A5061182098- Manufacturing Process and Optimization
- Mechanical Behavior of Composites
- Advanced Malware Detection Techniques
- Experimental Learning in Engineering
- 3D Shape Modeling and Analysis
- Advanced Multi-Objective Optimization Algorithms
- Optimal Experimental Design Methods
- Structural Load-Bearing Analysis
- Silicone and Siloxane Chemistry
- Polymer Nanocomposites and Properties
- Textile materials and evaluations
- Fuel Cells and Related Materials
- Injection Molding Process and Properties
- Advanced battery technologies research
- Mathematical Approximation and Integration
- Material Properties and Processing
- Electrocatalysts for Energy Conversion
- Numerical methods in inverse problems
- Synthesis and properties of polymers
- Industrial Vision Systems and Defect Detection
- Smart Grid Security and Resilience
- Epoxy Resin Curing Processes
- Structural Analysis and Optimization
- Network Security and Intrusion Detection
- Mathematical Inequalities and Applications
National Composites Centre
2024
University of Bristol
2024
Chung Yuan Christian University
1993-2007
Manufacture-induced defects are a critical issue in composites applications that result high volumes of material waste and costly experimental trials to help mitigate this. Advances process modelling techniques have enabled the prediction defects. However, computational cost these tools limits their usefulness an industrial context as they often struggle with ever-increasing size structures, present significant challenges undertaking large optimisation problems. In this work, recently...
In this research, a Gaussian process (GP) surrogate modelling framework for the forming of dry carbon-fibre textile was investigated. A particular focus work is development dimension reduction algorithms, allowing to solve high-dimensional sparse optimisation problems. The concept active subspace adopted find principal space problem. Then, low-dimensional (i.e., active) can be obtained by selecting directions with highest explained variance. kernel-combined GP format developed. This takes...
Abstract In this study, a commercially available nano‐sized silica (SiO 2 ) was surface‐modified via esterification with oleic acid (OA), relatively inexpensive and hydrophobic modifier. The ‐OA) nanoparticles were used to disperse in the poly(amic acid) solutions of commercial polyimide (PI), for two‐layer film, thermally imidized form series PI/silica nanocomposites. effects addition SiO ‐OA on properties as‐prepared nanocomposites studied. results indicated that exhibited improvements...
The composites manufacturing industry relies heavily on manual hand layup, unsuitable for increasing demands. Automated Fiber Placement (AFP) offers a solution, but setup complexity and extensive trials inflate costs. Digital tools promise to expedite development, CPU-intensive simulations limit large-scale parameter optimisation. This paper introduces Gaussian Process (GP) models understanding AFP parameters' relationship with nip-point temperature. GP emulator streamlines optimisation,...