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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 OSTI2022

Topology Optimization of 3D Flow Fields for Flow Batteries

We report as power generated from renewables becomes more readily available, the need for power-efficient energy storage devices, such as redox flow batteries, becomes critical for successful integration of renewables into the electrical grid. An important aspect of a redox flow battery is the planar flow field, which is usually composed of two-dimensional channels etched into a backing plate. As reactant-laden electrolyte flows into the flow battery, the channels in the flow field distribute the fluid throughout the reactive porous electrode. We utilize topology optimization to design flow fields with full three-dimensional geometry variation, i.e., 3D flow fields. Specifically, we focus on vanadium redox flow batteries and use the optimization algorithm to generate 3D flow fields evolved from standard interdigitated flow fields by minimizing the electrical and flow pressure power losses. To understand how these 3D designs improve performance, we analyze the polarization of the reactant concentration and exchange current within the electrode to highlight how the designed flow fields mitigate the presence of electrode dead zones. While interdigitated flow fields can be heuristically engineered to yield high performance by tuning channel and land dimensions, such a process can be laborious; this work provides a framework for automating that design process.

25 ENERGY STORAGE↗
DOE OSTI2024

Solvent-Dependent Dynamics of Cellulose Nanocrystals in Process-Relevant Flow Fields

Flow-assisted alignment of anisotropic nanoparticles is a promising route for the bottom-up assembly of advanced materials with tunable properties. While aligning processes could be optimized by controlling factors such as solvent viscosity, flow deformation, and the structure of the particles themselves, it is necessary to understand the relationship between these factors and their effect on the final orientation. In this study, we investigated the flow of surface-charged cellulose nanocrystals (CNCs) with the shape of a rigid rod dispersed in water and propylene glycol (PG) in an isotropic tactoid state. In situ scanning small-angle X-ray scattering (SAXS) and rheo-optical flow-stop experiments were used to quantify the dynamics, orientation, and structure of the assigned system at the nanometer scale. The effects of both shear and extensional flow fields were revealed in a single experiment by using a flow-focusing channel geometry, which was used as a model flow for nanomaterial assembly. Due to the higher solvent viscosity, CNCs in PG showed much slower Brownian dynamics than CNCs in water and thus could be aligned at lower deformation rates. Moreover, CNCs in PG also formed a characteristic tactoid structure but with less ordering than CNCs in water owing to weaker electrostatic interactions. The results indicate that CNCs in water stay assembled in the mesoscale structure at moderate deformation rates but are broken up at higher flow rates, enhancing rotary diffusion and leading to lower overall alignment. Albeit being a study of cellulose nanoparticles, the fundamental interplay between imposed flow fields, Brownian motion, and electrostatic interactions likely apply to many other anisotropic colloidal systems.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Towards Reconstruction of Complex Flow Fields Using Unit Flows

Many complex turbulent flows in nature and engineering can be qualitatively regarded as being constituted of multiple simpler unit flows. The objective of this work is to characterize the coherent structures in such complex flows as a combination of constituent unitary flow structures for the purpose of reduced-order representation. While turbulence is clearly a non-linear phenomenon, we aim to establish the degree to which the optimally weighted superposition of unitary flow structures can represent the complex flow structures. The rationale for investigating such superposition stems from the fact that the large-scale coherent structures are generated by underlying flow instabilities that may be reasonably described using linear analysis. Clearly, the degree of validity of superposition will depend on the flow under consideration. In this work, we take the first step toward establishing a procedure for investigating superposition. Experimental data of single and triple tandem jets in crossflow are used to demonstrate the procedure. A composite triple tandem jet flow field is generated from optimal superposition of single jet data and compared against ‘true’ triple jet data. Direct comparisons between the true and composite fields are made for spatial, temporal, and kinetic energy content. The large-scale features (obtained from proper orthogonal decomposition or POD) of true and composite tandem jet wakes exhibit nearly 70% agreement in terms of modal eigenvector correlation. Corresponding eigenvalues reveal that the kinetic energy of the flow is also emulated with only a slight overprediction. Temporal frequency features are also examined in an effort to completely characterize POD modes. The proposed method serves as a foundation for more rigorous and robust dimensional reduction in complex flows based on unit flow modes.

Kristo, Paul J.↗
DOE OSTI2022

Evaluation of bio-inspired flow fields in a mediated Li-S flow battery for grid energy storage

Lithium-sulfur is a redox flow battery with high energy density for applications in safe, reliable, and lasting scaling of energy. However, lithium-based batteries often encounter platting as a problem thanks to poor Li-ions deposition after cycling. Aiming to reduce this impact, a uniform and continuous flow of ions is needed. On this work, novel bio-inspired flow fields in the electrochemical cell were tested to improve ions flowability and lithium platting control, ultimately enhancing battery performance and life. To secure Li-S efficient, low-cost, and secure energy storage capabilities, we chose a configuration with decamethylferrocene and cobaltocene acting as redox mediators, Li metal as anode and sulfur kept in a separate catholyte reservoir. Flow test and battery results insinuated a beneficial influence of bio-inspired designs in flowing electrolyte uniformly with less pressure and pump power in comparison to other conventional designs used in the industry, with an encouraging ability to approach a cheap, safe, and reliable Li-S grid energy storage.

25 ENERGY STORAGE↗
DOE OSTI2021

Flow battery flow field having volume that is function of power parameter, time parameter and concentration parameter

A flow battery includes a cell that has first and second flow fields spaced apart from each other and an electrolyte separator layer. A supply/storage system is external of the cell and includes first and second vessels fluidly connected with the first and second flow fields, and first and second pumps configured to selectively move first and second fluid electrolytes between the vessels and the first and second flow fields. The flow fields each have an electrochemically active zone that is configured to receive flow of the fluid electrolytes. The electrochemically active zone has a total open volume that is a function of at least one of a power parameter of the flow battery, a time parameter of the pumps and a concentration parameter of the fluid electrolytes.

Smeltz, Andrew↗
DOE OSTI2024

Flow field design for zero-gap microbial electrolysis cells using synthetic and real wastewater

Increasing performance in microbial electrolysis cells (MECs) requires the development of optimized reactor configurations with minimal internal resistance and capable to operate with real wastewater. Here, the impact of two different flow fields (serpentine and circular) was examined in zero-gap MECs with synthetic and real wastewaters. The serpentine flow field enabled a uniform distribution of the electrolyte in the anode chamber, resulting in larger current densities at lower flow rates compared to the circular flow field. Electrochemical tests using synthetic media with high buffer capacity revealed more stable and higher performance with the serpentine flow field compared to the circular flow path, producing larger current density (23.7 ± 0.8 A/m 2 vs 21.9 ± 5.6 A/m 2 ), hydrogen production rate (75.8 ± 4.1 L/L-d vs 54.3 ± 2.4 L/L-d), cathodic coulombic efficiency (>91 % vs >50 %), and an overall lower internal resistance (12.5 ± 0.5 mΩm 2 vs 14.8 ± 3.7 mΩm 2 ). Continuous operation for over 30 days with real wastewater indicated higher tolerance of the MECs with serpentine flow field toward media with large concentration of suspended solids, producing a current density of 5.4 ± 1.1 A/m 2 and a hydrogen production rate of 22.2 ± 6.2 L/L-d. Furthermore, the results presented here underscore the importance of reactor design and architecture in optimizing MEC performance for hydrogen production from liquid wastes.

flow path↗
DOE OSTI2026

Towards a Unified Low-Cost Flow Plate, Flow-Field, PTL Solution for Proton Exchange Membrane Electrolyzers

Proton exchange membrane (PEM) water electrolysis is a highly efficient method for hydrogen production. Research cells typically consist of one proton exchange membrane, two catalyst layers, two porous transport layers, two flow-field plates, and two endplates. In commercial systems, the machined flow-field plates that are employed in research cells are typically replaced by stamped parts or open mesh material solutions to reduce manufacturing cost at scale. Nonetheless, the cell contains about 8 total interfaces: bipolar plate / flow plate material / porous transport medium / electrode / membrane / electrode / porous transport medium / flow plate material / bipolar plate. All these materials and interfaces need to be optimized for maximum performance and efficiency. Reducing the amount of interfaces by combining individual cell components directly benefits the fabrication cost (by reducing the parts count and the needs for surface coatings) and the electrochemical performance (by reducing ohmic losses). We have designed a novel PEM electrolysis cell with a piece of channeled titanium felt functioning as both the anode flow-field and the PTL, referred to as the channeled diffusion layer (CDL). The pores of the felt facilitate both in-plane and through-plane diffusion, ensuring maximum catalyst utilization while also minimizing mass transport loss. The titanium felt can be mass manufactured with existing stamping and forming methods and is therefore a promising candidate to reduce the capital cost of PEM electrolyzers whilst improving hydrogen production efficiency. Experiments conducted with 3mg IrOx/cm2 loading MEAs have shown a approximately 40% boost in peak current by implementing the CDL design. Low catalyst-loading MEAs are being tested in ongoing experiments and their results will be discussed and compared.

08 HYDROGEN↗
DOE OSTI2021

Design, Flow Field, and Heat Transfer Characterization of the Conjugate Aero-Thermal Test Facility at NETL

A new aerothermal test facility was constructed for the purpose of studying film cooling performance in an environment that accurately simulates conjugate heat transfer characteristics that exist in engine operation. Here, this paper details the design of the facility and the plan for conducting steady state film cooling experiments to improve the understanding of conjugate heat transfer scaling from laboratory to engine conditions. The test facility consists of two separate low channels (hot gas/coolant) and each gas path has a flow conditioning section, a convergent nozzle and a test section/channel with viewports. Numerical simulations were conducted to predict flow field characteristics supporting the design of the flow loop facility. Preliminary experiments were conducted to characterize the flow field using velocity and temperature profile measurements. In addition, infrared (IR) thermography methods were developed to measure surface temperatures on the hot side of the test plate. The IR measurement methods including calibration of the IR camera is explained in detail. It was concluded that appropriate hot gas path flow conditioning could be achieved using a strainer-like tube, a perforated plate, and a honeycomb-mesh screen system upstream of the test section. Flow field measurements from preliminary experiments showed that the boundary layer profile follows the law of the wall.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Scale-Up of Electrode Coating and Flow-Field for Commercial Hydrogen Peroxide Electrolyzer: Cooperative Research and Development Final Report, CRADA Number CRD-17-00687

Hydrogen peroxide is currently produced at central chemical plants via the anthraquinone oxidation process. This process produces environmental pollutants that are costly to remediate, requires hazardous long distance shipping of highly concentrated peroxide (50% or 70%), and necessitates extra handling costs related to storage and dilution. Peroxygen Systems, Inc. (PSi) is developing breakthrough technology for on-site hydrogen peroxide production. PSi’s on-site on-demand electrolyzer can reduce the cost of producing hydrogen peroxide by 50%, while also completely eliminating the cost and safety issues associated with shipping and handling of high concentration hydrogen peroxide. The challenge for PSi is scaling. To support the next step toward commercialization (customer pilot tests), scaling the prototype into larger single cells and 20-40 cell stacks is required. In addition to internal hardware and flow-field design efforts at PSi, NREL will address three critical problems for this scale-up effort: (1) demonstrating a large scale roll-to-roll (R2R) process to coat uniform electrode materials for 100 cm2 and 500 cm2 stack testing, (2) demonstrating an in-line diagnostic to achieve better electrode quality control, and (3) performing in situ cell/stack testing to better understand and optimize the performance of the flow field design.

28 EE - Advanced Manufacturing Office (EE-5A)↗
DOE OSTI2021

Evaluating the Influence of Rotor-Casing Eccentricity on Turbine Efficiency Including Time-Resolved Flow Field Measurements

Abstract The clearance that exists between the casing and turbine blade tips is one of the key drivers of efficiency in gas turbine engines. For this reason, engine manufacturers utilize precise manufacturing techniques and may use clearance control systems to minimize tip clearances to reduce associated losses. Despite these efforts, turbines typically exhibit some nominal casing ovality or rotor-casing eccentricity, and changes to blade tip clearance during operation commonly occur due to thermal and mechanical stresses. The present study investigates non-axisymmetric tip clearance effects by creating a rotor-casing eccentricity in a one-stage axial test turbine operating in a continuous-duration mode at engine-relevant conditions with engine representative hardware. A magnetic levitation bearing system was leveraged to move the turbine shaft to vary the rotor-casing eccentricity without test section disassembly. The results of this study indicate that rotor-casing eccentricity does not affect overall turbine efficiency over the range that was tested, but does locally influence efficiency and the rotor exit flow field. Comparisons of flow angle and secondary flow kinetic energy (SKE) agreed with previous studies and existing analytical methods, respectively. Collectively, these results indicate that tip clearance can be studied locally on an eccentric rotor.

Engineering↗
DOE OSTI2023

Uncertainty quantification of bank vegetation impacts on the flood flow field in the American River, California, using large‐eddy simulations

Bank vegetation plays a key role in both hydrodynamics and morphodynamics of natural rivers; however, these effects are often unaccounted for in the computational flow dynamics of natural waterways. Recent studies using the large‐eddy simulation (LES), however, have attempted to gain insights into the impacts of bank vegetation on the mean flow field of the natural rivers using a vegetation model, which applies a sink term to the momentum equations of motion. This approach accounts for the effects of the vegetation and provides a practical approach to account for the complex patches of bank vegetation in large‐scale rivers. To implement the vegetation model, a drag coefficient reflecting the overall resistance of vegetal structures to the flow is needed, but due to the lack of calibrated data and range of size, density and type of vegetation, this parameter can be a significant source of uncertainty in the model results. Here, in this study, we use uncertainty quantification (UQ) to investigate the hydrodynamics and bed shear results when a bank vegetation is incorporated in an LES model. To this end, we used the polynomial chaos expansion and Monte Carlo sampling techniques to determine the uncertainties associated with the drag coefficient in the vegetation model and from uncertainties in the bed roughness and inflow discharge. The UQ analysis provided spatially varying confidence levels for the spanwise and vertical distribution of velocity magnitude and for the bed shear stress distributions. In addition, Sobol indices were computed to indicate the relative influence that each parameter had on the overall uncertainty. In general, it was found that uncertainty in flow discharge was the dominant source of uncertainty; however, the drag coefficient in the vegetation model and the bed roughness parameter also made significant contribution to the uncertainty near the banks and bed, respectively.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Using temperature and flow fields to detect gas leakage from canisters containing spent nuclear fuel: Applications to RAMM-TM

The multi-physics STAR-CCM+ code has been used to simulate the temperature and flow fields in canister gas leakage experiments conducted by using a 1/4.5-scale model storage cask. The simulations were conducted at Argonne National Laboratory’s Laboratory Computing Resource Center, utilizing high-performance computing resources. Development of STAR-CCM+ simulation models for the 1/4.5-scale model cask is described herein, followed by validation of the simulation results against experimental data. Canister depressurization and thermal response during gas leakage are discussed, along with analyses of the leakage path and allowable leakage rate. The insights gained from the STAR-CCM+ simulations and leakage analyses will help guide future experiments and actual industry applications of Argonne’s Remote Area Modular Monitoring system for canister surface temperature measurement (RAMM-TM) to enable effective aging management of spent fuel during extended dry storage, as well as help reduce risks to public safety and health and protect the environment.

Canister gas leakage↗
DOE OSTI2024

Conceptual design of a Doppler spectrometer for 102 m/s cross-field flows in tokamak divertors

The cross-field transport in the scrape-off-layers (SOLs) and divertors in tokamaks is of a similar size to the poloidal component of the parallel flow, thereby significantly impacting the plasma transport there. However, its direct observation has been challenging because the drift velocity (102–103 m/s) is significantly below the detection limit of conventional diagnostics. To realize cross-field ion flow measurement, a variety of systematic uncertainties in the system must be narrowed down. Here, we develop a conceptual design of the Doppler spectrometry that enables us to measure the impurity flows with 102-m/s accuracy based on an in situ wavelength-calibration technique developed in the astrophysics field, the iodine-cell method. We discuss its properties and applicability. In particular, the scaling relation between wavelength accuracy and various spectroscopic parameters is newly presented, which suggests the high importance of the wavelength resolution of the system. Based on transport simulations for the JT-60SA divertor, the feasibility of the system is assessed.

Fujii, Keisuke↗
DOE OSTI2023

Flow field characteristics of a 127-pin rod bundle with hexagonal spacer grids

A determination of nominal flow phenomena in liquid metal fast reactor (LMFR) fuel assemblies is critical toward generation-IV reactor development. Axially positioned spacer grids are used to maintain the geometry of hexagonal rod bundles and simultaneously introduce perturbations in the flow. Three-dimensional (3D) printed asymmetric honeycomb spacer grids were installed in a prototypical 127-pin LMFR fuel assembly model to study complex fluid dynamics interactions induced by the spacer grid and rods. To characterize flow dynamics in this intricate geometry, time-resolved particle image velocimetry (TR-PIV) using the matched-index-of-refraction method was employed to obtain non-intrusive velocity measurements for three axial planes (one near-wall and two interior planes) at a Reynolds number of 6000. The statistical TR-PIV results compared sub-channel-dependent normalized time-averaged velocity, velocity fluctuations, Reynolds stress, vorticity, and turbulence kinetic energy distributions. TR-PIV line profiles characterized downstream spacer grid flow dynamics. Two-point spatial and spatial–temporal cross-correlation fields revealed local coherent structures and quantified convection velocities of traveling vortices. Spatial–temporal decomposition using dynamic mode decomposition (DMD) applied to the near-wall vorticity fields extracted turbulent structures and flow instabilities in the wake region of the spacer grid, along with their decay and frequency rates. Reduced-order velocity fields from DMD reconstructions identified the most energy-containing coherent structures persistent in the near-wall region. This research provides experimental data sets and analyses of flow behavior in rod bundles with hexagonal spacer grids. In conclusion, the results are critical toward LMFR design and geometry optimization, crucial for the validation of computational fluid dynamics and reduced-order flow models.

42 ENGINEERING↗
DOE OSTI2024

Informative and non-informative decomposition of turbulent flow fields

Not all the information in a turbulent field is relevant for understanding particular regions or variables in the flow. Here, we present a method for decomposing a source field into its informative Φ I (x, t) and residual Φ R (x, t) components relative to another target field. The method is referred to as informative and non-informative decomposition (IND). All the necessary information for physical understanding, reduced-order modelling and control of the target variable is contained in Φ I (x, t), whereas Φ R (x, t) offers no substantial utility in these contexts. The decomposition is formulated as an optimisation problem that seeks to maximise the time-lagged mutual information of the informative component with the target variable while minimising the mutual information with the residual component. The method is applied to extract the informative and residual components of the velocity field in a turbulent channel flow, using the wall shear stress as the target variable. We demonstrate the utility of IND in three scenarios: (i) physical insight into the effect of the velocity fluctuations on the wall shear stress; (ii) prediction of the wall shear stress using velocities far from the wall; and (iii) development of control strategies for drag reduction in a turbulent channel flow using opposition control. In case (i), IND reveals that the informative velocity related to wall shear stress consists of wall-attached high- and low-velocity streaks, collocated with regions of vertical motions and weak spanwise velocity. This informative structure is embedded within a larger-scale streak–roll structure of residual velocity, which bears no information about the wall shear stress. In case (ii), the best-performing model for predicting wall shear stress is a convolutional neural network that uses the informative component of the velocity as input, while the residual velocity component provides no predictive capabilities. Finally, in case (iii), we demonstrate that the informative component of the wall-normal velocity is closely linked to the observability of the target variable and holds the essential information needed to develop successful control strategies.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Stability and Performance of an Undersea Kite Operating in a Turbulent Flow Field

In this paper, we examine the effects of flow disturbances resulting from turbulence on the dynamic behavior of an underwater energy-harvesting kite system that executes periodic figure-8 flight. Due to the periodic nature of the kite’s operation, we begin by assessing orbital stability using the Floquet analysis and stroboscopic intersection analysis of a Poincaré section, with the former analysis performed on a simplified “unifoil” model and the latter performed on a six-degree-of-freedom (6-DOF)/flexible tether model. With periodic stability established, a frequency-domain analysis based on a linearization about the kite’s path is used to predict the quality of flight path tracking as a function of the turbulence frequency. To validate the accuracy of these simulation-based predictions under flow disturbances, we compare the predictions of the kite’s behavior against the results of small-scale tow testing experiments performed in a controlled pool environment.

13 HYDRO ENERGY↗
DOE OSTI2022

Neural network–based pore flow field prediction in porous media using super resolution

Direct pore-scale simulations of fluid flow through porous media are computationally expensive to perform for realistic systems. Previous works have demonstrated using the geometry of the microstructure of porous media to predict the velocity fields therein based on neural networks. However, such trained neural networks do not perform well for unseen porous media with a large degree of heterogeneity. In this study we propose that incorporating a coarse velocity field in the input of neural networks is an effective way to improve the prediction performance. The coarse velocity field can be simulated with a low computational cost and provides global information to regularize the ill-posedness of the learning problem, which is usually caused by the use of local geometries due to the computational resource constraints. We show that incorporating the coarse-mesh velocity field significantly improves the prediction accuracy of the fine-mesh velocity field by comparison to the prediction that relies on geometric information alone, especially for the porous medium with a large interior vuggy pore space. We also show the flexibility of training the network in using coarse velocity fields with various resolutions. The results suggest that even using coarse velocity field with a very low resolution, the predictions are still enhanced and close to the ground truths. The feasibility of the method is further demonstrated by testing the trained network on real rocks. This study highlights the merits of incorporating a coarse-mesh velocity field into the input for neural networks, which provides global, physics-based information for the model, thereby improving the model's generalization capability.

42 ENGINEERING↗