Abstract
This paper presents the requirements for a tailored design ecosystem to accelerate the development of a new turbo-reactor for hydrocarbon cracking. The objective of this novel turbo-reactor concept is to eliminate carbon emissions from the radiant section of the plant. However, the time constraint for this energy- and carbon-intensive cracking industry to fully decarbonize is severely restricted. Therefore, the development of this new concept must be accelerated to a market-ready product within a limited time frame. However, the novelty of the design requirements and the unique level of complexity of the flow physics result in inadequate experimental data, with insufficient time and resources to develop a new measurement database. This shifts the design system towards computer-aided engineering platforms; however for the turbo-reactor, the uncertainty level of these low-order numerical tools (e.g., RANS and throughflow solvers) is elevated for three reasons. First, blockage, deviation and loss correlations integrated within throughflow solvers are unsuitable to capture the flow physics in the turbo-reactor. Second, RANS turbulence closure models need to be re-calibrated for this machine. Finally, due to the chemical reactions, the working fluid properties vary significantly along the gas path and strongly influence the aerodynamics. A new tailored design ecosystem is proposed to address these challenges. The relatively low Reynolds number regime throughout the turbo-reactor enables upfront and routine eddy-resolving simulations to be performed. This allows the new design system to feature a feedback mechanism in which high-fidelity CFD data is used to calibrate lower-fidelity — but less CPU intensive — design tools and empirical correlations. Crucially, the new toolchain is customized in order to capture the influence of the reactions on the thermodynamic properties, as well as to provide the aerodynamic designer with immediate insight into how stage-design modifications influence the reaction product yield distribution. This paper demonstrates the capabilities of an efficient aerodynamic-chemistry coupling methodology that has been implemented within an in-house CFD solver.
