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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A physics-driven Σ-Y atomization model for heavy-duty engine simulations

The atomization of a liquid jet is a multi-scale and multi-physics problem of interest for many engineering applications. Particularly, it drives the fuel-oxidizer mixing and dictates the efficiency of combustion engines. High-fidelity multi-phase simulations remain challenging due to the excessive computational cost required to capture all the atomization scales. Thus, atomization models are necessary to represent sub-grid liquid structures. Here, in this work, a modified Σ-Y model in the context of Eulerian-Lagrangian Spray Atomization (ELSA) is used to transport the surface area density of the spray. The model's predictive performance is assessed under various operating conditions relevant to heavy-duty engines using the Engine Combustion Network (ECN) Spray C and Spray D research-grade injectors. The classic droplet collision formulation of the Σ-Y model alone does not replicate the response of the measured spray surface area to changes in injector, ambient pressure, and injection pressure, requiring individual tuning of the model's parameters. Instead, a transition between dense and dilute spray breakup mechanisms is proposed in terms of the average droplet spacing. The collision breakup mechanism represents the dilute spray, whereas the droplet size in the dense spray is driven by a competition between the integral scale of turbulence and the balance between the turbulent kinetic energy and the surface energy of the droplets. Such an approach minimizes the requirements for model tuning. Moreover, the role of the constants of a compressible standard k-ε RANS model is assessed in the injector's internal flow and external spray simulation framework, and an updated set is proposed. The results are validated against x-ray radiography and Ultra-Small Angle X-ray Scattering (USAXS) data and highlight the predictive capabilities of the proposed physics-driven Σ-Y model, which is compatible with engine simulation turnaround times.

42 ENGINEERING↗
DOE OSTI2020

Elucidating the Impact of Flow on Material-Sensitive Critical Heat Flux and Boiling Heat Transfer Coefficients: An Experimental Study with Various Materials

In this work, steady-state internal flow boiling critical heat flux (CHF) experiments were carried out at 10°C inlet subcooling and atmospheric pressure (84 kPa at an altitude of about 5300 feet) with mass flux ranging from 200 to 2,000 kg/m 2 -s on seven tube materials, including the accident-tolerant fuel cladding candidate FeCrAl (C26M) alloy. At a relatively low flow rate, the sensitivity of CHF to different materials was appreciable (the average difference among the tested materials was 19% at 200 kg/m 2 -s). As the absolute CHF differences stayed constant for higher flow rates, the increased flow rate led to reduced relative CHF differences among the tested materials (average relative difference of 15% at 1,000 kg/m 2 -s). FeCrAl alloy claddings that were oxidized under simulated Light Water Reactor (LWR) conditions yielded CHF comparable to as-received FeCrAl alloy cladding, with less than 1.8% difference. Experimental CHF results imply marginal material sensitivity impacts on the departure from nucleate boiling ratio in steady-state nuclear reactor cores. Yet, for accident progression analysis, material sensitivity may hold importance, as boiling behavior variation at low mass flux is appreciable. Macroscopic material parameters (surface wettability, surface roughness, and thermal properties) do not provide a suitable explanation for observed material-sensitive CHFs. Yet, surface roughness and thermal effusivity revealed power and linear relations, respectively, to the nucleate boiling heat transfer coefficients at low mass flux. At high mass flux, material sensitivity on nucleate boiling heat transfer significantly decreased due to the increased shear stress on boiling surface overwhelming material-related boiling implications.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Flow boiling transient critical heat flux tests with stainless steel and FeCrAl: Transient correlation implementation, model calibration, and sensitivity analysis

In this study, steady-state and transient internal-flow critical heat flux (CHF) experiments were carried out under two flow conditions, at atmospheric pressure, on 316 stainless steel (316-SS) and iron-chromium-aluminum (FeCrAl) tubes. Slow power transients at a low mass flow (300 kg/m 2 - s) with very low subcooling (X e =-0.0054) generated premature CHFs, which were prevented by faster power transients and high mass flow (1000 kg/m 2 - s). The measured transient CHFs increased linearly with increasing power transients, compared with the steady-state CHF. Yet, the wall superheat at the CHFs decreased with faster power transients. Transient CHF correlations highlighting heterogeneous spontaneous nucleation were calibrated to the measured CHFs and compared with other existing correlations. Transient CHF multipliers were acquired from pool and flow boiling empirical CHF correlations that were generated. The multipliers were applied to the RELAP5-3D nuclear system code to analyze the discrepancies between the measured data and the predicted CHF and post-CHF behavior, which improved peak cladding temperature predictions by 24.6%. A variance-based global sensitivity study perturbing the experimental uncertainties and cladding material thermal properties showed the diminishing influence of flow boiling heat transfer with increasing power transients, highlighting the significance of the volumetric heat capacity for the cladding integrity during transients. Transient CHF correlations were applied to the most limiting design basis accident: a hot-zero-power reactivity-initiated accident on a generic pressurized water reactor RELAP5-3D model.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Computational Characterization and Boundary Condition Models of a Jet Interaction Fluidic Oscillator

Fluidically oscillating jet actuators that generate sweeping jets when supplied with a pressurized fluid have been used to mitigate separation and reduce drag in a range of flow control applications. Their implementation in future flight vehicles would require fundamental understanding and accurate predictive techniques of the physics of their internal flow and jet formation. The present investigations focus on high-fidelity, time-accurate simulations to characterize the flow physics of the actuator in quiescent conditions. An important element of the present simulations is to demonstrate the ability of the computational fluid dynamics (CFD) solver to predict the jet characteristics and provide a basis for the development of improved boundary conditions (BC) without entirely resolving the geometrical features of the fluidic device. The CFD-predicted oscillation frequencies of the engendered jets were found to be in excellent agreement with experiments, even on two-dimensional meshes. The study revealed that three-dimensional simulations are required to capture some of the flow features of the sweeping jet such as the double peak in time-averaged velocity distributions downstream of the actuator’s orifice that were measured in experiments. Furthermore, several approaches for modeling the actuator were implemented and assessed in quiescent conditions. The evaluation of a boundary condition at the device throat, based on the phase-averaged flow variables, provides the basis for devising surface-based boundary conditions. The influence and necessity of including turbulent characteristics as part of the boundary conditions have also been identified.

42 ENGINEERING↗
DOE OSTI2024

A miniature jet pump for slurries

Here, this work reports on the design and performance of a jet pump system to pump slurries. The jet pump uses a high-velocity water jet to entrain and pump the slurry. This pumping action requires no valves and does not use moving solid parts. Hence, the system can be readily sealed, and the pumping action creates no observable mechanical damage to slurry particles. We tested carbon black beads suspended in water at concentrations of 0.0, 0.2, and 2.0 wt% at primary jet flow rates of 50 and 100 mL/min. Our measurements show an approximately linear decrease in entrainment ratio (slurry-to-jet flow rate) and absolute slurry flow rate with increasing adverse (load) pressure difference. The entrainment ratio is a strong function of the absolute jet flow rate. Pump performance was insensitive to slurry composition. Micron-resolution particle image velocimetry (micro-PIV) revealed qualitative changes in the pump’s internal flow due to changes in absolute jet flow rate, including evidence of the suppression of a vortex at higher flow rates. These findings establish key operational parameters for the jet pump and highlight its potential in a variety of slurry flow pumping applications. The pump is particularly suited for flow electrode slurries (e.g. as used for energy storage and water treatment) as it maintains particle integrity and can be used with standard tubing, tube fittings, and sealing methods.

42 ENGINEERING↗
DOE OSTI2025

FreeMHD: Validation and verification of the open-source, multi-domain, multi-phase solver for electrically conductive flows

The extreme heat fluxes in the divertor region of tokamaks may require an alternative to solid plasma-facing components, for the extraction of heat and the protection of the surrounding walls. Flowing liquid metals are proposed as an alternative, but raise additional challenges that require investigation and numerical simulations. Free surface designs are desirable for plasma-facing components, but steady flow profiles and surface stability must be ensured to limit undesirable interactions with the plasma. Previous studies have mainly used steady-state, 2D, or simplified models for internal flows and have not been able to adequately model free-surface liquid metal (LM) experiments. Therefore, FreeMHD has been recently developed as an open-source magnetohydrodynamics (MHD) solver for free-surface electrically conductive flows subject to a strong external magnetic field. The FreeMHD solver computes incompressible free-surface flows with multi-region coupling for the investigation of MHD phenomena involving fluid and solid domains. The model utilizes the finite-volume OpenFOAM framework under the low magnetic Reynolds number approximation. FreeMHD is validated using analytical solutions for the velocity profiles of closed channel flows with various Hartmann numbers and wall conductance ratios. Next, experimental measurements are then used to verify FreeMHD, through a series of cases involving dam breaking, 3D magnetic fields, and free-surface LM flows. These results demonstrate that FreeMHD is a reliable tool for the design of LM systems under free surface conditions at the reactor scale. Furthermore, it is flexible, computationally inexpensive, and can be used to solve fully 3D transient MHD flows.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Reynolds stress tensor measurements using magnetic resonance velocimetry: expansion of the dynamic measurement range and analysis of systematic measurement errors

This study presents magnetic resonance velocimetry (MRV) Reynolds Stress measurements in a periodic hill channel with a hill Reynolds number of Re = 29,500. The velocity encoding scheme is based on the ICOSA6 method with six icosahedral encoding directions and multiple encoding values are measured to increase the dynamic range. The full Reynolds stress tensor is obtained from a voxel-wise three-dimensional Gaussian fit using the magnitude data of all acquisitions. The MRV results are compared to a wall-resolved large eddy simulation and laser Doppler velocimetry measurements conducted in the same channel. It is shown that the MRV Reynolds stress data have excellent precision and agree qualitatively with the reference data. However, there are apparent systematic deviations. One of the most prominent error contributions is the signal attenuation caused by higher orders of motion, which leads to an overestimation of the turbulence level. Another fundamental error is identified in the assumption that the turbulence is Gaussian distributed. With the presented reconstruction technique, the MRV data are fitted to a statistical model, and depending on the examined flow setup, the Gaussian model can lead to considerable errors. Possible ways of how to reduce all identified errors are presented. In summary, this technique enables Reynolds stress tensor measurements in complex internal flows with high dynamic range and excellent precision. However, several issues need to be resolved to make the turbulence quantification more accurate.

42 ENGINEERING↗
DOE OSTI2022

On the effect of mixing-driven vaporization in a homogeneous relaxation modeling framework

The homogeneous relaxation model (HRM) is one of the most widely used models to describe the liquid–gas phase transition in multiphase flows due to the occurrence of cavitation. However, in its original formulation, the HRM does not account for the presence of ambient gas species, which generally limits its applicability to the injector's internal flow where ambient gases are negligible. In this work, a mixing-driven vaporization (MDV) model was developed to extend the capability of the HRM in handling the mixing effect in the regions external to the nozzle, where vapor–liquid equilibrium for multi-species mixtures of fuel and ambient gas is considered. Herein, to assess the model performance, simulations of the Engine Combustion Network's Spray G injector were performed with the HRM and the MDV model under both flash-boiling and evaporating conditions. It was found that the MDV model led to a better match against x-ray measurements of fuel density in the near-nozzle region. In contrast to the HRM, the MDV model was able to reproduce the vaporization process in the mixing zone at the edge of the fuel jet, which aligns with the expected physics. This resulted in substantial differences in the prediction of other flow characteristics such as mixture temperature and pressure. Furthermore, this work demonstrates that evaporation timescales have a considerable effect on the MDV model's predictions, as shown by a parametric study in which a time factor was introduced to mimic the effect of different timescales due to different phase change mechanisms.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Data-Driven Model Reduction of Multiphase Flow in a Single-Hole Automotive Injector

Fuel injector design has a substantial influence on the performance and emissions of direct injection engines. To date, large eddy simulations coupled with a single-fluidmixture modeling approach have shown great success in evaluating the complex interplay among injector design, fuel properties, and operating conditions on the injector performance. However, this simulation approach is too computationally expensive to be used by industry routinely for injector design due to the fine temporal and spatial resolution required to resolve wall-bounded flow within the injector. The work presented in this paper highlights a potential pathway to addressing this issue. To study the influence of injector design, fuel properties, and operating conditions on injector performance, large eddy simulations were performed to model the turbulent multiphase flow development through a side-oriented singlehole diesel injector. Using Latin hypercube sampling, the design space spanning a range of fuel properties, operating conditions, and needle lifts were explored. Two techniques for dimensionality reduction, namely proper orthogonal decomposition and autoencoders, were compared to evaluate their accuracy in representing the flow in a reduced dimensional space. Finally, based on the findings from this work, recommendations are provided in using machine learning approaches within the context of emulation to construct reduced-ordermodels for internal flow development relevant to automotive applications.

42 ENGINEERING↗
DOE OSTI2022

System and method for engineered ceramic packages for use in fluid treatment technologies

The present disclosure relates to a fluid modification system having a container structure and a plurality of independent, ceramic elements. The ceramic elements may be arranged in random orientations and contained in the container structure, thus causing a fluid flow entering the container structure at any given cross-section location to flow over the surfaces of a first subplurality of the ceramic elements, and through the porous walls of a second subplurality of the ceramic elements, before exiting at a second location of the container structure. Each one of the ceramic elements has at least one of a nanofibrous or nanoporous microstructure to enable internal flow both through a wall structure thereof, and over and around the wall structure to affect performance.

Kelly, James Patrick↗
DOE OSTI2020

Controlled 3D nanoparticle deposition by drying of colloidal suspension in designed thin micro-porous architectures

Nanoparticle deposition by drying of colloidal suspension in thin micro-porous architectures has attracted a lot of attention in scientific research as well as industrial applications. However, the underlying mechanisms of such three-dimensional (3D) deposition are not yet fully revealed due to the complexity of the co-occurring processes of two-phase fluid flows, phase change and mass transport. Consequently, the control of 3D nanoparticle deposition remains a challenge. We use a combined experimental and numerical approach to achieve controlled 3D nanoparticle deposition by drying of colloidal suspension in two pillar-based thin micro-porous architectures. By the design of pillar layout, rectangular-spiral and circular-spiral deposition configurations are obtained globally. By varying the surface wettability, vertically symmetric and sloped nanoparticle depositions can be achieved locally. While the numerical modeling reveals the mechanisms of liquid internal flow, as well as the impact of local drying rate on nanoparticle transport, accumulation and final deposition, the experimental results of deposition configurations validate the controlling strategies. This combined experimental and numerical work provides a framework to achieve desired 3D nanoparticle deposition in thin micro-porous architectures, with a thorough understanding of the underlying mechanisms of two-phase fluid flows, phase change and mass transport.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Inertially enhanced mass transport using 3D-printed porous flow-through electrodes with periodic lattice structures

Significance The efficient utilization of electrical energy is an increasingly important challenge, especially as renewable energy sources become cheaper and demand increases. Electrochemical reactors utilizing flow-through electrodes (FTEs) provide an attractive path toward the efficient utilization of electrical energy. Their commercial viability and ultimate adoption hinge on attaining high current densities to drive cost competitiveness. There are limited opportunities for engineering FTE materials, as these are often random, disordered media. Alternatively, three-dimensional (3D)–printed FTEs provide the opportunity to quickly explore the impact of engineered electrode architectures on device performance. We demonstrate that 3D-printed FTEs have the potential to exceed the performance of conventional materials by using the expanded design freedom to engineer the internal flow.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2024

Quantitative near-field water–air spray measurements at elevated pressures by neutron radiography imaging

Extensive experimental research on high-pressure spray has been conducted for decades to deepen our understanding and optimize its use in transportation, aviation, and propulsion applications; however, the near-field and in-nozzle flow characteristics are not fully understood. Dense near-field spray is among the most challenging diagnostic tasks since light is severely scattered and diffused by the liquid droplets and columns. In this work, the near-field spray and in-nozzle flow characteristics of an aeration nozzle at elevated pressures were characterized by neutron radiography imaging at the Oak Ridge National Laboratory High Flux Isotope Reactor. Neutron imaging benefits via strong penetration depths for some metals (i.e., aluminum, lead, and steel) and is sufficiently sensitive to detection of light elements, especially for hydrogen-based molecules, due to the large incoherent scattering cross section of neutrons. Both two-dimensional snapshots of the near-field spray and a three-dimensional tomographic scan of the nozzle geometry and in-nozzle water were obtained. This work provides new quantitative characterization of practical metal nozzle geometry for accurate boundary conditions, internal flow patterns inside the nozzle, and high-pressure spray flows. In conclusion, the findings may be used to improve performance and operating conditions of transportation vehicles and propulsion systems.

42 ENGINEERING↗
DOE OSTI2025

Active-noise-induced dynamic clustering of passive colloidal particles

Active fluids generate spontaneous, often chaotic mesoscale flows. Harnessing these flows to drive soft materials embedded within an active fluid into structures with controlled length scales and lifetimes is a key challenge at the interface between the fields of active matter and nonequilibrium self-assembly. Here, we present a simple and efficient computational approach to model soft materials advected by active fluids, by simulating particles moving in a spatiotemporally correlated noise field. To illustrate our approach, we simulate the dynamical self-organization of repulsive colloids within such an active noise field. The colloids form structures whose sizes and dynamics can be tuned by the correlation time and length of the active fluid, and range from small rotating droplets to clusters with internal flows and system-spanning sizes that vastly exceed the active correlation length. Our results explain how the interplay between active fluid time and length scales and emergent driven assembly can be used to rationally design functional assemblies. More broadly, our approach can be used to efficiently simulate diverse active fluids and other systems with spatiotemporally correlated noise.

Brownian dynamics↗
DOE OSTI2025

An attention-based neural ordinary differential equation framework for modeling inelastic processes

To preserve strictly conservative behavior as well as model the variety of dissipative behavior displayed by solid materials, we propose a significant enhancement to the internal state variable-neural ordinary differential equation (ISV-NODE) framework. In this data-driven, physics-constrained modeling framework internal states are inferred rather than prescribed. The ISV-NODE consists of: (a) a stress model dependent on observable deformation and inferred internal state, and (b) a model of the evolution of the internal states. The enhancements to ISV-NODE proposed in this work are multifold: (a) a partially input convex neural network stress potential provides polyconvexity in terms of observed strain while leaving the inferred state unconstrained, and (b) an internal state flow model uses common latent features to inform novel attention-based gating and drives the flow of internal state only in dissipative regimes. We demonstrated that this architecture can accurately model dissipative and conservative behavior across an isotropic, isothermal elastic-viscoelastic-elastoplastic spectrum with three exemplars, while maintaining fundamental principles by design.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Wire-coil insert optimization for high-heat-load/flux synchrotron components

Many synchrotron components require high levels of internal-flow, forced-convection heat transfer to minimize surface temperatures, thermal gradients, and thermally induced stress on high-power beam-interacting surfaces. Wire-coil inserts, physically similar to a common spring, are mechanically fitted inside of component cooling passages to optimize heat transfer performance. They are routinely used in Advanced Photon Source (APS) front end and beamline high-heat-load/flux components to significantly enhance convection heat transfer-up to 400% compared to plain open passages. This has the additional benefit of greatly reducing coolant flow requirements for these components. Using several cooling passage sizes, five different wire sizes, and a range of pitch values, an experimental investigation conducted at the APS has determined the average heat transfer coefficient and resulting pressure loss as a function of water flow rate for 65 different wire-coil inserts. Data from this study have been non-dimensionalized and generalized to yield relationships that can be used to determine the heat transfer performance and resulting pressure loss for any given wire-coil insert that may be used at the APS. Through data reduction, the wire-coil insert characteristic dimensions have also been optimized to yield the highest heat transfer enhancement while minimizing the coolant flow requirements. These generalized expressions for wirecoil inserts will be presented, and they can be used by scientists and engineers during the component design process to evaluate achievable heat transfer performance and associated pressure loss, aiding in the establishment of optimized operating parameters and cooling passage flow distribution schemes.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Effects of detailed geometry and real fluid thermodynamics on Spray G atomization

We present recent results toward the quantification of spray characteristics at engine conditions for an eight-hole counter-bored (stepped) GDI injector-Spray G in the ECN denomination. This computational study is characterized by two novel features: the detailed description of a real injector's internal surfaces via tomographic reconstruction; and a general equation of state that represents the thermodynamic properties of homogeneous liquid-vapor mixtures. The combined level-set moment-of-fluid approach, coupled to an embedded boundary formulation for moving solid walls, makes it possible to seamlessly connect the injector's internal flow to the spray. The Large Eddy Simulation (LES) discussed here presents evidence of partial hydraulic flipping and, during the closing transient, string cavitation. Results are validated by measurements of spray density profiles and droplet size distribution.

42 ENGINEERING↗
DOE OSTI2023

Convolutional Neural Network–Aided Temperature Field Reconstruction: An Innovative Method for Advanced Reactor Monitoring

In this study, the capabilities of a physics-informed convolutional neural network (CNN) for reconstructing the temperature field from a limited set of measurements taken at the boundaries of internal flows are demonstrated. Such an approach enables the development of less invasive monitoring methods for real-time plant diagnostics. As a test case, a Molten Salt Fast Reactor (MSFR) design was selected. This circulating fuel reactor has received interest from both scientific and industrial communities due to its intrinsic safety and sustainability. Molten salt flows in such reactors, however, can present highly localized temperature peaks that can induce significant thermal stresses onto the vessel walls. At these local maxima, the salt temperature may exceed a thousand kelvins, which makes a direct measurement challenging or even unfeasible. The proposed CNN algorithm allows one to detect indirectly such discontinuities through an accurate, albeit indirect, temperature measurement method during reactor operation. The datasets employed to train and test the machine learning models in the present work were generated with Nek5000, a computational fluid dynamics (CFD) code developed at Argonne National Laboratory. The CNN algorithm is trained with CFD results that span a set of MSFR operational power and flow ranges. Here, to demonstrate the efficacy of the algorithm, predictions are made for test cases contained within the training range but for which the CFD data were not used when training. Results demonstrate that the proposed technique properly characterizes temperature peaks and distributions within the domain for a broad range of scenarios.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗