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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Challenging Practices of Algebraic Battery Life Models through Statistical Validation and Model Identification via Machine-Learning

Various modeling techniques are used to predict the capacity fade of Li-ion batteries. Algebraic reduced-order models, which are inherently interpretable and computationally fast, are ideal for use in battery controllers, technoeconomic models, and multi-objective optimizations. For Li-ion batteries with graphite anodes, solid-electrolyte-interphase (SEI) growth on the graphite surface dominates fade. This fade is often modeled using physically informed equations, such as square-root of time for predicting solvent-diffusion limited SEI growth, and Arrhenius and Tafel-like equations predicting the temperature and state-of-charge rate dependencies. In some cases, completely empirical relationships are proposed. However, statistical validation is rarely conducted to evaluate model optimality, and only a handful of possible models are usually investigated. This article demonstrates a novel procedure for automatically identifying reduced-order degradation models from millions of algorithmically generated equations via bi-level optimization and symbolic regression. Identified models are statistically validated using cross-validation, sensitivity analysis, and uncertainty quantification via bootstrapping. On a LiFePO 4 /Graphite cell calendar aging data set, automatically identified models utilizing square-root, power law, stretched exponential, and sigmoidal functions result in greater accuracy and lower uncertainty than models identified by human experts, and demonstrate that previously known physical relationships can be empirically "rediscovered" using machine learning.

25 ENERGY STORAGE↗
DOE OSTI2019

Validating Performance Models for Hybrid Power Plant Control Assessment

The need for simple, but accurate performance models of wind turbine generators (WTGs), photovoltaic (PV) plants, and battery energy storage systems (BESS) for various hybrid power plant (HPP) studies motivates the present work. Particularly, the development and verification stage of HPP controls requires reduced-order models to minimize the complexity and computation effort of simulation platforms. In this paper, such models are proposed, and the most essential parts of the models are validated through field measurements. The models target power system integration studies involving active and reactive power, as well as frequency and voltage regulation where detailed models, as proposed in the standards, can be cumbersome. Field measurements of two Vestas WTGs, one 1-MW PV plant, and one 1-MW/1-MWh BESS are used for model validation. The results show that the WTG and PV performance models correctly estimate the power generation variability according to fluctuations in wind speed and solar irradiance. The BESS performance model provides satisfactory results related to grid-forming control performance and estimation of state-of-charge. The presented validation work enables using the proposed performance models for power system studies and HPP control design in all model-based design stages, that is, preliminary analysis, design, verification, and validation with a high level of confidence.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Comparison of Bifacial Solar Irradiance Model Predictions With Field Validation

Models predicting rear irradiance for bifacial systems are critical to establish accurate estimates of energy yield. In this paper, we compare five published bifacial irradiance models, varying clearance, row spacing, tilt, and albedo to measure the sensitivity to these parameters. Bifacial energy gains (BG E ) as high as 20% are predicted for some configurations. Model agreement is generally good for low ground clearance (clearance heights lower than 0.75 times the collector width), but at higher clearances, finite system size and edge effects become a significant factor in simulations, stretching assumptions of infinite system extent made in some models. In addition, rear irradiance uniformity is improved at high ground clearance, as expected. A test-bed construction and results are described for comparison between modeled and measured data in Golden, CO, USA. Finally, the investigations indicate that model agreement for BG E calculation is better than 2% (absolute) when compared with measured results, depending on the system configuration.

14 SOLAR ENERGY↗
DOE OSTI2020

Calibrating Synchronous-Generator-Interfaced DG Models in Microgrids Using Multiple Event Data

Microgrids, consisting of distributed generators (DGs), loads, and energy storage systems, play an important role in future smart grids. In order to evaluate how microgrids operate and their dynamic response, it is necessary to develop accurate dynamic models of DGs in microgrids. This paper proposes a systematic method to calibrate synchronous-generator-interfaced DG models. Challenges associated with model validation in microgrids are analyzed. Underlying parameters are categorized into two groups, i.e., the steady-state parameters and time constants, which are estimated in two successive stages using multiple event data. This methodology ensures that the validated model with the estimated parameters are applicable for all events. A modified unscented Kalman filter (UKF) is proposed to deal with the cases in which measurement of power angle is unavailable. The effectiveness of the proposed method is validated using field test data of a 2.6 MVA diesel generator in a real microgrid.

Wang, Zhiwen↗
DOE OSTI2021

An Application for Validation of Power Distribution System Models in an ADMS Environment

An accurate model of a power distribution system is the foundation for model-based applications that ensure efficient and reliable grid operation in an advanced distribution management system (ADMS) environment. However, these models are error-prone and comprehensive model validation is challenging due to lack of standards-based systems, data originating from disparate databases and other sources, and the constantly evolving nature of modern power distribution systems. In this paper, a novel framework for comprehensive model validation is described. The proposed application, the Model Validator, ensures that a model is both consistent and feasible by validating the derivative static and operational network model. A modular architecture for the application has been implemented and integrated with an open-source standards-based platform for ADMS application development, GridAPPS-D, allowing new validation capability to be added with minimal time and effort. The Model Validator application is demonstrated on the IEEE 13-bus, 123-bus, and 8500-node test cases over three validation scenarios.

Poudel, Shiva↗
DOE OSTI2017

Hierarchical calibration and validation for modeling bench-scale solvent-based carbon capture. Part 1: Non-reactive physical mass transfer across the wetted wall column

A hierarchical model calibration and validation are proposed here for quantifying the confidence level of mass transfer prediction using a computational fluid dynamics (CFD) model, where the solvent-based carbon dioxide (CO 2 ) capture is simulated and the predicted results are compared to the corresponding bench-scale experimental data. Two unit problems with an increasing level of complexity are proposed to break down the complex physical/chemical processes of solvent-based CO 2 capture into relatively simpler problems to separate the effects of physical transport and chemical reaction. This paper focuses on the calibration and validation of the first unit problem, i.e., the CO 2 mass transfer across a falling ethanolamine (MEA) film in the absence of chemical reaction. This problem is investigated both experimentally and numerically using non-reactive nitrous oxide (N 2 O) as a surrogate for CO 2 . To capture motion of the gas-liquid interface, a volume of fluid method is employed with a one-fluid formulation to compute the mass transfer between the two phases. Parallel bench-scale experiments are designed and conducted to validate and calibrate the CFD models using a general Bayesian calibration approach. Two important transport parameters, Henry's constant and gas diffusivity, are calibrated to produce the posterior distributions, which will be used as input for the second unit problem to address the chemical absorption of CO 2 across the MEA falling film, where both mass transfer and chemical reaction are involved. Finally, mass transfer coefficients predicted by CFD are also compared with those predicted by the traditional/empirical correlations under both steady and wavy falling film conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

WEC-SIM Phase 1 Validation Testing -- Numerical Modeling of Experiments: Preprint

The Wave Energy Converter Simulator (WEC-Sim) is an open-source code jointly developed by Sandia National Laboratories and the National Renewable Energy Laboratory. It is used to model wave energy converters subjected to operational and extreme waves. In order for the WEC-Sim code to be beneficial to the wave energy community, code verification and physical model validation is necessary. This paper describes numerical modeling of the wave tank testing for the 1:33-scale experimental testing of the floating oscillating surge wave energy converter. The comparison between WEC-Sim and the Phase 1 experimental data set serves as code validation. This paper is a follow-up to the WEC-Sim paper on experimental testing, and describes the WEC-Sim numerical simulations for the floating oscillating surge wave energy converter.

16 TIDAL AND WAVE POWER↗
DOE OSTI2016

Hierarchical Multi-Scale Approach To Validation and Uncertainty Quantification of Hyper-Spectral Image Modeling

Validating predictive models and quantifying uncertainties inherent in the modeling process is a critical component of the HARD Solids Venture program [1]. Our current research focuses on validating physics-based models predicting the optical properties of solid materials for arbitrary surface morphologies and characterizing the uncertainties in these models. We employ a systematic and hierarchical approach by designing physical experiments and comparing the experimental results with the outputs of computational predictive models. We illustrate this approach through an example comparing a micro-scale forward model to an idealized solid-material system and then propagating the results through a system model to the sensor level. Our efforts should enhance detection reliability of the hyper-spectral imaging technique and the confidence in model utilization and model outputs by users and stakeholders.

Engel, David W.↗
DOE OSTI2017

Modelling and validation of particle size distributions of supported nanoparticles using the pair distribution function technique

The particle size of supported catalysts is a key characteristic for determining structure–property relationships. It is a challenge to obtain this information accurately and in situ using crystallographic methods owing to the small size of such particles (<5 nm) and the fact that they are supported. In this work, the pair distribution function (PDF) technique was used to obtain the particle size distribution of supported Pt catalysts as they grow under typical synthesis conditions. The PDF of Pt nanoparticles grown on zeolite X was isolated and refined using two models: a monodisperse spherical model (single particle size) and a lognormal size distribution. The results were compared and validated using scanning transmission electron microscopy (STEM) results. Both models describe the same trends in average particle size with temperature, but the results of the number-weighted lognormal size distributions can also accurately describe the mean size and the width of the size distributions obtained from STEM. Since the PDF yields crystallite sizes, these results suggest that the grown Pt nanoparticles are monocrystalline. This work shows that refinement of the PDF of small supported monocrystalline nanoparticles can yield accurate mean particle sizes and distributions.

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

A comprehensive framework for validating simulation models of power system equipment using terminal measurements

Accurate simulation of power-plants is essential to the planning and operation of modern power grids. The current methods used to periodically check power-plant simulation models have many open questions about their limitations and accuracy. The research in this project explored using Monte-Carlo Experimentation (MCE) as a means for answering these important questions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

DIII-D research advancing the physics basis for optimizing the tokamak approach to fusion energy

DIII-D physics research addresses critical challenges for the operation of ITER and the next generation of fusion energy devices. This is done through a focus on innovations to provide solutions for high performance long pulse operation, coupled with fundamental plasma physics understanding and model validation, to drive scenario development by integrating high performance core and boundary plasmas. Substantial increases in off-axis current drive efficiency from an innovative top launch system for EC power, and in pressure broadening for Alfven eigenmode control from a co-/counter-I p steerable off-axis neutral beam, all improve the prospects for optimization of future long pulse/steady state high performance tokamak operation. Fundamental studies into the modes that drive the evolution of the pedestal pressure profile and electron vs ion heat flux validate predictive models of pedestal recovery after ELMs. Understanding the physics mechanisms of ELM control and density pumpout by 3D magnetic perturbation fields leads to confident predictions for ITER and future devices. Validated modeling of high-Z shattered pellet injection for disruption mitigation, runaway electron dissipation, and techniques for disruption prediction and avoidance including machine learning, give confidence in handling disruptivity for future devices. For the non-nuclear phase of ITER, two actuators are identified to lower the L–H threshold power in hydrogen plasmas. With this physics understanding and suite of capabilities, a high poloidal beta optimized-core scenario with an internal transport barrier that projects nearly to Q = 10 in ITER at ~8 MA was coupled to a detached divertor, and a near super H-mode optimized-pedestal scenario with co-I p beam injection was coupled to a radiative divertor. The hybrid core scenario was achieved directly, without the need for anomalous current diffusion, using off-axis current drive actuators. Also, a controller to assess proximity to stability limits and regulate β N in the ITER baseline scenario, based on plasma response to probing 3D fields, was demonstrated. Finally, innovative tokamak operation using a negative triangularity shape showed many attractive features for future pilot plant operation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗