A5070239109- Topology Optimization in Engineering
- Composite Structure Analysis and Optimization
- Advanced Multi-Objective Optimization Algorithms
- Bone Tissue Engineering Materials
- Additive Manufacturing and 3D Printing Technologies
- Probabilistic and Robust Engineering Design
- Cellular and Composite Structures
- Mechanical Engineering and Vibrations Research
- Acoustic Wave Phenomena Research
- Vehicle Noise and Vibration Control
- Structural Health Monitoring Techniques
- Structural Load-Bearing Analysis
- Innovations in Concrete and Construction Materials
- 3D Printing in Biomedical Research
- Composite Material Mechanics
- Asphalt Pavement Performance Evaluation
- Remote Sensing and Land Use
- Structural Analysis of Composite Materials
- Structural Analysis and Optimization
- Robotic Locomotion and Control
- Robotic Mechanisms and Dynamics
- Rock Mechanics and Modeling
- Robotic Path Planning Algorithms
- Effects of Vibration on Health
- Fatigue and fracture mechanics
The University of Sydney
2021-2024
Shandong University of Science and Technology
2024
Tongji University
2019-2022
While ceramic additive manufacturing (AM) technologies have shown great promise to create functional scaffolds with tailored biomechanical properties, the true potential of these advanced techniques has not been fully exploited yet due lack practical optimisation design approaches. To address this challenge, a machine learning (ML)-based approach is proposed herein where 3D printing are combined fabricate functionally graded composed Triply Periodic Minimal Surfaces (TPMS), aiming fulfil...
Although additive manufacturing has offered substantially new opportunities and flexibility for fabricating 3D complex lattice structures, effective design of such sophisticated structures with desired multifunctional characteristics remains a demanding task. To tackle this challenge, we develop an inventive multiscale topology optimisation approach additively manufactured lattices by leveraging derivative-aware machine learning algorithm. Our objective is to optimise non-uniform unit cells...
Abstract In the past three decades, biomedical engineering has emerged as a significant and rapidly growing field across various disciplines. From an perspective, biomaterials, biomechanics, biofabrication play pivotal roles in interacting with targeted living biological systems for diverse therapeutic purposes. this context, silico modelling stands out effective efficient alternative investigating complex interactive responses vivo. This paper offers comprehensive review of swiftly...
Tissue scaffolds have emerged as a promising solution for treatment of critical size bone defects, offering significant advantages over conventional strategies. One the key functionalities is their ability to promote long-term ingrowth effectively. To enhance this functionality, we develop novel dynamic optimisation framework customise achieving maximum outcomes certain period in study. improve design efficiency, extensively leverage machine learning (ML) techniques within our proposed...
In this study, a novel multi-objective reliability-based design optimization (MORBDO) method considering the maximum allowable deviation range of variables is proposed for reducer housing electric vehicles. First, numerical model established by ABAQUS and verified experiments. A radial basis function (RBF) neural network used to construct approximate finite element model. The structural parameters RBF are optimized using heuristic global ability particle swarm (PSO) algorithm. Sequential...
Abstract This study proposes a machine learning (ML) based approach for optimizing fiber orientations of variable stiffness carbon reinforced plastic (CFRP) structures, where neural networks are developed to estimate the objective function and analytical sensitivities with respect design variables as substitute finite element analysis (FEA). To reduce number training samples improve regression accuracy, an active strategy is implemented by successively supplying effective along suboptimal...
The planetary gear train is often used as the main device for decelerating and increasing torque of drive motor electric vehicles. Considering lightweight requirement existing uncertainty in structural design, a multi-objective optimization design (MUOD) framework developed vehicle this study. volume transmission efficiency are taken into consideration objectives. manufacturing size, material, load input considered uncertainties. An approximate direct decoupling model, based on subinterval...
To address the frequent occurrence of rock burst disasters in areas with wide coal pillars during mining western area China, pillar Tingnan mine Shanxi Province was used as research background. Theoretical analysis, numerical simulation, and field tests were to establish mechanical criterion energy for dynamic instability pillars. The process mechanism under static load disturbances revealed, a prevention control scheme proposed. results indicated that when above reached stress failure index...
This study addressed the topology optimization of a carbon fiber reinforced plastic (CFRP) laminated battery-hanging structure an electric vehicle. To accommodate parameterization for thickness and orientation CFRP materials, discrete material (DMTO) technique was adopted. include metal as reinforcement into simultaneously, DMTO extended here to achieve concurrent topology, selection plate. Manufacturing constraints were applied, including suppressing intermediate void across direction...
<div class="section abstract"><div class="htmlview paragraph">With the growing prosperity of long-distance freight and urban logistics industry, demand for cargo trucks is gradually increasing. The connecting bracket critical part truck chassis, which bears load transmitted by road excitation reduces damage to frame caused load. However, occurrence rough conditions inevitable in heavy-duty transportation. In this paper, durability tests fatigue life analysis are carried out on...