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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 217 records · Page 12

Temperature Homogeneity under Selective and Localized Microwave Heating in Structured Flow Reactors

Selective heating of different phases of multiphase systems via microwaves can result in energy savings and suppression of side reactions. However, materials properties and operating conditions that maximize temperature gradients are poorly understood. Here we utilize computational fluid dynamics (CFD) computations and temperature measurements in structured flow reactors (monoliths) in a monomodal microwave cavity to assess the temperature difference between the walls and the fluid and develop a simple lumped model to estimate when temperature gradients exist. We also explore the material’s thermal and electrical properties of structured reactors for isothermal catalyst conditions. We propose that CFD simulations can be used as a nonintrusive, predictive tool of temperature homogeneity. Importantly, we demonstrate that localized heating in the bed under several conditions rather than selective heating is responsible for the selectivity enhancement. Furthermore, our results indicate that structured beds made of high thermal conductivity materials avoid arcing and enable temperature homogeneity and low electrical conductivity materials allow microwaves to penetrate the domain.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

O 2 based resonantly ionized photoemission thermometry analysis of supersonic flows

Characterization of the thermal gradients within supersonic and hypersonic flows is essential for understanding transition, turbulence, and aerodynamic heating. Developments in novel, impactful non-intrusive techniques are key for enabling flow characterizations of sufficient detail that provide experimental validation datasets for computational simulations. In this work, Resonantly Ionized Photoemission Thermometry (RIPT) signals are directly imaged using an ICCD camera to realize the techniques 1D measurement capability for the first time. The direct imaging scheme presented for oxygen-based RIPT (O 2 RIPT) uses the previously established calibration data to direct excite various resonant rotational peaks within the S-branch of the C 3 Π, ( v = 2) ← X 3 Σ( v ′ = 0) absorption band of O 2 . The efficient ionization of O 2 liberates electrons that induce electron avalanche ionization of local N 2 molecules generating N 2 + , which primarily deexcites via photoemissions of the first negative band of N 2 + ( B 2 Σ <#comment/> u + − <#comment/> X 2 Σ <#comment/> g + ) . When sufficient lasing energy is used, the ionization region and subsequent photoemission signal is achieved along a 1D line thus, if directly imaged can allow for gas temperature assignments along said line; demonstrated here of up to five centimeters in length. The temperature gradients present within the ensuing shock train of a supersonic under expanded free jet serves as a basis of characterization for this new RIPT imaging scheme. The O 2 RIPT results are extensively compared and validated against well-known and established techniques (i.e., CARS and CFD). The direct imaging capability fully realizes the technique’s fundamental potential and is expected to be the standard of implementation going forward. The direct imaging capability can play instrumental roles in future scientific studies that rely upon acute characterization of thermal gradients within a medium that cannot be easily resolved by a point. Furthermore, the removal of the spectrometer greatly reduces the cost, complexity, and optical alignment associated with prior RIPT measurements.

42 ENGINEERING↗

Thermal Modeling of Advanced Test Reactor Fuel in a Generalized Dry Storage System Under Hypothetical Accident Conditions

Work was performed to investigate the thermal behavior of a sealed aluminum-clad spent nuclear fuel (ASNF) dry storage configuration under hypothetical accident conditions during long-term storage. The considered system consists of a concrete dry storage overpack; a welded over canister, backfilled with argon; and nine Department of Energy (DOE) standardized canisters (DOESCs) loaded with ASNF, backfilled with helium gas. One technical concern associated with the long-term storage of ASNF includes radiolytic hydrogen generation. The yield of large quantities of hydrogen could lead to DOESC over pressurization or a flammable internal atmosphere. While flammability concerns can be resolved by preventing the ingress of oxygen, the canister pressure is partially controlled by the atmosphere temperature. This memorandum summarizes the results of modeling and simulation (M&S) work completed with Star CCM+ (a computational fluid dynamics [CFD] software) considering the thermal effects of a fully engulfing flame and another scenario with the vent ports of the concrete dry storage overpack completely blocked. The goal was to determine the bounding maximum temperature of the DOESC internal atmosphere to evaluate a worst-case pressure scenario, as well as the critical vent port blockage durations.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Recent Progress on Numerical Modeling for Microgravity Electric Field Flames: Preprint

This paper presents the recent progress on the NASA Physical Science Informatics (PSI) project PeleLM CFD of Ion Driven Winds from Diffusion Flames in simulating the E-FIELD Flames microgravity results. The focus of this project is to comprehensively simulate the behavior of a small diffusion flame under the influence of an externally applied electric field in zero-gravity. To date, the capability of accurately simulating electric field flames has eluded researchers because the system exhibits dramatic ranges of coupled temporal and spatial scales. Moreover, in earth gravity the hot combustion products are subject to buoyancy effects that are difficult to isolate from those generated by the electric field. This work is an implementation in an existing powerful simulation framework (PeleLM) for this problem using PeleLMeX in order to validate the model and investigate the complex coupled system. The current effort includes establishing the domain of a diffusion coflow burner, examining the boundary conditions, flame geometry and ignition with gravitational forces and also with an electric field applied. A detailed model is used that includes the chemistry of charged ions and chemiluminescent flame intermediates to capture any feedback between ion-driven convection and combustion behavior, and to allow quantitative comparisons with experimental measurements.

coflow flames↗

CFD Evaluation of Pressure Change Along Coolant Passages in Sodium-Cooled Fast Reactor with Nek5000

To support the design efforts of advanced sodium-cooled fast reactors (SFRs), a series of computational fluid dynamics (CFD) simulations are performed to investigate the pressure change along various flow passages in the proposed SFR system. The simulations are carried out with the state-of-the-art spectral element flow solver, Nek5000. Two specific case studies are presented in this paper: the flow exiting the axial neutron reflector channels and the flow entering the fuel pin bundle. Due to the high Reynolds numbers expected, a Reynolds-averaged Navier-Stokes (RANS) approach is necessary to model the turbulence. A newly developed regularized k-omega RANS model is adopted in the related CFD calculations. The first case study explores the effect of Reynolds number on the pressure change when flow exits the reflector channels. The pressure change in this case has two major contributors: the change due to wall friction and the Bernoulli effect. It is noted that the nondimensional pressure loss follows a log-linear trend up to Re = 10 5 , and then the trend is flattened. In the second case study, the advanced NekNek coupling capability is tested where an integral domain can be divided into multiple subdomains with coupling interfaces, which would greatly ease the meshing process of complex engineering geometries and potentially save computational resources. The preliminary results obtained so far confirm the consistency between the NekNek results and those produced by regular Nek5000 simulation. The presented work demonstrates the readiness and flexibility of the related CFD techniques, which is part of the broader effort to leverage cutting-edge CFD to inform the advanced nuclear reactor designs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Numerical modeling of hydrogen mixing in a direct-injection engine fueled with gaseous hydrogen

Hydrogen is considered as one of the most promising options to achieve effective decarbonization of the energy and transportation sectors. As such, it has recently been receiving increasing attention because of its promising potential as an energy carrier for advanced energy and propulsion systems. With a focus on internal combustion engines, direct injection (DI) of gaseous hydrogen during the compression stroke offers great potential for high engine efficiency and specific power while reducing the risk of backfiring and pre-ignition issues. Therefore, many experimental and numerical efforts have recently been dedicated to understanding the physical and chemical behaviors of hydrogen in engine during mixing and combustion. This study focuses on computational fluid dynamics (CFD) modeling of the hydrogen DI process in a hydrogen optical research engine. Under the conditions studied, gaseous hydrogen is injected into the combustion chamber via a centrally located single-hole injector at a pressure of 100 bar. Two configurations, namely low-and high-tumble, are investigated to understand the impact of different in-cylinder flow patterns on the fuel-air mixture preparation. Simulations are carried out using the commercial CFD software CONVERGE. Here, the in-cylinder turbulence is modeled with an unsteady Reynolds-averaged Navier-Stokes (URANS) formulation closed by the renormalization group (RNG) k-ε model. Several numerical methods and model constants, including but not limited to turbulent Schmidt number, are evaluated. The numerical results are systematically compared against experimental measurements of velocity and hydrogen concentration fields on the vertical center plane to assess the performance of the CFD model, unveil the physics of hydrogen mixing, and establish best practices for modeling hydrogen DI under relatively high injection pressure conditions.

33 ADVANCED PROPULSION SYSTEMS↗

Effect of coaxial nozzle wear on catchment efficiency in direct energy deposition built components

Laser based Direct Energy Deposition (DED) systems using metallic powder feedstock are recognized as a promising manufacturing method for their ability to shorten production cycles and create complex part geometries. Components are built by generating a melt pool with a high-power laser beam while material is coaxially injected and left to solidify. An impediment to large scale use of DED lies in poor powder catchment efficiency, the condition in which a portion of injected powder escapes the melt pool resulting in a ratio of decreased printed material mass to mass of supplied feedstock. The wear state of a coaxial nozzle on a DED system within a hybrid manufacturing machine tool has been observed to decrease catchment efficiency over time. Herein this study investigates this effect by adapting flow visualization techniques to an in-situ process monitoring format, the implementation of a Computational Fluid Dynamics (CFD) simulation, and deposition testing. Nozzle geometric defects due to wear are identified and categorized, and the impact of nozzle tip wear, resulting in axial tip reduction, on powder catchment efficiency is proven by multiple calculation methods. A linear correlation between catchment efficiency and powder stream diameter is identified, causing a 15–20% loss in efficiency sustained over incremental nozzle tip reduction up to − 1 mm. These results provide a foundation for further study of wear effects and Zero defect manufacturing solutions for powder fed DED systems.

42 ENGINEERING↗

Implementation of Detailed Polyethylene Pyrolysis Kinetics into CFD Simulations using Machine Learning

Municipal solid waste (MSW) and waste plastics have received significant attention due to the issues of waste generation and storage, as well as their potential as an energy resource. High-density polyethylene (HDPE) makes up a large portion of plastic waste and has been the subject of several conversion studies. However, the mechanisms associated with converting HDPE through pyrolysis and gasification are extensive and complex making them difficult to implement into high-fidelity computational fluid dynamic (CFD) simulations. For this project, a primary pyrolysis mechanism containing 42 unique species and 737 heterogeneous reactions was used to generate kinetic data over a range of operating conditions. A machine learning (ML) model was developed to replicate the results of the detailed pyrolysis mechanism while significantly increasing the computational efficiency. A deep operator network (DeepONet) architecture was adopted to train the model using time steps relevant to CFD simulations. The ML used physics-based loss functions to ensure mass conservation. The ML model has been deployed in simple MFiX CFD simulations, single particle, and an experimental drop tube reactor, and has shown promising performance compared to the original scheme.

Houston, Ross↗

Numerical Modeling of a Two-Stage Ocean Current Turbine

The Equinox Ocean Turbines (EQOT) current energy converter has a unique design with power generation in two small-diameter turbines attached to the tips of a large-diameter passive rotor. This configuration offers some key advantages for capturing ocean currents. With no centrally placed generator, almost no reaction torque is required at the nacelle of the main large-diameter rotor, and the small-diameter tip turbine generators operate at a higher speed and lower torque. The physics that determine the performance and loads on the turbine are also unique. The interactions of the flow field between the two stages and the general architecture of the system cannot be captured with traditional mid-fidelity modeling tools. For design iterations and large sets of load cases, it is important to have mid-fidelity models that can capture the important phenomenon with enough accuracy to identify global trends. This work uses a limited set of high-fidelity computational fluid dynamics (CFD) simulations to help inform the selection of and construction of a custom mid-fidelity model. Mid-fidelity modeling approaches were verified by comparing key turbine performance quantities to those found with the CFD model. Hydrodynamic interactions of the two-stage rotor were identified through high-fidelity CFD modeling. This highlighted the impact of the main rotor tip vortex and wake on the secondary rotor apparent inflow. This results in a relative flow rotation and sharp deficit, that change the optimal secondary rotor rotation speed and adds unsteadiness to the blade loading respectively. Multiple mid-fidelity approaches were evaluated for their ability to capture these effects. A simple approximation of the combined-stage performance based on single-stage BEM provides a reasonable rough prediction, especially near the peak TSR values, with some larger discrepancy at higher TSRs. Predicting the combined-stage performance based on single-stage CFD data improves this prediction across the TSR range. Although the combined-stage modeling in OLAF was not successful in this stage of the project, it showed promise as a mid-fidelity method, assuming the parameters can be tuned to account for the significant differences in time and length scales between the main and secondary rotors. This may be addressed through code changes in future work. A significant finding from the OLAF work was the agreement between the vortex core radius values found independently via a parameter space search and via CFD. The technique of using single-stage secondary rotor BEM, with a custom inflow taken from single-stage main rotor CFD or OLAF, provides an efficient method to capture one-way coupled flow interactions. This method provided generally good predictions of the impact of the flow rotation on the secondary rotor but struggled to accurately predict the peaks of the unsteady load progression. Future work could include some superposition of a tuned main rotor trailing edge viscous wake into the custom inflow to better predict this interaction.

16 TIDAL AND WAVE POWER↗

Pore-scale CFD simulations of clay mobilization in natural porous media due to fresh water injection

The present work investigates mechanisms of permeability impairment as a result of low-salinity fluid injection into brine-saturated porous media containing dispersible clays. Here, we present a computational fluid dynamics model at the pore-scale to simulate detachment, migration and straining of fine particles in porous media. The model uses an immersed boundary method to simulate the motion of clay fines in a fluid. In addition to the hydrodynamic forces, we model the Derjaguin-Landau-Verwey-Overbeek forces (DLVO) between clay fines and grains. Our simulations show the impact of the injected fluid's salinity and velocity on the concentration of clay fines retained on the grain surface. We see clay particles dislodging from the grain surface in clusters of up to 12 particles. Our simulation results also demonstrate clogging of narrow pore spaces by the detached particles from the grain surfaces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A two-equation soot-in-flamelet modeling approach applied under Spray A conditions

Soot production (including formation and oxidation) is studied in the transient, high-pressure and turbulent n-dodecane Spray A flames from the Engine Combustion Network (ECN) using computational fluid dynamics (CFD) simulations. A two-equation soot-in-flamelet modeling approach is applied within the framework of the Unsteady Flamelet Progress Variable (UFPV) model and results are validated against experimental data. Equations for soot mass fraction and soot number density derived in the mixture fraction space are solved in the context of detailed flamelet calculations. Source terms for the different steps in the soot chemistry are tabulated and incorporated in the flamelet manifold. For the reference condition, the modeling approach based on the tabulated flamelet manifold reduces the computational cost of a CFD calculation by approximately 40 times compared to a non-tabulated well-mixed (WM) modeling approach. The soot-in-flamelet approach is then extended to study the effect of ambient oxygen concentration, ambient mixture composition and ambient temperature on soot production. Results show that the modeling approach is able to capture the experimental trends for the soot volume fraction (SVF) with good quantitative agreement, especially in the soot ramp-up region.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Modeling Marangoni Convection using a Velocity-Time Relationship

The Waste Treatment and Immobilization Plant (WTP) at the U.S. Department of Energy’s (DOE’s) Handford site is designed to treat 56 million gallons of radioactive waste through vitrification. The melting vessels physical and chemical integrity is essential to maintain, as failure has a high safety and financial penalty. Monofrax® K-3 refractory, the material widely used for the melting vessel, undergoes significant corrosion over time, concentrated at the triple-point junction between the gaseous atmosphere, refractory, and glass melt, producing a characteristic neck-like profile that significantly limits refractory service life. Accurate prediction of the corrosion within the melter can be used to prevent this and extend the lifetime of the melters. A computational fluid dynamics (CFD) model was previously developed, and predicted subsurface refractory corrosion, but failed to predict the neck-line profile observed experimentally. To address this limitation, the glass-melt meniscus geometry at the glass-refractory interface was estimated from experimentally measured neck profiles and wettability experiments. A curve was fitted to the neck profile to identify the triple point location, and the meniscus shape was characterized by a contact angle of 1°. A velocity profile accounting for Marangoni convection-driven corrosion was derived from the estimated meniscus geometry. Surface tension measurements from LORPM14R1 glasses of varying composition were coupled with K-3 coupon dissolution rates to establish a surface tension–time relationship. This analytical velocity-time model was integrated into the existing CFD framework to improve prediction of the neck corrosion profile. Work was done in a computational setting with national collaboration, resulting in professional development through presentational and technical writing growth.

36 - MATERIALS SCIENCE↗

Tidal Turbine Test, Downeast Turbines, July 12, 2021

Downeast Turbines tested a tidal turbine prototype with novel rotor/channel system and lateral effluent discharge apparatus (LEDA), during five days of testing in the flume at Alden Lab. Three days of testing (July 12-14, 2021) focused on turbine power metrics of torque and rpm, which were low, and then two days of follow-up testing (July 27-28, 2021) focused on LEDA performance metrics of pressure differential and rates of volumetric flow, with encouraging results. Next step is to to characterize, and even optimize, configurations of the LEDA, using 3D-CFD as a helpful tool, to refine its shape and explore its limits of performance as a means of effluent discharge that augments performance of an instream turbine. An improved configuration of the LEDA will be re-combined with the rotor/channel system of the turbine prototype, and ultimately, the rotor will be re-sized (enlarged), to better match the LEDA's performance capabilities in drawing through a rate of volumetric flow. This submission is Downeast Turbines' Post Access Report for the test event. It includes the files described here (next below), and several reference links. "Downeast TEAMER-Post-Access-Report...docx" is a document file containing the report. "Appendices A, B, and C" are included in this file, and so are "Figures #1-7." "Appendix D - Test Data Workbooks.zip" is an archive file containing all post access data (raw data tables, calculating tables, and graphs), presented in fourteen Excel workbooks as described in the report. "Appendix E - Post Access Figures.zip" is an archive file containing "Figures #8-52," of the report.

16 TIDAL AND WAVE POWER↗

INTEGRATE – Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements

The INTEGRATE (Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements) project developed a new inverse-design capability for the aerodynamic design of wind turbine rotors using invertible neural networks. Training data was obtained from improved turbulence and transition models for RANS and hybrid RANS/LES solvers with machine-learned physics-based data-augmented corrections and then using the resulting neural-network(s) augmented RANS model to run thousands of 2-D and 3-D CFD simulations.

17 WIND ENERGY↗

Aerodynamic Characterization of 3D Scanned Wind Turbine Blades Using Experimental and Computational Methods

This study presents an aerodynamic characterization of 3D scanned wind turbine blades using both experimental and computational methods. The research was conducted by Gulf Wind Technology and Sandia National Laboratories. The primary objective was to investigate the aerodynamic impacts of leading-edge manufacturing defects on wind turbine blades. The study utilized the Stratasys NEO 800 3D Printer for high-precision manufacturing and the GWT Accelerator Wind Tunnel for experimental testing. Computational simulations were performed using COMSOL Multiphysics to model the wind tunnel and analyze flow characteristics and OpenFOAM to study the aerodynamic impacts of leading-edge defects. OpenFAST was used to estimate how these defects can lead to revenue losses for wind farm operators as high as 6%. The results demonstrated significant aerodynamic performance variations due to defects, with detailed analysis provided through wind tunnel and CFD data. The findings contribute to the understanding of defect impacts on wind turbine blade performance and offer insights for future design improvements.

17 WIND ENERGY↗

Assessing the Heat Transfer Modeling Capabilities of CFD Software for Involute-Shaped Plate Research Reactors

The ongoing efforts to convert High-Performance Research Reactors (HPRRs) using Highly Enriched Uranium (HEU) to Low-Enriched Uranium (LEU) fuel require reliable thermal–hydraulic assessments of modified core designs. The involute-shaped fuel plates used in several major HPRRs present unique modeling challenges due to their compact core geometries and high heat flux conditions. This study evaluates the capability of three commercial CFD tools, STAR-CCM+, COMSOL, and ANSYS CFX, to predict cladding-to-coolant heat transfer using Reynolds-Averaged Navier–Stokes (RANS) methods within the thermal–hydraulic regimes of involute-shaped plate reactors. Broad sensitivity analysis was conducted across a range of reactor-relevant parameters using two turbulence models (k−ϵ and k−ω SST) and different near-wall treatment strategies. The results were benchmarked against the Sieder–Tate correlation and experimental data from historic studies. The codes produced consistent results, showing good agreement with the empirical correlation of Sieder–Tate and the experimental measurements. The findings support the use of these commercial CFD codes as effective tools for assessing the thermal–hydraulic performance of involute-shaped plate HPRRs and guide future LEU core development.

CFD↗

A physics-constrained neural ordinary differential equations approach for robust learning of stiff chemical kinetics

The high computational cost associated with solving for detailed chemistry poses a significant challenge for predictive computational fluid dynamics (CFD) simulations of turbulent reacting flows. While deep learning techniques have been explored to develop faster surrogate models, they often fail to integrate reliably with CFD solvers. This instability arises because traditional deep learning approaches optimize for training error without ensuring compatibility with ordinary differential equation (ODE) solvers, resulting in accumulation of errors over time. Recently, neuralODE (NODE) based approaches have been shown to be a promising technique to emulate and accelerate detailed chemistry computations. Here, in the present work, we extend this NODE framework for stiff chemical kinetics by incorporating mass conservation constraints directly into the loss function during training. This ensures that the total mass as well as the individual elemental species masses are conserved in an a-posteriori manner. Proof-of-concept studies are performed with the novel physics-constrained NODE (PC-NODE) approach for homogeneous autoignition of hydrogen-air mixture over a range of composition and thermodynamic conditions. It is demonstrated that the PC-NODE framework not only improves the physical consistency of the resulting data-driven model with respect to mass conservation criteria, but also improves training efficiency. PC-NODE is shown to achieve 2–100× speedup relative to the hydrogen-air detailed chemical mechanism depending on the type of the ODE solver (implicit or explicit) used during autoregressive inference tests. Lastly, a-posteriori studies are performed wherein the trained PC-NODE model is coupled with a CFD solver. It is shown that higher accuracy is achieved with PC-NODE relative to the purely data-driven NODE approach. Moreover, PC-NODE also exhibits robustness and generalizability to unseen initial conditions from within (interpolative capability) as well as outside (extrapolative capability) the training regime.

computational combustion↗

MFIX DEM Enhancement for Industry-Relevant Flows (Final Report)

The overall goal of this two-phase project is to implement performance improvements of the Multiphase Flow with Interphase Exchanges (MFIX) Discrete Element Model (DEM) code that enable a transformative shift for industrial use. Prior to this effort, the largest simulations performed using MFIX are O(10 7 ) particles. This falls short of the O(10 9 ) particle simulations that must be completed on a timescale of days or weeks (vs. months or years) to enable simulations with physically-relevant domain sizes to be incorporated into industrial design cycles within five years. This was accomplished by tailoring best-in-class practices to bear on the unique challenges posed by the MFIX-DEM algorithm and code base. Scientific simulations (e.g., in cosmology, turbulent combustion) routinely use massively parallel computing to update far more particles in short wall clock times. Results from Phase 1 (1.5 years in duration) indicated significant gains in speed were possible for a wide range of benchmark cases. Moreover, a survey sent to >35 companies indicates that the timing is ideal for such an enhanced tool, with >80% of the respondents indicating that DEM is already value-added or will be within the next 5 years, and >70% of the respondents indicating that improved speed is the top computational priority. In Phase 2 (3.5 years in duration), the two major barriers that hinder industry from effectively using multiphase Computational Fluid Dynamics (CFD) to cut costs and improve performance, namely computational overhead and confidence in predictions, continued to be addressed. Regarding the former, the results from Phase 1 to guide the effort, with enhancements focused on an improved time-stepping algorithm and particle sorting. Four target problems of 1 billion particles each and increasing complexity were identified: homogeneous cooling, tumbler with continuous particle size distribution, discharge from a rectangular hopper and a cylindrical riser. Each of these were successfully simulated for relevant time scales (on order of seconds) using less than 24 hours of wall clock time. These represent the first 1-billion particle DEM simulations performed with MFIX, namely using the MFIX-Exa code. This code is currently under development at NETL in collaboration with Lawrence Berkeley National Laboratory. Regarding the second barrier on predictive uncertainty, experiments from Phase 1 (interacting nozzles - hydrodynamics only) and Phase 2 (very small-scale segregation experiments) were used to demonstrate the ability of two simplified approaches to uncertainty quantification (UQ). By limiting the number of particles, UQ based on the simplified treatment was compared to standard UQ, which was shown to have much higher computational demands. Experiments were also performed on a pilot-scale stripper unit to provide validation data for future CFD-DEM simulations and UQ.

20 FOSSIL-FUELED POWER PLANTS↗