software and its accuracy checked. The achieved results are at first spot cooling point temperature 294.9 K, COPc1 as 0.0203, second spot cooling point temperature 284.2 K, and COPc2 as 0.1628. This work proved that for solving multi-attribute decision-making problems, grey relational analysis methodology was efficient.","PeriodicalId":37601,"journal":{"name":"International Journal for Simulation and Multidisciplinary Design Optimization","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58002260","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}
Hao Yue, D. Bassir, H. Medromi, Hua Ding, K. Abouzaid
In order to overcome the propre disadvantages of FW(Fixed-Wing) and VTOL(Vertical-Taking-Off-and-Landing) UAV (Unmanned Aerial Vehicle) and extend its application, the hybrid drone is invested more in recent years by researchers and several classifications are developed on the part of dual system. In this article, an innovative hybrid UAV is raised and studied by introducing the canard configuration that is coupled with conventional delta wing as well as winglet structure. Profited by Computational Fluid Dynamics (CFD) and Response Surface Method (RSM), a multilevel optimization approach is practically presented and concerned in terms of cruise flight mode: adopted by an experienced-based distribution strategy, the total lift object is respectively assigned into the delta wing (90–95%) and canard wing(5–10%) which is applied into a two-step optimization: the first optimization problem is solved only with the parameters concerned with delta wing afterwards the second optimization is successively concluded to develop the canard configuration considering the optimized delta wing conception. Above all, the optimal conceptual design of the delta and canard wing is realized by achieving the lift goal with less drag performance in cruise mode.
{"title":"Optimal design of Vertical-Taking-Off-and-Landing UAV wing using multilevel approach","authors":"Hao Yue, D. Bassir, H. Medromi, Hua Ding, K. Abouzaid","doi":"10.1051/smdo/2020020","DOIUrl":"https://doi.org/10.1051/smdo/2020020","url":null,"abstract":"In order to overcome the propre disadvantages of FW(Fixed-Wing) and VTOL(Vertical-Taking-Off-and-Landing) UAV (Unmanned Aerial Vehicle) and extend its application, the hybrid drone is invested more in recent years by researchers and several classifications are developed on the part of dual system. In this article, an innovative hybrid UAV is raised and studied by introducing the canard configuration that is coupled with conventional delta wing as well as winglet structure. Profited by Computational Fluid Dynamics (CFD) and Response Surface Method (RSM), a multilevel optimization approach is practically presented and concerned in terms of cruise flight mode: adopted by an experienced-based distribution strategy, the total lift object is respectively assigned into the delta wing (90–95%) and canard wing(5–10%) which is applied into a two-step optimization: the first optimization problem is solved only with the parameters concerned with delta wing afterwards the second optimization is successively concluded to develop the canard configuration considering the optimized delta wing conception. Above all, the optimal conceptual design of the delta and canard wing is realized by achieving the lift goal with less drag performance in cruise mode.","PeriodicalId":37601,"journal":{"name":"International Journal for Simulation and Multidisciplinary Design Optimization","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58002757","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}
Razamin Ramli, Siti Nurin Ima Ahmad, Syariza Abdul-Rahman, A. Wibowo
This paper presents an intelligent tabu search (TS) approach for solving a complex real-world nurse rostering problem (NRP). Previous study has suggested that improvement on neighborhoods and smart intensification of a TS could produce faster and fitted solution. In order to enhance the TS, this paper introduces an improvement to the neighborhoods and explores on the neighborhoods exploitations of TS to solve the NRP. The methodology consists of two phases: initialization and neighborhood. The semi-random initialization is employed for finding a good initial solution during the initialization phase which avoids the violation of hard constraints, while the neighborhood phase is established for further improving the solution quality with a special representation and innovative neighborhood generations within TS algorithm. The aim is to move sample points towards a high-quality solution while avoiding local optima by utilising a calculated force value. It is observed that the enhancement strategy could improve the solution quality of the constructed roster. It is concluded that the TS with enhancements approach is able to assign effective and efficient shift duties for the NRP especially when related with real-world working regulations and nurses preferences.
{"title":"A tabu search approach with embedded nurse preferences for solving nurse rostering problem","authors":"Razamin Ramli, Siti Nurin Ima Ahmad, Syariza Abdul-Rahman, A. Wibowo","doi":"10.1051/smdo/2020002","DOIUrl":"https://doi.org/10.1051/smdo/2020002","url":null,"abstract":"This paper presents an intelligent tabu search (TS) approach for solving a complex real-world nurse rostering problem (NRP). Previous study has suggested that improvement on neighborhoods and smart intensification of a TS could produce faster and fitted solution. In order to enhance the TS, this paper introduces an improvement to the neighborhoods and explores on the neighborhoods exploitations of TS to solve the NRP. The methodology consists of two phases: initialization and neighborhood. The semi-random initialization is employed for finding a good initial solution during the initialization phase which avoids the violation of hard constraints, while the neighborhood phase is established for further improving the solution quality with a special representation and innovative neighborhood generations within TS algorithm. The aim is to move sample points towards a high-quality solution while avoiding local optima by utilising a calculated force value. It is observed that the enhancement strategy could improve the solution quality of the constructed roster. It is concluded that the TS with enhancements approach is able to assign effective and efficient shift duties for the NRP especially when related with real-world working regulations and nurses preferences.","PeriodicalId":37601,"journal":{"name":"International Journal for Simulation and Multidisciplinary Design Optimization","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58001878","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 the present analysis, the effect of face width on the bending strength of spur gear has been studied. For this purpose face width of spur gear has been varied from 20 mm to 30 mm with a scale of 2 mm. Geometry of spur gear has been drawn using AutoCAD and the gear model has been simulated for bending stress using analysis software (ANSYS).Analytical equations (AGMA bending equations) have been used to find out analytical solution. Bending stress has been calculated at the gear tooth for different values of load. The simulation results have been compared with analytical solutions obtained using AGMA equations. It has been found from the results that increase in face width of spur gear results in decrease in bending stress and hence increase in bending strength.
{"title":"Effect of face width of spur gear on bending stress using AGMA and ANSYS","authors":"Hardial Singh, D. Kumar","doi":"10.1051/smdo/2020017","DOIUrl":"https://doi.org/10.1051/smdo/2020017","url":null,"abstract":"In the present analysis, the effect of face width on the bending strength of spur gear has been studied. For this purpose face width of spur gear has been varied from 20 mm to 30 mm with a scale of 2 mm. Geometry of spur gear has been drawn using AutoCAD and the gear model has been simulated for bending stress using analysis software (ANSYS).Analytical equations (AGMA bending equations) have been used to find out analytical solution. Bending stress has been calculated at the gear tooth for different values of load. The simulation results have been compared with analytical solutions obtained using AGMA equations. It has been found from the results that increase in face width of spur gear results in decrease in bending stress and hence increase in bending strength.","PeriodicalId":37601,"journal":{"name":"International Journal for Simulation and Multidisciplinary Design Optimization","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"58002348","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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