Computational Fluid Dynamics Combustion Modeling for Rotating Detonation Engines
Presentation on Rotating Detonation Engines (RDE) combustion modeling.
Strakey, Peter↗
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Computational Fluid Dynamics (CFD) Modeling of Wetted Wall Absorption Columns for Solvent-Based Post-Combustion Carbon Capture Applications
2022 AIChE Annual Meeting, Phoenix, AZ, November 13-18, 2022
Shah, Yash Girish↗
Conversion degree and heat transfer in the cold cap and their effect on glass production rate in an electric melter
A predictive model of melt rate in waste glass vitrification operations is needed to inform melter operations during normal and off-normal operations. This paper describes the development of a model of the cold cap (the reacting melter feed floating on molten glass in a glass melter) that couples heat transfer with the feed-to-glass conversion kinetics. The model was applied to four melter feeds designed for high-level and low-activity nuclear waste feeds using the material properties, either measured or estimated, to obtain temperature and conversion distribution within the cold cap. The cold cap model, when coupled with a computational fluid dynamics model of a Joule-heated glass melter, allows the prediction of the glass production rate and power consumption. The results show reasonable agreement with the melting rates measured during pilot-scale melter tests.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
A Poisson equation method for prescribing fully developed non-Newtonian inlet conditions for computational fluid dynamics simulations in models of arbitrary cross-section
Prescribing inlet boundary conditions for computational fluid dynamics (CFD) simulations of internal flow in complex geometries such as anatomical vascular models is challenging. In the absence of patient-specific inlet velocity data, a common approach for long blood vessels is to assume that the inlet flow is fully developed. In vessels of irregular cross section, however, prescribing fully developed conditions is complicated due to the lack of a general closed-form analytical solution. In this study, we develop a simple Poisson equation method for prescribing fully developed inlet conditions for the flow of either Newtonian or non-Newtonian fluids in CFD models of arbitrary cross-section. We first derive the generalized Poisson equation for fully developed flow of a non-Newtonian fluid and we then develop and verify a methodology for numerically computing the solution on any planar boundary domain. In addition, we develop a simple extension of the method for prescribing a non-orthogonal inlet velocity that represents fully developed flow from an upstream tube that is connected to the CFD inlet at a non-orthogonal angle. This may be used to investigate a common source of uncertainty in CFD simulations of internal flow that is due to a lack of information concerning the exact streamwise flow direction at the inlets. Comparison to several Newtonian and non-Newtonian benchmark verification solutions shows the method to be extremely accurate. As a practical demonstration case, we use the method to prescribe fully developed conditions on multiple non-circular inlets for the non-Newtonian flow of blood in a patient-specific model of the inferior vena cava (IVC). Finally, we further demonstrate the utility of the method by performing a sensitivity study using the patient-specific IVC model, wherein we investigate the influence of inlet velocity flow direction on the non-Newtonian IVC hemodynamics. Given its simplicity and computational efficiency, the method is shown to be far superior to alternative approaches for prescribing fully developed inlet conditions in such complicated geometries. In conclusion, to facilitate the adoption of our Poisson equation method, we have distributed our OpenFOAM source code and the associated test cases from this study as open-source software.
97 MATHEMATICS AND COMPUTING↗
QUIC-fire: A fast-running simulation tool for prescribed fire planning
Coupled fire-atmospheric modeling tools are increasingly used to understand the complex and dynamic behavior of wildland fires. Multiple research tools linking combustion to fluid flow use Navier-Stokes numerical solutions coupled to a thermodynamic model to understand fire-atmospheric feedbacks, but these computational fluid dynamics approaches require high-performance computing resources. We present a new simulation tool called QUIC-Fire to rapidly solve these feedbacks by coupling the mature 3-D rapid wind solver QUIC-URB to a physics-based cellular automata fire spread model Fire-CA. QUIC-Fire uses 3-D fuels inputs similar to the CFD model FIRETEC, allowing this tool to simulate effects of fuel structure on local winds and fire behavior. Results comparing fire behavior metrics to the computational fluid dynamic model FIRETEC show strong agreement. As a result, QUIC-Fire is the first tool intended to provide an opportunity for prescribed fire planners to compare, evaluate and design burn plans, including complex ignition patterns and coupled fire atmospheric feedbacks.
54 ENVIRONMENTAL SCIENCES↗
Machine learning for nonintrusive model order reduction of the parametric inviscid transonic flow past an airfoil
Fluid flow in the transonic regime finds relevance in aerospace engineering, particularly in the design of commercial air transportation vehicles. Computational fluid dynamics models of transonic flow for aerospace applications are computationally expensive to solve because of the high degrees of freedom as well as the coupled nature of the conservation laws. While these issues pose a bottleneck for the use of such models in aerospace design, computational costs can be significantly minimized by constructing special, structure-preserving surrogate models called reduced-order models. In this work, we propose a machine learning method to construct reduced-order models via deep neural networks and we demonstrate its ability to preserve accuracy with a significantly lower computational cost. In addition, our machine learning methodology is physics-informed and constrained through the utilization of an interpretable encoding by way of proper orthogonal decomposition. Application to the inviscid transonic flow past the RAE2822 airfoil under varying freestream Mach numbers and angles of attack, as well as airfoil shape parameters with a deforming mesh, shows that the proposed approach adapts to high-dimensional parameter variation well. Notably, the proposed framework precludes the knowledge of numerical operators utilized in the data generation phase, thereby demonstrating its potential utility in the fast exploration of design space for diverse engineering applications. Comparison against a projection-based nonintrusive model order reduction method demonstrates that the proposed approach produces comparable accuracy and yet is orders of magnitude computationally cheap to evaluate, despite being agnostic to the physics of the problem.
97 MATHEMATICS AND COMPUTING↗
CRN Modeling of Ammonia RQL Combustion using a Partially-Stirred Reactor Approach
Ammonia is a promising alternative to hydrogen with high energy density and favorable storage and transport characteristics. However low flammability and a propensity for high nitrogen oxide (NOx) emissions make direct utilization challenging. Recently, two-stage rich-quench-lean (RQL) combustion strategies have shown promise in achieving low NOx emissions with ammonia. In this approach, the rich stage serves to oxidize a portion of the fuel, while thermally decomposing as much of the remaining ammonia as possible, generating hydrogen. In the second (lean) stage, air is rapidly introduced, burning out the hydrogen and residual ammonia. Two-stage RQL combustion of ammonia has been investigated in the open literature both experimentally and numerically. In general, idealized chemical reactor network (CRN) models predict NOx concentrations below that of 2D/3D computational fluid dynamics models and experiments. The primary drivers of these discrepancies may be largely attributed to finite rate mixing non-adiabatic operation. The typical CRN model is comprised of a perfectly-stirred-reactor (PSR), followed by a plug-flow-reactor (PFR), meant to represent the flame, and post-flame zones, respectively. In the two-stage RQL approach two PSR-PFR networks are arranged sequentially, corresponding to the rich and lean stages, with secondary air injection in between. In the authors’ past work, this arrangement has demonstrated the significant sensitivity of exit NOx to the rich stage equivalence ratio, while the amount of secondary air injection was shown to be less critical. In this paper, the CRN model is extended to (1) include the impacts of heat loss and (2) utilize a partially-stirred-reactor (PaSR) approach to study the impacts of mixing on emissions performance. Varying amounts of heat loss are applied to the rich relaxation zone to understand emissions performance and changes to optimization of equivalence ratio and residence time. Premixed and non-premixed configurations are considered in the rich stage PaSR, with varying degrees of mixing intensity to study the interaction between mixing, transport, and kinetic timescales. Critically, the impact of mixing between hot products and secondary air injection is studied to understand practical injector needs. Results show unburnt ammonia leaving the rich stage as a primary contributor to NOx emissions – driven both by increased heat loss and reduced mixing rates. Furthermore, heat losses have shown to create conditions which are conducive to increased N2O formation in the lean stage. The results of this study will be considered in the context of developing optimized two-stage RQL combustors for ammonia..
advanced gas turbines↗
Chemical Reactor Network Modeling of Ammonia Rich-Quench-Lean Combustion Using a Partially Stirred Reactor Approach
Ammonia is a promising alternative to hydrogen with high energy density and favorable storage and transport characteristics. However, low flammability and a propensity for high nitrogen oxide (NO x ) emissions make direct utilization challenging. Recently, two-stage rich-quench-lean (RQL) combustion strategies have shown promise in achieving low NO x emissions with ammonia. In this approach, the rich stage serves to oxidize a portion of the fuel while thermally decomposing as much of the remaining ammonia as possible, generating hydrogen. In the second (lean) stage, air is rapidly introduced, burning out the hydrogen and residual ammonia. Two-stage RQL combustion of ammonia has been investigated in the open literature both experimentally and numerically. In general, idealized chemical reactor network (CRN) models predict NO x concentrations below those of 2D/3D computational fluid dynamics models and experiments. The primary drivers of these discrepancies may be largely attributed to finite rate mixing nonadiabatic operation. The typical CRN model is comprised of a perfectly-stirred-reactor (PSR), followed by a plug-flow-reactor (PFR), meant to represent the flame, and postflame zones, respectively. In the two-stage RQL approach two PSR-PFR networks are arranged sequentially, corresponding to the rich and lean stages, with secondary air injection in between. In the authors' past work, this arrangement has demonstrated the significant sensitivity of exit NO x to the rich stage equivalence ratio, while the amount of secondary air injection was shown to be less critical. In this paper, the CRN model is extended to (1) include the impacts of heat loss and (2) utilize a partially-stirred-reactor (PaSR) approach to study the impacts of mixing on emissions performance. Varying amounts of heat loss are applied to the rich relaxation zone to understand emissions performance and changes to optimization of equivalence ratio and residence time. Premixed and nonpremixed configurations are considered in the rich stage PaSR, with varying degrees of mixing intensity to study the interaction between mixing, transport, and kinetic timescales. Critically, the impact of mixing between hot products and secondary air injection is studied to understand practical injector needs. Results show unburnt ammonia leaving the rich stage as a primary contributor to NO x emissions – driven both by increased heat loss and reduced mixing rates. Furthermore, heat losses have been shown to create conditions that are conducive to increased N 2 O formation in the lean stage. In conclusion, the results of this study will be considered in the context of developing optimized two-stage RQL combustors for ammonia.
Combustion↗
Numerical simulation of parametric resonance in point absorbers using a simplified model
Abstract Parametric resonance is a non‐linear phenomenon in which a system can oscillate at a frequency different from its exciting frequency. Some wave energy converters are prone to this phenomenon, which is usually detrimental to their performance. Here, a computationally efficient way of simulating parametric resonance in point absorbers is presented. The model is based on linear potential theory, so the wave forces are evaluated at the mean position of the body. However, the first‐order variation of the body's centres of gravity and buoyancy is taken into account. This gives essentially the same result as a more rigorous approach of keeping terms in the equation of motion up to second order in the body motions. The only difference from a linear model is the presence of non‐zero off‐diagonal elements in the mass matrix. The model is benchmarked against state‐of‐the‐art non‐linear Froude–Krylov and computational fluid dynamics models for free decay, regular wave, and focused wave group cases. It is shown that the simplified model is able to simulate parametric resonance in pitch to a reasonable accuracy even though no non‐linear wave forces are included. The simulation speed on a standard computer is up to two orders of magnitude faster than real time.
16 TIDAL AND WAVE POWER↗
Multicycle large-eddy simulations of a direct-injection hydrogen-fueled optical engine
Hydrogen (H 2 ) is a carbon-free chemical energy carrier and one promising solution for achieving effective decarbonization of the transportation sector, particularly for internal combustion engines (ICEs). With a focus on ICEs, and compared to port-fuel injection, direct injection (DI) of gaseous H 2 during the compression stroke offers potential advantages, which include backfire avoidance and reduction of preignition occurrence. In these last two decades, much research, experimental and numerical, has been devoted to understanding H 2 's mixing and combustion processes in ICEs. Computational fluid dynamics modeling efforts commonly rely on unsteady Reynolds-averaged Navier Stokes (URANS) turbulence frameworks, mostly due to their computational affordability. However, many authors have pointed out the opportunity to perform large-eddy simulations (LESs) to investigate the cyclic variability of H 2 engines and assess potential advantages of using LES in place of URANS, especially for lean operation. This study addresses this knowledge gap and presents a computational fluid dynamics (CFD) study of the H 2 DI process in an optical engine operating at relatively low tumble conditions, using multicycle LESs. In conclusion, the manuscript presents a thorough validation of the results against experimental data available from the literature as well as direct comparison with URANS, demonstrating the feasibility of multicycle LESs for CFD modeling of DI H 2 -fueled ICEs.
Direct injection↗
Impact of molten salt inflow on the temperature distribution in thermal energy storage tanks at startup for central receiver concentrating solar power plants
Concentrating Solar Power (CSP) systems with molten salt thermal energy storage (TES) tanks are one of the most promising, renewable-based energy conversion technologies for larger-scale power generation. The TES tank is one of the most critical components in CSP plants due to its high-temperature operation (up to 565 °C), daily thermal cycling, and intermittent solar radiation conditions. The plant startup is one of the most challenging operation conditions that could lead to damaging thermal gradients due to low salt inventory levels. In this study an analytical model for the sparger ring was developed and integrated with a detailed computational fluid dynamics model of a commercial-scaled molten salt tank. The integrated model allows an accurate representation of the tank operation to evaluate the effect of molten salt inflow on the mixing process. The tank filling process during plant startup was analyzed considering sparger rings with variations in design features, including inlet orifice configurations, number of orifices, direction of the inlets, and orifice diameter. The results demonstrated that higher temperature gradients are obtained in the tank floor during the plant startup. A sparger ring configuration with a predetermined orifice inlet inclination (30°, 45° and 60°) leads to significant temperature differences in the floor, between 57 °C and 62 °C, but better homogeneity in the temperature of the salt inventory. Lower salt inflow velocities result in a more homogeneous floor temperature, with maximum temperature differences under 38 °C. The sparger ring configuration with 52 orifices of 1-in. diameter and vertical flow showed better homogeneity in the temperature differences as a function of the salt level and lower temperature gradients in the tank floor. Because large temperature gradients in the tank's floor have been identified as one of the main factors contributing to tank failures, assessing various sparger ring design features is fundamental to determining proper inflow conditions that lead to low-temperature gradients and reducing failure susceptibility.
14 SOLAR ENERGY↗
Development of a two-zone zero-dimensional mixing model for actively fueled prechamber engines
In this numerical work, a zero-dimensional, two-zone mixing model was developed and validated to capture the mixture preparation process of an actively fueled prechamber engine. The model was developed for ethanol-gasoline fuel blends but is applicable to various fuels of interest relevant to prechamber applications. The model was exercised to demonstrate the effects of boundary conditions, fuel composition, and residual content on the mixture stoichiometry predictions. The 0D model showed reasonable agreement in prechamber equivalence ratio predictions with higher fidelity computational fluid dynamics modeling, but the accuracy of model was constrained to the governing assumptions of the injection process. The modeling assumptions surrounding the non-dimensional injection of mass into the prechamber were scrutinized to identify key areas of model improvement. The results indicate heat transfer effects play a crucial role in the evaporation of the fuel within the confined auxiliary chamber, especially when considering fuels with high latent heat of vaporization. Additionally, the presence of fuel films that collect on the prechamber surfaces complicated the modeled evaporative cooling loses as the modeling suggests the films evaporate primarily by means of conduction from the boundary. Furthermore, the developed model serves as a simplified framework to generate calibration maps of prechamber fueling or run real time as an open loop control strategy such that desired prechamber mixture proportions are effectively targeted.
Zero-dimensional↗
A Review of Modeling Approaches for Predicting Frost Growth and Defrosting on Tube-Fin Heat Exchangers: Preprint
Frost formation and growth on the evaporator surface is a common process that deteriorates the air-refrigerant heat transfer and restricts airflow. This degrades the performance of the vapor compression system by increasing temperature lift and air-side pressure drop. To accurately predict these effects during coil frosting, as well as the energy use and duration of the defrost process, there is a need to estimate the heat and mass transfer, momentum transport, and solid-liquid and liquid-vapor phase change. Therefore, in the past few decades, continuous effort has been made to model frosting and defrosting processes using approaches ranging from empirical correlations to computational fluid dynamic models. To provide a clearer overview for researchers, engineers, and manufacturers in this field, this paper provides a comprehensive literature review for frosting and defrosting models. The paper begins with theoretical background of frost formation and defrost processes, and then reviews the common modeling approaches in literature and their underlying assumptions when trying to account for various physical phenomenon. Based on the literature review, the most critical modeling effort for frost formation is the determination of frost densification rate and frost growth rate. Various methods to predict these two parameters are reviewed. Empirical correlations commonly used for frost density and thermal conductivity are presented and compared. For the defrost process, various multi-stage models have been proposed with different assumptions. Some assume the presence of air gap between the tube wall and the frost, while others consider the melted frost flow due to gravity. We also review physics-based and empirical approaches to integrate defrost models into heat pump models. We conclude by identifying research gaps and providing recommendations.
defrost↗
Computationally Aided Design of a Small-Scale Waste-Glass Melter - 20452
To provide mission support to the WTP for the vitrification of legacy nuclear tank waste at the Hanford site, a reduced-scale vitrification pilot system is being designed to process simulated and actual radioactive tank wastes. The waste stored in underground tanks will be separated into HLW and LAW fractions, where the majority is LAW by mass (approximately 90%) and HLW by activity (greater than 95%). The first tank waste to be processed at the WTP will be LAW. Because Hanford tank waste and the resultant melter feed compositions are known to vary widely, pilot-scale operations are essential to identify potential problems, provide needed data, confirm assumptions, and determine impacts to full-scale melters and off-gas systems from these different feeds. In addition, the reduced-scale melter system must be capable of quickly providing results to operations without the typically high cost of full-scale radioactive operations and to provide an engineering platform in close proximity to local operations staff. The objectives of this computational modeling effort are to produce process conditions like those encountered in the WTP LAW melters and to minimize the volume of radioactive waste necessary for the evaluations. To this end, melter design features are being explored to increase production without significantly increasing surface area or melter-glass volumes or compromising data quality. In support of these objectives, a set of computational fluid dynamic models was developed to provide insight into the flow patterns within these small melters and evaluate design features to increase production without significantly increasing glass inventory. Computed velocities were evaluated at the interface between the cold cap and the molten-glass pool and within the bulk-glass pool. Since melt rate correlates with the velocity underneath the cold cap, this information can be used to select design features that produce the highest gains. (authors)
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
A numerical evaluation of the ambient air temperature in the Electron-Ion Collider tunnel
The Electron-Ion Collider (EIC) is a next-generation collider-accelerator that may require consistent operating temperature conditions for the beams within the accelerator tunnels to maintain stable operation. Variations in ambient temperature within the tunnel can cause thermal expansion of beampipe and component supports and can negatively affect the tunnel equipment, impacting the stability of the beamline. Modifications will be made to the Relativistic Heavy Ion Collider (RHIC) at Brookhaven National Laboratory (BNL) to create the EIC, which necessitates a temperature model that addresses these modifications. To approach this problem, the consistency of temperature changes in different tunnel sections was first evaluated by plotting RHIC tunnel temperature data at various times of the day and year. From this data, a tunnel section was selected and a 2D temperature model was created for RHIC, EIC, and EIC with added cooling configurations. Soil temperature data was analyzed to determine the maximum, average, and mode soil temperatures, which were used as boundary conditions in different temperature scenarios. Computational fluid dynamics modeling was used to create 2D temperature profiles for the configurations. From this model, the predicted temperatures indicate that further analysis is required to validate the boundary conditions and benchmark the current conditions to allow the prediction of the tunnel ambient conditions at EIC. This research can be used as a preliminary model to create an EIC tunnel cooling system that will increase the operational stability of the EIC. As a result of my work this summer, I have become familiar with computational fluid dynamics, including creating fluid dynamic simulations using ANSYS Fluent and related software. I have also learned about the project process required for planning large-scale engineering projects.
43 PARTICLE ACCELERATORS↗
PNNL - WRF-LES - Convective - TTU
This dataset includes large-eddy simulation (LES) output from a convective atmospheric boundary layer (ABL) simulation of observations at the SWIFT tower near Lubbock, Texas on July 4, 2012. The dataset was used to assess the LES models for simulation of canonical convective ABL. The dataset can be used for comparison with other LES and computational fluid dynamics model outputs.
17 WIND ENERGY↗
ANL - WRF-LES - Convective - TTU
This dataset includes large-eddy simulation (LES) output from a convective atmospheric boundary layer (ABL) simulation of observations at the SWIFT tower near Lubbock, Texas on July 4, 2012. The dataset was used to assess the LES models for simulation of canonical convective ABL. The dataset can be used for comparison with other LES and computational fluid dynamics model outputs.
17 WIND ENERGY↗
LANL - WRF-LES - Convective - TTU
This dataset includes large-eddy simulation (LES) output from a convective atmospheric boundary layer (ABL) simulation of observations at the SWIFT tower near Lubbock, Texas on July 4, 2012. The dataset was used to assess the LES models for simulation of canonical convective ABL. The dataset can be used for comparison with other LES and computational fluid dynamics model outputs.
17 WIND ENERGY↗