At the Translation Energy Research Centre (TERC) at the University of Sheffield from 29 May - 5 June 2024, I participated in an innovative experiment involving 128 channels Tunable Diode Laser Absorption Spectroscopy (TDLAS) to analyze the emissions from an Auxiliary Power Unit (APU). This cutting-edge technique utilizes specific laser wavelengths to measure the absorption of gases, providing precise data on the concentration and dynamics of exhaust emissions. The experiment aimed to enhance our understanding of the APU's performance and its environmental impact, contributing to the development of cleaner auxiliary power technologies.
At the Translation Energy Research Centre (TERC) at the University of Sheffield from July 3-7, 2023, I participated in an innovative experiment involving Tunable Diode Laser Absorption Spectroscopy (TDLAS) to analyze the emissions from an Auxiliary Power Unit (APU). This cutting-edge technique utilizes specific laser wavelengths to measure the absorption of gases, providing precise data on the concentration and dynamics of exhaust emissions. The experiment aimed to enhance our understanding of the APU's performance and its environmental impact, contributing to the development of cleaner auxiliary power technologies. The findings from this experiment will assist in optimizing APU designs for better fuel efficiency and reduced emissions, aligning with global sustainability goals.
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At the UKCCSRC Autumn 2022 Conference held at the University of Edinburgh, me and David had the opportunity to present a poster on "CO2 Frost Formation During Cryogenic Carbon Capture Using Tomography Analysis." This study focuses on utilizing tomography analysis to investigate CO2 frost formation, a significant challenge in the efficiency of cryogenic carbon capture processes. The poster session facilitated a rich exchange of ideas, highlighting novel techniques for monitoring and optimizing frost control, which is crucial for enhancing the performance of cryogenic systems. Engaging with other researchers provided valuable feedback and new perspectives, further advancing our understanding of CCS technologies.
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At the MTCUE 2022, the World Conference on Multiphase Transportation, Conversion, and Utilization of Energy, hosted virtually from Xi'an, China, from July 27-31, 2022, I presented a talk on "CNN-based Liquid Hold-up Estimation in Counter-Current Flow using Electrical Capacitance Tomography." This discussion centered on leveraging Convolutional Neural Networks (CNN) to enhance the accuracy and reliability of liquid hold-up measurements in counter-current flow systems, a critical aspect for optimizing energy conversion processes. The use of Electrical Capacitance Tomography (ECT) coupled with CNN introduces a robust method for real-time and non-invasive monitoring, driving advancements in flooding diagnostics.
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At the UKCCSRC Spring 2022 Conference on "Building Capacity for CCS Deployment," held at the University of Sheffield on April 20-21, 2022, I presented a poster titled "Study of CO2 Frost Formation During Cryogenic Carbon Capture Using Tomography Analysis." This presentation focused on the use of advanced tomography techniques to understand the dynamics of CO2 frost formation, a key challenge in the efficiency of cryogenic carbon capture systems.
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At the PCCC6 2021 Conference, hosted virtually from the UK on October 19-21, I delivered a talk on "Feasibility of Tomography Analysis to Study CO2 Frost Formation During Cryogenic Carbon Capture." This presentation explored the innovative use of tomography techniques to understand and manage CO2 frost, a crucial aspect of improving cryogenic carbon capture efficiency. My talk highlighted the technical details and potential breakthroughs in monitoring and optimizing frost formation processes.
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At the WCIPT-10 Global World Congress, a virtual conference held from September 13-16, 2021, I presented on "CNN for Packed Column Liquid Hold-up Estimation with Finite Element Modelling of ECT." This research delves into the integration of Convolutional Neural Networks (CNN) and finite element modeling to enhance the accuracy of Electrical Capacitance Tomography (ECT) in estimating liquid hold-up within packed columns. This innovative approach addresses complex challenges in the process industry by combining machine learning with advanced imaging techniques, offering significant improvements in process optimization and efficiency.
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At the UK Fluids Conference, held virtually from September 8-10, 2021, I had the opportunity to present our recent work about CNN-based Packed Column Liquid Hold-up Estimation using ECT and Finite Element Modelling. This research utilizes Convolutional Neural Networks (CNN) integrated with Electrical Capacitance Tomography (ECT) and finite element modeling to accurately predict liquid hold-up in packed columns—a critical parameter in optimizing industrial separation processes. The presentation sparked engaging discussions on the fusion of AI with traditional imaging techniques, showcasing how these technologies can revolutionize process monitoring and control in fluid dynamics.
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At the 1st FERIA Conference held at the University of Nottingham in September 2021, I presented our research on "Preliminary Study of CO2 Frost Formation during Cryogenic Carbon Capture using Tomography Analysis." This study explores innovative tomography techniques to understand and optimize CO2 frost formation, a critical aspect of enhancing cryogenic carbon capture processes. The presentation facilitated engaging discussions with other experts in the field, providing valuable insights that will guide future research. This conference was an excellent platform for showcasing our initial findings and learning from the pioneering work of others in energy research.
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During a follow-up session at the University of Chester from October 27 to November 2, 2020, we conducted our second test using Electrical Capacitance Tomography (ECT) to monitor CO2 frost. This continuation of our pioneering research further validated ECT's effectiveness in visualizing and quantifying CO2 frost accumulation. These tests are critical as they refine our ability to predict and manage frost-related challenges in CO2 transport and storage systems. The insights gained are paving the way for more reliable and safer CO2 management practices, highlighting the importance of innovative imaging techniques in environmental technology.
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In a groundbreaking experiment conducted at the University of Chester from October 27 to November 2, 2020, we conducted the first test of Electrical Capacitance Tomography (ECT) for monitoring CO2 frost buildup. This novel application of ECT aims to enhance our understanding and management of CO2 deposition in various environmental and industrial settings. The initial results are promising, demonstrating ECT's potential to provide real-time, non-invasive imaging of frost formation, thereby offering a critical tool for improving safety and efficiency in CO2 handling and storage operations. This test marks a significant step forward in our research endeavors.
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At the 2019 IEEE International Conference on Imaging Systems and Techniques in Abu Dhabi, I presented our paper on "Simulation of Flooding Phenomenon in Packed Columns using Electrical Capacitance Tomography." This innovative research explores advanced imaging techniques to simulate and analyze the dynamics within packed columns for carbon capture applications, enhancing our understanding and control of the flooding phenomenon. The conference provided a valuable platform to exchange ideas and receive feedback from leading experts in the field, further shaping our approach to optimizing carbon capture processes.
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At the UKCCSRC PACT facility training in Sheffield, Yuan Chen, Xiaoyu Wei, LABIB Mennatallah and David Cann engaged in hands-on experiments with advanced CO2 capture technologies. Highlights included operating a biomass combustion boiler and an amine capture plant, gaining practical insights into carbon capture mechanisms and efficiency. This experience bridged academic research with industry practices, emphasizing the importance of novelty and deep understanding of the equipment used in carbon capture processes.
During the UKCCSRC Autumn Programme Conference at the University of Edinburgh on September 4-5, 2019, 1st year PhD student Yuan Chen and his supervisor Dr Chang Liu and Dr Jiabin Jia shared his latest findings in Tomography technoloy for carbon capture applications. His findings emphasized the need for innovative packing materials to enhance efficiency and reduce costs in carbon capture processes. The UKCCSRC conference, a hub for global carbon capture experts, enabled Yuan to exchange ideas with peers, fostering collaborations that bridge the gap between research and practical applications.