scholarly journals Vibration Characteristic Based Material Optimization of an Automated Wheelchair

2021 ◽  
Vol 1116 (1) ◽  
pp. 012097
Author(s):  
Faraz Ahmad ◽  
Manish chandra sati ◽  
Mukesh singh shahi ◽  
Aakash Chauhan
2017 ◽  
Vol 7 (3) ◽  
pp. 10
Author(s):  
PAGE TOM ◽  
THORSTEINSSON GISLI ◽  
◽  

2016 ◽  
Vol 58 (3) ◽  
pp. 260-268 ◽  
Author(s):  
Hassan S. Hedia ◽  
Saad M. Aldousari ◽  
Noha Fouda

Symmetry ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 315
Author(s):  
Zeyun Shi ◽  
Jinkeng Lin ◽  
Jiong Chen ◽  
Yao Jin ◽  
Jin Huang

Many man-made or natural objects are composed of symmetric parts and possess symmetric physical behavior. Although its shape can exactly follow a symmetry in the designing or modeling stage, its discretized mesh in the analysis stage may be asymmetric because generating a mesh exactly following the symmetry is usually costly. As a consequence, the expected symmetric physical behavior may not be faithfully reproduced due to the asymmetry of the mesh. To solve this problem, we propose to optimize the material parameters of the mesh for static and kinematic symmetry behavior. Specifically, under the situation of static equilibrium, Young’s modulus is properly scaled so that a symmetric force field leads to symmetric displacement. For kinematics, the mass is optimized to reproduce symmetric acceleration under a symmetric force field. To efficiently measure the deviation from symmetry, we formulate a linear operator whose kernel contains all the symmetric vector fields, which helps to characterize the asymmetry error via a simple ℓ2 norm. To make the resulting material suitable for the general situation, the symmetric training force fields are derived from modal analysis in the above kernel space. Results show that our optimized material significantly reduces the asymmetric error on an asymmetric mesh in both static and dynamic simulations.


Agronomy ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 107
Author(s):  
Mahmudur Rahman ◽  
Lei Liu ◽  
Bronwyn J. Barkla

Rapeseed oil-extracted expeller cake mostly contains protein. Various approaches have been used to isolate, detect and measure proteins in rapeseeds, with a particular focus on seed storage proteins (SSPs). To maximize the protein yield and minimize hazardous chemical use, isolation costs and the loss of seed material, optimization of the extraction method is pivotal. For some studies, it is also necessary to minimize or avoid seed-to-seed cross-contamination for phenotyping and single-tissue type analysis to know the exact amount of any bioactive component in a single seed, rather than a mixture of multiple seeds. However, a simple and robust method for single rapeseed seed protein extraction (SRPE) is unavailable. To establish a strategy for optimizing SRPE for downstream gel-based protein analysis, yielding the highest amount of SSPs in the most economical and rapid way, a variety of different approaches were tested, including variations to the seed pulverization steps, changes to the compositions of solvents and reagents and adjustments to the protein recovery steps. Following SRPE, 1D-SDS-PAGE was used to assess the quality and amount of proteins extracted. A standardized SRPE procedure was developed and then tested for yield and reproducibility. The highest protein yield and quality were obtained using a ball grinder with stainless steel beads in Safe-Lock microcentrifuge tubes with methanol as the solvent, providing a highly efficient, economic and effective method. The usefulness of this SRPE was validated by applying the procedure to extract protein from different Brassica oilseeds and for screening an ethyl methane sulfonate (EMS) mutant population of Brassica rapa R-0-18. The outcomes provide useful methodology for identifying and characterizing the SSPs in the SRPE.


Author(s):  
Tarun Gangwar ◽  
Dominik Schillinger

AbstractWe present a concurrent material and structure optimization framework for multiphase hierarchical systems that relies on homogenization estimates based on continuum micromechanics to account for material behavior across many different length scales. We show that the analytical nature of these estimates enables material optimization via a series of inexpensive “discretization-free” constraint optimization problems whose computational cost is independent of the number of hierarchical scales involved. To illustrate the strength of this unique property, we define new benchmark tests with several material scales that for the first time become computationally feasible via our framework. We also outline its potential in engineering applications by reproducing self-optimizing mechanisms in the natural hierarchical system of bamboo culm tissue.


Sign in / Sign up

Export Citation Format

Share Document