Design Optimization of a Twist Compliant Mechanism With Nonlinear Stiffness

2013 ◽  
Author(s):  
Yashwanth Tummala ◽  
Mary Frecker ◽  
Aimy Wissa ◽  
James E. Hubbard
Keyword(s):  
Optimization Problem ◽  
Inner Core ◽  
Compliant Mechanism ◽  
Twist Angle ◽  
Von Mises Stress ◽  
Nonlinear Stiffness ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Specific Loading

A contact aided compliant mechanism called twist compliant mechanism is presented in this paper. This mechanism has nonlinear stiffness when it is twisted in both directions along its axis. The inner core of the mechanism is responsible for its flexibility in one twisting direction. The contact surfaces of the cross-members and compliant sectors are responsible for its high stiffness in the opposite direction. A twist compliant mechanism with desired twist angle and stiffness can be designed by choosing the right thickness of its cross-members, thickness of the core and thickness of its sectors. A multi-objective optimization problem with three objective functions is proposed in this paper, and used to design an optimal twist compliant mechanism with desired deflection. The objective functions are to minimize the mass and maximum von Mises stress observed, while minimizing or maximizing the twist angles under specific loading conditions. The multi-objective optimization problem proposed in this paper is solved using an ornithopter flight research platform as a case study, with the goal of using the twist compliant mechanism to achieve passive twisting of the wing during upstroke, while keeping the wing fully extended and rigid during the downstroke. Prototype twist compliant mechanisms have been fabricated using a waterjet cutter and will be tested as part of future work.

scholarly journals Braille Block Detection via Multi-Objective Optimization from an Egocentric Viewpoint

Sensors ◽  
2021 ◽  
Vol 21 (8) ◽  
pp. 2775
Author(s):  
Tsubasa Takano ◽  
Takumi Nakane ◽  
Takuya Akashi ◽  
Chao Zhang
Keyword(s):  
Optimization Problem ◽  
Line Pair ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Optimization Framework ◽  
Visually Impaired People ◽  
Comprehensive Comparison ◽  
Basic Characteristics ◽  
Support Devices

In this paper, we propose a method to detect Braille blocks from an egocentric viewpoint, which is a key part of many walking support devices for visually impaired people. Our main contribution is to cast this task as a multi-objective optimization problem and exploits both the geometric and the appearance features for detection. Specifically, two objective functions were designed under an evolutionary optimization framework with a line pair modeled as an individual (i.e., solution). Both of the objectives follow the basic characteristics of the Braille blocks, which aim to clarify the boundaries and estimate the likelihood of the Braille block surface. Our proposed method was assessed by an originally collected and annotated dataset under real scenarios. Both quantitative and qualitative experimental results show that the proposed method can detect Braille blocks under various environments. We also provide a comprehensive comparison of the detection performance with respect to different multi-objective optimization algorithms.

On Solving the Multi-Objective Software Package Upgradability Problem

2018 ◽  
Vol 9 (2) ◽  
pp. 18-38
Author(s):  
Noureddine Aribi ◽  
Yahia Lebbah
Keyword(s):  
Open Source Software ◽  
Software Package ◽  
Optimization Problem ◽  
Mixed Integer ◽  
Software Systems ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Before And After ◽  
The Stability

Free and open source software (FOSS) distributions are increasingly based on the abstraction of packages to manage and accommodate new features before and after the deployment stage. However, due to inter-package dependencies, package upgrade entails challenging shortcomings of deployment and management of complex software systems, inhibiting their ability to cope with frequent upgrade failures. Moreover, the upgrade process may be achieved according to some criteria (maximize the stability, minimize outdated packages, etc.). This problem is actually a multi-objective optimization problem. Throughout the article, the authors propose a Leximax approach based on mixed integer linear programming (MILP) to tackle the upgradability problem, while ensuring efficiency and fairness requirements between the objective functions. Experiments performed on real-world instances, from the MANCOOSI project, show that the authors' approach efficiently finds solutions of consistently high quality.

Optimization of a Bend-Twist-and-Sweep Compliant Mechanism

2014 ◽  
Author(s):  
Joseph Calogero ◽  
Mary Frecker ◽  
Aimy Wissa ◽  
James E. Hubbard
Keyword(s):  
Compliant Mechanism ◽  
Twist Angle ◽  
High Stress ◽  
Peak Stress ◽  
The Other ◽  
Optimal Designs ◽  
Von Mises Stress ◽  
Loading Conditions ◽  
Objective Functions ◽  
Von Mises

The overall goal of this research is to develop design optimization methodologies for compliant mechanisms that will provide passive shape change. Our previous work has focused on designing two separate contact-aided compliant elements (CCE): one for bend-and-sweep deflections, called the bend-and-sweep compliant element (BSCE), and another for twist deflection, called the twist compliant element (TCE). In the current paper, all three degrees of freedom, namely bending, twist, and sweep, are achieved simultaneously using a single passive contact-aided compliant mechanism. A new objective function for a contact-aided compliant mechanism is introduced and the results of the optimization procedure are presented. A bend-twist-and-sweep compliant element (BTSCE) can be inserted into the leading edge spar of an ornithopter, which is an avian-scale flapping wing un-manned air vehicle. The multiple objective functions of the optimization problem presented in this paper are: for upstroke, maximize tip bending and sweep deflections, maximize twist angle, and minimize the mass and peak von Mises stress in the BTSCE, and for downstroke, minimize tip bending and sweep deflections, minimize twist angle, and minimize the mass and peak von Mises stress in the BTSCE. This allows a designer to select a CCE from a set of optimal designs to accomplish all three displacement goals. The BTSCE was modeled using a commercial finite element program and optimized using NSGA-II, a genetic algorithm. The results for a single angled compliant joint (ACJ) for quasi-static upstroke loading conditions are presented. Two optimal designs are discussed and compared, one with a moderate peak stress and moderate deflections, the other with a high peak stress and large deflections. The optimization results are then compared to the previous results for the two independent CCEs. A design study showed that the angle of the ACJ needs to be obtuse to achieve a positive twist angle during upstroke, and an acute contact angle reduces peak stress. The deflection objective functions were relatively insensitive to eccentricity for upstroke and downstroke compared to the other parameters, and a high stress penalty was paid for any gains in deflection. The downstroke objective functions were relatively insensitive to all parameters compared to the upstroke objective functions, and were much smaller in magnitude. The optimization showed that under simplified upstroke loading conditions, the BTSCE with a single ACJ allowed bending deflection near 30% of the length of the BTSCE, twist angle near 0.14 radians, and sweep deflection near 5% of the length of the BTSCE.

scholarly journals MULTI-OBJECTIVE OPTIMIZATION WITH OPTIMAL COMBINATION CRITERIA s APPLIED TO DETERMINE FREEZE DRYING REGIME FOR CRUSTACEAN GROUP (PENAEUS MONODON)

2010 ◽  
Vol 13 (2) ◽  
pp. 59-71
Author(s):  
Dzung Tan Nguyen ◽  
Hai Xuan Le ◽  
Dzung Van Trinh
Keyword(s):  
Freeze Drying ◽  
Optimization Problem ◽  
Penaeus Monodon ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Technological Regime ◽  
Multi Objective ◽  
Energy Expenditures ◽  
Temperature And Pressure ◽  
Drying Regime

This article presents research results from the freeze drying regime for penaeus monodon based-on the solution of the multi-objective optimization problem. Experiments were carried out to determine the objective functions to describe influence of technological parametres (temperature and pressure of sublimation environment, times of freeze drying) during processing freeze drying. The multi-objective optimization problem was solved by Utopian point method with combination criteria s. The best technological regime for freeze drying was determined. At received freeze drying regime we have minimal energy expenditures, minimal contraction of product and minimal loss of vitamin c, humidity of material meet requirements from 2 to 6 percentage and maximal absorbent return of product.

scholarly journals Design of Pareto-Optimal Radar Receive Filters

2011 ◽  
Vol 57 (4) ◽  
pp. 477-481 ◽  
Author(s):  
Antonio De Maio ◽  
Marco Piezzo ◽  
Salvatore Iommelli ◽  
Alfonso Farina
Keyword(s):  
Quadratic Forms ◽  
Optimization Problem ◽  
Pareto Optimal ◽  
Relative Importance ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Sidelobe Level ◽  
Multi Objective ◽  
Optimal Theory ◽  
Peak Sidelobe Level

Design of Pareto-Optimal Radar Receive Filters This paper deals with the design of radar receive filters jointly optimized with respect to sidelobe energy and sidelobe peaks via Pareto-optimal theory. We prove that this criterion is tantamount to jointly minimizing two quadratic forms, so that the design can be analytically formulated in terms of a multi-objective optimization problem. In order to solve it, we resort to the scalarization technique, which reduces the vectorial problem into a scalar one using a Pareto weight defining the relative importance of the two objective functions. At the analysis stage, we assess the performance of the receive filters in correspondence of different values of the Pareto weight highlighting the performance compromises between the Integrated Sidelobe Level (ISL) and the Peak Sidelobe Level (PSL).

An Optimal Study of a Gripper Compliant Mechanism Based on Fuzzy-Taguchi Method

2013 ◽  
Vol 418 ◽  
pp. 141-144 ◽  
Author(s):  
Thanh Phong Dao ◽  
Shyh Chour Huang
Keyword(s):  
Taguchi Method ◽  
Optimization Problem ◽  
Virtual Work ◽  
Compliant Mechanism ◽  
Vertical Force ◽  
Horizontal Force ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Rigid Body Model ◽  
Energy Store

In this paper, a gripper mechanism with two flexible elements for grasping the objects was investigated. In general, to achieve the good the flexibility and the life strength, the flexible hinges often offer the highest elastic energy store while the lowest stress concentration is also required simultaneously. Therefore, to handle this multi-objective optimization problem, this study used the fuzzy logic based Taguchi method. The two input parameters, namely a vertical force and a horizontal force that primarily influence the displacement and the stress. These were controlled with regard to two-objective functions as the torque of torsional spring and the stress. In addition, formulating two-objective functions was based on the procedure of a pseudo-rigid-body model (PRBM) and the principle of virtual work. The results found that a vertical force of 0.5 lb and a horizontal force of 0.4 lb are favorable parameters for a suggested gripper. Using ANOVA, the results also revealed that a vertical force is the most significant parameter with highest F value of 1.188.

scholarly journals MULTI-OBJECTIVE OPTIMIZATION WITH OPTIMAL STANDARD COMBINATION OF R APPLIED TO DETERMINE REGIME TECHNOLOGICAL FREEZE DRYING OF PENAEUS MERGUIENSIS

2010 ◽  
Vol 13 (2) ◽  
pp. 66-75
Author(s):  
Dzung Tan Nguyen ◽  
Hai Xuan Le ◽  
Dzung Van Trinh
Keyword(s):  
Freeze Drying ◽  
Optimization Problem ◽  
Minimum Energy ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Optimal Regime ◽  
Multi Objective ◽  
Energy Expenditures ◽  
Vitamine C ◽  
Penaeus Merguiensis

This article presents research results of determinative regime technological freeze drying of Penaeus Merguiensis by method to solve a multi-Objective optimization problem with optimal standard combination of R. Experimental research was carried out building objective functions to describe influence of technological element (temperature of sublimation environment, pressure of sublimation environment and times of freeze drying) during processing freeze drying. By restricted zone (optimal standard combination of R) method determined optimal regime technological freeze drying have minimum energy expenditures/1 kg product, minimum humidity of material, maximum absorbent return of product, minimum contraction of product and minimum loss of vitamine c.

An Interval-Based Approach for Evolutionary Multi-Objective Optimization of Project Portfolios

2019 ◽  
Vol 18 (04) ◽  
pp. 1317-1358 ◽  
Author(s):  
Fausto Balderas ◽  
Eduardo Fernandez ◽  
Claudia Gomez-Santillan ◽  
Nelson Rangel-Valdez ◽  
Laura Cruz
Keyword(s):  
Optimization Problem ◽  
Pareto Frontier ◽  
Region Of Interest ◽  
Project Portfolio ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Public Project ◽  
Multi Objective ◽  
Imperfect Knowledge ◽  
Project Portfolios

Project portfolio selection is addressed here as a multi-objective optimization problem. This work introduces an interval-based method that takes into consideration imperfect knowledge of the contribution of projects to a portfolio, the project requirements, available resources and preference parameters in the model. The multi-objective optimization problem is solved using an evolutionary algorithm that is adapted to handle intervals. To direct the search toward the region of interest of the Pareto frontier, the preferences of the decision maker (DM) are incorporated using an interval-based outranking approach. This allows to address problems with many objective functions; intransitive preferences and incomparability situations can also be handled using this approach. In terms of analyzing robustness, the DM can obtain different solutions according to his/her level of conservatism. The effectiveness of this proposal was tested both on an example from the related literature and another example of a public project portfolio with nine objective functions and large number of applicant projects.

scholarly journals A New Approach to Group Multi-Objective Optimization under Imperfect Information and Its Application to Project Portfolio Optimization

2021 ◽  
Vol 11 (10) ◽  
pp. 4575
Author(s):  
Eduardo Fernández ◽  
Nelson Rangel-Valdez ◽  
Laura Cruz-Reyes ◽  
Claudia Gomez-Santillan
Keyword(s):  
Portfolio Optimization ◽  
Imperfect Information ◽  
Model Parameters ◽  
Final Decision ◽  
Project Portfolio ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
New Approach ◽  
Multi Objective ◽  
Group Member

This paper addresses group multi-objective optimization under a new perspective. For each point in the feasible decision set, satisfaction or dissatisfaction from each group member is determined by a multi-criteria ordinal classification approach, based on comparing solutions with a limiting boundary between classes “unsatisfactory” and “satisfactory”. The whole group satisfaction can be maximized, finding solutions as close as possible to the ideal consensus. The group moderator is in charge of making the final decision, finding the best compromise between the collective satisfaction and dissatisfaction. Imperfect information on values of objective functions, required and available resources, and decision model parameters are handled by using interval numbers. Two different kinds of multi-criteria decision models are considered: (i) an interval outranking approach and (ii) an interval weighted-sum value function. The proposal is more general than other approaches to group multi-objective optimization since (a) some (even all) objective values may be not the same for different DMs; (b) each group member may consider their own set of objective functions and constraints; (c) objective values may be imprecise or uncertain; (d) imperfect information on resources availability and requirements may be handled; (e) each group member may have their own perception about the availability of resources and the requirement of resources per activity. An important application of the new approach is collective multi-objective project portfolio optimization. This is illustrated by solving a real size group many-objective project portfolio optimization problem using evolutionary computation tools.

Auto-sharing parameters for transfer learning based on multi-objective optimization

2021 ◽  
pp. 1-13
Author(s):  
Hailin Liu ◽  
Fangqing Gu ◽  
Zixian Lin
Keyword(s):  
Transfer Learning ◽  
Optimization Problem ◽  
Data Sets ◽  
Multi Objective Optimization ◽  
Particle Swarm Optimizer ◽  
Real World Data ◽  
Data Set ◽  
Target Task ◽  
Main Research ◽  
Multi Objective

Transfer learning methods exploit similarities between different datasets to improve the performance of the target task by transferring knowledge from source tasks to the target task. “What to transfer” is a main research issue in transfer learning. The existing transfer learning method generally needs to acquire the shared parameters by integrating human knowledge. However, in many real applications, an understanding of which parameters can be shared is unknown beforehand. Transfer learning model is essentially a special multi-objective optimization problem. Consequently, this paper proposes a novel auto-sharing parameter technique for transfer learning based on multi-objective optimization and solves the optimization problem by using a multi-swarm particle swarm optimizer. Each task objective is simultaneously optimized by a sub-swarm. The current best particle from the sub-swarm of the target task is used to guide the search of particles of the source tasks and vice versa. The target task and source task are jointly solved by sharing the information of the best particle, which works as an inductive bias. Experiments are carried out to evaluate the proposed algorithm on several synthetic data sets and two real-world data sets of a school data set and a landmine data set, which show that the proposed algorithm is effective.

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