International Conference on Production, Energy & Reliability (ICPER2020) – Call for papers

Dear fellow Colleagues, On behalf of our Centre Director Prof Guan Heng Yeoh, also an advisory committee member of ICPER2020, we proudly invite you to submit your work on production, energy, sustainability and reliability. This conference will be held in the Borneo Convention Centre Kuching (BCCK), Kuching, Malaysisa, on 14-16 July 2020. The paper submission Read more about International Conference on Production, Energy & Reliability (ICPER2020) – Call for papers[…]

Application of Machine Learning Techniques to Formulate Simulation Inputs for Fire Models

Inspired by the advanment of repid development in “machine learning” techniques, we now proposed using genetic algorithm theory to optimise the pyrolysis kinetics input data of any polymer composites for our fire field models (i.e. computational fluid dynamics based). Typically, pyrolysis kinetics is extracted via thermal gravemetry (TGA), where the solid decomposition is studied in Read more about Application of Machine Learning Techniques to Formulate Simulation Inputs for Fire Models[…]

AFAC19 – Research Forum presentation

On 27th August 2019, our Centre Director Prof Guan Heng Yeoh has delivered a plenary section in the AFAC19 research forum hosted in Melbourne Convention and Exhibition Centre (MCEC), Victoria, Australia. Australasian Fire and Emergency Service Authorities Council (AFAC) is a national council for fire & emergency service, partnering with Bushfire Natural Hazards CRC and Read more about AFAC19 – Research Forum presentation[…]

Using New 2D Nano-sheet Materials to Enhance Fire Safety for Lithium-ion Batteries

MXenes are a newly discovered class of two dimensional transition metal carbides, nitrides and carbonnitrides. They are emerging materials for electrochemical storage and possible use in lithiumion batteries for applications such as cell phones and electric vehicles. However, their practical applications are currently limited by challenges with manufacturing, and fire and explosion safety.

Developing a Predictive Model for Soot Particle Distribution

We have recently developed our own predictive model to understand soot particle size distribution adopting the Discrete Quadrature Method of Moments (DQMOM) Population Balance Approach (PBA). Using this technique, we can simulate the variation of size and number of particulates for any given time and space in enclosure field. This model incorporates interactive fire phenomena, Read more about Developing a Predictive Model for Soot Particle Distribution[…]

Development of bio-based fire retardants from apples

Recent advancement of bio-based aerogels has shown large potential as an absorbent material for resolving the global crude oil leakage issue. Owing to the bio-degradable features, these materials causes less damage to the ocean ecosystem while can effectively remove the oil pollution. A good example of bio-based aerogel material is pectin, which is an organic Read more about Development of bio-based fire retardants from apples[…]