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Results for “Scaling Validation”

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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Megawatt-Scale Low Temperature Electrolyzer Research Capability

The development and installation of a flexible low-temperature electrolyzer research capability at the multi-MW scale with integrated renewables will help lower the cost barrier to entry for electrolyzer manufactures needing at scale system and stack evaluation and enable more electrolyzer manufactures to accelerate to commercialization with building block scale demonstration and validation. This NREL capability represents a DOE HFTO investment to support the $1B DOE Clean Hydrogen Electrolysis Program working to achieve the Hydrogen Shot goal of $1 for 1 kg hydrogen in 1 decade, lower greenhouse gas emissions and criteria pollutants, build clean energy infrastructure, and provide pathways to private sector uptake.

electrical grid↗
NASA NTRS1998

Effect of Finite Computational Domain on Turbulence Scaling Law in Both Physical and Spectral Spaces

The well-known translation between the power law of energy spectrum and that of the correlation function or the second order structure function has been widely used in analyzing random data. Here, we show that the translation is valid only in proper scaling regimes. The regimes of valid translation are different for the correlation function and the structure function. Indeed, they do not overlap. Furthermore, in practice, the power laws exist only for a finite range of scales. We show that this finite range makes the translation inexact even in the proper scaling regime. The error depends on the scaling exponent. The current findings are applicable to data analysis in fluid turbulence and other stochastic systems.

Hou, Thomas Y.↗
NASA NTRS2008

Computational Analyses in Support of Sub-scale Diffuser Testing for the A-3 Facility: Aero-Acoustic Analyses and Experimental Validation - Part 3

A unique assessment of acoustic similarity scaling laws and acoustic analogy methodologies in predicting the far-field acoustic signature from a sub-scale altitude rocket test facility at the NASA Stennis Space Center was performed. A directional, point-source similarity analysis was implemented for predicting the acoustic far-field. In this approach, experimental acoustic data obtained from "similar" rocket engine tests were appropriately scaled using key geometric and dynamic parameters. The accuracy of this engineering-level method is discussed by comparing the predictions with acoustic far-field measurements obtained. In addition, a CFD solver was coupled with a Lilley's acoustic analogy formulation to determine the improvement of using a physics-based methodology over an experimental correlation approach. In the current work, steady-state Reynolds-averaged Navier-Stokes calculations were used to model the internal flow of the rocket engine and altitude diffuser. These internal flow simulations provided the necessary realistic input conditions for external plume simulations. The CFD plume simulations were then used to provide the spatial turbulent noise source distributions in the acoustic analogy calculations. Preliminary findings of these studies will be discussed.

Allgood, Daniel C.↗
DOE OSTI2023

Fabrication, Modeling, and Testing of a Prototype for Particle Thermal Energy Storage Containment

Increasing penetration of variable renewable energy resources requires the deployment of energy storage at a range of durations. Long-duration energy storage (LDES) technologies will fulfill the need to firm variable renewable energy resource output throughout the year. Conventional electrochemical batteries (e.g., lithium-ion) are uneconomical in this role due to high energy capacity costs. Thermal energy storage (TES) is one promising technology for LDES applications because of its siting flexibility and ease of scaling. Particle-based TES systems use low-cost solid particles that have higher temperature limits than the molten salts used in traditional concentrated solar power systems. A key component in particle-based TES systems is the containment silo for the high-temperature (> 1100 degrees C) particles. This study combined experimental testing and computational modeling methods to design and characterize the performance of a particle containment silo for LDES applications. A containment silo prototype was built at a laboratory scale and used to validate a congruent transient finite element analysis (FEA) model. The validation compared the actual and predicted temperature profile through the prototype over six days as the particles cooled from their initial temperature. The performance of a commercial scale (> 5 GWhth) was then characterized using the validated model. The transient FEA model was subject to several charge-discharge cycles to mimic a possible operating schedule. The commercial-scale model predicted a storage efficiency in excess of 95% after five days of storage with a design storage temperature of 1200 degrees C. Insulation material and concrete temperature limits were considered as well. The validation of the methodology means the FEA model can simulate a range of scenarios for future applications. This work supports the development of a promising LDES technology with implications for grid-scale electrical energy storage, but also for thermal energy storage for industrial process heating applications.

ENERGY STORAGE↗
DOE OSTI2020

A non-intrusive optical (NIO) approach to characterize heliostats in utility-scale power tower plants: Methodology and in-situ validation

No reliable in-situ optical characterization tool is available that can efficiently and accurately measure various optical errors of individual heliostats in a utility-scale power-tower plant. Here, an innovative non-intrusive optical (NIO) approach is proposed to measure mirror surface slope error, mirror facet canting error, and heliostat tracking error based on reflection images using the natural target—the tower—in a heliostat field. The NIO approach adopts various techniques in photogrammetry, reflectometry, and geometrical optics to first determine the camera position and the actual tower position with respect to the heliostat. Then, Snell’s law is applied to find the surface normal at the reflection point or line of a reflection image and derive the surface slope error, mirror facet canting error, and heliostat tracking error accordingly. In addition, an in-situ validation is performed to demonstrate the feasibility of the NIO approach. Analysis with multiple sets of reflection images on one single heliostat of interest demonstrates that the NIO method can achieve a measurement uncertainty of 0.22 mrad for mirror facet slope error (root-mean-square) at the given test conditions. The sensitivity of measurement uncertainty to various parameters will be presented in a separate work. In the future, state-of-the-art unmanned aerial systems (UAS) are planned to perform the efficient image collection with a goal to complete the survey across a utility-scale field of over 10,000 heliostats within one or a few days depending on the number of UASs. The development of the NIO approach is expected to fill the critical gap for successful solar-field operation and maintenance, which is necessary for the global growth of the solar power-tower technology. The NIO approach can also be applied to any relevant industry requiring high-precision mirror surface shape characterization.

14 SOLAR ENERGY↗
DOE OSTI2024

High-Temperature Fe-Based Fischer–Tropsch Synthesis: Experimentally Validated Kinetic Models Implemented at Pellet and Reactor Scales

Pellet- and reactor-scale models for Fischer–Tropsch synthesis (FTS) with a Fe–K/silica catalyst were developed to investigate the sensitivity of the hydrocarbon products and carbon dioxide selectivity to process conditions and feed composition at high temperature (350–400 °C), moderate pressure (1–10 bar), and a range of H 2 /CO ratios (3–1). The major objective of this paper is to develop, validate, and evaluate a high-temperature FTS model that is then used to assess the feasibility of process integration with syngas production. Since there is limited kinetic data available, in literature at these conditions, bench-scale reactor tests were conducted to obtain operational data for parameter fitting of kinetic expressions used in the model. This resulting kinetic model demonstrated agreement with the experimental data with an R 2 of 0.97 to the testing data set and, thus, was feasible to apply at pellet and reactor scales. Here, multiple pellet sizes were modeled to detail the role of transport limitations as the sphere’s diameter approached and exceeded 1 mm. Application of the reactor model indicated that hydrocarbon selectivity depended strongly on temperature, whereas the ratio of olefin to paraffin products decreased with increasing temperature, pressure, and H 2 /CO ratio. Product selectivity was not sensitive to the conversion of carbon monoxide. Furthermore, the roles of the pressure and H 2 /CO ratio were closely coupled. At a H 2 /CO ratio of 3, only slight variations in selectivity occurred over a pressure range of 1–20 bar, whereas at a ratio of 1, selectivity could vary by as much as 30% over the same pressure range. At pressures below 5 bar and temperatures above 350 °C, minimal selectivity to heavy hydrocarbons (C 12+ ) is obtained, and selectivity to midrange products (C 5–11 ) rapidly declined as pressure dropped below 5 bar, which indicated that an operational pressure of at least 5 bar is needed to achieve reasonable yields in this temperature range. These results, while tentative, provide guidelines for further experimentation and evaluation of integrated FTS processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Multiphysics simulation of recent experiments on alkali‐silica reaction expansion in reinforced concrete members

Alkali‐silica reaction (ASR) is an important degradation process that causes volumetric expansion and damage in concrete, and is affected significantly by the local temperature, moisture and stress conditions that often vary across the regions of a structure. Numerical simulation is essential to predict the progression and effects of ASR on the performance of structures. Because of the interactions between thermal and moisture transport and mechanical deformation, it is important for numerical models to represent all these physical phenomena and the coupling between them. Simulations of ASR in reinforced concrete (RC) structures are further complicated by the need to capture interactions between concrete and embedded reinforcing bars. Here, this paper describes the implementation of a scalable, coupled‐physics ASR model for simulating RC structures and assesses the ability of that model to predict ASR‐induced expansion in recent laboratory tests on RC block and beam specimens. These laboratory tests and the simulation approach were selected because of their applicability to RC structural‐scale simulations. This validation study helps builds confidence the ability of this approach to model ASR expansion in large, complex RC structures, which is a current high‐priority need.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Optimizing Conductivity and Hardness in Cu–Nb Nanolamellar Composites Fabricated Through Accumulative Roll Bonding Without Intermittent Heat Treatments

High strength/high conductivity Cu–XNb nanolamellar bimetallic composites (where X < 50 pct) were successfully processed via accumulative roll bonding. No intermittent heat treatments were used which increases industrial applicability. Estimates of conductivity from published models were validated at length scales of ~ 150 nm but were shown to be four times too low for composites with layer thicknesses < 40 nm. Nanoscale composites with conductivity of ~ 47 pct IACS and 99 Rockwell B hardness were fabricated.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Luminescence dosimetry for evaluation of the external exposure in Metlino, upper Techa River valley, Southern Urals, Russia: Analysis of new results

Luminescence dosimetry was applied in the former settlement of Metlino, Southern Urals, Russia as part of a full-scale study to validate the Techa River Dosimetry System (TRDS) 2016 for the upper Techa River region. The village, which was evacuated in 1956, was located 7 km downstream of the release point of liquid radioactive waste by the Mayak plutonium facility. Several brick samples were taken from north-eastern and south-eastern walls of the granary, facing the former Techa river shoreline and floodplain. Samples were all taken at the same height and measured at different depths into the brick. For the majority of brick samples, good Optically Stimulated Luminescence properties of the quartz grains were observed. In some cases, however, strong levels of sensitization and/or signal recuperation were encountered which necessitated adjustment in the measurement protocols. Anthropogenic doses in bricks varied from 1.5 to 6.6 Gy and the horizontal profiles along both walls showed significant variation, which is explained on a qualitative basis. Further, a dose depth profile is observed for selected samples, which is different from the dose depth profile measured and simulated for samples from the north-western wall of the granary in previous studies. This is qualitatively explained by the differences in source configuration.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2020

Accelerating high-strain continuum-scale brittle fracture simulations with machine learning

Failure in brittle materials under dynamic loading conditions is a result of the propagation and coalescence of microcracks. Simulating this discrete crack evolution at the continuum level is computationally expensive or, in some cases, intractable, resulting in the need to make broad assumptions or neglect key physics. In this work, we have developed an approach using machine learning that overcomes the current inability to represent meso-scale physics at the macro-scale. Our approach leverages damage and stress data from a computationally expensive high-fidelity model that explicitly resolves microcrack behavior to build an inexpensive machine learning emulator. Once trained, the machine learning emulator is used to predict the evolution of crack length statistics, which then informs a continuum-scale constitutive model. This results in a significant speed-up of the workflow by four orders of magnitude. Both the machine learning emulator and the continuum-scale model are validated against the high-fidelity model and experimental data, respectively, showing excellent agreement. There are two key findings. The first is that we can reduce the dimensionality of the problem, establishing that the machine learning emulator only needs the length of the longest crack and one of the maximum stress components to capture the necessary physics. Another compelling finding is that the emulator can be trained in one experimental setting and transferred successfully to predict behavior in a different setting.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Exponential Water Uptake in Ionomer Membranes Results from Polymer Plasticization

Water content is the most influential factor in the performance of ion-exchange membranes (IEMs), controlling their mechanical rigidity, ionic conductivity, and degradation rates. Membranes absorb water exponentially at high water activity (a w ), making that region of the sorption isotherm the most influential on membrane properties. Plasticization of the polymer by water has been proposed to cause this exponential uptake at high a w . However, an integrated microscopic picture of the structure, thermodynamic, and mechanical properties of IEMs as a function of a w has remained elusive. In this work, we use large-scale molecular simulations validated with experimental measurements to compute the sorption isotherms, Young’s modulus, polymer dynamics, and structure of IEMs. The simulations unveil that the exponential increase in water uptake (WU) coincides in all cases with the glass to rubber transition of the membrane, as measured through its Young’s modulus and segmental polymer dynamics. Functionalization of the polymer with alkyl groups further contributes to its plasticization, increasing the WU at a given a w and ion-exchange capacity (IEC). The alkyl chains act synergistically with water to plasticize the polymer matrix and allow water penetration in the membrane. The simulations reveal that the width of the water channels depends on the ratio λ of water to ions in the polymer but is independent of its IEC. We conclude that differences in the polymer matrix–not the water channels–are responsible for the distinct uptake response of IEMs to the thermodynamic driving force of water activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Development of an Amine Oxide Polyzwitterion Brush Martini Model with Polarizable Water and Ions

Abstract In order to accurately simulate the fouling process of proteins onto polyzwitterion brushes, models that accurately capture the hydration properties and chain conformations of such brushes must first be established. We developed a Martini coarse-grained (CG) model for amine oxide polyzwitterion (PNOMA) brushes, a promising class of antifouling materials, in polarizable water and ions by fitting to all-atom bond and angle distributions, monomer hydration free energy, monomer–monomer distance potential of mean force (PMF), and monomer–salt radial distribution functions (RDFs). Martini 2.2P was selected for compatibility with the established polarizable water and ion models. For comparison with PNOMA, we also constructed models for conventional sulfobetaine (PSBMA) and phosphorylcholine (PMPC) polyzwitterions and the polycation PMETAC using established nonbonded bead types from the literature and refitting bond and angle potentials. We simulated each polymer brush chemistry for varying grafting density and chain length, validating brush height scaling relations against experimental data. The CG models captured the relative hydration strengths among different polyzwitterion chemistries, and brush heights extrapolated to higher molecular weights are in agreement with experimental ellipsometry data. We find that chain swelling of the superhydrophilic PNOMA brushes lies between that of the traditional polyzwitterions PSBMA/PMPC and the polycation PMETAC. For PNOMA brushes in NaCl solution, simulated brush height decreases with salt concentration due to the selectively strong interactions between amine oxide and sodium ions.

Walker, Christopher C. [Oak Ridge National Laborat↗
DOE OSTI2023

Coupled Lattice Boltzmann Modeling Framework for Pore-Scale Fluid Flow and Reactive Transport

In this paper, we propose a modeling framework for pore-scale fluid flow and reactive transport based on a coupled lattice Boltzmann model (LBM). We develop a modeling interface to integrate the LBM modeling code parallel lattice Boltzmann solver and the PHREEQC reaction solver using multiple flow and reaction cell mapping schemes. The major advantage of the proposed workflow is the high modeling flexibility obtained by coupling the geochemical model with the LBM fluid flow model. Consequently, the model is capable of executing one or more complex reactions within desired cells while preserving the high data communication efficiency between the two codes. Meanwhile, the developed mapping mechanism enables the flow, diffusion, and reactions in complex pore-scale geometries. We validate the coupled code in a series of benchmark numerical experiments, including 2D single-phase Poiseuille flow and diffusion, 2D reactive transport with calcite dissolution, as well as surface complexation reactions. The simulation results show good agreement with analytical solutions, experimental data, and multiple other simulation codes. In addition, we design an AI-based optimization workflow and implement it on the surface complexation model to enable increased capacity of the coupled modeling framework. Compared to the manual tuning results proposed in the literature, our workflow demonstrates fast and reliable model optimization results without incorporating pre-existing domain knowledge.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Direct genome-scale screening of Gluconobacter oxydans B58 for rare earth element bioleaching

Abstract The transition to a sustainable energy economy will require an enormous increase in the supply of rare earth elements (REEs). Bioleaching offers a promising alternative to conventional hydrometallurgical methods for REE extraction from low-grade ores. However, exploiting this potential remains challenging due to large gaps in our understanding of the genetics involved, and inadequate biological tools to address them. We generated a highly non-redundant whole-genome knockout collection for the bioleaching microbe Gluconobacter oxydans B58, reducing redundancy by 85% compared to the previous best collection. This new collection was directly screened for bioleaching neodymium from a synthetic monazite powder, identifying 89 genes important for bioleaching, 68 of which have not previously been associated with this mechanism. We conducted bench-scale experiments to validate the extraction efficiency of promising strains: 8 demonstrated significant increases in extraction by up to 111% (δ GO_1598 , disruption of the gene encoding the orotate phosphoribosyltransferase enzyme PyrE), and one strain significantly reduced it by 97% (δ GO_1096 , disruption of the gene encoding the GTP-binding protein TypA). Notable changes in pH were only observed for 3 strains, suggesting an important role for non-acid mechanisms in bioleaching. These findings provide valuable insights into further enhancing REE-bioleaching by G. oxydans through genetic engineering.

Marecos, Sabrina (ORCID:0000000158529933)↗
DOE OSTI2023

Precision Tests of the Nonlinear Mode Coupling of Anisotropic Flow via High-Energy Collisions of Isobars

Valuable information on dynamics of expanding fluids can be inferred from the response of such systems to perturbations in their initial geometry. We apply this technique in high-energy 96 Ru+ 96 Ru and 96 Zr+ 96 Zr collisions to scrutinize the expansion dynamics of the quark-gluon plasma, where the initial geometry perturbations are sourced by the differences in deformations and radial profiles between 96 Ru and 96 Zr, and the collective response is captured by the change in anisotropic flow V n between the two collision systems. Using a transport model, we analyze how the nonlinear coupling between lower-order flow harmonics V 2 and V 3 to the higher-order flow harmonics V 4 and V 5 , expected to scale as V 4 NL = χ 4 V 2 2 and V 5NL = χ 5 V 2 V 3 , gets modified as one moves from 96 Ru+ 96 Ru to 96 Zr+ 96 Zr systems. We find that these scaling relations are valid to high precision: variations of order 20% in V 4NL and V 5NL due to differences in quadrupole deformation, octupole deformation, and nuclear skin modify χ 4 and χ 5 by about 1–2%. Percent-level deviations are however larger than the expected experimental uncertainties and could be measured. Therefore, collisions of isobars with different nuclear structures are a unique tool to isolate subtle nonlinear effects in the expansion of the quark-gluon plasma that would be otherwise impossible to access in a single collision system.

Physics↗
DOE OSTI2026

Integration of Multiple Real-time Simulation Platforms with AIO for Scalability

This paper introduces a practical and scalable approach to extend interoperability of Controller Hardware in the Loop (CHIL) validations for large scale microgrids, networked microgrids, and power electronics-based feeders. The work focuses on integrating multiple real-time simulators using Analog Input/Output (AIO) interface techniques in heterogeneous CHIL environment. It explores interfacing methods, highlighting key challenges related to dynamic accuracy and maintaining bidirectional power balance. A comparative evaluation of the Ideal Transformer Method is presented, assessing its effectiveness in multi-CHIL integration scenarios. The feasibility of this setup is demonstrated through a real-time use case involving multiple Typhoon HIL and Opal-RT platforms, showcasing its applicability for distributed system studies.

Khalid, Mohammad [ORNL] (ORCID:0000000179208805)↗
DOE OSTI2021

Modeling and Simulation of Power-Electronic Inverters in Analog Electronic Circuit Simulators

This paper demonstrates how equivalent-circuit representations of grid-following power-electronic inverters can be realized within a SPICE-based development environment using common circuit components and VerilogA code. This facilitates computationally lean simulations of inverter networks leveraging the strengths of SPICE in large-scale simulations. We validate the approach with time-domain simulations for a modified version of the IEEE standard 118-bus system modeled in Virtuoso (a SPICE-based solver). Simulation results are compared-focusing on accuracy and computation speed-with results from a commonly used power-electronics simulation package. We note a significant decrease in simulation time with comparable signal resolution when simulating the network in SPICE.

Billmeyer, Ryan↗
DOE OSTI2022

Hierarchical Control of Megawatt-Scale Charging Stations for Electric Trucks with Distributed Energy Resources

Electrifying medium- and heavy-duty trucks is critical to decarbonizing the transportation sector. Energy needs of electric trucks will likely require megawatt-scale charging stations, which could significantly stress the electric distribution grid. Distributed energy resources (DER) can alleviate this stress and reduce charging costs with proper management. To that end, this work develops a hierarchical predictive control algorithm for future multi-port megawatt-scale charging stations that can provide real-time energy management for stations, decide charging rates, dispatch energy storage system (ESS), and provide grid voltage support. We integrate three algorithmic components: (i) an energy management optimization (EMO) that provides supervisory control to DER assets and charging loads at minute scale, (ii) a real-time energy management system (RT-EMS) that heuristically compensates for fast disturbances at sub-second scale, and (iii) a model predictive control (MPC)-based battery management system (BMS) that communicates future charging demands to the EMO, to manage the overall megawatt-scale site. Additionally, validation in a controller hardware-in-the-loop (CHIL) environment shows that the hierarchical controller can reduce the total energy consumption from the grid by approximately 28% compared to an uncontrolled case for the station configuration in this paper, without impacting charging time.

24 POWER TRANSMISSION AND DISTRIBUTION↗