Deep learning-based dispersion prediction model for hazardous chemical leaks using transfer learning

No abstract is available for this paper.

• Publication year

  2024

• Venue

  Chemical engineering research & design

• Publication date

  2024-05-01

• Fields of study

  Not labeled

• Identifiers
  DOI 10.1016/j.psep.2024.05.125
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Hydrogen leakage location prediction at hydrogen refueling stations based on deep learning

  2023cited by this paper
• Research on predicting the diffusion of toxic heavy gas sulfur dioxide by applying a hybrid deep learning model to real case data.

  2023cited by this paper
• Towards deep probabilistic graph neural network for natural gas leak detection and localization without labeled anomaly data

  2023cited by this paper
• Real-time hydrogen release and dispersion modelling of hydrogen refuelling station by using deep learning probability approach

  2023cited by this paper
• CFD-modelling of large-scale LH2 release and explosion experiments

  2023cited by this paper
• Real-time pipeline leak detection and localization using an Attention-based LSTM approach

  2023cited by this paper
• Integrating Process Dynamics in Data-driven Models of Chemical Processing Systems

  2023cited by this paper
• Real-time plume tracking using transfer learning approach

  2023cited by this paper
• A systematic review of consequence modeling studies of the process accidents in Iran from 2006 to 2022

  2023cited by this paper
• Safety analysis of hydrogen leakage accident with a mobile hydrogen refueling station

  2023cited by this paper
• Prediction model for the evolution of hydrogen concentration under leakage in hydrogen refueling station using deep neural networks

  2023cited by this paper
• A perspective survey on deep transfer learning for fault diagnosis in industrial scenarios: Theories, applications and challenges

  2022cited by this paper
• Application of long short-term memory recurrent neural networks for localisation of leak source using 3D computational fluid dynamics

  2022cited by this paper
• Numerical investigation of the dispersion features of hydrogen gas under various leakage source conditions in a mobile hydrogen refueling station

  2022cited by this paper
• Machine learning based quantitative consequence prediction models for toxic dispersion casualty

  2022cited by this paper
• Dispersion modeling and assessment of natural gas containing hydrogen released from a damaged gas transmission pipeline

  2022cited by this paper
• Real-time natural gas release forecasting by using physics-guided deep learning probability model

  2022cited by this paper
• Safety barrier performance assessment by integrating computational fluid dynamics and evacuation modeling for toxic gas leakage scenarios

  2022cited by this paper
• Research on Natural Gas Leakage and Diffusion Characteristics in Enclosed Building Layout

  2022cited by this paper
• Gas leakage detection using spatial and temporal neural network model

  2022cited by this paper
• Hazards of toluene storage tanks in a petrochemical plant: modeling effects, consequence analysis, and comparison of two modeling programs

  2021cited by this paper
• Spatiotemporal and layout-adaptive prediction of leak gas dispersion by encoding-prediction neural network

  2021cited by this paper
• Deep learning based quantitative property-consequence relationship (QPCR) models for toxic dispersion prediction

  2021cited by this paper
• A deep learning model for process fault prognosis

  2021cited by this paper
• Fault detection and diagnosis to enhance safety in digitalized process system

  2021cited by this paper
• What is being transferred in transfer learning?

  2020cited by this paper
• Transfer learning for process fault diagnosis: Knowledge transfer from simulation to physical processes

  2020cited by this paper
• Failure analysis integrated with prediction model for LNG transport trailer and thermal hazards induced by an accidental VCE: A case study

  2020cited by this paper
• Development of Flammable Dispersion Quantitative Property–Consequence Relationship Models Using Extreme Gradient Boosting

  2020cited by this paper
• Fault detection and diagnosis based on transfer learning for multimode chemical processes

  2020cited by this paper
• Fault detection and diagnosis in process system using artificial intelligence-based cognitive technique

  2020cited by this paper
• Toxic gas dispersion prediction for point source emission using deep learning method

  2019cited by this paper
• A Comprehensive Survey on Transfer Learning

  2019cited by this paper
• Direct Prediction of the Toxic Gas Diffusion Rule in a Real Environment Based on LSTM

  2019cited by this paper
• Toxic gas release modeling for real-time analysis using variational autoencoder with convolutional neural networks

  2018cited by this paper
• Comparison of Machine Learning Models for Hazardous Gas Dispersion Prediction in Field Cases

  2018cited by this paper
• Deep convolutional neural network model based chemical process fault diagnosis

  2018cited by this paper
• Robust data-driven model to study dispersion of vapor cloud in offshore facility

  2018cited by this paper
• Verification and validation of Phast consequence models for accidental releases of toxic or flammable chemicals to the atmosphere

  2018cited by this paper
• Dense gas dispersion model development and testing for the Jack Rabbit II phase 1 chlorine release experiments

  2018cited by this paper
• Atmospheric dispersion prediction and source estimation of hazardous gas using artificial neural network, particle swarm optimization and expectation maximization

  2018cited by this paper
• A deep belief network based fault diagnosis model for complex chemical processes

  2017cited by this paper
• Comparison of UDM and CFD simulations of a time varying release of LPG in geometrical complex environment

  2017cited by this paper
• Contaminant dispersion prediction and source estimation with integrated Gaussian-machine learning network model for point source emission in atmosphere.

  2016cited by this paper
• The real-time estimation of hazardous gas dispersion by the integration of gas detectors, neural network and gas dispersion models.

  2015cited by this paper

• A novel attention-enhanced deep learning framework for intelligent fault detection and diagnosis in dynamic chemical processes

  2026cites this paper
• UNet-ConvLSTM-based prediction of radionuclide dispersion under a decommissioning accident condition of Qinshan Phase I Nuclear Power Plant

  2026cites this paper
• Multi-task deep learning for pollutant source inversion with DFNN, LSTM, and Transformer architectures

  2026cites this paper
• Probabilistic risk assessment of VCE for chemical equipment, case study: Storage and transportation process of N-decane

  2025cites this paper
• Machine Learning for safety distances prediction during emergency response of toxic dispersion accidental scenarios

  2025cites this paper
• Efficient estimation of natural gas leakage source terms using physical information and improved particle filtering

  2025cites this paper
• Functional evidential reasoning model (FERM) – A new systematic approach for exploring hazardous chemical operational accidents under uncertainty

  2025cites this paper
• A new framework for water quality instabilities simulation by artificial intelligence approaches and optimization algorithms under uncertainty

  2025cites this paper
• A physics-informed data-driven model applied for gas dispersion

  2025cites this paper
• Evaluating the generalizability and transferability of acoustic leak detection models for water distribution networks.

  2025cites this paper
• Real-Time Gas Dispersion Model Prediction on Offshore Platforms based on CNN_Transformer Model

  2025cites this paper
• Assessing leak detection and localization techniques for application in end-of-line leakage stations in the industrial sector

  2025cites this paper
• Development of Convolutional Neural Network-Based Models for Efficient and Reliable Flashpoint Prediction

  2025cites this paper
• Performance analysis of optimized machine learning models for hydrogen leakage and dispersion prediction via genetic algorithms

  2025cites this paper
• Underwater Gas Leak Quantification by Convolutional Neural Network Using Images

  2025cites this paper
• Prediction of Settling Velocity of Microplastics by Multiple Machine-Learning Methods

  2024cites this paper
• Fast Identification of Flammable Chemicals Based on Broad Learning System

  2024cites this paper