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DOE OSTI2021

Non-invasive characterization of complex coronary lesions

Conventional invasive diagnostic imaging techniques do not adequately resolve complex Type B and C coronary lesions, which present unique challenges, require personalized treatment and result in worsened patient outcomes. These lesions are often excluded from large-scale non-invasive clinical trials and there does not exist a validated approach to characterize hemodynamic quantities and guide percutaneous intervention for such lesions. This work identifies key biomarkers that differentiate complex Type B and C lesions from simple Type A lesions by introducing and validating a coronary angiography-based computational fluid dynamic (CFD-CA) framework for intracoronary assessment in complex lesions at ultrahigh resolution. Among 14 patients selected in this study, 7 patients with Type B and C lesions were included in the complex lesion group including ostial, bifurcation, serial lesions and lesion where flow was supplied by collateral bed. Simple lesion group included 7 patients with lesions that were discrete, <10mm long and readily accessible. Intracoronary assessment was performed using CFD-CA framework and validated by comparing to clinically measured pressure-based index, such as FFR. Local pressure, endothelial shear stress (ESS) and velocity profiles were derived for all patients. We validates the accuracy of our CFD-CA framework and report excellent agreement with invasive measurements (n=14,R 2 =0.6,p=0.0013). Ultra-high resolution achieved by the model enable physiological assessment in complex lesions and quantify hemodynamic metrics in all vessels up to 1mm in diameter. Importantly, we demonstrate that in contrast to traditional pressure-based metrics, there is a significant difference in the intracoronary hemodynamic forces, such as ESS, in complex lesions compared to simple lesions at both resting and hyperemic physiological states [n = 14, p=0.03]. Higher ESS was observed in the complex lesion group (7.0±4.7 Pa) than in simple lesion group (4.8±3.6 Pa). Complex coronary lesions have higher ESS compared to simple lesions, such differential hemodynamic evaluation can provide much the needed insight into the increase in adverse outcomes for such patients and has incremental prognostic value over traditional pressure-based indices, such as FFR.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

FLEX-FUEL MIXING CONTROLLED COMBUSTION ENABLED BY PRECHAMBER IGNITION

There is an imminent need to displace fossil diesel fuel with cleaner burning, domestically produced, renewable fuels for use in heavy-duty engines. Bioethanol is a prime candidate as it widely adopted in the U.S. as a gasoline additive ranging in volume percentage from 10% (E10) up to 85% (E85). Direct substitution of market available ethanol-gasoline blends for diesel fuel is not plausible as the stark reactivity differences would not constitute the same ignition quality nor achieve auto-ignition at all. This work focuses on the development of prechamber enabled mixing-controlled combustion (PC-MCC) as an advanced combustion strategy to facilitate reliable ignition and diffusion style combustion ethanol-gasoline fuel blends. PC-MCC involves integration of an actively fueled prechamber (PC) into a conventional compression ignition combustion system. When ignited, the PC ejects hot turbulent jets into the main combustion chamber that then interact with the direct injected fuel, prompting immediate ignition. The PC jet flames provide a robust thermal ignition source that allows the engine to operate agnostic of fuel composition, or flex-fuel. Computational fluid dynamics (CFD) modeling was used to assess critical design features of the PC while garnering insights into the ignition strategies that facilitate robust performance. A key finding was the ignition performance benefits of fuel-rich PC operation which yield exothermic jets. Based on the numerical findings, a prototype igniter was tested experimentally on both single and multi-cylinder engine platforms at a variety of operating conditions. The experimental results indicate flex-fuel PC-MCC is well capable of diesel-like combustion processes by demonstrating matched or improved gross thermal efficiencies and load variability within 2%. Fuel grade ethanol (E98) exhibited consistently lower NOx and immeasurable soot across the load space. E98 also demonstrated a significant improvement in thermal efficiency at light loads.

Zeman, Jared↗

DOE OSTI2021

Oxygen enrichment combustion to reduce fossil energy consumption and emissions in hot rolling steel production

The reheating furnace operation in the hot mill is natural gas- and electricity-intensive. Oxygen enrichment combustion for reheating furnaces has been proposed to curb and replace natural gas use. In this study, heat transfer in steel slabs in the combustion environment of a push-type reheating furnace was simulated using a computational fluid dynamics (CFD) model. Two oxygen enrichment methods that optimized for performance were selected— a medium oxygen enrichment (MOE) case and an oxy-fuel (OF) case. A life cycle analysis (LCA) characterized the energy and emission profiles of an integrated iron and steel manufacturing process using the two oxygen enrichment cases for the hot mill. These conditions were evaluated for energy use and carbon intensity and compared with a baseline case. Results show that with oxygen enrichment, natural gas consumption can decrease by 19.6%–26.8%, total energy consumption (natural gas and electricity) can decrease by 15.1%–20.7% in the hot mill. Emissions of greenhouse gases can decrease by 11.1%–15.2% in the two optimized cases with 14%–27% reductions in regulated criteria pollutants (nitrogen oxides, carbon monoxide, particulate matter, volatile organic compounds, black carbon, organic carbon, and volatile organic carbons). There is a tradeoff between reducing natural gas consumption and increasing electricity demand from a life cycle perspective. Although the OF case resulted in higher energy- and emissions-related benefits, the MOE case showed the more desirable heat flux uniformity, which is key to maintaining product quality. The analysis suggests that oxygen enrichment in the reheating furnace process can have a significant impact on hot mill environmental performance and become a contributing factor in transitioning to low-carbon steel manufacturing.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Numerical Analysis of Fuel Effects on Advanced Compression Ignition Using a Cooperative Fuel Research Engine Computational Fluid Dynamics Model

Growing environmental concerns and demand for a better fuel economy are driving forces that motivate the research for more advanced engines. Multi-mode combustion strategies have gained attention for their potential to provide high thermal efficiency and low emissions for light-duty applications. These strategies target optimizing the engine performance by correlating different combustion modes to load operating conditions. The extension from boosted spark ignition (SI) mode at high loads to advanced compression ignition (ACI) mode at low loads can be achieved by increasing the compression ratio and utilizing intake air heating. Further, in order to enable an accurate control of intake charge condition for ACI mode and rapid mode-switches, it is essential to gain fundamental insights into the autoignition process. Within the scope of ACI, homogeneous charge compression ignition (HCCI) mode is of significant interest. It is known for its potential benefits, operation at low fuel consumption, low NOx, and particulate matter (PM) emissions. In the present work, a virtual Cooperative Fuel Research (CFR) engine model is used to analyze fuel effects on ACI combustion. In particular, the effect of fuel octane sensitivity (S) (at constant Research Octane Number (RON)) on autoignition propensity is assessed under beyond-RON (BRON) and beyond-MON (BMON) ACI conditions. The three-dimensional CFR engine computational fluid dynamics (CFD) model employs a finite-rate chemistry approach with a multi-zone binning strategy to capture autoignition. Two binary blends with Research Octane Number (RON) of 90 are chosen for this study: primary reference fuel (PRF) with S = 0 and toluene–heptane (TH) blend with S = 10.8, representing paraffinic and aromatic gasoline surrogates. Reduced mechanisms for these blends are generated from a detailed gasoline surrogate kinetic mechanism. Simulation results with the reduced mechanisms are validated against experimental data from an in-house CFR engine, with respect to in-cylinder pressure, heat release rate, and combustion phasing. Thereafter, the sensitivity of combustion behavior to ACI operating condition (BRON versus BMON), air-fuel ratio (λ = 2 and 3), and engine speed (600 and 900 rpm) is analyzed for both fuels. It is shown that the sensitivity of a fuel’s autoignition characteristics to λ and engine speed significantly differs at BRON and BMON conditions. Moreover, this sensitivity is found to vary among fuels, despite the same RON. It is also observed that the presence of low-temperature heat release (LTHR) under BRON condition leads to more sequential autoignition and longer combustion duration than BMON condition. Finally, the study indicates that the octane index (OI) fails to capture the trend in the variation of autoignition propensity with S under the BMON condition.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2026

FY26 Progress on Demonstration of a Multiphysics Steady State Capability for Modeling Core Radial Expansion in SFRs

Under the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program, an integrated multiphysics approach is being developed to model the core bowing phenomena important to liquid metal-cooled fast reactors. Core bowing is an important passive safety mechanism in liquid metal-cooled fast reactors and involves multiphysics effects including radiation transport, fluid flow, heat transfer, and mechanical response to temperature and flux gradients. This report summarizes recent progress on developing a multiphysics, MOOSE-based workflow to predict core bowing and associated reactivity feedback. Significant new capabilities in the reactor physics code Griffin - sodium backfill and pin power reconstruction for deformed geometries - were applied in this effort. This year’s work included verification, code comparisons, sensitivity studies, and coupled demonstrations that advance the state of MOOSE-based core bowing workflow. Griffin’s sodium backfill capability was verified by demonstrating that its automated treatment of geometry expansion and material-density updates reproduces manual calculations exactly, confirming solid mass conservation and proper coolant backfilling in expanded geometries. Reconstructed pin powers were compared for Griffin’s ductheterogeneous and ring-heterogeneous treatments in single-, seven-, and nineteen-assembly cases, with best agreement observed in lower-leakage configurations and the duct-heterogeneous approach offering substantially lower computational cost. Thermal-hydraulic sensitivity sensitivities showed that MOOSE SCM, SAM, and CFD are expected to produce similar deformation predictions despite variances in their temperature predictions, and that explicit treatment of inter-assembly flow becomes increasingly important as gap flow rate increases. Finally, coupled demonstrations on small multi-assembly configurations using Griffin, MOOSE Solid Mechanics, MOOSE SCM, and Heat Conduction produced physically consistent reactivity feedback from thermal expansion and bowing. The coupled demonstrations simulated grid plate expansion as well as resultant core bowing at full power conditions. Simplifications were made in current workflow, namely the assumption of instantaneous full power conditions following hot zero power, and pre-expanding the Griffin geometry axially due to lack of an axial fuel pin expansion model and temperature feedback to Griffin.

Wozniak, Nicholas↗

DOE OSTI2022

Effects of Port Angle on Scavenging of an Opposed Piston Two-Stroke Engine

Opposed-piston 2-stroke (OP-2S) engines have the potential to achieve higher thermal efficiency than a typical diesel engine. However, the uniflow scavenging process is difficult to control over a wide range of speeds and loads. Scavenging performance is highly sensitive to pressure dynamics, port timings, and port design. This study proposes an analysis of the effects of port vane angle on the scavenging performance of an opposed-piston 2-stroke engine via simulation. A CFD model of a three-cylinder opposed-piston 2-stroke was developed and validated against experimental data collected by Achates Power Inc. One of the three cylinders was then isolated in a new model and simulated using cycle-averaged and cylinder-averaged initial/ boundary conditions. This isolated cylinder model was used to efficiently sweep port angles from 12 degrees to 29 degrees at different pressure ratios. Results indicate that scavenging performance is correlated with the bulk swirl ratio generated by these port angles. Scavenging performance is also sensitive to the pressure ratio across the engine. It was concluded that, for a given pressure ratio, the smallest port angle produces the best scavenging; however, previous work indicates lower bulk swirl ratio during combustion can have an impact on emissions formation.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

Direct Numerical Simulation of the Flow through a Randomly Packed Pebble Bed

The proposition for molten salt and high-temperature gas-cooled reactors has increased the focus on the dynamics and physics in randomly packed pebble beds. Research is being conducted on the validity of these designs as a possible contestant for the fourth-generation nuclear power systems. A detailed understanding of the coolant flow behavior is required in order to ensure proper cooling of the reactor core during normal and accident conditions. In order to increase the understanding of the flow through these complex geometries and enhance the accuracy of lower-fidelity modeling, high-fidelity approaches such as direct numerical simulation (DNS) can be utilized. Nek5000, a spectral-element computational fluid dynamics (CFD) code, was used to develop DNS fluid flow data. The flow domain consisted of 147 pebbles enclosed by a bounding wall. In the work presented, the Reynolds numbers ranged from 430 to 1050 based on the pebble diameter and inlet velocity. Characteristics of the flow domain such as volume averaged porosity, axial porosity, and radial porosity were studied and compared with correlations available in the literature. Friction factors from the DNS results for all Reynolds numbers were compared with correlations in the literature. The first- and second-order statistics show good agreement with the available experimental data. Turbulence length scales were analyzed in the flow. Reynolds stress anisotropy was characterized by utilizing invariant analysis. Overall, the results of the analysis in this study provide deeper understanding of the flow behavior and the effect of the wall in packed beds.

Yildiz, Mustafa Alper↗

DOE OSTI2024

Isothermal Compressor Computational Fluid Dynamics Simulations (Final Report)

Carnot Compression is a startup company developing an innovative technology for air and gas compression. This technology is inherently oil-free and isothermal due to the use of water to simultaneously compress and cool the gas throughout the process. Isothermal gas compression eliminates the need to cool the compressed gas so it may lead to significant energy savings. The development of Carnot’s isothermal compressor is limited by the lack of insight into the flow and detailed behavior of the fluids (water and air/gas) inside the air end. Previous and current attempts at Computational Fluid Dynamics (CFD) simulations by Carnot have been unable to provide the level of accuracy required to use simulations for technology development. In this Cooperative Research and Development Agreement (CRADA) project, Oak Ridge National Laboratory (ORNL) used the CFD package Star-CCM+ to successfully develop a CFD simulation, providing the much-needed insight required to speed up the development. The work is intended to enable Carnot Compression to unlock its technology potential to a level sufficient for commercialization of the intended first product. The work will also prepare Carnot to scale the technology to much larger and more energy intensive applications, positioning it to broaden the product applications. Successful development of the technology has the potential to result in 20% or more efficiency gains for compression processes, or about $3 billion in annual energy savings potential for the U.S. alone.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

Validation of two-layer model for underexpanded hydrogen jets

Previous studies have shown that the two-layer model more accurately predicts hydrogen dispersion than the conventional notional nozzle models without significantly increasing the computational expense. However, the model was only validated for predicting the concentration distribution and has not been adequately validated for predicting the velocity distributions. In the present study, particle imaging velocimetry (PIV) was used to measure the velocity field of an underexpanded hydrogen jet released at 10 bar from a 1.5 mm diameter orifice. The two-layer model was the used to calculate the inlet conditions for a two-dimensional axisymmetric CFD model to simulate the hydrogen jet downstream of the Mach disk. The predicted velocity spreading and centerline decay rates agreed well with the PIV measurements. The predicted concentration distribution was consistent with data from previous planar Rayleigh scattering measurements used to verify the concentration distribution predictions in an earlier study. The jet spreading was also simulated using several widely used notional nozzle models combined with the integral plume model for comparison. These results show that the velocity and concentration distributions are both better predicted by the two-layer model than the notional nozzle models to complement previous studies verifying only the predicted concentration profiles. Thus, this study shows that the two-layer model can accurately predict the jet velocity distributions as well as the concentration distributions as verified earlier. Though more validation studies are needed to improve confidence in the model and increase the range of validity, the present work indicates that the two-layer model is a promising tool for fast, accurate predictions of the flow fields of underexpanded hydrogen jets.

08 HYDROGEN↗

DOE OSTI2024

Assessing Critical Conditions for Scour Near Obstructions using Bed Shear, Particle Onset of Motion Balances, and CFD-DEM Modeling of Granular Beds

Computational Fluid Dynamics combined with a Discrete Element Method is one of the computational methods that can be used to model multiphase flows. In this method various phases, gas and liquid or solid, are present in the same computational domain. The local averaged Navier–Stokes equations determine the flow of the continuous phase fluid and are solved using the traditional CFD finite volume approach. DEM is based on a Lagrangian formulation, which solves the equations of motion, expressed in ordinary differential equations, for representative particles as they move in space and time. The interactions between the continuous fluid phase and discrete solid phase are modeled with the use of Newton’s laws of motion via drag force. The particles interact with each other and with the boundaries of the fluid continuum, and the resulting contact forces are included in the equations of motion. The properties of solid particles and boundaries are treated as elastic bodies, with specified density, elastic modulus, and Poisson’s ratio. Particle shapes may vary from single spherical particles to more complex-shaped composite particles. The particles may be introduced into the domain by random or structured injection at a point, surface, or volume, depending on the application. More details on the formulation can be found in the Simcenter STAR-CCM+ User’s Manual and OpenFOAM website.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2019

Effect of Char Loading on Reduction Kinetics of Cu-Based Oxygen Carriers in a Drop-Tube Fluidized-Bed Reactor at Temperatures from 850 to 1100 °C: Experiment and CFD Modeling

Chemical-looping combustion with oxygen uncoupling (CLOU) is a process using gaseous or solid hydrocarbon fuels and is a promising carbon capture and storage (CCS) technology. In CLOU, combustion of the fuel is achieved through the release of gaseous O 2 from an oxygen carrier material such as CuO and is favored at high temperatures and low O 2 partial pressures. The primary objectives of this study were to (1) compare values for the apparent rate constant k ov ( T ) for the overall rate of reduction of a CuO carrier, either alone or in the presence of coal char obtained from the pyrolysis of Powder River Basin (PRB) coal, and (2) develop and validate a computational fluid dynamics (CFD) model for the CuO/PRB coal char system based on known kinetics of the individual CuO and Cu 2 O reduction, combustion, and gasification reactions. Two oxygen carriers consisting of 20 wt % CuO/Al 2 O 3 and 9 wt % CuO/Al 2 O 3 were prepared by physical mixing and by incipient wetness impregnation (IWI), respectively. Kinetic analyses were conducted in the temperature range of 850–1100 °C. The CFD model typically reproduced experimental values of k ov ( T ) to within ±10%. We note the increase in k ov ( T ) caused by addition of only 0.075 g of PRB char per gram of CuO was modest at 1100 °C, but was more than 3-fold at 850 °C. Combustion and gasification of the coal char not only produced CO, opening another pathway for CuO reduction in addition to the CLOU reaction, but also resulted in the over-reduction of Cu 2 O to the undesired metallic Cu. Production of Cu metal increased with respect to char loading.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

An Orthogonal Recursive Bisection (ORB) Based Time Advancement Algorithm for CFD-DEM Solvers

The time integration of the granular phase in coupled computational fluid dynamics (CFD) – discrete element method (DEM) simulations presents a unique computational challenge brought about by the large variations in particle collisional time scales. Particles in the dilute regions of the computational domain can be advanced with large time steps while dense regions require much smaller time increments. However, the time step size in most solvers is globally set as the limit for accuracy and stability imposed by the collisions and is typically orders of magnitude less than that required away from collisions. This work addresses this precise issue and provides a strategy to avoid the use of a global conservative small time step size for the entire set of particles.A novel time stepping algorithm for CFD-DEM solvers using a partitioning approach using orthogonal recursive bisection (ORB) that allows for variable time steps among particles is described and its computational performance is compared against baseline explicit methods, typically used in several CFD-DEM solvers. ORB has advantages of being relatively quick and easy to update incrementally and has the required heuristic behavior (i.e., it will split the region in half with a cluster on each side) when groups of particles are well separated (clustered). The algorithm presented in this work uses a local time stepping approach to resolve collisional time scales for subsets of particles that are present at the leaves of the ORB, thereby resulting in substantial reduction of computational cost. The parallel implementation of this method where a ``knapsack” algorithm is used in tandem with ORB for effective load-balancing is also presented, where a best possible partitioning is obtained based on number of particles and local time-stepping costs. The algorithm is tested against benchmark problems with varying particle distributions that include fluidized bed and riser flow scenarios. Preliminary results indicate that the approach is 2-3X faster than traditional explicit methods for problems that involve both dense and dilute regions, while maintaining the same level of accuracy.

adaptive timestepping↗

DOE OSTI2020

A multi-dimensional dataset for two-phase instability in low pressure natural circulation based on direct transient local measurement

Thermal hydraulic instability can challenge the control and the safety of nuclear reactors. This experimental research captures and investigates the instability in a low-pressure (1–10 atmospheres) natural circulation loop with an adiabatic chimney installed above the heated section. Direct transient local measurement of two-phase flow is performed at multiple axial locations along the flow channel with thermocouples and conductivity probes traversed by customized high-precision mechanisms. Based on the periodicity of oscillations, a post-processing method is proposed to align the data captured non-simultaneously to reconstruct the instability behavior in one representative period. The averaging operation over multiple oscillation cycles is performed to reduce the random errors. Cyclic phenomena are clearly demonstrated by the post-processed data, and rapid void fraction change induced by the flashing is observed to be significant in the driving mechanism for low pressure oscillations. Parametric effects of inlet subcooling, heat flux, inlet flow restriction and system pressure are studied within the experiment range, and qualitative results are explained and compared with existing literature. The ratio between the oscillation period and the travelling time of the fluid particle through the test section is compared with the theoretical value for the density wave oscillation. The new dataset contains directly measured transient multi-dimensional two-phase data along the flow channel for natural circulation under density wave oscillations. The generated dataset is valuable for the validation of system analysis codes and CFD codes in the simulation of natural circulation phenomena and dynamic two-phase flow.

42 ENGINEERING↗

DOE OSTI2019

A two-phase substrate model for enzymatic hydrolysis of lignocellulose: application to batch and continuous reactors

Abstract Background Enzymatic hydrolysis continues to have a significant projected production cost for the biological conversion of biomass to fuels and chemicals, motivating research into improved enzyme and reactor technologies in order to reduce enzyme usage and equipment costs. However, technology development is stymied by a lack of accurate and computationally accessible enzymatic-hydrolysis reaction models. Enzymatic deconstruction of cellulosic materials is an exceedingly complex physico-chemical process. Models which elucidate specific mechanisms of deconstruction are often too computationally intensive to be accessible in process or multi-physics simulations, and empirical models are often too inflexible to be effectively applied outside of their batch contexts. In this paper, we employ a phenomenological modeling approach to represent rate slowdown due to substrate structure (implemented as two substrate phases) and feedback inhibition, and apply the model to a continuous reactor system. Results A phenomenological model was developed in order to predict glucose and solids concentrations in batch and continuous enzymatic-hydrolysis reactors from which liquor is continuously removed by ultrafiltration. A series of batch experiments were performed, varying initial conditions (solids, enzyme, and sugar concentrations), and best-fit model parameters were determined using constrained nonlinear least-squares methods. The model achieved a good fit for overall sugar yield and insoluble solids concentration, as well as for the reduced rate of sugar production over time. Additionally, without refitting model coefficients, good quantitative agreement was observed between results from continuous enzymatic-hydrolysis experiments and model predictions. Finally, the sensitivity of the model to its parameters is explored and discussed. Conclusions Although the phenomena represented by the model correspond to behaviors that emerge from clusters of mechanisms, and hence a set of model coefficients are unique to the substrate and the enzyme system, the model is efficient to solve and may be applied to novel reactor schema and implemented in computational fluid dynamics (CFD) simulations. Hence, this modeling approach finds the right balance between model complexity and computational efficiency. These capabilities have broad application to reactor design, scale-up, and process optimization.

09 BIOMASS FUELS↗

DOE OSTI2020

Prediction of Performance Variation Caused by Manufacturing Tolerances and Defects in Gas Diffusion Electrodes of Phosphoric Acid (PA)–Doped Polybenzimidazole (PBI)-Based High-Temperature Proton Exchange Membrane Fuel Cells

The automated process of coating catalyst layers on gas diffusion electrodes (GDEs) for high-temperature proton exchange membrane fuel cells results inherently into a number of defects. These defects consist of agglomerates in which the platinum sites cannot be accessed by phosphoric acid and which are the consequence of an inconsistent coating, uncoated regions, scratches, knots, blemishes, folds, or attached fine particles—all ranging from μm to mm size. These electrochemically inactive spots cause a reduction of the effective catalyst area per unit volume (cm2/cm3) and determine a drop in fuel cell performance. A computational fluid dynamics (CFD) model is presented that predicts performance variation caused by manufacturing tolerances and defects of the GDE and which enables the creation of a six-sigma product specification for Advent phosphoric acid (PA)-doped polybenzimidazole (PBI)-based membrane electrode assemblies (MEAs). The model was used to predict the total volume of defects that would cause a 10% drop in performance. It was found that a 10% performance drop at the nominal operating regime would be caused by uniformly distributed defects totaling 39% of the catalyst layer volume (~0.5 defects/μm2). The study provides an upper bound for the estimation of the impact of the defect location on performance drop. It was found that the impact on the local current density is higher when the defect is located closer to the interface with the membrane. The local current density decays less than 2% in the presence of an isolated defect, regardless of its location along the active area of the catalyst layer.

Gurau, Vladimir (ORCID:0000000327429061)↗

DOE OSTI2021

Computational Fluid Dynamics Combustion Modeling for Rotating Detonation Engines

This paper focuses on the development and validation of a combustion model for Computational Fluid Dynamics (CFD) modeling of Rotating Detonation Engines. A zero-dimensional Partially Stirred Reactor (PaSR) with a detailed chemical kinetic mechanism for hydrogen and air is used to model turbulent combustion. The model is computationally efficient and is based on the notion of partial mixing at the sub-grid level with turbulent exchange between mixed and unmixed regions. The ability of the PaSR model to accurately represent both detonative and deflagrative combustion is assessed by validating the results against experimental data. The effects of mesh resolution on the solution are also studied in order to determine if a mesh independent solution is obtainable with the Large Eddy Simulation (LES) approach to modeling turbulence. A comparison is made between the PaSR model and simply ignoring turbulence chemistry interactions which assumes that all species are perfectly mixed at the sub-grid level.

Strakey, Peter↗

DOE OSTI2024

LES and RANS Spray Combustion Analysis of OME 3-5 and n-Dodecane

Clean-burning oxygenated and synthetic fuels derived from renewable power, so-called e-fuels, are a promising pathway to decarbonize compression–ignition engines. Polyoxymethylene dimethyl ethers (PODEs or OMEs) are one candidate of such fuels with good prospects. Their lack of carbon-to-carbon bonds and high concentration of chemically bound oxygen effectively negate the emergence of polycyclic aromatic hydrocarbons (PAHs) and even their precursors like acetylene (C 2 H 2 ), enabling soot-free combustion without the soot-NO x trade-off common for diesel engines. The differences in the spray combustion process for OMEs and diesel-like reference fuels like n-dodecane and their potential implications on engine applications include discrepancies in the observed ignition delay, the stabilized flame lift-off location, and significant deviations in high-temperature flame morphology. For CFD simulations, the accurate modeling and prediction of these differences between OMEs and n-dodecane proved challenging. This study investigates the spray combustion process of an OME 3 − 5 mixture and n-dodecane with advanced optical diagnostics, Reynolds-Averaged Navier–Stokes (RANS), and Large-Eddy Simulations (LESs) within a constant-volume vessel. Cool-flame and high-temperature combustion were measured simultaneously via high-speed (50 kHz) imaging with formaldehyde (CH 2 O) planar laser-induced fluorescence (PLIF) representing the former and line-of-sight OH* chemiluminescence the latter. Both RANS and LES simulations accurately describe the cool-flame development process with the formation of CH 2 O. However, CH 2 O consumption and the onset of high-temperature reactions, signaled by the rise of OH* levels, show significant deviations between RANS, LES, and experiments as well as between n-dodecane and OME. A focus is set on the quality of the simulated results compared to the experimentally observed spatial distribution of OH*, especially in OME fuel-rich regions. The influence of the turbulence modeling is investigated for the two distinct ambient temperatures of 900 K and 1200 K within the Engine Combustion Network Spray A setup. The capabilities and limitations of the RANS simulations are demonstrated with the initial cool-flame propagation and periodic oscillations of CH 2 O formation/consumption during the quasi-steady combustion period captured by the LES.

CFD↗

DOE OSTI2023

Analytical Study and Experimental Verification of Shear-Thinning Ink Flow in Direct Ink Writing Process

Abstract Direct ink writing (DIW) process is a facile additive manufacturing technology to fabricate three-dimensional (3D) objects with various materials. Its versatility has attracted considerable interest in academia and industry in recent years. As such, upsurging endeavors are invested in advancing the ink flow behaviors in order to optimize the process resolution and the printing quality. However, so far, the physical phenomena during the DIW process are not revealed in detail, leaving a research gap between the physical experiments and its underlying theories. Here, we present a comprehensive analytical study of non-Newtonian ink flow behavior during the DIW process. Different syringe-nozzle geometries are modeled for the comparative case studies. By using the computational fluid dynamics (CFD) simulation method, we reveal the shear-thinning property during the ink extrusion process. Besides, we study the viscosity, shear stress, and velocity fields, and analyze the advantages and drawbacks of each syringe-nozzle model. On the basis of these investigations and analyses, we propose an improved syringe-nozzle geometry for stable extrusion and high printing quality. A set of DIW printing experiments and rheological characterizations are carried out to verify the simulation studies. The results developed in this work offer an in-depth understanding of the ink flow behavior in the DIW process, providing valuable guidelines for optimizing the physical DIW configuration toward high-resolution printing and, consequently, improving the performance of DIW-printed objects.

Engineering↗