MGK guest lecture series

2023.12.14 (3-4.30 PM, Online Via Zoom) Investigation on CO2 geological sequestration in the deccan volcanic province through multiphase flow and reactive transport simulations

MGK guest lecture by Prof. Vikranth Kumar Surasani, BITS Pilani, India.

Abstract

Abstract:

Industrial activity is the primary source of carbon emissions with a estimated 78% of total contribution. Carbon capture and sequestration (CCS) technology is one of the alternatives to reduce CO₂ emissions, where the captured CO₂ is transported to the facilities using various storage techniques. Geologic carbon sequestration (GCS) is one such technique, where deep geological subsurface formation is used as permanent storage facility. Based on available geological, petrophysical, and geochemical properties, the Deccan volcanic province is one of India’s largest sinks for geological CO₂ sequestration. Approximately 5,000,000 km²of India is covered with Deccan basalt. The fate of injected CO₂ in the geological formations follow various physical trappings and chemical transformations which are classified as structural, residual, solubility, and mineral trapping mechanisms.

The current research investigates the possible implementation of CO₂ geological sequestration in the Deccan volcanic province. The numerical simulation analysis is carried out to analyse the influences of specific sequestration parameters like the injection rate and injection point; and geological parameters like top surface morphology, petrophysical properties variation, and geological features like stairsteps traps and anticline on the CO₂ plume migration in the subsurface formation domain. The effect of these sequestration and geological parameter variations is analysed on the trapping mechanism, sweeping efficiency and structural integrity over a geological time scale for the considered subsurface synthetic domain. The multiphase, multicomponent reactive transport modelling technique is utilized to conduct this analysis. The outcome of this research has shown insight into the potential implementation of CCS and a future estimate of CO₂ migration and CO₂ entrapment. Further, provide the impacts of sequestration and geological parameters over a geological time scale. Future studies will focus on caprock leakage analysis, leakage implications on different entrapment mechanisms and machine learning approaches to predict the entrapment percentage, leakage, and structural integrity research for long geological time scales.

Keywords: Carbon Capture and Storage, Geologic Carbon Sequestration, Trapping mechanisms, Sequestration parameters, Geological parameters, Reactive transport modelling.

MGK Guest lecture

2023.10.4-6 Modelling the combustion/gasification of biomass in fixed beds: an Eulerian-Eulerian approach

MGK guest lecture by Prof. Porteiro, Unviersity of Vigo, Spain.

Prof. Porteiro is Director of Sustainability Area at the Unviersity of Vigo (Spain) and an Expert in CFD simulations, combustion and biomass conversion processes. He will visit Bochum and Magdeburg and will give a presentation at both locations. The presentations are in presence.

MGK Guest lecture

2023.09.20 at 10:00 DNS and LES of turbulent reacting gas flows with detailed kinetics and liquid or solid particles

MGK guest lecture by Prof. Bénédicte Cuenot, CERFACS, France.

MGK Guest lecture

2023.08.16 at 10:00 "Machine Learning for Thermochemistry Tabulation"

MGK guest lecture by Dr. Rigopoulos, Imperial College London.

Location

The seminar will take place in lecture theatre H2 (room number A021) on the ground floor of Building 22A in Magdeburg. You may also participate electronically.

Abstract

Several methods for the computation of reacting flows involve real-time integration of chemical kinetics. These methods include transported probability density function (PDF) methods, direct numerical simulation (DNS), conditional moment closure (CMC), unsteady flamelet, multiple mapping closure (MMC), thickened flame model, linear eddy model (LEM), partially stirred reactor (PaSR, as in OpenFOAM) and laminar flame computation. The need for direct integration of kinetics often renders large-scale simulations with these methods prohibitively expensive. This issue can be overcome by tabulation, which is the pre-computing and storage of computationally expensive operations. Tabulation raises further issues, however, such as the anticipation and coverage of the states to be encountered during simulation and the avoidance of excessive memory requirements.
The present seminar will describe a tabulation approach with artificial neural networks (ANNs), which are a class of machine learning models that can be employed for function approximation. After a review of the first-generation ANN tabulation methods, we will discuss recent developments that enable the generation of data-driven models able of accommodating a wide range of reacting flows, including laminar flamelets and premixed flames, turbulent non-premixed and premixed flames and flames with fuel blends and energy losses. The main elements of the methodology will be discussed, together with an explanation of how they lead to enhanced generalisation, accuracy and error control.