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Research Topic : Affective computing
Australian State/Territory : VIC
Australian State/Territory : NSW
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  • Funded Activity

    Linkage Projects - Grant ID: LP0455343

    Funder
    Australian Research Council
    Funding Amount
    $70,668.00
    Summary
    DEVELOPING A SMART FIRE RISK ADVISORY SYSTEM USING FIRE MODELLING AND KNOWLEDGE-BASED SYSTEMS TECHNOLOGIES. This project aims to develop a prototype fire risk advisory system for fire prevention and protection. Intelligent knowledge-based systems technologies will be tailored to provide a standardised approach for fire risk analysis by using collective expertise of fire engineers and fire modelling. This project will lead to a significant advancement to the development of intelligent systems tec .... DEVELOPING A SMART FIRE RISK ADVISORY SYSTEM USING FIRE MODELLING AND KNOWLEDGE-BASED SYSTEMS TECHNOLOGIES. This project aims to develop a prototype fire risk advisory system for fire prevention and protection. Intelligent knowledge-based systems technologies will be tailored to provide a standardised approach for fire risk analysis by using collective expertise of fire engineers and fire modelling. This project will lead to a significant advancement to the development of intelligent systems techniques for industrial applications and provide a better fire risk analysis tool for fire protection and preventions with the benefit of reduced risk for buildings.
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    Funded Activity

    Linkage Projects - Grant ID: LP0347399

    Funder
    Australian Research Council
    Funding Amount
    $69,099.00
    Summary
    OPTIMISATION OF COMPACT BOILING HEAT EXCHANGERS USING ARTIFICIAL NEURAL NETWORK. Compact heat exchangers are increasingly considered for duties in many industrial applications, involving phase change processes of boiling and condensation. In many cases such applications are completely new and no previous experience or information is available for constructive design of compact heat exchangers. This project aims to develop a commercially-viable design methodology that will be innovative and novel .... OPTIMISATION OF COMPACT BOILING HEAT EXCHANGERS USING ARTIFICIAL NEURAL NETWORK. Compact heat exchangers are increasingly considered for duties in many industrial applications, involving phase change processes of boiling and condensation. In many cases such applications are completely new and no previous experience or information is available for constructive design of compact heat exchangers. This project aims to develop a commercially-viable design methodology that will be innovative and novel with in mind of robust and speedy computations of key design parameters of compact boiling heat exchangers through the artificial neural networks (ANN) model and maintaining the inherent accuracy associated with the solutions of the boiling flow and heat transfer processes from computational fluid dynamics (CFD) and validated using experimental data. It will provide a cutting edge to the Industry Partner to compete successfully on the local and global market fronts in designing and manufacturing compact boiling heat exchangers.
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    Showing 1-2 of 2 Funded Activites

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