scholarly journals Multi-Objective Optimization Method for Posture Prediction of Symmetric Static Lifting Using a Three-Dimensional Human Model

2020 ◽  
Vol 18 (2) ◽  
Author(s):  
Sirous Azizi ◽  
Afsaneh Dadarkhah ◽  
Alireza Asgharpour Masouleh
Keyword(s):  
Performance Measures ◽  
Three Dimensional ◽  
Human Model ◽  
Virtual Human ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Biomechanical Models ◽  
Human Models ◽  
Posture Prediction ◽  
Lifting Task

Background: The development of virtual human models has recently gained considerable attention in biomechanical studies intending to design for ergonomics. The computer-based simulations of virtual human models can reduce the time and cost of the design cycle. There is an increasing interest in finding the realistic posture of the human body with applications in prototype design and reduction of injuries in the workplace. Objectives: This paper presents a generic method based on a multi-objective optimization (MOO) for posture prediction of a sagittal-plane lifting task. Methods: Improved biomechanical models are used to formulate the predicted posture as a MOO problem. The lifting task has been defined by seven performance measures that are mathematically represented by the weighted sum of cost functions. Specific weights are assigned for each cost function to predict both stoop and squat type postures. Some inequality constraints have been used to ensure that the virtual human does not assume a completely unrealistic configuration. Results: The method can predict the hand configuration effectively. Simulations reveal that predicting a squat posture requires the minimization of certain objective functions, while these measures are less significant for the prediction of a stooped posture. Conclusions: In this study, a MOO-based posture prediction model with a validation process is presented. We employed a three-dimensional model to evaluate the applicability of using a combination of seven performance measures to the posture prediction of symmetric lifting tasks. Results have been compared with the available empirical data to validate the simulated postures. Furthermore, the assigned weights are obtained for a range of percentiles from 50% male to 90% female according to the postures obtained by 3D SSPPTM software.

Multi-objective optimization-based method for kinematic posture prediction: development and validation

Robotica ◽  
2010 ◽  
Vol 29 (2) ◽  
pp. 245-253 ◽  
Author(s):  
Jingzhou (James) Yang ◽  
Tim Marler ◽  
Salam Rahmatalla
Keyword(s):  
Performance Measures ◽  
Human Performance ◽  
Design Tool ◽  
Upper Body ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Validation Criteria ◽  
Posture Prediction ◽  
Development And Validation ◽  
Digital Human

SUMMARYPosture prediction plays an important role in product design and manufacturing. There is a need to develop a more efficient method for predicting realistic human posture. This paper presents a method based on multi-objective optimization (MOO) for kinematic posture prediction and experimental validation. The predicted posture is formulated as a multi-objective optimization problem. The hypothesis is that human performance measures (cost functions) govern how humans move. Twelve subjects, divided into four groups according to different percentiles, participated in the experiment. Four realistic in-vehicle tasks requiring both simple and complex functionality of the human simulations were chosen. The subjects were asked to reach the four target points, and the joint centers for the wrist, elbow, and shoulder and the joint angle of the elbow were recorded using a motion capture system. We used these data to validate our model. The validation criteria comprise R-square and confidence intervals. Various physics factors were included in human performance measures. The weighted sum of different human performance measures was used as the objective function for posture prediction. A two-domain approach was also investigated to validate the simulated postures. The coefficients of determinant for both within-percentiles and cross-percentiles are larger than 0.70. The MOO-based approach can predict realistic upper body postures in real time and can easily incorporate different scenarios in the formulation. This validated method can be deployed in the digital human package as a design tool.

scholarly journals A Three-Dimensional Numerical and Multi-Objective Optimal Design of Wavy Plate-Fins Heat Exchangers

Processes ◽  
2020 ◽  
Vol 9 (1) ◽  
pp. 9
Author(s):  
Chao Yu ◽  
Xiangyao Xue ◽  
Kui Shi ◽  
Mingzhen Shao
Keyword(s):  
Heat Exchangers ◽  
Cfd Simulation ◽  
Three Dimensional ◽  
Basis Functions ◽  
Approximation Model ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm ◽  
Colburn Factor ◽  
Heat Exchange Efficiency

This paper presents a method for optimizing wavy plate-fin heat exchangers accurately and efficiently. It combines CFD simulation, Radical Basis Functions (RBF) with multi-objective optimization to improve the performance. The optimization of the Colburn factor j and the friction coefficient f is regarded as a multi-objective optimization problem, due to the existence of two contradictory goals. The approximation model was obtained by Radical Basis Functions, and the shape of the heat exchanger was optimized by multi-objective genetic algorithm (MOGA). The optimization results showed that j increased by 17.62% and f decreased by 20.76%, indicating that the heat exchange efficiency was significantly enhanced and the fluid structure resistance reduced. Then, from the aspects of field synergy and tubulence energy, the performance advantage of the optimized structure was further confirmed.

Multi-day evaluation of space domain awareness architectures via decision analysis and multi-objective optimization

2022 ◽  
pp. 154851292110677
Author(s):  
Albert R Vasso ◽  
Richard G Cobb ◽  
John M Colombi ◽  
Bryan D Little ◽  
David W Meyer
Keyword(s):  
Decision Analysis ◽  
Performance Measures ◽  
Research Effort ◽  
National Policy ◽  
Space Environment ◽  
Multi Objective Optimization ◽  
Space Object ◽  
Multi Objective ◽  
Average Maximum ◽  
Us Government

The US Government is the world’s de facto provider of space object cataloging data, but it is challenged to maintain pace in an increasingly complex space environment. This work advances a multi-disciplinary approach to better understand and evaluate an underexplored solution recommended by national policy in which current collection capabilities are augmented with non-traditional sensors. System architecting techniques and extant literature identified likely needs, performance measures, and potential contributors to a conceptualized Augmented Network (AN). Multiple hypothetical architectures of ground- and space-based telescopes with representative capabilities were modeled and simulated on four separate days throughout the year, then evaluated against performance measures and constraints using Multi-Objective Optimization. Decision analysis and Pareto optimality identified a small, diverse set of high-performing architectures while preserving design flexibility. Should decision-makers adopt the AN approach, this research effort indicates (1) a threefold increase in average capacity, (2) a 55% improvement in coverage, and (3) a 2.5-h decrease in the average maximum time a space object goes unobserved.

Multi-objective optimization of a novel crash box with a three-dimensional negative Poisson’s ratio inner core

2017 ◽  
Vol 233 (2) ◽  
pp. 263-275 ◽  
Author(s):  
ChunYan Wang ◽  
SongChun Zou ◽  
WanZhong Zhao
Keyword(s):  
Energy Absorption ◽  
Optimization Algorithm ◽  
Poisson’S Ratio ◽  
Inner Core ◽  
Three Dimensional ◽  
Poisson's Ratio ◽  
Negative Poisson’S Ratio ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Negative Poisson's Ratio

The crash box can absorb energy from the beam as much as possible, so as to reduce the collision damage to the front part of the car body and protect the safety of passengers. This work proposes a novel crash box filled with a three-dimensional negative Poisson’s ratio (NPR) inner core based on an inner hexagonal cellular structure. In order to optimize and improve the crash box’s energy absorption performance, the multi-objective optimization model of the NPR crash box is established, which combines the optimal Latin hypercube design method and response surface methodology. Then, the microstructure parameters are further optimized by the multi-objective particle swarm optimization algorithm to obtain an excellent energy absorption effect. The simulation results show that the proposed NPR crash box can generate smooth and controllable deformation to absorb the total energy, and it can further enhance the crashworthiness through the designed optimization algorithm.

scholarly journals Automatic three-dimensional-scanned garment fitting based on virtual tailoring and geometric sewing

2019 ◽  
Vol 14 ◽  
pp. 155892501882531 ◽  
Author(s):  
Li Duan ◽  
Zhong Yueqi ◽  
Wu Ge ◽  
Hu Pengpeng
Keyword(s):  
Human Body ◽  
Feature Matching ◽  
Three Dimensional ◽  
Experimental Results ◽  
Human Model ◽  
Geometrical Method ◽  
Human Models ◽  
Feature Lines ◽  
Fitting Method ◽  
Geometrical Features

In this article, we presented a new automatic three-dimensional-scanned garment fitting method for A-Pose-scanned human models. Both the garment and the human body were decomposed based on feature lines defined by various landmarks. The patches of the three-dimensional garment were automatically positioned around the human model by setting up the correspondence via feature matching. Virtual sewing was engaged to obtain the final results of virtual dressing. The penetration between cloth model and human model was solved by a geometrical method constrained by Laplacian-based deformation. The experimental results indicated that the proposed method was an efficient way for redressing various garments onto various human models while maintaining the original geometrical features of garments.

Capturing Three-Dimensional In Vivo Lumbar Intervertebral Joint Kinematics Using Dynamic Stereo-X-Ray Imaging

2013 ◽  
Vol 136 (1) ◽  
Author(s):  
Ameet K. Aiyangar ◽  
Liying Zheng ◽  
Scott Tashman ◽  
William J. Anderst ◽  
Xudong Zhang
Keyword(s):  
Lumbar Spine ◽  
Three Dimensional ◽  
Lumbar Vertebrae ◽  
Lumbar Vertebra ◽  
Weight Lifting ◽  
Data Set ◽  
X Ray ◽  
Biomechanical Models ◽  
Lifting Task

Availability of accurate three-dimensional (3D) kinematics of lumbar vertebrae is necessary to understand normal and pathological biomechanics of the lumbar spine. Due to the technical challenges of imaging the lumbar spine motion in vivo, it has been difficult to obtain comprehensive, 3D lumbar kinematics during dynamic functional tasks. The present study demonstrates a recently developed technique to acquire true 3D lumbar vertebral kinematics, in vivo, during a functional load-lifting task. The technique uses a high-speed dynamic stereo-radiography (DSX) system coupled with a volumetric model-based bone tracking procedure. Eight asymptomatic male participants performed weight-lifting tasks, while dynamic X-ray images of their lumbar spines were acquired at 30 fps. A custom-designed radiation attenuator reduced the radiation white-out effect and enhanced the image quality. High resolution CT scans of participants' lumbar spines were obtained to create 3D bone models, which were used to track the X-ray images via a volumetric bone tracking procedure. Continuous 3D intervertebral kinematics from the second lumbar vertebra (L2) to the sacrum (S1) were derived. Results revealed motions occurring simultaneously in all the segments. Differences in contributions to overall lumbar motion from individual segments, particularly L2–L3, L3–L4, and L4–L5, were not statistically significant. However, a reduced contribution from the L5–S1 segment was observed. Segmental extension was nominally linear in the middle range (20%–80%) of motion during the lifting task, but exhibited nonlinear behavior at the beginning and end of the motion. L5–S1 extension exhibited the greatest nonlinearity and variability across participants. Substantial AP translations occurred in all segments (5.0 ± 0.3 mm) and exhibited more scatter and deviation from a nominally linear path compared to segmental extension. Maximum out-of-plane rotations (<1.91 deg) and translations (<0.94 mm) were small compared to the dominant motion in the sagittal plane. The demonstrated success in capturing continuous 3D in vivo lumbar intervertebral kinematics during functional tasks affords the possibility to create a baseline data set for evaluating the lumbar spinal function. The technique can be used to address the gaps in knowledge of lumbar kinematics, to improve the accuracy of the kinematic input into biomechanical models, and to support development of new disk replacement designs more closely replicating the natural lumbar biomechanics.

Multi-Objective Optimization of Suspension and Seat for Vehicle Ride Dynamics Behavior Using NSGA-II Method

2013 ◽  
Author(s):  
Kang Song ◽  
Xiao-kai Chen ◽  
Yi Lin
Keyword(s):  
Human Body ◽  
Pareto Frontier ◽  
Elastic Model ◽  
Pareto Optimal ◽  
Objective Functions ◽  
Multi Objective Optimization ◽  
Work Space ◽  
Multi Objective ◽  
Biomechanical Models ◽  
Seat Cushion

A seven degree-of-freedoms human body-seat-suspension model was built for multi-objective optimization of vehicle ride dynamics behavior. Biomechanical models of human body and elastic model of seat cushion were integrated with classical 1/4 car model. The root mean square values of head acceleration of human body, together with suspension work space and dynamic tire load, were selected as objective functions of optimization. Non-dimension method was introduced into the formulation of objective functions so that optimization could be independent of different running conditions. Parameter sensitivity analysis was utilized to explore the relation between objective functions and parameters of suspension and seat cushion. Based on the results of analysis, design variables were determined. Non-dominated Sorting Genetic Algorithm - II was used in this multi-objective optimization problem to compute Pareto optimal set and Pareto frontier. Results indicate that Pareto frontier includes two parts. These two parts have the nearly same range of dynamic tire load and share partial range of suspension work space in objective function space. In design variable space, two parts respectively correspond to two different distribution areas of Pareto optimal solution set. So, for the same expected objective, parameters of suspension and seat cushion usually have at least one available combination, which improves the flexibility of optimal design.

Sign in / Sign up

Export Citation Format

Share Document