A novel multibody dynamics modeling method is proposed for two-dimensional (2D) team lifting prediction. The box itself is modeled as a floating-base rigid body in Denavit-Hartenberg representation. The interactions between humans and box are modeled as a set of grasping forces which are treated as unknowns (design variables) in the optimization formulation. An inverse-dynamics-based optimization method is used to simulate the team lifting motion where the dynamic effort of two humans is minimized subjected to physical and task-based constraints. The design variables are control points of cubic B-splines of joint angle profiles of two humans and the box, and the grasping forces between humans and the box. Two numerical examples are successfully simulated with different box weights (20 Kg and 30 Kg, respectively). The humans’ joint angle, torque, ground reaction force, and grasping force profiles are reported. The joint angle profiles are validated with the experimental data.
{"title":"Two-Dimensional Team Lifting Prediction With Different Box Weights","authors":"Asif Arefeen, Y. Xiang","doi":"10.1115/detc2020-22115","DOIUrl":"https://doi.org/10.1115/detc2020-22115","url":null,"abstract":"\u0000 A novel multibody dynamics modeling method is proposed for two-dimensional (2D) team lifting prediction. The box itself is modeled as a floating-base rigid body in Denavit-Hartenberg representation. The interactions between humans and box are modeled as a set of grasping forces which are treated as unknowns (design variables) in the optimization formulation. An inverse-dynamics-based optimization method is used to simulate the team lifting motion where the dynamic effort of two humans is minimized subjected to physical and task-based constraints. The design variables are control points of cubic B-splines of joint angle profiles of two humans and the box, and the grasping forces between humans and the box. Two numerical examples are successfully simulated with different box weights (20 Kg and 30 Kg, respectively). The humans’ joint angle, torque, ground reaction force, and grasping force profiles are reported. The joint angle profiles are validated with the experimental data.","PeriodicalId":164403,"journal":{"name":"Volume 9: 40th Computers and Information in Engineering Conference (CIE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125458466","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}
Aditya Balu, Sambit Ghadai, S. Sarkar, A. Krishnamurthy
Computer-aided Design for Manufacturing (DFM) systems play an essential role in reducing the time taken for product development by providing manufacturability feedback to the designer before the manufacturing phase. Traditionally, DFM rules are hand-crafted and used to accelerate the engineering product design process by integrating manufacturability analysis during design. Recently, the feasibility of using a machine learning-based DFM tool in intelligently applying the DFM rules have been studied. These tools use a voxelized representation of the design and then use a 3D-Convolutional Neural Network (3D-CNN), to provide manufacturability feedback. Although these frameworks work effectively, there are some limitations to the voxelized representation of the design. In this paper, we introduce a new representation of the computer-aided design (CAD) model using orthogonal distance fields (ODF). We provide a GPU-accelerated algorithm to convert standard boundary representation (B-rep) CAD models into ODF representation. Using the ODF representation, we build a machine learning framework, similar to earlier approaches, to create a machine learning-based DFM system to provide manufacturability feedback. As proof of concept, we apply this framework to assess the manufacturability of drilled holes. The framework has an accuracy of more than 84% correctly classifying the manufacturable and non-manufacturable models using the new representation.
{"title":"Orthogonal Distance Fields Representation for Machine-Learning Based Manufacturability Analysis","authors":"Aditya Balu, Sambit Ghadai, S. Sarkar, A. Krishnamurthy","doi":"10.1115/detc2020-22487","DOIUrl":"https://doi.org/10.1115/detc2020-22487","url":null,"abstract":"\u0000 Computer-aided Design for Manufacturing (DFM) systems play an essential role in reducing the time taken for product development by providing manufacturability feedback to the designer before the manufacturing phase. Traditionally, DFM rules are hand-crafted and used to accelerate the engineering product design process by integrating manufacturability analysis during design. Recently, the feasibility of using a machine learning-based DFM tool in intelligently applying the DFM rules have been studied. These tools use a voxelized representation of the design and then use a 3D-Convolutional Neural Network (3D-CNN), to provide manufacturability feedback. Although these frameworks work effectively, there are some limitations to the voxelized representation of the design. In this paper, we introduce a new representation of the computer-aided design (CAD) model using orthogonal distance fields (ODF). We provide a GPU-accelerated algorithm to convert standard boundary representation (B-rep) CAD models into ODF representation. Using the ODF representation, we build a machine learning framework, similar to earlier approaches, to create a machine learning-based DFM system to provide manufacturability feedback. As proof of concept, we apply this framework to assess the manufacturability of drilled holes. The framework has an accuracy of more than 84% correctly classifying the manufacturable and non-manufacturable models using the new representation.","PeriodicalId":164403,"journal":{"name":"Volume 9: 40th Computers and Information in Engineering Conference (CIE)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124926210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The goal of this paper is to develop the groundwork for automated synthesis of function models. To this end, an evolutionary algorithm based framework has been developed. A parameterization method that can completely describe any given function models has been proposed. The parameterization makes the function models compatible for use within the evolutionary algorithm framework. Validation of the parameterization method is carried out by using an evolutionary algorithm to synthesize the function models for five different electromechanical products. The algorithm converged in each case, indicating that the method is satisfactory and that function models can actually be synthesized using an evolutionary framework. In addition, the adaptation of several a priori rules for use in this framework has been proposed. These rules are categorized as grammar, logical and feature based rules. An updated evolutionary framework that incorporates these rules is also presented.
{"title":"Evolutionary Approach to Function Model Synthesis: Development of Parameterization and Synthesis Rules","authors":"A. Gill, Chiradeep Sen","doi":"10.1115/detc2020-22664","DOIUrl":"https://doi.org/10.1115/detc2020-22664","url":null,"abstract":"\u0000 The goal of this paper is to develop the groundwork for automated synthesis of function models. To this end, an evolutionary algorithm based framework has been developed. A parameterization method that can completely describe any given function models has been proposed. The parameterization makes the function models compatible for use within the evolutionary algorithm framework. Validation of the parameterization method is carried out by using an evolutionary algorithm to synthesize the function models for five different electromechanical products. The algorithm converged in each case, indicating that the method is satisfactory and that function models can actually be synthesized using an evolutionary framework. In addition, the adaptation of several a priori rules for use in this framework has been proposed. These rules are categorized as grammar, logical and feature based rules. An updated evolutionary framework that incorporates these rules is also presented.","PeriodicalId":164403,"journal":{"name":"Volume 9: 40th Computers and Information in Engineering Conference (CIE)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124769206","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}
M. Messina, Simon Teves, G. W. Scurati, M. Carulli, F. Ferrise
As the popularity of winter outdoor sports is increasing, a growing number of users are engaging in activities in uncontrolled terrain, thus training for avalanche rescue is more important than ever. Traditional training takes place through workshops and in field sessions, presenting limitations to the training availability, since they require time, organization and specific weather conditions. This is problematic since the use of transceivers to locate buried individuals is not trivial and requires practice. Virtual Reality (VR) training has shown to be effective in several fields, especially in the context of hazardous conditions and emergencies, which require decision making under time pressure and management of complex tools in uncontrolled or unsafe environments. Examples include disaster medicine, military operations, and other fields in which actions must be performed precisely in short time frame. In this work, we present the development of an immersive VR system for avalanche rescue training as a complementary tool to the traditional techniques in order to prepare the trainee for field training sessions. We discuss the definition of the system requirements, the design and implementation of the tool, and considerations regarding hardware and software. Finally, we discuss possible limitations and future development.
{"title":"Development of Virtual Reality Training Scenario for Avalanche Rescue","authors":"M. Messina, Simon Teves, G. W. Scurati, M. Carulli, F. Ferrise","doi":"10.1115/detc2020-22414","DOIUrl":"https://doi.org/10.1115/detc2020-22414","url":null,"abstract":"\u0000 As the popularity of winter outdoor sports is increasing, a growing number of users are engaging in activities in uncontrolled terrain, thus training for avalanche rescue is more important than ever. Traditional training takes place through workshops and in field sessions, presenting limitations to the training availability, since they require time, organization and specific weather conditions. This is problematic since the use of transceivers to locate buried individuals is not trivial and requires practice. Virtual Reality (VR) training has shown to be effective in several fields, especially in the context of hazardous conditions and emergencies, which require decision making under time pressure and management of complex tools in uncontrolled or unsafe environments. Examples include disaster medicine, military operations, and other fields in which actions must be performed precisely in short time frame. In this work, we present the development of an immersive VR system for avalanche rescue training as a complementary tool to the traditional techniques in order to prepare the trainee for field training sessions. We discuss the definition of the system requirements, the design and implementation of the tool, and considerations regarding hardware and software. Finally, we discuss possible limitations and future development.","PeriodicalId":164403,"journal":{"name":"Volume 9: 40th Computers and Information in Engineering Conference (CIE)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123301981","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}
Improvement design, which is characterized by minimum necessary changes to a past product, is employed to reuse verified and experienced parts to create a new product faster, reliable, and economically sound. However, as products become so complex that changes to some parts propagates concomitant changes to other parts, which makes it difficult to enjoy the advantages of improvement design. Therefore, design changes have to be contemplated at the early phase of design. This paper proposes an improvement design planning method based on House of quality. Parts of a product to be changed and directions on which they are changed are explored in terms of opportunity to improve product and risk of worsening other parts. By exploring the possible design in the trade-off between the opportunity and the risk, design change plan that comprises proper parts of a product to be changed can be decided. A case study on a solar boat design demonstrates the applicability and validity of the proposed method.
{"title":"A Method to Specify Part of a System to Change in Improvement Design","authors":"K. Oizumi, K. Aoyama","doi":"10.1115/detc2020-22360","DOIUrl":"https://doi.org/10.1115/detc2020-22360","url":null,"abstract":"\u0000 Improvement design, which is characterized by minimum necessary changes to a past product, is employed to reuse verified and experienced parts to create a new product faster, reliable, and economically sound. However, as products become so complex that changes to some parts propagates concomitant changes to other parts, which makes it difficult to enjoy the advantages of improvement design. Therefore, design changes have to be contemplated at the early phase of design. This paper proposes an improvement design planning method based on House of quality. Parts of a product to be changed and directions on which they are changed are explored in terms of opportunity to improve product and risk of worsening other parts. By exploring the possible design in the trade-off between the opportunity and the risk, design change plan that comprises proper parts of a product to be changed can be decided. A case study on a solar boat design demonstrates the applicability and validity of the proposed method.","PeriodicalId":164403,"journal":{"name":"Volume 9: 40th Computers and Information in Engineering Conference (CIE)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123311496","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}
Through experience, designers develop guiding principles, or heuristics, to aid decision-making in familiar design domains. Generalized versions of common design heuristics have been identified across multiple domains and applied by novices to design problems. Previous work leveraged a sample of these common heuristics to assist in an agent-based design process, which typically lacks heuristics. These predefined heuristics were translated into sequences of specifically applied design changes that followed the theme of the heuristic. To overcome the upfront burden, need for human interpretation, and lack of generality of this manual process, this paper presents a methodology that induces frequent heuristic sequences from an existing timeseries design change dataset. Individual induced sequences are then algorithmically grouped based on similarity to form groups that each represent a shared general heuristic. The heuristic induction methodology is applied to data from two human design studies in different design domains. The first dataset, collected from a truss design task, finds a highly similar set of general heuristics used by human designers to that which was hand selected for the previous computational agent study. The second dataset, collected from a cooling system design problem, demonstrates further applicability and generality of the heuristic induction process. Through this heuristic induction technique, designers working in a specified domain can learn from others’ prior problem-solving strategies and use these strategies in their own future design problems.
{"title":"Automated Heuristic Induction From Human Design Data","authors":"L. Puentes, J. Cagan, Christopher McComb","doi":"10.1115/detc2020-22151","DOIUrl":"https://doi.org/10.1115/detc2020-22151","url":null,"abstract":"\u0000 Through experience, designers develop guiding principles, or heuristics, to aid decision-making in familiar design domains. Generalized versions of common design heuristics have been identified across multiple domains and applied by novices to design problems. Previous work leveraged a sample of these common heuristics to assist in an agent-based design process, which typically lacks heuristics. These predefined heuristics were translated into sequences of specifically applied design changes that followed the theme of the heuristic. To overcome the upfront burden, need for human interpretation, and lack of generality of this manual process, this paper presents a methodology that induces frequent heuristic sequences from an existing timeseries design change dataset. Individual induced sequences are then algorithmically grouped based on similarity to form groups that each represent a shared general heuristic. The heuristic induction methodology is applied to data from two human design studies in different design domains. The first dataset, collected from a truss design task, finds a highly similar set of general heuristics used by human designers to that which was hand selected for the previous computational agent study. The second dataset, collected from a cooling system design problem, demonstrates further applicability and generality of the heuristic induction process. Through this heuristic induction technique, designers working in a specified domain can learn from others’ prior problem-solving strategies and use these strategies in their own future design problems.","PeriodicalId":164403,"journal":{"name":"Volume 9: 40th Computers and Information in Engineering Conference (CIE)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130528277","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}
Akihito Asakura, T. Hirogaki, E. Aoyama, Hiroyuki Kodama
In recent years, the needs associated with the development of new technologies in the manufacturing industry that utilize big data typified by the Internet-of-Things (IoT) and artificial intelligence (AI) have been increasing. Recent computer-aided manufacturing (CAM) systems have evolved so that unskilled technicians can create tool paths relatively easily with numerically controlled (NC) programs, but tool-cutting conditions used for machining cannot be automatically determined. Therefore, many unskilled technicians often set the cutting conditions based on the recommended conditions described in the tool catalog. However, given that the catalog contains large-scale data on machining technology, setting the proper conditions becomes a time-consuming and inefficient process. In this study, we aimed to construct a system to support unskilled technicians to determine the optimum machining conditions. To this end, we constructed a prediction model using a random forest machine learning method to predict the cutting conditions. It was confirmed that the prediction with the random forest method can be performed with high accuracy based on the cutting conditions recommended by the tool maker. Thus, the effectiveness of this method was verified.
{"title":"Data Mining From Endmill Tool Catalog Information Based on the Use of a Machine Learning Method","authors":"Akihito Asakura, T. Hirogaki, E. Aoyama, Hiroyuki Kodama","doi":"10.1115/detc2020-22126","DOIUrl":"https://doi.org/10.1115/detc2020-22126","url":null,"abstract":"\u0000 In recent years, the needs associated with the development of new technologies in the manufacturing industry that utilize big data typified by the Internet-of-Things (IoT) and artificial intelligence (AI) have been increasing. Recent computer-aided manufacturing (CAM) systems have evolved so that unskilled technicians can create tool paths relatively easily with numerically controlled (NC) programs, but tool-cutting conditions used for machining cannot be automatically determined. Therefore, many unskilled technicians often set the cutting conditions based on the recommended conditions described in the tool catalog. However, given that the catalog contains large-scale data on machining technology, setting the proper conditions becomes a time-consuming and inefficient process. In this study, we aimed to construct a system to support unskilled technicians to determine the optimum machining conditions. To this end, we constructed a prediction model using a random forest machine learning method to predict the cutting conditions. It was confirmed that the prediction with the random forest method can be performed with high accuracy based on the cutting conditions recommended by the tool maker. Thus, the effectiveness of this method was verified.","PeriodicalId":164403,"journal":{"name":"Volume 9: 40th Computers and Information in Engineering Conference (CIE)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133663700","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}
B. Graber, A. Iliopoulos, J. Michopoulos, J. Steuben, A. Birnbaum, R. Fischer, L. Johnson, P. Bernhardt, J. M. Coombs, E. Gorzkowski, E. Patterson
Ceramic powders are commonly used as precursors for several ceramic part manufacturing processes. Their dielectric characterization is necessary for all the cases where electromagnetic radiation is used to induce heating. In support of such activities at the U.S. Naval Research Laboratory, the present work introduces a technique for measuring the complex dielectric constants of ceramic powders at microwave frequencies. The data produced by this technique is critical for the proper modeling of ceramic powder microwave absorption and will assist in ongoing research into volumetric microwave sintering. This technique involves a transmission line measurement using a network analyzer and waveguide setup. Dielectric parameters are then extracted from these measurements using two established methods. Complex relative permittivity measurements are presented for ceramic powders ofyttria stabilized zirconia (YSZ), barium titanate (BaTiO3), zinc oxide (ZnO), and titanium dioxide (TiO2) as well as a method for containing the sample shape during measurement. Experiments were carried out between 25 and 40GHz; in the Ka microwave band. Experimental results suggest that the dielectric constant (ε′) of these powders are similar to those of bulk. Results are compared to lower frequency reference data showing reasonable agreement.
{"title":"Measuring Dielectric Properties of Ceramic Powders at Microwave Frequencies for Material Processing Applications","authors":"B. Graber, A. Iliopoulos, J. Michopoulos, J. Steuben, A. Birnbaum, R. Fischer, L. Johnson, P. Bernhardt, J. M. Coombs, E. Gorzkowski, E. Patterson","doi":"10.1115/detc2020-22482","DOIUrl":"https://doi.org/10.1115/detc2020-22482","url":null,"abstract":"\u0000 Ceramic powders are commonly used as precursors for several ceramic part manufacturing processes. Their dielectric characterization is necessary for all the cases where electromagnetic radiation is used to induce heating. In support of such activities at the U.S. Naval Research Laboratory, the present work introduces a technique for measuring the complex dielectric constants of ceramic powders at microwave frequencies. The data produced by this technique is critical for the proper modeling of ceramic powder microwave absorption and will assist in ongoing research into volumetric microwave sintering. This technique involves a transmission line measurement using a network analyzer and waveguide setup. Dielectric parameters are then extracted from these measurements using two established methods. Complex relative permittivity measurements are presented for ceramic powders ofyttria stabilized zirconia (YSZ), barium titanate (BaTiO3), zinc oxide (ZnO), and titanium dioxide (TiO2) as well as a method for containing the sample shape during measurement. Experiments were carried out between 25 and 40GHz; in the Ka microwave band. Experimental results suggest that the dielectric constant (ε′) of these powders are similar to those of bulk. Results are compared to lower frequency reference data showing reasonable agreement.","PeriodicalId":164403,"journal":{"name":"Volume 9: 40th Computers and Information in Engineering Conference (CIE)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132049051","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}
Ronak R. Mohanty, Riddhi R. Adhikari, Vinayak R. Krishnamurthy
In this paper, we present a study to explore the symmetry of kinesthetic perception. Our goal is to add to the growing literature that investigates haptics technologies for therapeutic and rehabilitative applications. To this end, we study how selective activation/ deactivation of haptic (specifically force) feedback affects human perception during symmetric bi-manual (two-handed) spatial tasks. We conducted a simple experiment where healthy individuals are tasked with stretching a virtual spring using two symmetrically located haptics devices that provide an equal amount of resistive forces on each hand while pulling the spring. In this experiment, we implement four kinesthetic conditions, namely (1) feedback on both hands, (2) feedback only on dominant hand, (3) feedback only on non-dominant hand, and (4) no feedback as our control. Our first goal was to determine if there exists a range of spring stiffness in which the individual incorrectly perceives bi-manual forces when the feedback is deactivated on one hand. Subsequently, we also wanted to investigate what range of spring stiffness would lead to such perceptual illusions. Our studies show that not only does such a range exist, wide enough so as to be potentially utilized in future rehabilitative applications. Interestingly, we also observe that for few cases, symmetry can be independent of the kinesthetic perception.
{"title":"Kinesthetic Perceptual Symmetry in Bi-Manual Interactions: An Exploratory Study","authors":"Ronak R. Mohanty, Riddhi R. Adhikari, Vinayak R. Krishnamurthy","doi":"10.1115/detc2020-22723","DOIUrl":"https://doi.org/10.1115/detc2020-22723","url":null,"abstract":"\u0000 In this paper, we present a study to explore the symmetry of kinesthetic perception. Our goal is to add to the growing literature that investigates haptics technologies for therapeutic and rehabilitative applications. To this end, we study how selective activation/ deactivation of haptic (specifically force) feedback affects human perception during symmetric bi-manual (two-handed) spatial tasks. We conducted a simple experiment where healthy individuals are tasked with stretching a virtual spring using two symmetrically located haptics devices that provide an equal amount of resistive forces on each hand while pulling the spring. In this experiment, we implement four kinesthetic conditions, namely (1) feedback on both hands, (2) feedback only on dominant hand, (3) feedback only on non-dominant hand, and (4) no feedback as our control. Our first goal was to determine if there exists a range of spring stiffness in which the individual incorrectly perceives bi-manual forces when the feedback is deactivated on one hand. Subsequently, we also wanted to investigate what range of spring stiffness would lead to such perceptual illusions. Our studies show that not only does such a range exist, wide enough so as to be potentially utilized in future rehabilitative applications. Interestingly, we also observe that for few cases, symmetry can be independent of the kinesthetic perception.","PeriodicalId":164403,"journal":{"name":"Volume 9: 40th Computers and Information in Engineering Conference (CIE)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116450436","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}
Steven N. Rodriguez, A. Iliopoulos, J. Michopoulos, J. Jaworski
The relationship between rotor-blade aeroelasticity and tip-vortex stability is investigated numerically. An aeroelastic framework based on the free-vortex wake and finite element methods is employed to model a subscaled helicopter rotor in hover and forward-tilted conditions. A linear eigenvalue stability analysis is performed on tip vortices to associate the coupled impact of aeroelastic effects and vortex evolution. Prior numerical investigations have shown that highly flexible wind turbine rotor-blades have the potential to decrease levels of the instability of tip vortices. The present work focuses on testing these findings against a subscaled rotor within the range of helicopter operational rotation frequencies. The presented work aims to develop further insight into rotor-wake interactions and blade-vortex interaction to explore the mitigation of adverse rotorcraft operational conditions, such as their effect on aerodynamic-induced airframe vibrations and the associated life-cycle fatigue performance.
{"title":"Investigating the Coupled Effects Between Rotor-Blade Aeroelasticity and Tip Vortex Stability","authors":"Steven N. Rodriguez, A. Iliopoulos, J. Michopoulos, J. Jaworski","doi":"10.1115/detc2020-22632","DOIUrl":"https://doi.org/10.1115/detc2020-22632","url":null,"abstract":"\u0000 The relationship between rotor-blade aeroelasticity and tip-vortex stability is investigated numerically. An aeroelastic framework based on the free-vortex wake and finite element methods is employed to model a subscaled helicopter rotor in hover and forward-tilted conditions. A linear eigenvalue stability analysis is performed on tip vortices to associate the coupled impact of aeroelastic effects and vortex evolution. Prior numerical investigations have shown that highly flexible wind turbine rotor-blades have the potential to decrease levels of the instability of tip vortices. The present work focuses on testing these findings against a subscaled rotor within the range of helicopter operational rotation frequencies. The presented work aims to develop further insight into rotor-wake interactions and blade-vortex interaction to explore the mitigation of adverse rotorcraft operational conditions, such as their effect on aerodynamic-induced airframe vibrations and the associated life-cycle fatigue performance.","PeriodicalId":164403,"journal":{"name":"Volume 9: 40th Computers and Information in Engineering Conference (CIE)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116736356","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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