Multi-Constraint Topology Optimization of Forging Machine Bed for Light Weight Design

In order to minimize the fuel consumption, the topology optimization and sizing optimization are applied in the light-weight design of frame for energy-saving vehicle. The investigation consists of two stages. In the first stage, the static analysis and topology optimization were carried on the original frame to obtain the optimal layout. Then the sizing optimization was explored to find the feasible section dimension of beam. The simulation results revealed that the stress concentration and excessive local deformation of vehicle frame structure have been remarkably improved, meanwhile, the frame’s weight has been decreased more than 15.0%. It is concluded that the optimization method is effective to obtain the optimal light-weight design for vehicle frame.

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Aircraft Skin Stretch-Forming Die Light-Weight Design Using Topology Optimization

Materials Science Forum ◽

10.4028/www.scientific.net/msf.697-698.600 ◽

2011 ◽

Vol 697-698 ◽

pp. 600-603 ◽

Cited By ~ 1

Author(s):

Ji Hong Zhu ◽

H. Wang ◽

W.H. Zhang ◽

X.J. Gu

Keyword(s):

Numerical Simulation ◽

Topology Optimization ◽

Topology Design ◽

Surface Load ◽

Light Weight ◽

Stretch Forming ◽

Weight Design ◽

Aircraft Skin ◽

Skin Stretch ◽

Skin Stretch Forming

The purpose of this paper is to use the topology optimization method to solve the light-weight design problem of large aircraft skin stretch-forming die. The platform of ABAQUS is firstly used for numerical simulation of skin stretch-forming. And the surface load conditions are therefore obtained. The topology optimization is carried out accordingly to maximize the structural stiffness with the material properties and the boundary conditions properly defined. Referring to the obtained topology design, the optimal structure is reconstructed and then evaluated by the non-linear numerical simulation of stretch-forming. Compared with the traditional design, the numerical results have shown that the topology design can improve the stiffness and strength of the stretch-forming die significantly.

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Evolution-Strategies-Driven Optimization on Secure and Reconfigurable Interconnection PUF Networks

Electronics ◽

10.3390/electronics10050537 ◽

2021 ◽

Vol 10 (5) ◽

pp. 537

Author(s):

Hongxiang Gu ◽

Miodrag Potkonjak

Keyword(s):

Machine Learning ◽

State Of The Art ◽

Evolution Strategies ◽

Light Weight ◽

Network Configuration ◽

System Complexity ◽

Physical Unclonable Functions ◽

Output Stability ◽

Output Mapping ◽

Weight Design

Physical Unclonable Functions (PUFs) are known for their unclonability and light-weight design. However, several known issues with state-of-the-art PUF designs exist including vulnerability against machine learning attacks, low output randomness, and low reliability. To address these problems, we present a reconfigurable interconnected PUF network (IPN) design that significantly strengthens the security and unclonability of strong PUFs. While the IPN structure itself significantly increases the system complexity and nonlinearity, the reconfiguration mechanism remaps the input–output mapping before an attacker could collect sufficient challenge-response pairs (CRPs). We also propose using an evolution strategies (ES) algorithm to efficiently search for a network configuration that is capable of producing random and stable responses. The experimental results show that applying state-of-the-art machine learning attacks result in less than 53.19% accuracy for single-bit output prediction on a reconfigurable IPN with random configurations. We also show that, when applying configurations explored by our proposed ES method instead of random configurations, the output randomness is significantly improved by 220.8% and output stability by at least 22.62% in different variations of IPN.

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