<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-07-08T08:44:08Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/AF882B88-D180-45E3-8283-826940C00BC7" ns1:id="AF882B88-D180-45E3-8283-826940C00BC7"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/CEB9A51E-C027-440E-87D6-644065C36043" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/6F8B10D7-D890-4E4C-80E5-BD6EF671823A" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/6F8B10D7-D890-4E4C-80E5-BD6EF671823A" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/49CE1A16-66A9-4F59-A70D-33185F63078F" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2025-09-29T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/9B633ABB-6405-485A-8FA7-DC83FAA46F86" ns1:rel="FUND" ns1:start="2025-05-31T23:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">10158645</ns2:identifier></ns2:identifiers><ns2:title>Precise Thermophysical Properties of Hydrogen Containing Streams; for Optimisation of Smart ResSim for Hydrogen</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Grant for R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>This project focused on advancing the capabilities of thermodynamic modelling for hydrogen-rich systems, particularly in applications where impurities play a significant role. The work will be organised into several distinct phases, each targeting a critical aspect of hydrogen's thermophysical properties and its implications for industrial use. The project will be leveraging the combined expertise of Zodan Solutions and TUV SUD NEL as A4I Partner to improve the accuracy of our Smart ResSim technology for hydrogen transportation &amp;amp; storage applications.

In this pioneering project, our primary mission is to enhance our cutting-edge technology's ability to accurately analyse and predict the behaviour of hydrogen transportation and geological storage. Initially focusing on the UK market, with a vision to expand globally, our ambitious goal is to accelerate the development of Smart ResSim, our state-of-the-art technology at Zodan Solutions. Through our previous IUK A4I Projects, this technology evolved into a sophisticated system that enables customers to perform precise monitoring and optimisation of CO2 storage processes. This initiative creates exciting opportunities for Zodan Solutions to position itself as a leader in the emerging hydrogen economy.

Our project aims to further refine our novel machine learning and mathematical models using newly generated experimental datasets of hydrogen containing fluids that represent real field conditions. This effort focuses on addressing key challenges with cost-effective solutions before commercial deployment, in the areas of hydrogen transportation and subsurface geological storage, with an emphasis on the UK continental shelf (UKCS). The project's technological advancements are designed to fill the current gap in the hydrogen market, where no readily available off-the-shelf solutions exist for these complex challenges:

1. Enhancement of the Smart ResSim Platform: We aim to optimise the Smart ResSim platform from Zodan Solutions using hydrogen thermophysical properties datasets collected under real field conditions.
2. Advancement of Thermodynamic Models: We will further develop our smart models and thermodynamic equations of state (EoSs), significantly benefiting the hydrogen sector by reducing measurement uncertainties.
3. Precise Monitoring of Hydrogen fluid flow in porous media: The project will focus on advanced monitoring techniques to analyse the propagation and geochemical interactions of hydrogen-rich fluids as they move through geological porous media.
4. Validation of Reactive Fluid Transport Models: We will validate our unique machine-learned models for hydrogen rich fluid transport ensuring that these models are robust, reliable, and ready for real-world application in hydrogen storage and transport scenarios.</ns2:abstractText></ns2:project>