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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

An interface-aware sub-scale dynamics multi-material cell model for solids with void closure and opening at all speeds

Here, we present a multi-material cell model (closure model) for demanding arbitrary Lagrangian-Eulerian (ALE) simulations of fluids and solids. It is based on the interface-aware sub-scale dynamics (IASSD) approach which utilizes the exact material interface geometry within the computational cell to calculate internal material interactions. Our formulation of the closure model also aims to improve the accuracy in low-speed impact events. Voids are used to represent ambient vacuum and internal free boundaries of the distinct materials. Void regions can close and open at contact surfaces, allowing a transition from contact physics to free motion in vacuum. The coupling of void closure and opening with a new formulation of the IASSD model for solids is tested on several one- and two-dimensional numerical examples, ranging from gas expansion in vacuum to planar and round object impacts at various speeds.

42 ENGINEERING↗
DOE OSTI2024

DECOVALEX-2023: Task B Final Report

In all repository concepts for the geological disposal of radioactive waste, an engineered barrier system (EBS) is used to encapsulate the waste canister, or, to act as borehole or gallery seals. These systems are often based on bentonite clays due to their low permeability and high swelling capacity enabling the closure of engineering voids. However, in all repository concepts gases will be generated through the corrosion of metallic materials (under anoxic conditions), the radioactive decay of waste and the radiolysis of water. Thus, understanding the processes and mechanisms controlling the advective movement of gas (as a discrete phase) in clay-based materials is a key aspect when assessing the impact of gas flow in a repository safety case.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Improvements to CTF Closure Models for Modelling of Two-Phase Flow

This report documents the efforts to improve the CTF prediction of void fraction and two-phase pressure drop by improving two-phase closure models. Previous validation activities have revealed that CTF tends to overpredict void fraction and two-phase pressure drop. In response to this, two approaches were taken to improve CTF’s predictive capabilities. Based on findings that the interfacial drag and subcooled boiling models significantly impact void prediction, alternative closure models for these physical effects were found and implemented into the code. An extensive assessment was performed by using the existing and newly added two-phase experimental data, which showed that void prediction, wall temperature, and two-phase pressure-drop results are improved by using the newly implemented models. A second approach for improving CTF modeling accuracy involved the use of a Bayesian calibration process that uses CTF validation data to optimize selected modeling coefficients and closure model multipliers to achieve a more accurate prediction of experimental results. A similar assessment was performed with calibrated models that improved the void and pressure-drop prediction for test cases that were both included and not included in the calibration dataset. Results of this study will be used to change the models used in CTF to achieve more accurate BWR analyses moving forward. This study also identified opportunities for improving additional closure models and other opportunities to use calibration techniques to improve CTF.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Bipolar Membranes with an Electrospun 3D Junction

Freestanding bipolar membranes (BPMs) with an entirely new and transformative morphology were fabricated and characterized. The key disruptive design element was a water-splitting/water-generation junction layer of finite thickness composed of interwoven and interlocking electrospun anion-exchange polymer (AEP) fibers and cation-exchange polymer (CEP) fibers. Methods were developed to sandwich the 3D junction layer between two pre-formed dense AEP and CEP films., with the closure of all interfiber voids, where the processing steps are easily incorporated into a commercial roll-to-roll membrane manufacturing scheme. A series of membranes were made using different polymers and junction layers to identify the optimum morphology and composition for water-splitting and water-generation applications. For water splitting, the 3D junction BPMs worked remarkably well with operating current densities at/above 1.0 A/cm2 (10X greater than commercial BPMs) at a transmembrane voltage drop of only 1.1 V. In water generation mode, the 3D junction BPMs operated at 0.5 A/cm2, a world-record current density. The membranes were found to exhibit outstanding durability and can be manufactured at scale for low cost. The high operating current densities and stable long-term operation are due to the 3D junction layer design, where there is a high interfacial area for water splitting or water generation reactions and where the interlocking fibers prevent delamination of the outer films. These new BPMs are ideal candidate materials for both existing water-splitting electrodialysis separations and new electrochemical processes, such as large-scale direct air capture of CO 2 , reactors for CO 2 reduction, self-hydrating fuel cells, and redox flow batteries.

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2021

Computational Fluid Dynamics (CFD) Simulations of Taylor Bubbles in Vertical and Inclined Pipes with Upward and Downward Liquid Flow

Summary Two-phase flow is a common occurrence in pipes of oil and gas developments. Current predictive tools are based on the mechanistic two-fluid model, which requires the use of closure relations to predict integral flow parameters such as liquid holdup (or void fraction) and pressure gradient. However, these closure relations carry the highest uncertainties in the model. In particular, significant discrepancies have been found between experimental data and closure relations for the Taylor bubble velocity in slug flow, which has been determined to strongly affect the mechanistic model predictions (Lizarraga-García 2016). In this work, we study the behavior of Taylor bubbles in vertical and inclined pipes with upward and downward flow using a validated 3D computational fluid dynamics (CFD) approach with level set method implemented in a commercial code. A total of 56 cases are simulated, covering a wide range of fluid properties, pipe diameters, and inclination angles: Eo ∈ [10, 700]; Mo ∈ [1×10–6, 5×103]; ReSL ∈ [–40, 10]; θ ∈ [5°, 90°]. For bubbles in vertical upward flows, the simulated distribution parameter, C0, is successfully compared with an existing model. However, the C0 values of downward and inclined slug flows where the bubble becomes asymmetric are shown to be significantly different from their respective vertical upward flow values, and no current model exists for the fluids simulated here. The main contributions of this work are (1) the relatively large 3D numerical database generated for this type of flow, (2) the study of the asymmetric nature of inclined and some vertical downward slug flows, and (3) the analysis of its impact on the distribution parameter, C0.

Engineering↗
DOE OSTI2020

Probing interfacial momentum closures in two-phase bubbly flow with machine learning-aided methods

Computational fluid dynamics (CFD) approach has already reached a high level of maturity for single-phase flows, however the development of closure models for two-phase flow requires additional attention. Multiphase CFD (M-CFD) methods resolve the conservation equations for mass, momentum and energy while differing in the approaches and strategies adopted in the physical closure models. The most widely adopted framework for M-CFD is the Eulerian-Eulerian two-fluid approach which assumes that all phases are co-existing inside each computational cell. For each fluid, the full set of conservation equations is solved; therefore, each fluid has a different velocity field. For adiabatic two-phase flow, the mechanisms of the interfacial momentum transfer are modeled by the interfacial forces representing different physical mechanisms. One of the crucial issues in the development and application of two-fluid model is the understanding of the interfacial momentum closures which determines the bubble distribution and migration behaviors. Dedicated experiments are performed to support the physical understanding and drive the closures’ development. However, limitations exist due to the uncertainties in the experimental measurement and the simplified analytical assumptions which have difficulties on representing the complex non-linear flow fields. In this paper, a data-driven approach, Feature Similarity Measurement (FSM), is developed and proposed to resolve the challenges of modeling the interfacial forces closures. Case study is performed with two-phase flow scenarios where the high-fidelity experimental data is available. Within the Eulerian-Eulerian two-fluid framework, only momentum equations for gas and liquid phases are solved and reduced-order interfacial momentum closures are aided with FSM. Predictions of void fraction and velocity fields are analyzed and demonstrate the potential of machine learning-driven interfacial forces closures.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

ANTS

The ANTS code (Alternate Non-Linear Two-phase Solver) is based on a novel non-linear solution algorithm for the solution of the two-phase, subchannel fluid equations. It achieves its performance through decoupling of the two-phase momentum equations (axial and transverse) from the axial phasic mass and energy equations which allows for a nested non-linear iteration scheme. This enables a plane-by-plane solution which the inner iteration focuses on a reduced non-linear equation set for the primitives in phasic mass flow rate, enthalpy and void for each node edge. Single node edges are coupled as part of the outer iteration via surface mass fluxes which appear as source terms in the inner iteration scheme. The outer iteration readily accommodates two-phase flow phenomena closure relationships for subchannel mixing and void drift. A primary feature is the use of a non-staggered mesh computational mesh and steady-state iterative solver in contrast to all existing subchannel codes.

Kropaczek, David J↗
DOE OSTI2022

CTF Improved Drag Model and Flow Regime Transition Criteria

The demand for accurate prediction of two-phase flow behavior in a boiling water reactor (BWR) requires a comprehensive understanding of flow regime, void fraction, heat transfer, and pressure drop. The CTF subchannel code, which is used for the Thermal/Hydraulic (T/H) solution in the Consortium for Advanced Simulation of Light Water Reactors (CASL)-developed Virtual Environment for Reactor Application (VERA) core simulator, is being further developed for BWR applications. In support of this goal, the present work highlights some of the two-phase closure model developments towards improving the CTF void fraction prediction, especially for subcooled boiling. The drift-flux approach has been well-developed for upward dispersed two-phase flows and proven to be accurate in predicting void fraction in bubbly and slug flow regimes. In this work, these kinematic constitutive relations for the drift-flux velocity have been implemented into CTF to describe the interfacial drag of bubbly flow as an alternative to the existing model for better void fraction prediction. The success of these constitutive relations also relies on a good flow regime map that accounts for flow conditions and channel geometry. A more reliable flow regime transition criteria that account for the flow condition has also been implemented in this study for modeling the flow regime transition criteria. The newly implemented models are shown to give improved void fraction predictions in comparison to experimental data.

Hizoum, Belgacem↗
DOE OSTI2023

Continued Development and Advanced Testing of DPC Filler Cements (on FY22 R&D and Demonstration Activities) (Progress Report)

Commercial generation of energy by nuclear power plants in the United States (U.S.) has produced thousands of metric tons of spent nuclear fuel (SNF), the disposal of which is the responsibility of the U.S. Department of Energy (DOE). Utilities typically utilize the practice of storing this SNF in dual-purpose canisters (DPCs). DPCs were designed, licensed, and loaded to meet Nuclear Regulatory Commission (NRC) requirements that preclude the possibility of a criticality event during SNF storage and transport, but were not designed or loaded to preclude the possibility of a criticality event during the regulated post-closure period following disposal, which could be up to 1,000,000 years (Price, 2019). There are several options being investigated that could facilitate the disposal of SNF stored in DPCs in a geologic repository (Hardin et al., 2015; SNL 2020b; SNL 2021b). These include: (1) repackage the SNF into canisters that are designed to prevent criticality during the regulated post-closure period following disposal, but with an increased disposal cost estimated at approximately $\$$20B in United States dollars (USD) (Freeze et al., 2019); (2) analysis of the probability and consequences of criticality from the direct disposal of DPCs during a 1,000,000-year post-closure period in several geologic disposal media (Price, 2019); and (3) filling the void space of a DPC with a material before its disposal that significantly limits the potential for criticality over the post-closure regulatory period. This report further investigates the third option, filling DPC already containing SNF with a material to limit the potential for criticality over the post-closure regulatory period.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Development of machine learning framework for interface force closures based on bubble tracking data

Interfacial force closures in the two-fluid model play a critical role for the predictive capabilities of void fraction distribution. However, the practices of interfacial force modeling have long been challenged by the inherent physical complexity of the two-phase flows. The rapidly expanding computational capabilities in the recent years have made high-fidelity data from the interface-captured direct numerical simulation become more available, and hence potential for data-driven interfacial force modeling has prevailed. In this work, we established a data-driven modeling framework integrated to the HZDR multiphase Eulerian-Eulerian framework for computational fluid dynamics simulations. The data-driven framework is verified in a benchmark problem, where a feedforward neural network managed to capture the non-linear mapping between bubble Reynolds number and drag coefficient and reproduce the void distribution resulting from the baseline model in the test case. The second focus is on utilizing the bubble tracking data set to form a closure for the bubble drag in the turbulent bubbly flow, in which the drag coefficient is set to be correlated with the bubble Reynolds number and the Eötvös number. Pseudo-steady state filtering in the Frenet Frame was carried out to obtain the drag coefficient from the turbulent bubbly flow data. The performance of the data-driven drag model is also examined through a case study, where improvement of model’s prediction near-wall is regarded necessary. In conclusion, discussion and further plans of investigation are provided.

42 ENGINEERING↗
DOE OSTI2026

Geologic stress modulates fluid mixing at fracture intersections

Fracture intersections are critical links that enable flow and transport in subsurface fracture networks, and their behavior strongly influences fluid mixing in a network. Although all subsurface fractures are subjected to geological stress, we lack a fundamental understanding of how fracture intersection geometry evolves under stress and how these changes influence fluid mixing. Here, we combine 3D printing, 3D X-ray tomographic imaging, and 3D pore-scale numerical simulations to reveal stress-induced changes in intersection geometry and their impact on mixing. Mixing is found to be strongly affected by partial closure of an intersection under stress. As an intersection closes, the void area for fluid flow and diffusion decreases leading to substantial deviations between conventional mixing models and full pore-scale modeling. To address this, we propose a modified mixing model that accounts for intersection deformation, which is essential for accurate modeling of solute transport and mixing through fracture networks.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Progress Toward Simulating Departure from Nucleate Boiling at High-Pressure Applications with Selected Wall Boiling Closures

Recently, a Eulerian-based two-fluid computational fluid dynamics (CFD) framework with a wall heat flux partitioning approach has been intensively investigated for departure from nucleate boiling (DNB) simulation under the U.S. Department of Energy–funded Consortium for Advanced Simulation of Light Water Reactors (CASL) program. Understanding of the DNB characteristics over a range of pressurized water reactor–like operating conditions and accurate prediction of boiling crisis in the nuclear power system have been grand challenges because of the large impact of DNB on reactor safety and operational economics. The ultimate goal of this task in the CASL program is to introduce a robust multiphase CFD–based DNB modeling framework that is capable of characterizing an entire boiling history in which the wall boiling mode experiences the following through multiple stages of heat transfer mode: (1) single-phase convective heat transfer, (2) nucleate boiling heat transfer, and (3) identification of the departure of nucleate boiling. To validate the CASL boiling model, we have benchmarked simulated DNB over three different flow channel configurations (pipe flow, 5 × 5 fuel bundle with mixing vane tests, and 5 × 5 fuel bundle without mixing vane tests) against experimental measurements, and the validation result with open literature is reported. The DNB detection criteria in the simulation are checked by monitoring the peak wall temperature, wall dryout factor, and net energy balance. In addition to the DNB performance test, some preliminary sensitivity results on closure model selection are reported to address the prediction capability of local void profile against measurements. The boiling simulation tested in this study exhibits a maximum deviation of 24% from the measured DNB value in a high-pressure (i.e., 138 bars) subcooled pipe flow test. The ranges of operating conditions are as follows: 1650 to 2650 kg/m 2 ·s for mass flux and 8.5 to 96 K for subcooled inlet temperature. The deviation is even reduced to 7% when the subcooled temperature is less than 40 K. Besides accuracy, base practice guidelines for DNB detection criteria are tested by monitoring three simulation variables: (1) maximum wall temperature, (2) wall dryout factor (i.e., K-value), and (3) energy balance. Numerical robustness of DNB simulation is largely achieved in most of the validation test except for a few high subcooled test cases.

42 ENGINEERING↗
DOE OSTI2026

040226_AnnularFuel_FuelPerformance_LRSv2

This slide deck summarizes a comparative fuel performance assessment of four annular fuel concepts for pressurized water reactor applications against a reference 17×17 fuel design. Overall, annular fuel geometry improves several key thermal-mechanical performance metrics, with the large-annulus configuration providing the most favorable balance of benefits. Relative to the reference design, annular fuel reduces peak fuel temperature by lowering thermal resistance through a thinner fuel pellet and smaller heat-conduction path. At the same time, the reduced fuel volume raises local burnup and correspondingly increases fission gas release. Despite this, rod internal pressure at end of life decreases because the annular geometry provides greater internal void volume. Annular designs also tend to delay fuel-cladding gap closure, although this advantage diminishes in thin-gap configurations where the smaller initial gap accelerates closure. Similarly, hoop stress and hoop strain are generally reduced for annular fuel, but both increase as the initial gap becomes smaller, indicating a potential cladding integrity concern for thin-gap designs. Corrosion performance shows no meaningful variation among the concepts considered. Taken together, the results indicate that annular fuel can offer significant performance advantages in a PWR environment, with large-annulus designs emerging as the strongest candidate while thin-gap geometries introduce more challenging mechanical margins.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Assessment of Measurement Uncertainties in the Jupiter High-240 Experiment

The Jupiter High-240 experiment performed in May of 2019 was previously discussed as a variant of the original Jupiter experiment incorporating plutonium metal alloy fuel plates with higher 240Pu content and lead plates, using both a reference configuration and a second configuration where eight lead plates were replaced with aluminum to simulate voiding. Measurements were recorded for experiment period, the “pressure” of the Comet ram upon closure for each near-critical measurement, and temperature. The experiment reactor period is the time it would take to increase the neutron population by a factor of e. For this experiment, the copper reflectors and upper third of the fuel sits upon a support structure with the lower fuel arrays raised up into the center of the reflectors using a ram (see Fig. 1). The recorded logbook temperature for each measurement corresponds to a resistance temperature detector (RTD) located at the top center of the upper fuel array. This paper summarizes the evaluated uncertainties for the Jupiter High 240 experiment as contributed via the recorded measurements and nuclear data and their assessed impact upon the computation of system reactivity and eigenvalue.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Uncertainty quantification for Multiphase-CFD simulations of bubbly flows: a machine learning-based Bayesian approach supported by high-resolution experiments

In this paper, we developed a machine learning-based Bayesian approach to inversely quantify and reduce the uncertainties of multiphase computational fluid dynamics (MCFD) simulations for bubbly flows. The proposed approach is supported by high-resolution two-phase flow measurements, including those by double-sensor conductivity probes, high-speed imaging, and particle image velocimetry. Local distributions of key physical quantities of interest (QoIs), including the void fraction and phasic velocities, are obtained to support the Bayesian inference. In the process, the epistemic uncertainties of the closure relations are inversely quantified while the aleatory uncertainties from stochastic fluctuations of the system are evaluated based on experimental uncertainty analysis. The combined uncertainties are then propagated through the MCFD solver to obtain uncertainties of the QoIs, based on which probability-boxes are constructed for validation. The proposed approach relies on three machine learning methods: feedforward neural networks and principal component analysis for surrogate modeling, and Gaussian processes for model form uncertainty modeling. The whole process is implemented within the framework of an open-source deep learning library PyTorch with graphics processing unit (GPU) acceleration, thus ensuring the efficiency of the computation. The results demonstrate that with the support of high-resolution data, the uncertainties of MCFD simulations can be significantly reduced. The proposed approach has the potential for other applications that involve numerical models with empirical parameters.

42 ENGINEERING↗
DOE OSTI2022

Improvement of two-phase closure models in CTF using Bayesian inference

Under the Consortium for Advanced Simulation of Light Water Reactors (CASL) program, extensive capabilities have been developed in CTF to analyze light-water reactors (LWRs) for normal operating conditions, departure from nucleate boiling (DNB), and system transients. However, further improvements are required in the modeling and simulation of boiling water reactors (BWRs), which is a focus of the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program. In this work, CTF validation results were used to optimize selected modeling coefficients by calibrating to experimental data using a Bayesian inference approach. Here, calibration studies were conducted to improve (vapor) void fraction prediction without worsening the two-phase pressure drop prediction, as well as to improve the two-phase pressure drop prediction. Calibration was performed for interfacial drag and wall shear models. Surrogates were developed to alleviate the computational expense required for sampling the parameter space using Markov chain Monte Carlo (MCMC). An assessment performed with calibrated models demonstrated an improvement of CTF in its prediction of key parameters such as void fraction and two-phase pressure drop.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

The role of micro-inertia on the shock structure in porous metals

The behavior of porous materials under shock loading is a multi-scale problem bridging orders of magnitude across the macroscale geometry and the microscale pores. Under static loading, this problem is well understood, relating mechanisms of pore closure and crushing to the equivalent macroscale models. The dynamic response of porous solids under shock loading is related to the effects of viscoplasticity and micro-acceleration fields around the void boundaries. The significance of the micro-inertia effects in modeling the dynamic behavior of porous materials remains an open question. In this work, an experimental investigation on closed-cell porous aluminum with small porosity provides the evidence for the first time of micro-inertia’s fundamental role in describing the shock structure in these materials. Materials with different levels of porosity were manufactured using a modified process of additive manufacturing to achieve a mean pore size below 50$\mu$m. Plate impact experiments on porous aluminum samples were conducted at pressures in the range of 2 to 11 GPa. The structure of the steady shock was characterized as a function of porosity and shown to validate behavior revealed by an analytical approach (Czarnota et al. [J. Mech. Phys. Solids 107 (2017)]), highlighting the fundamental role of micro-inertia effects in such cases.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Interface capturing simulations of bubble population effects in PWR subchannels

As the computational power of high-performance computing (HPC) facilities grows, so too does the feasibility of using first principle based simulation to study turbulent two-phase flows within complex pressurized water reactor (PWR) geometries. Direct numerical simulation (DNS), integrated with an interface capturing method, allows for the collection of high-fidelity numerical data using advanced analysis techniques. The research presented here employs the massively parallel, finite-element based, unstructured mesh code, PHASTA, to simulate a set of two-phase bubbly flows through PWR subchannel geometries including auxiliary structures (spacer grids and mixing vanes). The main objective of the presented work is to analyze bubble dynamics and turbulence interactions at varying bubble concentrations to support the development of advanced two-phase flow closure models. Turbulent two-phase flows in PWR subchannels were simulated at hydraulic Reynolds numbers of 81,000 with bubble concentrations of 3%–15% by gas volume fraction (768–3928 resolved bubbles, respectively) and compared against a 1% void fraction case (262 bubbles) that had been previously simulated. The finite element mesh utilized for the study at higher bubble concentrations was composed of 1.55 billion elements, compared to the previous study which employed 1.11 billion elements, ensuring all turbulence scales and individual bubbles within the flow are fully resolved. For each case, the resolved initial bubble size was 0.65 mm in diameter (resolved with 25 grid points across the diameter). The simulations were analyzed to find flow features such as the mean velocity profile, bubble relative velocity and the effect of the bubbles on the turbulent conditions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗