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Near-field prediction of chemical hazard diffusion based on improved differential evolution algorithm and fireworks

Chaoshuai Han^1,2, Xuezheng Zhu³, Jin Gu¹

¹Equipment Support Teaching and Research Section, Institute of NBC Defence, Beijing, China.

Environmental Monitoring and Assessment

|September 15, 2021

Summary

A new chemical hazard diffusion model (CHDNFP) uses computational fluid dynamics (CFD) and a hybrid optimization algorithm (IDEFWA) for accurate near-field predictions. This approach enhances safety by improving the simulation of hazardous substance dispersion.

Keywords:

CFD Chemical hazard Diffusion simulation FWA IDEFWA Near-field prediction

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Area of Science:

Computational fluid dynamics (CFD)
Chemical hazard diffusion modeling
Optimization algorithms

Background:

CFD technology offers advantages for simulating small to medium-scale chemical hazard diffusion.
Accurate prediction of chemical dispersion is crucial for emergency response and risk assessment.

Purpose of the Study:

To develop and validate a near-field chemical hazard diffusion prediction model (CHDNFP).
To enhance model accuracy and efficiency using a hybrid optimization algorithm (IDEFWA).

Main Methods:

CHDNFP model construction based on conservation equations (component, momentum, turbulence).
Implementation of non-uniform mesh refinement, model discretization, and iterative equation solving.
Design of IDEFWA, integrating Differential Evolution Algorithm (DEA) and Fireworks Algorithm (FWA) for predictive modeling.

Main Results:

IDEFWA reduced relative root mean square error to ~25% in tracer experiments.
IDEFWA demonstrated faster and more accurate solutions compared to ABCA and GA.
CHDNFP-IDEFWA showed comparable accuracy to PISOFOAM, with a 26.05% improvement in calculation accuracy.

Conclusions:

The CHDNFP model coupled with IDEFWA provides accurate and efficient near-field chemical hazard diffusion predictions.
IDEFWA is a robust optimization algorithm for enhancing predictive model performance.
The developed model offers a significant advancement over existing methods for chemical hazard simulation.