IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Structural sizing and shape optimisation of a load celleSAT Journals
Abstract This paper presents a structural application of a sizing and shape based on a reliability-related multi-factor optimisation. The application to a load cell design confirmed that this method is highly effective and efficient in terms of sizing and shape optimisation. A simple model of the S-type load cell is modelled in finite element analysis software and the systematic optimisation method is applied. Structural responses and geometrical sensitivities are analysed by a FE method, and reliability performance is calculated by a reliability loading-case index (RLI). The evaluation indices of performances and loading cases are formulated, and an overall performance index is presented to quantitatively evaluate a design. Index Terms: Multifactor optimisation, Finite element analysis, Load cell
Power system state estimation using teaching learning-based optimization algo...TELKOMNIKA JOURNAL
The main goal of this paper is to formulate power system state estimation (SE) problem as a constrained nonlinear programming problem with various constraints and boundary limits on the state variables. SE forms the heart of entire real time control of any power system. In real time environment, the state estimator consists of various modules like observability analysis, network topology processing, SE and bad data processing. The SE problem formulated in this work is solved using teaching leaning-based optimization (TLBO) technique. Difference between the proposed TLBO and the conventional optimization algorithms is that TLBO gives global optimum solution for the present problem. To show the suitability of TLBO for solving SE problem, IEEE 14 bus test system has been selected in this work. The results obtained with TLBO are also compared with conventional weighted least square (WLS) technique and evolutionary based particle swarm optimization (PSO) technique.
Electronics system thermal management optimization using finite element and N...TELKOMNIKA JOURNAL
The demand for high-performance, smaller-sized, and multi-functional electronics component
poses a great challenge to the thermal management issues in a printed circuit board (PCB)
design. Moreover, this thermal problem can affect the lifespan, performance, and the reliability of
the electronic system. This project presents the simulation of an optimal thermal distribution for various
samples of electronics components arrangement on PCB. The objectives are to find the optimum
components arrangement with minimal heat dissipation and cover small PCB area. Nelder-Mead
Optimization (NMO) with Finite Element method has been used to solve these multi-objective problems.
The results show that with the proper arrangement of electronics components, the area of PCB has been
reduced by 26% while the temperature of components is able to reduce up to 40%. Therefore, this study
significantly benefits for the case of thermal management and performance improvement onto the electronic
product and system.
Presented in this short document is a description of what is called Advanced Process Monitoring (APM) as described by Hedengren (2013). APM is the term given to the technique of estimating unmeasured but observable variables or "states" using statistical data reconciliation and regression (DRR) in an off-line or real-time environment and is also referred to as Moving Horizon Estimation (MHE) (Robertson et. al., 1996). Essentially, the model and data define a simultaneous nonlinear and dynamic DRR problem where the model is either engineering-based (first-principles, fundamental, mechanistic, causal, rigorous) or empirical-based (correlation, statistical data-based, observational, regressed) or some combination of both (hybrid).
The article presents a new method of the optimal design of the electrical rotating machine based on the genetic algorithm which can used for all electrical rotating machine types and to predict their properties. The new method for optimal design allows obtaining the new electrical rotating machine which mass is lower than mass of the conventional electrical rotating machine by two times. As the result of optimal electrical rotating machine design by using the proposed method, the value of the rotor active length is lower by 2.37 times, and the current density is higher by 1.7 times in comparison with the initial electrical rotating machine. The losses are increased by only 25% (power, rotation and materials frequency of both electrical rotating machine are the same). It was also found that the optimality of a particular design scheme, including the rotor magnetic system or the groove type depends on the complex of sizes. Moreover, the change of this complex leads to a change in the optimum design scheme.
Structural sizing and shape optimisation of a load celleSAT Journals
Abstract This paper presents a structural application of a sizing and shape based on a reliability-related multi-factor optimisation. The application to a load cell design confirmed that this method is highly effective and efficient in terms of sizing and shape optimisation. A simple model of the S-type load cell is modelled in finite element analysis software and the systematic optimisation method is applied. Structural responses and geometrical sensitivities are analysed by a FE method, and reliability performance is calculated by a reliability loading-case index (RLI). The evaluation indices of performances and loading cases are formulated, and an overall performance index is presented to quantitatively evaluate a design. Index Terms: Multifactor optimisation, Finite element analysis, Load cell
Power system state estimation using teaching learning-based optimization algo...TELKOMNIKA JOURNAL
The main goal of this paper is to formulate power system state estimation (SE) problem as a constrained nonlinear programming problem with various constraints and boundary limits on the state variables. SE forms the heart of entire real time control of any power system. In real time environment, the state estimator consists of various modules like observability analysis, network topology processing, SE and bad data processing. The SE problem formulated in this work is solved using teaching leaning-based optimization (TLBO) technique. Difference between the proposed TLBO and the conventional optimization algorithms is that TLBO gives global optimum solution for the present problem. To show the suitability of TLBO for solving SE problem, IEEE 14 bus test system has been selected in this work. The results obtained with TLBO are also compared with conventional weighted least square (WLS) technique and evolutionary based particle swarm optimization (PSO) technique.
Electronics system thermal management optimization using finite element and N...TELKOMNIKA JOURNAL
The demand for high-performance, smaller-sized, and multi-functional electronics component
poses a great challenge to the thermal management issues in a printed circuit board (PCB)
design. Moreover, this thermal problem can affect the lifespan, performance, and the reliability of
the electronic system. This project presents the simulation of an optimal thermal distribution for various
samples of electronics components arrangement on PCB. The objectives are to find the optimum
components arrangement with minimal heat dissipation and cover small PCB area. Nelder-Mead
Optimization (NMO) with Finite Element method has been used to solve these multi-objective problems.
The results show that with the proper arrangement of electronics components, the area of PCB has been
reduced by 26% while the temperature of components is able to reduce up to 40%. Therefore, this study
significantly benefits for the case of thermal management and performance improvement onto the electronic
product and system.
Presented in this short document is a description of what is called Advanced Process Monitoring (APM) as described by Hedengren (2013). APM is the term given to the technique of estimating unmeasured but observable variables or "states" using statistical data reconciliation and regression (DRR) in an off-line or real-time environment and is also referred to as Moving Horizon Estimation (MHE) (Robertson et. al., 1996). Essentially, the model and data define a simultaneous nonlinear and dynamic DRR problem where the model is either engineering-based (first-principles, fundamental, mechanistic, causal, rigorous) or empirical-based (correlation, statistical data-based, observational, regressed) or some combination of both (hybrid).
The article presents a new method of the optimal design of the electrical rotating machine based on the genetic algorithm which can used for all electrical rotating machine types and to predict their properties. The new method for optimal design allows obtaining the new electrical rotating machine which mass is lower than mass of the conventional electrical rotating machine by two times. As the result of optimal electrical rotating machine design by using the proposed method, the value of the rotor active length is lower by 2.37 times, and the current density is higher by 1.7 times in comparison with the initial electrical rotating machine. The losses are increased by only 25% (power, rotation and materials frequency of both electrical rotating machine are the same). It was also found that the optimality of a particular design scheme, including the rotor magnetic system or the groove type depends on the complex of sizes. Moreover, the change of this complex leads to a change in the optimum design scheme.
Bond graphs and genetic algorithms for design and optimization of active dyna...eSAT Journals
Abstract The aim of this work is to propose a methodology of sizing in a frame of the conception of mechatronic systems in particular and active dynamic ones, in general. This methodology will support conceptual design step [1]. We propose a collaborative design approach based on Bond Graph tool and Genetic algorithms. Mechatronic systems have a passive part and active part. In our approach we establish a hard interaction between passive and active parts. This interaction will be materialized in taking into account of control criteria in the evolution (synthesis) phase of passive part. This initiative treats functional aspects, both structural and behavioral; while respecting interactions between passive and active parts. In our approach we treat functional, structural and behavioral aspects in order to validate a post-project solution. Optimization needs Behavioral models which are systematically deducted from bond-graph structural models. Thus, retained bond graph elements which constitute passive part will be obtained, done by optimization Genetic Algorithms procedure. In this procedure Gramians of controllability and of observability represent the fitness function. The proposed method will be applied to an automatic transmission of a scooter and validated by a dynamic simulation. Keywords: Modeling, dynamic system, Bond graph, Gramians of controllability, Genetic algorithms
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Optimization of Surface Roughness Index for a Roller Burnishing Process Using...paperpublications3
Abstract: The main objective of this dissertation is to optimize the roughness index for a roller burnishing process. The factors have been identified from literature review. These barriers may be of market, cultural, human resource.management, financial, economical, attitudinal, environmental, geographical and technological type. Technology transfer barriers threats the movement of physical structure, knowledge, skills, organization value and capital from the developed to developing countries. Clear understanding of these barriers may help the practitioners to find out various ways to deal with them. This may further facilitate successful implementation of technology transfer. Technology transfer may be said to be successful if Transferor (seller) and the transferee (buyer) can effectively utilize the technology for business gain. The transfer involves cost and expenditure that should be agreed by the transferee and transferor. The process is affected by various factors that hinder Technology Transfer. These factors named Barriers. In the present work, Interpretive Structure Modeling (ISM) is used for the analysis and comparison of various factors important for Technology Transfer. The important parameters are identified and self-interaction matrixes proposed with the help of Interpretive Structure Modeling which evaluates the inhibiting power of these parameters. This index can be used in comparison of different factors responsible for Roller Burnishing Processes.
Power System Reliability Assessment in a Complex Restructured Power SystemIJECEIAES
The basic purpose of an electric power system is to supply its consumers with electric energy as parsimoniously as possible and with a sensible degree of continuity and quality. It is expected that the solicitation of power system reliability assessment in bulk power systems will continue to increase in the future especially in the newly deregulated power diligence. This paper presents the research conducted on the three areas of incorporating multi-state generating unit models, evaluating system performance indices and identifying transmission paucities in complex system adequacy assessment. The incentives for electricity market participants to endow in new generation and transmission facilities are highly influenced by the market risk in a complex restructured environment. This paper also presents a procedure to identify transmission deficiencies and remedial modification in the composite generation and transmission system and focused on the application of probabilistic techniques in composite system adequacy assessment
Wind farm layout optimization (WFLO) is the process of optimizing the location of turbines in a wind farm site, with the possible objective of maximizing the energy production or minimizing the average cost of energy. Conventional WFLO methods not only limit themselves to prescribing the site boundaries, they are also generally applicable to designing only small-to-medium scale wind farms (<100 turbines). Large-scale wind farms entail greater wake-induced turbine interactions, thereby increasing the computa- tional complexity and expense by orders of magnitude. In this paper, we further advance the Unrestricted WFLO framework by designing the layout of large-scale wind farms with 500 turbines (where energy pro- duction is maximized). First, the high-dimensional layout optimization problem (involving 2N variables for a N turbine wind farm) is reduced to a 6-variable problem through a novel mapping strategy, which allows for both global siting (overall land configuration) and local exploration (turbine micrositing). Sec- ondly, a surrogate model is used to substitute the expensive analytical WF energy production model; the high computational expense of the latter is attributed to the factorial increase in the number of calls to the wake model for evaluating every candidate wind farm layout that involves a large number of turbines. The powerful Concurrent Surrogate Model Selection (COSMOS) framework is applied to identify the best surrogate model to represent the wind farm energy production as a function of the reduced variable vector. To accomplish a reliable optimum solution, the surrogate-based optimization (SBO) is performed by implementing the Adaptive Model Refinement (AMR) technique within Particle Swarm Optimization (PSO). In AMR, both local exploitation and global exploration aspects are considered within a single optimization run of PSO, unlike other SBO methods that often either require multiple (potentially mis- leading) optimizations or are model-dependent. By using the AMR approach in conjunction with PSO and COSMOS, the computational cost of designing very large wind farms is reduced by a remarkable factor of 26, while preserving the reliability of this WFLO within 0.05% of the WFLO performed using the original energy production model.
This paper presents the implementation of multiple distributed generations planning in distribution system using computational intelligence technique. A pre-developed computational intelligence optimization technique named as Embedded Meta EP-Firefly Algorithm (EMEFA) was utilized to determine distribution loss and penetration level for the purpose of distributed generation (DG) installation. In this study, the Artificial Neural Network (ANN) was used in order to solve the complexity of the multiple DG concepts. EMEFA-ANN was developed to optimize the weight of the ANN to minimize the mean squared error. The proposed method was validated on IEEE 69 Bus distribution system with several load variations scenario. The case study was conducted based on the multiple unit of DG in distribution system by considering the DGs are modeled as type I which is capable of injecting real power. Results obtained from the study could be utilized by the utility and energy commission for loss reduction scheme in distribution system.
Multi Area Economic Dispatch Using Secant Method and Tie Line MatrixIJAPEJOURNAL
In this paper, Secant method and tie line matrix are proposed to solve multi area economic dispatch (MAED) problem with tie line loss. Generator limits of all generators in each area are calculated at given area power demands plus export (or import) using secant method and the generator limits of all generators are modified as modified generator limits. Central economic dispatch (CED) problem is used to determine the output powers of all generators and finally power flows in all tie lines are determined from tie line matrix. Here, Secant method is applied to solve the CED problem. A modified tie line matrix is used to find power flow in each tie line and then tie line loss is calculated from the power flow in each tie line. The proposed approach has been tested on two-area (two generators in each area) system and four-area (four generators in each area) system. It is observed from various cases that the proposed approach provides optimally best solution in terms of cost with tie line loss with less computational burden.
Interior Dual Optimization Software Engineering with Applications in BCS Elec...BRNSS Publication Hub
Interior optimization software and algorithms programming methods provide a computational tool with
a number of applications. Theory and computational demonstrations/techniques were primarily shown
in previous articles. The mathematical framework of this new method, (Casesnoves, 2018–2020), was
also proven.The links among interior optimization, graphical optimization (Casesnoves, 2016–7), and
classical methods in non-linear equations systems were developed. This paper is focused on software
engineering with mathematical methods implementation in programming as a primary subject. The
specific details for interior optimization computational adaptation on every specific problem, such as
engineering, physics, and electronics physics, are explained. Second subject is electronics applications
of software in the field of superconductors. It comprises a series of new BCS equation optimization
for Type I superconductors, based on previous research for other different Type I superconductors
previously published. A new dual optimization for two superconductors is simulated. Results are
acceptable with low errors and imaging demonstrations of the interior optimization utility.
This short note describes a relatively simple methodology, procedure or approach to increase the performance of already installed industrial models used for optimization, control, simulation and/or monitoring purposes. The method is called Excess or X-Model Regression (XMR) where the concept of “excess modeling” or an X-model is taken from the field of thermodynamics to describe the departure or residual behaviour of real (non-ideal) gases and liquids from their ideal state (Kyle, 1999; Poling et. al., 2001; Smith et. al., 2001). It has also been applied to model the non-ideal or nonlinear behaviour of blending motor gasoline octanes with its synergistic and antagonistic interactional effects (Muller, 1992).
The fundamental idea of XMR is to calibrate, train, fit or estimate, using actual data and multiple linear regression (MLR) or ordinary least squares (OLS), the deviations of the measured responses from the existing model responses. The existing model may be a glass, grey or black-box model (known or unknown, linear or nonlinear, implicit/open or explicit/closed) depending on the use of the model. That is, for optimization and control the model structure and parameters are available given that derivative information is required although for simulation and monitoring, the model may only be observed through the dependent output variables given the necessary independent input variables.
Optimum reactive power compensation for distribution system using dolphin alg...IJECEIAES
The distribution system represents the connection between the consumers and entire power network. The radial structure is preferred for distribution system due to its simple design and low cost. It suffers from problems of rising power losses higher than the transmission system and voltage drop. One of the important solutions to evolve the system voltage profile and to lower system losses is the reactive power compensation which is based on the optimum choice of position and capacitor size in the network. Different models of loads such as constant power (P), constant current (I), constant impedance (Z), and composite (ZIP) are implemented with comparisons among them in order to identify the most effective load type that produces the optimal settlement for minimization loss reduction, voltage profile enhancement and cost savings. Dolphin Optimization Algorithm (DOA) is applied for selecting the sizes and locations of capacitors. Two case studies (IEEE 16-bus and 33-bus) are employed to evaluate the different load models with optimal reactive power compensation. The results show that ZIP model is the best to produce the optimal solution for capacitors position and sizes. Comparison of results with literature works shows that DOA is the most robust among the other algorithms.
Optimum penetration depth of cantilever sheet pile walls in dry granular soil Ahmed Ebid
in Cantilevered sheet
pile walls are commonly used in shoring systems of deep excavation down to about 5.00 m. The most common design procedure for this type
of flexible retaining structures is to determine the required penetration depth for stability and then increasing the calculated penetration
depth by 20% to 40% to achieve a factor of safety of about 1.5 to 2.0. This procedure has two disadvantages; first, the procedure does not
give accurate values for penetration depth or corresponding factor of safety, second, it ignores the effect of uncertainty in the used
geotechnical parameters. The first aim of this study is to overcome those two disadvantages by introduce an alternative formula to
determine the optimum penetration depth of cantilever sheet pile walls in dry granular soil based on reliability analysis concept, while, the
second aim is to study the impact of using the optimum depth on the cost of the shoring system. The study results assure the validity of
provision of increasing the calculated penetration depth by (20% to 40%) and introduced a formula to calculate the required penetration
depth to achieve probability of failure of 0.1% and proved that using this optimum depth can reduce the direct cost of the shoring system by
5% to 10% based on internal friction angle of soil.
A developer needs to evaluate software performance metrics such as power consumption at an early stage of design phase to make a device or a software efficient especially in real-time embedded systems. Constructing performance models and evaluation techniques of a given system requires a significant effort. This paper presents a framework to bridge between a Functional Modeling Approach such as FSM, UML etc. and an Analytical (Mathematical) Modeling Approach such as Hierarchical Performance Modeling (HPM) as a technique to find the expected average power consumption for different layers of abstractions. A Hierarchical Generic FSM “HGFSM” is developed to be used in order to estimate the expected average power. A case study is presented to illustrate the concepts of how the framework is used to estimate the average power and energy produced.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Bond graphs and genetic algorithms for design and optimization of active dyna...eSAT Journals
Abstract The aim of this work is to propose a methodology of sizing in a frame of the conception of mechatronic systems in particular and active dynamic ones, in general. This methodology will support conceptual design step [1]. We propose a collaborative design approach based on Bond Graph tool and Genetic algorithms. Mechatronic systems have a passive part and active part. In our approach we establish a hard interaction between passive and active parts. This interaction will be materialized in taking into account of control criteria in the evolution (synthesis) phase of passive part. This initiative treats functional aspects, both structural and behavioral; while respecting interactions between passive and active parts. In our approach we treat functional, structural and behavioral aspects in order to validate a post-project solution. Optimization needs Behavioral models which are systematically deducted from bond-graph structural models. Thus, retained bond graph elements which constitute passive part will be obtained, done by optimization Genetic Algorithms procedure. In this procedure Gramians of controllability and of observability represent the fitness function. The proposed method will be applied to an automatic transmission of a scooter and validated by a dynamic simulation. Keywords: Modeling, dynamic system, Bond graph, Gramians of controllability, Genetic algorithms
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Optimization of Surface Roughness Index for a Roller Burnishing Process Using...paperpublications3
Abstract: The main objective of this dissertation is to optimize the roughness index for a roller burnishing process. The factors have been identified from literature review. These barriers may be of market, cultural, human resource.management, financial, economical, attitudinal, environmental, geographical and technological type. Technology transfer barriers threats the movement of physical structure, knowledge, skills, organization value and capital from the developed to developing countries. Clear understanding of these barriers may help the practitioners to find out various ways to deal with them. This may further facilitate successful implementation of technology transfer. Technology transfer may be said to be successful if Transferor (seller) and the transferee (buyer) can effectively utilize the technology for business gain. The transfer involves cost and expenditure that should be agreed by the transferee and transferor. The process is affected by various factors that hinder Technology Transfer. These factors named Barriers. In the present work, Interpretive Structure Modeling (ISM) is used for the analysis and comparison of various factors important for Technology Transfer. The important parameters are identified and self-interaction matrixes proposed with the help of Interpretive Structure Modeling which evaluates the inhibiting power of these parameters. This index can be used in comparison of different factors responsible for Roller Burnishing Processes.
Power System Reliability Assessment in a Complex Restructured Power SystemIJECEIAES
The basic purpose of an electric power system is to supply its consumers with electric energy as parsimoniously as possible and with a sensible degree of continuity and quality. It is expected that the solicitation of power system reliability assessment in bulk power systems will continue to increase in the future especially in the newly deregulated power diligence. This paper presents the research conducted on the three areas of incorporating multi-state generating unit models, evaluating system performance indices and identifying transmission paucities in complex system adequacy assessment. The incentives for electricity market participants to endow in new generation and transmission facilities are highly influenced by the market risk in a complex restructured environment. This paper also presents a procedure to identify transmission deficiencies and remedial modification in the composite generation and transmission system and focused on the application of probabilistic techniques in composite system adequacy assessment
Wind farm layout optimization (WFLO) is the process of optimizing the location of turbines in a wind farm site, with the possible objective of maximizing the energy production or minimizing the average cost of energy. Conventional WFLO methods not only limit themselves to prescribing the site boundaries, they are also generally applicable to designing only small-to-medium scale wind farms (<100 turbines). Large-scale wind farms entail greater wake-induced turbine interactions, thereby increasing the computa- tional complexity and expense by orders of magnitude. In this paper, we further advance the Unrestricted WFLO framework by designing the layout of large-scale wind farms with 500 turbines (where energy pro- duction is maximized). First, the high-dimensional layout optimization problem (involving 2N variables for a N turbine wind farm) is reduced to a 6-variable problem through a novel mapping strategy, which allows for both global siting (overall land configuration) and local exploration (turbine micrositing). Sec- ondly, a surrogate model is used to substitute the expensive analytical WF energy production model; the high computational expense of the latter is attributed to the factorial increase in the number of calls to the wake model for evaluating every candidate wind farm layout that involves a large number of turbines. The powerful Concurrent Surrogate Model Selection (COSMOS) framework is applied to identify the best surrogate model to represent the wind farm energy production as a function of the reduced variable vector. To accomplish a reliable optimum solution, the surrogate-based optimization (SBO) is performed by implementing the Adaptive Model Refinement (AMR) technique within Particle Swarm Optimization (PSO). In AMR, both local exploitation and global exploration aspects are considered within a single optimization run of PSO, unlike other SBO methods that often either require multiple (potentially mis- leading) optimizations or are model-dependent. By using the AMR approach in conjunction with PSO and COSMOS, the computational cost of designing very large wind farms is reduced by a remarkable factor of 26, while preserving the reliability of this WFLO within 0.05% of the WFLO performed using the original energy production model.
This paper presents the implementation of multiple distributed generations planning in distribution system using computational intelligence technique. A pre-developed computational intelligence optimization technique named as Embedded Meta EP-Firefly Algorithm (EMEFA) was utilized to determine distribution loss and penetration level for the purpose of distributed generation (DG) installation. In this study, the Artificial Neural Network (ANN) was used in order to solve the complexity of the multiple DG concepts. EMEFA-ANN was developed to optimize the weight of the ANN to minimize the mean squared error. The proposed method was validated on IEEE 69 Bus distribution system with several load variations scenario. The case study was conducted based on the multiple unit of DG in distribution system by considering the DGs are modeled as type I which is capable of injecting real power. Results obtained from the study could be utilized by the utility and energy commission for loss reduction scheme in distribution system.
Multi Area Economic Dispatch Using Secant Method and Tie Line MatrixIJAPEJOURNAL
In this paper, Secant method and tie line matrix are proposed to solve multi area economic dispatch (MAED) problem with tie line loss. Generator limits of all generators in each area are calculated at given area power demands plus export (or import) using secant method and the generator limits of all generators are modified as modified generator limits. Central economic dispatch (CED) problem is used to determine the output powers of all generators and finally power flows in all tie lines are determined from tie line matrix. Here, Secant method is applied to solve the CED problem. A modified tie line matrix is used to find power flow in each tie line and then tie line loss is calculated from the power flow in each tie line. The proposed approach has been tested on two-area (two generators in each area) system and four-area (four generators in each area) system. It is observed from various cases that the proposed approach provides optimally best solution in terms of cost with tie line loss with less computational burden.
Interior Dual Optimization Software Engineering with Applications in BCS Elec...BRNSS Publication Hub
Interior optimization software and algorithms programming methods provide a computational tool with
a number of applications. Theory and computational demonstrations/techniques were primarily shown
in previous articles. The mathematical framework of this new method, (Casesnoves, 2018–2020), was
also proven.The links among interior optimization, graphical optimization (Casesnoves, 2016–7), and
classical methods in non-linear equations systems were developed. This paper is focused on software
engineering with mathematical methods implementation in programming as a primary subject. The
specific details for interior optimization computational adaptation on every specific problem, such as
engineering, physics, and electronics physics, are explained. Second subject is electronics applications
of software in the field of superconductors. It comprises a series of new BCS equation optimization
for Type I superconductors, based on previous research for other different Type I superconductors
previously published. A new dual optimization for two superconductors is simulated. Results are
acceptable with low errors and imaging demonstrations of the interior optimization utility.
This short note describes a relatively simple methodology, procedure or approach to increase the performance of already installed industrial models used for optimization, control, simulation and/or monitoring purposes. The method is called Excess or X-Model Regression (XMR) where the concept of “excess modeling” or an X-model is taken from the field of thermodynamics to describe the departure or residual behaviour of real (non-ideal) gases and liquids from their ideal state (Kyle, 1999; Poling et. al., 2001; Smith et. al., 2001). It has also been applied to model the non-ideal or nonlinear behaviour of blending motor gasoline octanes with its synergistic and antagonistic interactional effects (Muller, 1992).
The fundamental idea of XMR is to calibrate, train, fit or estimate, using actual data and multiple linear regression (MLR) or ordinary least squares (OLS), the deviations of the measured responses from the existing model responses. The existing model may be a glass, grey or black-box model (known or unknown, linear or nonlinear, implicit/open or explicit/closed) depending on the use of the model. That is, for optimization and control the model structure and parameters are available given that derivative information is required although for simulation and monitoring, the model may only be observed through the dependent output variables given the necessary independent input variables.
Optimum reactive power compensation for distribution system using dolphin alg...IJECEIAES
The distribution system represents the connection between the consumers and entire power network. The radial structure is preferred for distribution system due to its simple design and low cost. It suffers from problems of rising power losses higher than the transmission system and voltage drop. One of the important solutions to evolve the system voltage profile and to lower system losses is the reactive power compensation which is based on the optimum choice of position and capacitor size in the network. Different models of loads such as constant power (P), constant current (I), constant impedance (Z), and composite (ZIP) are implemented with comparisons among them in order to identify the most effective load type that produces the optimal settlement for minimization loss reduction, voltage profile enhancement and cost savings. Dolphin Optimization Algorithm (DOA) is applied for selecting the sizes and locations of capacitors. Two case studies (IEEE 16-bus and 33-bus) are employed to evaluate the different load models with optimal reactive power compensation. The results show that ZIP model is the best to produce the optimal solution for capacitors position and sizes. Comparison of results with literature works shows that DOA is the most robust among the other algorithms.
Optimum penetration depth of cantilever sheet pile walls in dry granular soil Ahmed Ebid
in Cantilevered sheet
pile walls are commonly used in shoring systems of deep excavation down to about 5.00 m. The most common design procedure for this type
of flexible retaining structures is to determine the required penetration depth for stability and then increasing the calculated penetration
depth by 20% to 40% to achieve a factor of safety of about 1.5 to 2.0. This procedure has two disadvantages; first, the procedure does not
give accurate values for penetration depth or corresponding factor of safety, second, it ignores the effect of uncertainty in the used
geotechnical parameters. The first aim of this study is to overcome those two disadvantages by introduce an alternative formula to
determine the optimum penetration depth of cantilever sheet pile walls in dry granular soil based on reliability analysis concept, while, the
second aim is to study the impact of using the optimum depth on the cost of the shoring system. The study results assure the validity of
provision of increasing the calculated penetration depth by (20% to 40%) and introduced a formula to calculate the required penetration
depth to achieve probability of failure of 0.1% and proved that using this optimum depth can reduce the direct cost of the shoring system by
5% to 10% based on internal friction angle of soil.
A developer needs to evaluate software performance metrics such as power consumption at an early stage of design phase to make a device or a software efficient especially in real-time embedded systems. Constructing performance models and evaluation techniques of a given system requires a significant effort. This paper presents a framework to bridge between a Functional Modeling Approach such as FSM, UML etc. and an Analytical (Mathematical) Modeling Approach such as Hierarchical Performance Modeling (HPM) as a technique to find the expected average power consumption for different layers of abstractions. A Hierarchical Generic FSM “HGFSM” is developed to be used in order to estimate the expected average power. A case study is presented to illustrate the concepts of how the framework is used to estimate the average power and energy produced.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Static analysis of c s short cylindrical shell under internal liquid pressure...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
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IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Detect and overcome the selfish problem in wifi network using energy sharingeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Transfer of ut information from fpga through ethernet interfaceeSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
Load balancing in public cloud combining the concepts of data mining and netw...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
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suffers from cost overruns frequently. As the most popular technique for object-oriented
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Structural sizing and shape optimisation of a load cell
1. IJRET: International Journal of Research in Engineering and Technology e-ISSN: 2319-1163 | p-ISSN: 2321-7308
__________________________________________________________________________________________
Volume: 02 Issue: 07 | Jul-2013, Available @ http://www.ijret.org 196
STRUCTURAL SIZING AND SHAPE OPTIMISATION OF A LOAD CELL
Chung Ket Thein1
1
School of Engineering, Taylor’s University, Selangor, Malaysia, ckthein@yahoo.com
Abstract
This paper presents a structural application of a sizing and shape based on a reliability-related multi-factor optimisation. The
application to a load cell design confirmed that this method is highly effective and efficient in terms of sizing and shape optimisation.
A simple model of the S-type load cell is modelled in finite element analysis software and the systematic optimisation method is
applied. Structural responses and geometrical sensitivities are analysed by a FE method, and reliability performance is calculated by
a reliability loading-case index (RLI). The evaluation indices of performances and loading cases are formulated, and an overall
performance index is presented to quantitatively evaluate a design.
Index Terms: Multifactor optimisation, Finite element analysis, Load cell
-------------------------------------------------------------------------------***------------------------------------------------------------------------------
1. INTRODUCTION
Rapid advances in multi-objective and multi-disciplinary
optimisation related to component designs as a tool in solving
engineering design problems. Multi-objective optimisation
that incorporates reliability assessment is presented [1]. This
research addresses a design optimisation problem in which the
load cell design is required to satisfy multiple criteria such as
mechanical strength and stiffness, mass, and reliability feature
under a single loading case.
Load cell is a device normally use in weighing industrial. The
capacity of load cell is vary from 25 kg up to 20 tons. One of
the most popular types of load cell is S-type load cell. It was
originally designed for in-line applications to convert
mechanical scale to digital by replacing the spring. A load cell
is a transducer that converts a force into electrical signal. The
force is sensed by a strain gauge that will be converted into
electrical signals.
The main objective of this paper is to design an S-type load
cell. Multi-objective and multi-disciplinary optimisation
technique and reliability analyses is applied in order to
minimise stress and displacement, mass, and to maximise the
reliability index simultaneously.
2. OPTIMISATION METHDOLOGY
This section deals with the combination of reliability analysis
and the Multifactor Optimisation of Structures Techniques
(MOST) [1] [2], as adopted in part of this paper.
2.1 Formulation of the optimization model
The requirements for a load cell design indicate that the
optimisation must involve multiple objectives and a number of
design variables. Thus, an optimisation procedure is to
establish a suitable method for evaluating this process;
however, complex cross-relationships make it difficult to
suitably appraise the design in order to yield an overall
quantitative performance index which truly represents the
character of the system. The optimisation tackles this problem
by employing a systematic method for evaluation based on the
concept of parameter profiles analysis [3]. This method
evaluates a load cell design by considering many individual
performance parameters for a single loading case, while also
considering cost and performance.
An m n matrix (dij
)—the so-called performance data matrix
(PDM)—is defined by a set of performance parameters Pi
(i =
1, 2,…, m) and loading case parameters Cj
(j = 1, 2,…, n),
respectively. The PDM is a schematic representation of a
collection of data as shown in Table 1. Thus, the data point dij
is the i-th performance Pi
of the structure at the loading case
Cj
. The data points of the matrix are obtained by a finite
element analysis and a reliability analysis of the structure. The
matrix lists every performance of the structure at every
individual loading case.
Table -1: Performance data matrix
C1 C2 ⋯ Cn
P1 d11 d12 ⋯ d1n
P2 d21 d22 ⋯ d2n
⋮ ⋮ ⋮ ⋮
Pm dm1 dm2 ⋯ dmn
A parameter profile matrix (PPM) is created to review the
profile of the performances for different loading cases (Table
2). The data point Dij
in the PPM is a non-dimensional number
with a range of 0–10. The PPM assesses the characteristic of
the structure with respect to the actual performances at their
worst acceptable limits and the best expected values of the
performances.
2. IJRET: International Journal of Research in Engineering and Technology e-ISSN: 2319-1163 | p-ISSN: 2321-7308
__________________________________________________________________________________________
Volume: 02 Issue: 07 | Jul-2013, Available @ http://www.ijret.org 197
Table -2: Parameter profile matrix
C1 C2 ⋯ Cn
P1 D11 D12 ⋯ D1n
P2 D21 D22 ⋯ D2n
⋮ ⋮ ⋮ ⋮
Pm Dm1 Dm2 ⋯ Dmn
The data point Dij
for the one acceptable limit (e.g., lower
limit) is calculated as follows:
10
ijij
ijij
ij
lb
ld
D (1)
where dij
is the actual value of the performance obtained from
the PDM, and lij
and bij
are the lower acceptable limit and the
best expected value, respectively. Equation (1) is valid for lij
<
dij
< bij; for dij
> bij
, Dij
= 10; and for dij
< lij
, Dij
= 0. The data
point for the cases of acceptable upper limit and double
acceptable limits can be calculated in a similar way.
In the optimisation model proposed, all the performance
parameters, no matter whether they are considered as
objectives or constraints, are collected into the PDM (Table 1).
By introducing acceptable limits and best level values for each
performance, a PPM (Table 2) can be founded. This procedure
transforms every performance parameter into a set of goal
functions in connection with loading cases. These goal
functions are the elements of the PPM. In this way, a goal
system is established and it brings all the performance data
into the range of 0-10. For every performance parameter, the
best goal is the same and its value is set to be 10. The goal
functions represent closenesses to the predetermined targets
(best level values of the performances). The closeness value
for each parameter is an adjustable quantity related to the
acceptable limit(s) and best level value of the performance.
Hence, the original optimisation problem is converted to the
problem of minimising the deviations between all these goal
functions and their pseudo targets quantitative value 10.
The mean and standard deviation (SD) are calculated for each
parameter and loading case in each column and row in the
PPM. A well-designed system should have low SDs and high
mean values (close to 10). The existence of high SDs signifies
that the system is likely to have significant problematic areas.
Therefore, a high SD for a row indicates variable system
performance at different loading cases for a particular
parameter. Conversely, a high SD for a column indicates that
the system is likely to have significant problematic
performance for the specific loading case.
The system can be further analysed using a parameter
performance index (PPI) and a case performance index (CPI),
which are defined as follows:
n
j ij
i
D
n
1
1
PPI , mi ,,2,1 and
m
i ij
j
D
m
1
1
CPI , nj ,,2,1 (2)
When i-th parameter is very vulnerable, some data points Dij
of the PPM will have values close to 0 and hence the PPIi will
also close to 0. Similarly, when the system is vulnerable at the
j-th loading case, CPIj will be close to 0. The highest values
for PPI and CPI are 10. PPI and CPI values that are close to 10
indicate good design, whereas values close to zero indicate
poor design. The system may be reviewed by using the
information in the indices, as follows:
A comparison of PPIs indicates whether the system
performs better with respect to some performances
than to others.
A comparison of CPIs shows whether the system
performs better under certain loading cases than
under others.
The mean values, CPIs, PPIs, and SDs provide an overall
performance assessment for the system and loading cases.
These indices are calculated by summing the inverse of the
data points as a performance rating to avoid the effect
associated with low scores being hidden by high scores. The
mean values are not used directly to rate the performance. To
simplify the calculations, the performance indices are
categorized into the range 0–10. This enables different loading
cases and parameters to be compared in order to gain an
overall perspective of the characteristics of the system.
According to the matrix profile analysis, PPI and CPI are
measures of the vulnerability of each performance parameter
and each loading case, respectively. Hence, the integration of
PPI and CPI indicates the vulnerability of a particular
parameter/loading case combination. The above design
synthesis concept provides a framework for formulating the
quantifiable portion of a system design, from which advanced
optimisation techniques can be developed. The optimisation
objective function should be an overall measurement of design
quality of a structural system. An overall performance index
(OPI) is used to develop the overall objective function. The
OPI, which takes the form of a qualitative score, can be
established for the system by considering all the performances
and all the loading cases. The OPI function lies in the range of
0–100. Each performance parameter and each loading case is
given a weighting value according to its importance. The OPI
can be expressed as follows (for the un-weighted case):
m
i
n
j
ji
nm 1 1
CPIPPI
100
OPI (3)
3. IJRET: International Journal of Research in Engineering and Technology e-ISSN: 2319-1163 | p-ISSN: 2321-7308
__________________________________________________________________________________________
Volume: 02 Issue: 07 | Jul-2013, Available @ http://www.ijret.org 198
},,2,1,{ maxmin
kixxx iii
The OPI can be used to compare the performances of different
designs under a same weighting system. The higher the OPI
score, the more reliable the design would be. The OPI reflects
the optimisation model (Eqn. (5) (see section 2.3)) and
assembles all the objectives in the model. The overall
objective function is maximised using the effective zero-order
method, employing conjugate search directions [2]. The OPI is
of great significance because it integrates all optimisation
objectives with all design constraints in such a way that all the
system performances are treated as objectives in the
optimisation. Once some of the performances are improved up
to their best levels, these performances will be transformed
into constraints until all the performances reach their best
levels or cannot be improved any more (convergence).
2.2 Reliability Analysis
A reliability loading-case index (RLI) is proposed which is a
new development of first-order reliability-related method [1].
This method is based on the FORM developed by Hasofer and
Lind (H–L) [4] and later extended by Rackwitz and Fiessler
(R–F) [5]. However, in the present approach a different
method is presented involving the evaluation of the RLI. The
RLI reflects all the possible outcomes such as the
performances and cost of the design and it can be formulated
as:
i
ij
d
Pj
d
WWRLI i
i
2
)(max
(4)
mi ,,2,1 and nj ,,2,1
where WPi
is a weighting factor (range, 0–1) which reflects
performance, dij
is a data point which indicates the
performance parameters and loading case, σdi
is the standard
deviation of the performances, and W is the magnification
factor applied to a particular parameter. i indicates the i-th
performance, and j indicates the j-th loading case.
W is used to amplify the MSNS values to ensure they are
significant when the design variable is changed, thereby
enabling the results to be easily assessed. It is assumed that W
cannot be equal to 0. Preliminary calculations indicate that this
factor should have a value in the range of 5–7.
2.3 A reliability-related multifactor optimization model
An optimisation method ―Multifactor Optimisation of
Structure Techniques‖ (MOST) has been incorporate with
reliability loading-case index (RLI) to execute a multi-factor
sizing optimisation. The design problem is to minimise the
structural mass, minimise the maximum stress minimise the
maximum displacement, and simultaneously maximise the
reliability loading-case index, subject to the design constraints
under single loading case. The optimisation problem to be
solved can be stated as follows:
find X = (x1, x2, …, xk)
min {M(X), σmax,j(X), and δmax,j(X) } and
max {RLIj(X)} (5)
s.t. {σmax,j ≤ σlim ; δmax,j ≤ δlim ; M ≤ Mlim ; RLIj ≥ RLIlim }
j = 1, 2, …, n
where k is the number of design variables, M is the structural
mass, σmax is the maximum stress of the structure, δmax is the
maximum displacement of the structure, RLI is the reliability
loading-case index, the subscript ‗lim‘ indicates a specified
performance limit for the structure, and n is the number of
loading cases. min
ix and max
ix are the lower and upper bounds
of the design variables of xi, respectively.
The implementation flowchart of the reliability-related
multifactor optimisation is illustrated in Fig. 1.
Fig -1: Implementation flow chart of the multifactor
optimisation methodology
3. NUMERICAL EXAMPLE
Consider a three dimensional structural S-Type load cell with
9 nodal points are given in Table 3. The initial structure has a
width (A1) of 50 mm and a height (A2) of 62 mm with the
volume of 27492 mm3
, as shown in Fig. 2. The structural
model annotated with 4 design variables which include width
(A1), height (A2), and thickness (A3 and A4). The centre hole
with ϕ16.5 mm is fixed in the optimisation process where an
electronic device is placed to take the strain deformation. Fig.
3 show that two M6 × 1 thread are taped at the centre of the
load cell and a M6 hole is drilled toward the centre of the hole
(see Fig. 3 – No.9). Since there are three M6 hole and thread
in the load cell where a minimum clearance of 3 mm must be
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Volume: 02 Issue: 07 | Jul-2013, Available @ http://www.ijret.org 199
kept, the thickness of the load cell is keep constant as 12.5
mm.
Table -3: Coordinates of nodal point of initial structure
X (mm) Y (mm) Z (mm)
1 0.0 0.0 0.0
2 50.0 0.0 0.0
3 50.0 43.0 0.0
4 50.0 52.0 0.0
5 50.0 62.0 0.0
6 0.0 62.0 0.0
7 0.0 19.0 0.0
8 0.0 10.0 0.0
9 25.0 31.0 0.0
Fig -2: S-type load cell (initial design)
Fig -3: Initial layout of the S-type load cell structure
The initial structure of S-type load cell is modelled using finite
element software in conjunction with MOST. The ANSYS
SOLID92 element is used to generate the finite element
model, which consists of 8407 quadrilateral elements, as
shown in Fig. 4. MOST uses the ‗input file‘ method in
ANSYS to perform the optimisation process until
convergence. In the optimization process, the finite element
modelling is executed using ANSYS command. The ‗input
file‘ is updated the improved design during each iteration
which is required by the finite element code during the
optimisation.
Fig -4: Finite element model of initial structure
In terms of boundary conditions, the areas of the bottom in all
directions are fixed to be zero. The S-type load cell is make up
of steel EN 24 with a load maximum is 2500 N (i.e., the safety
of factor is up to 2.5). The S-load cell is considered at a single
loading case, i.e. a uniform distributed load of P N/m2
. The
uniform distribution load is defined as:
𝑃 =
𝐹𝑜𝑟𝑐𝑒
𝑤𝑖𝑑𝑡 ℎ ×𝑡ℎ𝑖𝑐𝑘𝑛𝑒𝑠𝑠 𝑜𝑓 𝑙𝑜𝑎𝑑 𝑐𝑒𝑙𝑙
(5)
The material density is 7840 kg/m3
, the Young‘s modulus is
210 GPa, the yield stress is 600 MPa, and the Poisson‘s ratio
is 0.3. The overall objective of the design problem is to
minimise the stress (consequently to minimise the maximum
strain), the maximum displacement, and the structural mass,
and to maximise the reliability loading-case index (RLI).
Table 4 lists the standard deviation (σdi
) and weighting factor
(WPi
) (see Eqn. 4) of the maximum stress, maximum
displacement, structural mass, and the RLI. In this example,
the magnification factor is set to be 6.67.
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Volume: 02 Issue: 07 | Jul-2013, Available @ http://www.ijret.org 200
Table -4: The RLI design variables of individual weighing
factor and standard deviation
Performances
Standard
deviation (σdi
)
Weighting
factor (WPi
)
Maximum stress (MPa) 5 0.01
Maximum displacement (µm) 0.5 0.01
Mass (g) 50 0.88
RLI - 0.10
The design is subjected to a maximum strain of 980 µ,
maximum displacement of 60 µm is imposed on all nodes in
all direction (x, y and z) and the structural mass is required to
be less than 160 grams. From these values (980 µ, 60 µm, and
160 grams) and the equation (4), the minimum acceptable
value for reliability-loading case index is calculated to be
1.834.
The optimisation of the S-load cell required ni = 36 iterations
to converge. The initial and optimised are shown in Fig. 5.
The attributes of the initial and optimised designs are given in
Table 5. The optimum design yields a minimal structural mass
of 143 grams and a RLI of 1.365. The maximum displacement
showed marked reductions from 159 to 53.3 µm. The
maximum von-Mises stress also remarkably reduced from 241
to 203 MPa, in the optimised design, thereby increasing the
safety of factor to ~3. Post-RLI calculations of initial and
optimised designs are given in Fig. 6 – 8.
Fig -5: Distribution of von-Mises Stress (Pa) of initial (left)
and optimised designs (right)
Table -5: Attributes of the initial and optimized designs of the
S-type load cell
Loading case 1
Initial Optimised
Maximum von Mises stress (MPa) 241 203
Maximum displacement (µm) 159 53.3
Maximum strain (µ) 1150 974
Mass (g) 215 143
Reliability loading-case index RLI 1.365 2.052
Fig -6: RLI calculations – preliminary data
Fig -7: RLI calculation – results from ANSYS simulation
Fig -8: RLI calculation – post-result
In the S-type load cell design, a single loading case is
considered. The convergence histories in Chart 1 and Chart 2
show that the trends in maximum displacement and maximum
6. IJRET: International Journal of Research in Engineering and Technology e-ISSN: 2319-1163 | p-ISSN: 2321-7308
__________________________________________________________________________________________
Volume: 02 Issue: 07 | Jul-2013, Available @ http://www.ijret.org 201
stress. Charts 1 and 2 shows that an initially sharp decrease
(first iteration) in maximum displacement and maximum
stress. This is because the reduction of width and height of the
load cell which have a least impact on the stress and
displacement. As a result, the structural mass is reduced by
approximately 29% (see Chart 3). To attain convergence, the
height and width of the load cell shows a marked decrease by
approximately 4% and 30%, respectively.
The centre hole, ϕ16.5 mm, is fixed in the optimisation
process. Fig. 9 shows that the maximum strain distribution
across the width is increased by approximately 23%.
Chart -1: Optimisation convergence history of maximum
displacement
Chart -2: Optimisation convergence history of maximum
stress
Chart -3: Optimisation convergence history of mass and
design variables
Fig -9: Strain distribution of initial and optimised structure
across the width of load cell
CONCLUSIONS
A sizing and shape optimisation was presented that combines
a multifactor shape optimisation with a reliability loading-case
index using a parametric finite element model. The application
of this method to an S-type load cell was showed an
improvement of the structural performance and also indirectly
increased the profit by at least 30% (i.e., reducing the mass by
30%).
Future different shape optimisation on this S-type load cell
will be further analysing in order to withstand a maximum
load capacity at a minimum volume.
REFERENCES
[1]. Chung Ket Thein, Jing-Sheng Liu. Effective structural
sizing/shape optimisation through a reliability-related
multifactor optimisation approach. Multidiscipline Modeling
in Materials and Structures. 8(2)(2012): pp. 159 - 177
[2]. Liu, J.S. and Hollaway, L. Design optimisation of
composite panel structures with stiffening ribs under multiple
loading case. Computers & Structures. 78(4)(2000): pp. 637-
647.
[3]. Liu, J.S. and Thompson, G. The multi-factor design
evaluation of antenna structures by parameters profile
analysis. J. Engng Manufac. Proc Inst. Mech. Eng.
210(B5)(1996): pp. 449-456.
[4]. Hasofer, A.M. and Lind, N.C. Exact and invariant second-
moment code format. J. Eng MEch. Div. ASCE, 100(1)(1974):
pp. 111-121.
[5]. Rackwitz, R. and Fiessler, B. Structural reliability under
combined load sequences. Computers & Structures. 9(1978):
pp. 489-494.
BIOGRAPHIES
Chung Ket Thein was born in Malaysia. He
obtained his Bachelors and PhD in
Mechanical Engineering from University of
Hull, United Kingdom. His research
interests are the development of reliability
assessment and engineering design
optimisation using finite element method.