A Systematic Approach to Identifying a Set of Feasible Designs

2017 ◽  
Author(s):  
Hyeongmin Han ◽  
Sehyun Chang ◽  
Harrison Kim
Keyword(s):  
Design Problem ◽  
Constraint Satisfaction Problem ◽  
Optimization Technique ◽  
Iteration Process ◽  
Function Evaluation ◽  
Design Variables ◽  
Bicycle Model ◽  
Engineering Design Problems ◽  
Data Points ◽  
Feasible Solutions

In engineering design problems, designers set boundaries of design variables and solve the system to find the design variables that satisfy a target performance. Once lower and upper bounds for each performance index are set, the design problem becomes Constraint Satisfaction Problem (CSP). In this paper, CSP problem is transformed into an optimization problem with a penalty function. Also, by applying optimization technique, set of feasible solutions are acquired. The set of solutions and all the function evaluation during the iteration process are stored in database. By utilizing a database query, the best solution among the data points are selected for the design problem. For the numerical experiment, a CSP with three variables and a bicycle model of vehicle design is tested with different scenarios.

Improvement of the Static and Dynamic Characteristics of Magnetic Head Sliders by Optimum Design

1999 ◽  
Vol 122 (1) ◽  
pp. 280-287 ◽  
Author(s):  
Hiromu Hashimoto ◽  
Yasuhisa Hattori
Keyword(s):  
Objective Function ◽  
Optimum Design ◽  
Amplitude Ratio ◽  
Optimization Technique ◽  
Hard Disk Drives ◽  
Maximum Amplitude ◽  
Disk Surface ◽  
Operating Conditions ◽  
Magnetic Head ◽  
Design Variables

The aim of this paper is to develop a general methodology for the optimum design of magnetic head sliders in improving the spacing characteristics between a slider and disk surface under static and dynamic operating conditions of hard disk drives and to present an application of the methodology to the IBM 3380-type slider design. To generate the optimal design variables, the objective function is defined as the weighted sum of the minimum spacing, the maximum difference in the spacing due to variation of the radial location of the head, and the maximum amplitude ratio of the slider motion. Slider rail width, taper length, taper angle, suspension position, and preload are selected as the design variables. Before the optimization of the head, the effects of these five design variables on the objective function are examined by a parametric study, and then the optimum design variables are determined by applying the hybrid optimization technique, combining the direct search method and successive quadratic programming. From the obtained results, the effectiveness of optimum design on the spacing characteristics of magnetic heads is clarified. [S0742-4787(00)03701-2]

Optimization in Trajectory Planning of Multi-Jointed Fingers in Dextrous Hand Designs

1991 ◽  
Author(s):  
A. Meghdari ◽  
H. Sayyaadi
Keyword(s):  
Dynamic Programming ◽  
Motion Control ◽  
Trajectory Planning ◽  
Degrees Of Freedom ◽  
Optimization Technique ◽  
Dynamic Programming Algorithm ◽  
Programming Algorithm ◽  
Kinematics And Dynamics ◽  
Feasible Solutions ◽  
Dextrous Hand

Abstract An optimization technique based on the well known Dynamic Programming Algorithm is applied to the motion control trajectories and path planning of multi-jointed fingers in dextrous hand designs. A three fingered hand with each finger containing four degrees of freedom is considered for analysis. After generating the kinematics and dynamics equations of such a hand, optimum values of the joints torques and velocities are computed such that the finger-tips of the hand are moved through their prescribed trajectories with the least time or/and energy to reach the object being grasped. Finally, optimal as well as feasible solutions for the multi-jointed fingers are identified and the results are presented.

Nonlinear Optimal Design of Dynamic Mechanical Systems

1992 ◽  
Author(s):  
T. E. Potter ◽  
K. D. Willmert ◽  
M. Sathyamoorthy
Keyword(s):  
Objective Function ◽  
Optimization Problems ◽  
Iteration Process ◽  
Optimization Method ◽  
Linear Constraints ◽  
Sum Of Squares ◽  
Function Evaluation ◽  
Deformation Analysis ◽  
Nonlinear Constraints ◽  
Quadratic Constraints

Abstract Mechanism path generation problems which use link deformations to improve the design lead to optimization problems involving a nonlinear sum-of-squares objective function subjected to a set of linear and nonlinear constraints. Inclusion of the deformation analysis causes the objective function evaluation to be computationally expensive. An optimization method is presented which requires relatively few objective function evaluations. The algorithm, based on the Gauss method for unconstrained problems, is developed as an extension of the Gauss constrained technique for linear constraints and revises the Gauss nonlinearly constrained method for quadratic constraints. The derivation of the algorithm, using a Lagrange multiplier approach, is based on the Kuhn-Tucker conditions so that when the iteration process terminates, these conditions are automatically satisfied. Although the technique was developed for mechanism problems, it is applicable to any optimization problem having the form of a sum of squares objective function subjected to nonlinear constraints.

Optimization of a vacuum cleaner fan suction and shaft power using Kriging surrogate model and MIGA

2021 ◽  
pp. 095765092110496
Author(s):  
Soheil Almasi ◽  
Mohammad Mahdi Ghorani ◽  
Mohammad Hadi Sotoude Haghighi ◽  
Seyed Mohammad Mirghavami ◽  
Alireza Riasi
Keyword(s):  
Optimization Design ◽  
Optimization Technique ◽  
Internal Flow ◽  
Latin Hypercube Sampling ◽  
Sample Space ◽  
Geometrical Parameters ◽  
Vacuum Cleaner ◽  
Time Saving ◽  
Design Variables ◽  
Shaft Power

Optimization of vacuum cleaner fan components is a low-cost and time-saving solution to satisfy the increasing requirement for compact energy-efficient cleaners. In this study, surrogate-based optimization technique is used and for the first time it is focused on maximization of Airwatt parameter, which describes the fan suction power, as an objective function (Case II). Besides, the shaft power is minimized (Case I) as another optimization target in order to reduce the power consumption of the vacuum cleaner. 11 geometrical variables of 3 fan components including impeller, diffuser and return channel are selected as the optimization design variables. 80 training points are distributed in the sample space using Advanced Latin Hypercube Sampling (ALHS) technique and the outputs of sample points are calculated by means of CFD simulations. Kriging and RSA surrogate models have been fitted to the outputs of the sample space. Through coupling of constructed Kriging models and Multi-Island Genetic Algorithm (MIGA), the optimal design for each of the optimization cases is presented and evaluated using numerical simulations. A 20.22% reduction in shaft power in Case I and an improvement of 27.73% in Airwatt in Case II have been achieved as the overall results of this study. Despite achieving goals in both optimization cases, a slight decrease in Airwatt in Case I (−6.20%) and a slight increase in shaft power in Case II (+4.82%) are observed relative to primary fan. Furthermore, the Analysis of Variance (ANOVA) determines the importance level of design variables and their 2-way interactions on the objective functions. It was concluded that geometrical parameters related to all of the fan components must be considered simultaneously to conduct a comprehensive optimization. The reasons of enhancement in optimal cases compared with the reference design have been further investigated by analysis of the fan internal flow field. Post-processing of the CFD results demonstrates that the applied geometrical modifications cause a more uniform flow through the flow passages of the optimal fan components.

scholarly journals A Nonlinear Inverse Design Problem for a Pipe Type Heat Exchanger Equipped with Internal Z-Shape Lateral Fins and Ribs

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6424
Author(s):  
Cheng-Hung Huang ◽  
Chih-Yang Kuo
Keyword(s):  
Heat Exchanger ◽  
Thermal Performance ◽  
Design Problem ◽  
Direct Problem ◽  
Numerical Solutions ◽  
Three Dimensional ◽  
Design Variables ◽  
Non Linear ◽  
Inverse Design Problem ◽  
Η Value

A non-linear three-dimensional inverse shape design problem was investigated for a pipe type heat exchanger to estimate the design variables of continuous lateral ribs on internal Z-shape lateral fins for maximum thermal performance factor η. The design variables were considered as the positions, heights, and number of ribs while the physical properties of air were considered as a polynomial function of temperature; this makes the problem non-linear. The direct problem was solved using software package CFD-ACE+, and the Levenberg–Marquardt method (LMM) was utilized as the optimization tool because it has been proven to be a powerful algorithm for solving inverse problems. Z-shape lateral fins were found to be the best thermal performance among Z-shape, S-shape, and V-shape lateral fins. The objective of this study was to include continuous lateral ribs to Z-shape lateral fins to further improve η. Firstly, the numerical solutions of direct problem were solved using both polynomial and constant air properties and then compared with the corrected solutions to verify the necessity for using polynomial air properties. Then, four design cases, A, B, C and D, based on various design variables were conducted numerically, and the resultant η values were computed and compared. The results revealed that considering continuous lateral ribs on the surface of Z-shape lateral fins can indeed improve η value at the design working condition Re = 5000. η values of designs A, B and C were approximately 13% higher than that for Z-shape lateral fins, however, when the rib numbers were increased, i.e., design D, the value of η became only 11.5 % higher. This implies that more ribs will not guarantee higher η value.

scholarly journals Parallelization of computational algorithms for optimization problems with high time consumption

2018 ◽  
Vol 157 ◽  
pp. 02054 ◽  
Author(s):  
Milan Vaško ◽  
Marián Handrik ◽  
Alžbeta Sapietová ◽  
Jana Handriková
Keyword(s):  
Computational Models ◽  
Optimization Problems ◽  
Optimization Algorithms ◽  
Fe Analysis ◽  
Function Evaluation ◽  
Computational Algorithms ◽  
Distributed Computing Systems ◽  
Computing Systems ◽  
Time Consumption ◽  
Design Variables

The paper presents an analysis of the use of optimization algorithms in parallel solutions and distributed computing systems. The primary goal is to use evolutionary algorithms and their implementation into parallel calculations. Parallelization of computational algorithms is suitable for the following cases - computational models with a large number of design variables or cases where the objective function evaluation is time consuming (FE analysis). As the software platform for application of distributed optimization algorithms is using MATLAB and BOINC software package.

scholarly journals Formulation and Solution of an Inverse Reliability Problem to Simulate the Dynamic Behavior of COVID-19 Pandemic

2021 ◽  
Vol 22 (1) ◽  
pp. 91-107
Author(s):  
F. S. Lobato ◽  
G. M. Platt ◽  
G. B. Libotte ◽  
A. J. Silva Neto
Keyword(s):  
Dynamic Behavior ◽  
Differential Evolution Algorithm ◽  
Iteration Process ◽  
Real Data ◽  
The Novel ◽  
Design Variables ◽  
Different Types ◽  
Evolution Algorithm ◽  
Novel Coronavirus ◽  
Optimization Loop

Different types of mathematical models have been used to predict the dynamic behavior of the novel coronavirus (COVID-19). Many of them involve the formulation and solution of inverse problems. This kind of problem is generally carried out by considering the model, the vector of design variables, and system parameters as deterministic values. In this contribution, a methodology based on a double loop iteration process and devoted to evaluate the influence of uncertainties on inverse problem is evaluated. The inner optimization loop is used to find the solution associated with the highest probability value, and the outer loop is the regular optimization loop used to determine the vector of design variables. For this task, we use an inverse reliability approach and Differential Evolution algorithm. For illustration purposes, the proposed methodology is applied to estimate the parameters of SIRD (Susceptible-Infectious-Recovery-Dead) model associated with dynamic behavior of COVID-19 pandemic considering real data from China's epidemic and uncertainties in the basic reproduction number (R0). The obtained results demonstrate, as expected, that the increase of reliability implies the increase of the objective function value.

Partitioning and Guided Search: A Generalized Approach to Problem Solving in Preliminary Design

1989 ◽  
Author(s):  
S. Srinivasan ◽  
R. H. Allen
Keyword(s):  
Problem Solving ◽  
Expert Systems ◽  
Directed Search ◽  
Preliminary Design ◽  
Levels Of Abstraction ◽  
Guided Search ◽  
Structure Information ◽  
Design Variables ◽  
Minimum Number ◽  
Feasible Solutions

Abstract We report on using problem partitioning and constraint-guided search as a generalized approach to problem-solving in preliminary design. Specifically, a generic design template has been created as a tool to structure information to facilitate problem-solving in three different domains. The approach has been tested through the implementation of knowledge-based systems for the preliminary design of mechanical springs, composite sublaminates and expert systems. Information in each implementation has been partitioned as hierarchical levels of abstraction related through constraints. Function identifies the top level design goals to reduce the search involved for feasible solutions. Goal-directed search, driven by the design application and top-down refinement, reduces the number of possible alternatives. The commonalities extant in the domains have been represented as design goals at three levels of abstraction in the design template. Similar frame-based knowledge representations with inheritance hierarchies and mixed reasoning have been developed for the KEE™-based implementations in each domain. Distinctions among the domains have been modelled as low level slots in the frame hierarchy. Parametric studies in the domains of mechanical springs, composite sublaminates and expert systems indicate that the minimum number of decision levels required to characterize the preliminary design process in these domains is three; fewer levels would be insufficient to fundamentally characterize the designs. Further, it is observed hierarchical structuring of design information facilitates capturing the interactions among design variables at different levels of abstraction. By using the template representation and reasoning in other divisible domains, the effectiveness of our approach can be further investigated.

Multiobjective Design Optimization of Microchannel Cooling System Using High Performance Thermal Vias in LTCC Substrates

2013 ◽  
Vol 10 (1) ◽  
pp. 40-47 ◽  
Author(s):  
Aparna Aravelli ◽  
Singiresu S. Rao ◽  
Hari K. Adluru
Keyword(s):  
Heat Transfer ◽  
Design Optimization ◽  
High Performance ◽  
Cooling System ◽  
Optimization Technique ◽  
Optimization Theory ◽  
Thermal Design ◽  
Design Variables ◽  
Microchannel Cooling ◽  
Multiobjective Design

Increased heat generation in semiconductor devices for demanding applications leads to the investigation of highly efficient cooling solutions. Effective options for thermal management include passing of cooling liquid through the microchannel heat sink and using highly conductive materials. In the author's previous work, experimental and computational analyses were performed on LTCC substrates using embedded silver vias and silver columns forming microchannels. This novel technique of embedding silver vias along with forced convection using a coolant resulted in higher heat transfer rates. The present work investigates the design optimization of this cooling system (microheat exchanger) using systems optimization theory. A new multiobjective optimization problem was formulated for the heat transfer in the LTCC model using the log mean temperature difference (LMTD) method of heat exchangers. The goal is to maximize the total heat transferred and to minimize the coolant pumping power. Structural and thermal design variables are considered to meet the manufacturability and energy requirements. Pressure loss and volume of the silver metal are used as constraints. A hybrid optimization technique using sequential quadratic programming (SQP) and branch and bound method of integer programming has been developed to solve the microheat exchanger problem. The optimal design is presented and sensitivity analysis results are discussed.

A Model-Based Formulation of Robust Design

2005 ◽  
Vol 127 (3) ◽  
pp. 388-396 ◽  
Author(s):  
Khalid Al-Widyan ◽  
Jorge Angeles
Keyword(s):  
Covariance Matrix ◽  
Robust Design ◽  
Design Problem ◽  
Engineering Systems ◽  
Design Environment ◽  
Design Task ◽  
Model Based ◽  
Functional Relations ◽  
Design Variables ◽  
Environment Parameters

Laid down in this paper are the foundations on which the design of engineering systems, in the presence of an uncontrollable changing environment, can be based. The changes in environment conditions are accounted for by means of robustness. To this end, a theoretical framework as well as a general methodology for model-based robust design are proposed. Within this framework, all quantities involved in a design task are classified into three sets: the design variables (DV), grouped in vector x, which are to be assigned values as an outcome of the design task; the design-environment parameters (DEP), grouped in vector p, over which the designer has no control; and the performance functions (PF), grouped in vector f, representing the functional relations among performance, DV, and DEP. A distinction is made between global robust design and local robust design, this paper focusing on the latter. The robust design problem is formulated as the minimization of a norm of the covariance matrix of the variations in PF upon variations in the DEP, aka noise in the literature on robust design. Moreover, one pertinent concept is introduced: design isotropy. We show that isotropic designs lead to robustness, even in the absence of knowledge of the statistical properties of the variations of the DEP. To demonstrate our approach, a few examples are included.

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