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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

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↗
DOE OSTI2026

Machine learning based prediction of airflow maldistribution in air-to-refrigerant heat exchangers

Flow maldistribution is a common challenge in heat exchanger (HX) design and particularly important for air-to-refrigerant geometries where capacity losses can approach 65%. This has a major impact on central air conditioning systems, as compact duct design motivates the use of A-type HXs which are known to be affected by airflow maldistribution. Because velocity profiles are difficult to predict, components are often oversized leading to increased material cost, system footprint, and refrigerant charge. Several studies detail airflow maldistribution for individual HXs and packages, but findings cannot always be extrapolated to new designs. In this work, a machine learning (ML) based flow profile prediction framework is developed and applied to two common package configurations: (i) A-type and (ii) U-type HXs, across a broad range of HX geometries and flow rates. Porous media CFD simulations are validated against independent data for both package types as well as comprehensive in house measurements for a finless geometry with shape optimized non-round tubes, which validates the framework for new heat transfer surfaces. The ML models are trained on the porous media CFD simulations, predicting volumetric flow rate (VFR) within 1.1% and 1.9% with maximum relative L 2 norm errors of 0.48 and 0.65, respectively, while also delivering 10 5 speed up factor compared to full porous media CFD. HX level simulations show an up to 9% reduction in heat transfer from flow maldistribution, with greater losses occurring at smaller half apex angles. This framework enables rapid and highly accurate prediction of airflow maldistribution induced capacity degradation.

42 ENGINEERING↗
DOE OSTI2025

Development of a conduction-based model for analyzing frozen startup of alkali-metal heat pipes

One key area of interest in heat pipe modeling/simulation is to analyze the startup behavior of the liquid-metal heat pipes (LMHPs) from a frozen state. This so-called ‘frozen startup’ process involves a complex set of nonlinear mass and heat transport phenomena, including phase transitions from solid to liquid and vapor, multiphase interactions, microporous wick flow, and compressible vapor dynamics. The complexity of these processes makes it challenging to simulate LMHP’s frozen startup using conventional numerical methods or commercial computational fluid dynamics (CFD) software. This paper presents a simplified conduction-based modeling approach that can provide practical insights into the entire LMHP frozen startup process, while alleviating the challenges of modeling its complex physics. The theoretical foundation and physical assumptions of the proposed model are based solely on heat-conduction equation, allowing for a more tractable simulation without sacrificing essential physical accuracy. The proposed model was implemented in a commercial CFD software, and its prediction was compared with the experimental data obtained from sodium heat-pipe startup experiments. The comparison highlights the proposed model's ability to capture the transient thermal behavior of LMHP during frozen startup. This study not only validates the conduction-based frozen startup modeling method but also shows its potential as a practical and efficient tool for understanding the startup performance of the LMHP systems.

Microreactor↗
DOE OSTI2020

ROM-Based Surrogate Systems Modeling of EBR-II

We report the System Analysis Module (SAM), developed and maintained by Argonne National Laboratory, is designed to provide whole-plant transient safety analysis capabilities for a number of advanced non-light water reactors, including sodium-cooled fast reactor (SFR), lead-cooled fast reactor (LFR), and molten salt reactor (MSR)/fluoride-salt-cooled high-temperature reactor (FHR) designs. SAM is primarily constructed as a systems-level analysis tool, with the potential to incorporate reduced order models from three-dimensional computational fluid dynamics (CFD) simulations to improve characterization of complex, multidimensional physics. It is recognized that the computational expense associated with CFD can be intractable for various engineering analyses, such as uncertainty quantification, inference, and design optimization. This paper explores the reducibility of a SAM model using recent advances in randomized linear algebra techniques, which attempt to find recurring patterns in the various realizations generated by a model after randomly perturbing all its input parameters. The reduction is described in terms of fewer degrees of freedom (DOFs), referred to as the active DOFs, for the model variables such as input model parameters and model responses. The results indicate that there is significant room for additional reduction that may be leveraged for additional computational gains when employing SAM for engineering-intensive analyses that require repeated model executions. Different from physics-based reduction approaches, the proposed approach allows one to estimate upper bounds on the reduction errors, which are rigorously developed in this work. Finally, different methods for surrogate model construction, such as regression and neural network-based training, are employed to correlate the input and output active DOFs, which are related back to the original variables using matrix-based linear transformations.

42 ENGINEERING↗
DOE OSTI2022

Validation of Thermohydraulic Simulations using RELAP for Critical Dual Purpose Canisters

Simulations using the RELAP5-3D systems analysis code and STAR-CCM+, a high-fidelity CFD code, were performed on a model of a real-scale MPC-32 dual purpose canister undergoing a criticality event. These simulations were performed to provide code-to-code verification of the natural convection capabilities in RELAP5. The STAR-CCM+ simulations revealed various natural convection flow patterns that aided in the cooling of fission heat produced in the fuel rods in the canister. Negligible spatial temperature variations were observed across the canister in the STAR-CCM+ results, supporting the use of RELAP5 in predicting the sub-cooled regime. The surface-averaged rod temperature predicted by RELAP5 compared well with STAR-CCM+, verifying the predictive capability of RELAP5 for sub-cooled conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Effect of Surface Roughness on Dynamic Stall in Pitching Motion

Dynamic stall plays a critical role in determining the performance and stability of a wide range of fluid-dynamics systems in various engineering applications. This unsteady aerodynamic phenomenon is particularly significant for maneuvering aircraft wings, jet aircraft subjected to gust encounters, helicopter rotor blades, and wind turbine blades [1–3]. The prediction of the dynamic stall vortex (DSV) is challenging due to factors such as unsteady aerodynamics, three-dimensional (3-D) effects, turbulence and flow separation, incoming gust, and surface impact effects [4–6]. Hence, advanced computational techniques and modeling approaches in computational fluid dynamics (CFD) would be required to enhance the accuracy and reliability of DSV predictions in dynamic stall scenarios. In the past, Batther and Lee [7] employed delayed detached eddy simulations (DDES) to understand the flow physics associated with the onset of dynamic stall. Their approach demonstrated that DDES achieves results comparable to those obtained from large-eddy simulations at a reduced computational cost. In another study, Khalifa et al. [8] examined the 3-D aspects of dynamic stall on a NACA 0012 airfoil using DES solvers. In conclusion, the findings underlined the superiority of 3-D simulations over two-dimensional approaches, particularly in predicting the lift coefficient values and capturing dynamic stall stages more precisely.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Tutorial - Electric Motor and Integrated Traction Drive Thermal Management

The share of vehicles with fully electric propulsion systems is constantly increasing, and so is their traction drive power. The continuous push to increase power of electric vehicle (EV) traction drives necessitates their efficient cooling to prevent damage to temperature sensitive components of the drive system and achieving higher power outputs in a smaller footprint. With increasing power and power density of electric traction drives, their thermal management is becoming increasingly challenging. This tutorial will provide an overview of thermal management approaches for electric motors and power electronics in EV applications. It will review examples of current industry solutions for power-dense electric motor cooling, power electronics (inverter) cooling, their integration concepts and thermal management system solutions. We'll look at the advantages and challenges of power electronics integration into a single traction drive unit and respective thermal management system concepts. We'll talk about barriers to implementation of a unified thermal management system. The tutorial will also review key aspects of thermal management system design: modeling and simulation using FEA and CFD tools, experimental characterization, and general workflow for thermal management system evaluation.

ADVANCED PROPULSION SYSTEMS,DIRECT ENERGY CONVERSI↗
DOE OSTI2022

Validation of CFD simulations of the moored DeepCwind offshore wind semisubmersible in irregular waves

This article examines the use of computational fluid dynamics (CFD) simulations to predict the response of a floating wind platform to irregular-wave excitation. This work was conducted as part of the Reproducible CFD Joint Industry Project for Floating Offshore Wind Applications and involved verification across several participants and modeling tools and validation against experiments. The authors pay special attention to the uncertainties in both CFD results and experimental measurements. In this work, we perform detailed comparisons of the incident waves and the motion of a moored structure. The nonlinear, low-frequency resonance motion is of particular interest because it potentially drives the mooring and tower-base loads. The verification and validation study is partially successful in that the CFD simulations capture the low-frequency slow-drift motion well but underpredict the low-frequency pitch resonance. This underprediction can be attributed in part to the CFD incident waves, which showed some discrepancies with the experimental waves, especially around extreme events. The effects of the wave discrepancies are also estimated and investigated using a mid-fidelity OpenFAST model. Overall, the present study increases our confidence in using CFD simulations to predict the global performance of offshore wind platforms in irregular waves and to produce data for the calibration of lower-fidelity models.

17 WIND ENERGY↗
DOE OSTI2021

Numerical Study and Validation of Melting and Solidification in PCM Embedded Heat Exchangers with Straight Tube

Latent heat thermal energy storage (LHTES) systems have shown great potential to enable reliable use of renewable energy and load shifting. LHTES offer high storage density and release energy at near constant temperature because of its use of phase change materials (PCMs). The cylindrical PCM heat exchangers (PCMHX) are one of the most used technologies due to their simplicity. Numerical models for such PCMHX enable engineers to estimate their performance for different design parameters and operating conditions without having to test them all. However, modeling the phase change phenomena can be challenging. To better understand the difficulties involving accurate modeling of PCMHX, a cylindrical latent storage unit filled with PCM and water as in-tube heat transfer fluid (HTF) is numerically investigated. This paper presents a study based on a 2D-axisymmetric model of a straight tube embedded in PCM in a cylindrical container. CFD is used to study the charging (melting) and discharging (solidification) phenomena. The models are validated against experimental and numerical data from the literature. The predicted local PCM temperature profile over time agrees within 2K compared to the experimental values. The paper also presents a simple method to estimate the melting and solidification phase change temperature range from limited data provided by PCM manufacturers.

PCM, melting, solidification, CFD, heat exchanger↗
DOE OSTI2020

Investigating biomass composition and size effects on fast pyrolysis using global sensitivity analysis and CFD simulations

It is notoriously difficult to build an accurate universal model for biomass pyrolysis due to its sensitivity to a wide number of critical material attributes such as chemical species and physical sizes. In this work, a biomass pyrolysis kinetics with 32 heterogeneous reactions and 59 species was implemented in an open-source multiphase computational fluid dynamics (CFD) software MFiX and validated against two different experimental pyrolysis data sets that provided detailed data describing chemical component yields. The reaction scheme was then used to build a surrogate model and assess the sensitivity of pyrolysis yields to feedstock compositions. The sensitivity analysis determined that the yield of bio-char showed a strong positive sensitivity to the carbon-rich lignin and tannin pseudo-species in the reaction scheme while the bio-oil and bio-gas were correlated to oxygen-rich lignin pseudo-species. The reaction scheme was then integrated into a coarse-grained discrete element model to simulate fast pyrolysis in a bubbling fluidized bed over a range of feedstock particle sizes. The reactor simulations showed further sensitivity to particle size and hydrodynamics. Notably, particles under 0.5 mm have small heat transfer limitations but left the reactor before completely converting and thus reduced the bio-oil yield. Results from this study can be used to guide future development of highly accurate models for fast pyrolysis reactors with a variety of feedstock properties and operating conditions.

09 BIOMASS FUELS↗
DOE OSTI2022

Crucible Melter Simulation in Nek5000

Nuclear tank waste at the Hanford site is slated for vitrification in large scale refractory-lined melters to transform it into a stable borosilicate waste form suitable for long-term storage or disposal. Molten glass corrodes the refractory lining over time at a rate correlated to the velocity of molten glass against the refractory-lined wall. To properly design a melter and plan for maintenance, it is necessary to accurately model the glass flow and find the correlation between flow velocity and corrosion rate. This modeling was started in STAR-CCM+ CFD software and is being continued in Nek5000 for its fast-running and quick turnaround code. This poster explains the basic process of reconstructing the geometry, fluid properties, and heating of test melters in Nek5000. The geometry is imported from a mesh file and boundary conditions assigned based on surface IDs. The fluid properties are set in the .par and .usr case files. The heating of the actual crucibles in joule heating with electrodes but simulated in Nek5000 with a volumetric heat source term. This volumetric heat source is fit to the actual heating profile with piecewise polynomials and exponentials. Basic results and verification methods are explained in the poster, as well as further work that must be done to complete modeling.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Investigation of post-injection strategies for diesel engine Catalyst Heating Operation using a vapor-liquid-equilibrium-based spray model

Most multidimensional engine simulations spend much time solving for non-equilibrium spray dynamics (atomization, collision, vaporization). However, their accuracy is limited by significant grid dependency, and the need for extensive calibration. This is critical for modeling cold-start diesel fuel post injections, which occur at low temperatures and pressures, far from typical model validation ranges. At the same time, resolving micron-scale spray phenomena would render full Eulerian multiphase calculations prohibitive. In this study, an improved phase equilibrium based approach was implemented and assessed for simulating diesel catalyst heating operation strategies. A phase equilibrium solver based on the model by Yue and Reitz [1] was implemented: a fully multiphase CFD solver is employed with an engineering-size engine grid, and fuel injection is modeled using the standard Lagrangian parcels approach. Mass and energy from the liquid parcels are released to the Eulerian multiphase mixture according to an equilibrium-based liquid jet model. An improved phase equilibrium solver was developed to handle large real-gas mixtures such as those from accurate chemical kinetics mechanisms. The liquid-jet model was improved such that momentum transfer to the Eulerian solver better reproduces the physical spray jet structure. Validation of liquid/vapor penetration predictions showed that the model yields accurate results with very limited tuning and low sensitivity to the few calibration constants. In-cylinder simulations of diesel catalyst heating operation strategies showed that capturing spray structure is paramount when short, transient injection pulses and low temperatures are present. Furthermore, the EP model provides improved predictions of post-injection spray structure and ignitability, while conventional spray modeling does not capture the increase of liquid penetration during the expansion stroke. Finally, the only important EP model calibration constant, Cliq, does not affect momentum transfer, but it changes the local charge cooling distribution through the local energy transfer, which makes it candidate to additional research. The results confirm that non-equilibrium spray processes do not need to be resolved in engineering simulations of high-pressure diesel sprays.

42 ENGINEERING↗
DOE OSTI2023

Development and evaluation of a skeletal mechanism for EHN additized gasoline mixtures in large Eddy simulations of HCCI combustion

Advanced Low Temperature Combustion modes, such as the Sandia proposed Additive-Mixing Fuel Injection (AMFI), can unlock significant potential to boost fuel conversion efficiency and ultimately improve the energy conversion of internal combustion engines. This is a novel improved combustion process that is enabled by supplying small (<5%) variable amounts of autoignition improver to the fuel to enhance the engine operation and control. Common, diesel-fuel ignition-quality enhancing additive, 2-ethylexyl nitrate (EHN), is doped into gasoline to enable Sandia LTGC + AMFI combustion. This manuscript focuses on the development of a reduced sub-mechanism for EHN chemical kinetics at engine relevant conditions that is implemented into a skeletal mechanism for chemical kinetic studies of gasoline surrogate fuels. The mechanism validation utilized zero-dimensional numerical simulations and comparison to shock tube ignition-delay data of pure and EHN-doped n-heptane. Additional validation is presented with Homogeneous Charge Compression-Ignition (HCCI) engine data of pure and EHN-doped research-grade E10 gasoline. Then, the mechanism was deployed in a 3-D computational fluid dynamics (CFD) using Large Eddy Simulations (LES) to model the HCCI engine experiments of 0.4% vol EHN additized E10 gasoline at several equivalence ratios. Simulations showed a very good performance of the mechanism, and the model accurately reproduced (a) the ignition point, (b) combustion phasing, (c) combustion duration, and (d) the peak of the heat release rates of the engine experiments. The results show that EHN promotes Low-Temperature Heat Release, ultimately driving the gasoline to autoignite at thermodynamic conditions where the fuel would not otherwise ignite. Overall, this work demonstrates a viable reduced chemical-kinetic mechanism for EHN and shows that it can be combined with a skeletal gasoline mechanism for CFD-LES analysis of well-mixed LTGC that matches well with experimental results. The CFD-LES analysis also shows the spatial distribution of EHN-fuel interactions that control the autoignition throughout the combustion chamber.

Guleria, Gaurav↗
DOE OSTI2024

MFiX Development Updates

This presentation discusses recent developments of the Multiphase Flow with Interphase eXchanges (MFiX) software. A brief review of all modeling approaches along with their cost versus accuracy is provided to guide users when selecting a model for a given application. The main new features of the past five official releases of MFiX are described. Improvement in chemistry management allow for easier simulation setup, and faster simulation speed. Progress in the implementation of a thin-wall boundary condition is presented. The major new model development over the past year is the release of the Glued Sphere Particle model (GSP), where component spheres are combined together to represent non-spherical particles. The integration of Machine Learning (ML) workflow in the CFD process is discussed with two applications: a surrogate model for stiff chemistry and the development of a PIC stress model using ML.

Dietiker, Jeff↗
DOE OSTI2025

Summary of Multiphysics Modeling for Sublimation Mass Transfer

This report summarizes the effort to develop a multiphysics modeling framework for sublimation mass transfer processes. The aim of the project was to develop a multiphysics code capable of predicting phase change between solid and gas in a closed container, and the movement of material within such a container when exposed to various exterior environmental conditions. Two modeling frameworks were developed towards this aim: one with a high-fidelity computational fluid dynamics (CFD) structure, and the other as a fast reduced-order model. Ultimately, both attempts were unsuccessful due to instabilities in the code and physical processes for which there is no adequate numerical representation. Both modeling attempts are briefly detailed before providing a brief survey of recent updates in the literature, and a recommendation for future work on this subject.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Turbulence Modeling with Nek5000/RS, SOD2D and Alya

We present Validation and Verification (V & V) study of two high-order spectral element method (SEM) based Computational Fluid Dyanimcs (CFD) codes that we will utilize for work on turbulence modeling: Nek5000 and SOD2D. While the former solves the incompressible form of Navier-Stokes equation, the latter works with compressible set of equations and uses an entropy-viscosity formulation to account for the discontinuities for high Mach number flows. We demonstrate the accuracy of these codes for two benchmark sub-sonic turbulent flows: periodic channel and pipe flow, by carrying out first and second order statistical analysis, grid convergence and turbulent structure analysis using wall-resolved large eddy simulations (WRLES). Later, we report on the implementation and testing of various wall-modeling strategies for large eddy simulation of turbulent flows in Nek5000. These include both classical log-law based and decision-tree based machine-learning models. Accuracy of these closure strategies are analyzed and necessary future work is outlined.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Potassium carbonate decomposition modeling within rotating detonation engines for direct power extraction applications

We report that recently, there has been a significant interest in detonation-based combustion systems, such as rotating detonation engines (RDE), due to potential performance advantages in propulsion and energy applications. This includes improvements in thermodynamic efficiency, inherently high gas velocities, and the possibility of achieving an increase in total pressure (i.e. pressure gain) through the combustion process. Due to approximating a constant volume combustion process, these devices also tend to exhibit extremely high local gas temperatures relative to a comparable constant pressure combustor. These advantages overlap well with desirable performance characteristics of direct power extraction (DPE) technologies, such as a magnetohydrodynamic (MHD) generator. Typically, in DPE systems hot combustion products are seeded with an easily ionizable material such as potassium carbonate (K 2 CO 3 ) in order to boost the electrical conductivity. However, due to the short gas residence times within an RDE, it was unclear whether forming an electrically conductive combustion plasma would be feasible for integration with a downstream MHD generator. A model is presented which describes the heating, decomposition, and ionization of solid K 2 CO 3 particles and aqueous solutions of K 2 CO 3 in water, for a given initial particle diameter. This model was combined with available computational fluid dynamics (CFD) data for an oxygen-methane RDE in a one-way coupled Eulerian-Lagrangian framework to predict particle trajectories and the corresponding heating, decomposition, and ionization histories. Electrical conductivities were computed using a previously developed model, and a method was proposed to determine an equivalent average electrical conductivity. Results show that particle sizes below ~30 µm are able to fully decompose before reaching the exit of the RDE. While the one-way coupled nature of the simulations precluded rigorous evaluation of the effects of seed material on detonability, a substantial temperature reduction is expected at the detonation wave front due to heating and decomposition. A preliminary comparison is presented between the RDE and an equivalent constant pressure adiabatic combustor, showing a potential performance advantage for the RDE.

42 ENGINEERING↗