Recent application of Computational Fluid Dynamics (CFD) in process safety and loss prevention: A review
In recent years, significant progress has been made to ensure that process industries are
among the safest workplaces in the world. However, with the increasing complexity of …
among the safest workplaces in the world. However, with the increasing complexity of …
A review on cone calorimeter for assessment of flame-retarded polymer composites
The cone calorimeter is an efficient instrument used to evaluate the reaction-to-fire
properties of measured materials via simulating a forced combustion bench-scale fire …
properties of measured materials via simulating a forced combustion bench-scale fire …
Machine learning and deep learning in chemical health and safety: a systematic review of techniques and applications
Machine learning (ML) and deep learning (DL) are a subset of artificial intelligence (AI) that
can automatically learn from data and can perform tasks such as predictions and decision …
can automatically learn from data and can perform tasks such as predictions and decision …
Prediction of methane hydrate formation conditions in salt water using machine learning algorithms
Predicting formation conditions of gas hydrates in salt water is important for the management
of hydrate in processes such as flow assurance, deep-water drilling, and hydrate-based …
of hydrate in processes such as flow assurance, deep-water drilling, and hydrate-based …
Prediction of BLEVE blast loading using CFD and artificial neural network
Abstract Boiling Liquid Expanding Vapour Explosions (BLEVEs) are extreme explosions
driven by nonlinear physical processes associated with explosively expanded vapour and …
driven by nonlinear physical processes associated with explosively expanded vapour and …
Accelerated design of flame retardant polymeric nanocomposites via machine learning prediction
Improving the flame retardancy of polymeric materials used in engineering applications is an
increasingly important strategy for limiting fire hazards. However, the wide variety of flame …
increasingly important strategy for limiting fire hazards. However, the wide variety of flame …
Prediction of attachment efficiency using machine learning on a comprehensive database and its validation
Colloidal particles can attach to surfaces during transport, but the attachment depends on
particle size, hydrodynamics, solid and water chemistry, and particulate matter. The …
particle size, hydrodynamics, solid and water chemistry, and particulate matter. The …
Predicting flammability-leading properties for liquid aerosol safety via machine learning
Flammable and explosive hazards, which have been well studied, are major safety concerns
in industrial processes. However, the liquid aerosolization phenomenon, which increases …
in industrial processes. However, the liquid aerosolization phenomenon, which increases …
Deep learning based quantitative property-consequence relationship (QPCR) models for toxic dispersion prediction
It is crucial for emergency responders to makes a quick and accurate prediction of toxic
chemical dispersions, which can lead to massive injuries and casualties. In this study, a toxic …
chemical dispersions, which can lead to massive injuries and casualties. In this study, a toxic …
Development of solubility prediction models with ensemble learning
The solubility parameter is widely used to select suitable solvents for polymers in the
polymer-processing industry. In this study, we established a Hildebrand solubility parameter …
polymer-processing industry. In this study, we established a Hildebrand solubility parameter …