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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Evaluation of lithium as a tritium storage medium for betavoltaics

Lithium foils were demonstrated to absorb surrogate protium for tritium-powered betavoltaics. 20μm thick lithium foils were hole-punched from a ribbon of electrodeposited lithium on copper foil. The lithium foils were loaded with hydrogen in a custom Sievert apparatus where the pressure drop showed full hydriding at a hydrogen pressure of 2 bar and at all loading temperatures above the lithium melting point at 190, 200, 225, 250, and 300. Lithium hydride formation was confirmed with Raman spectroscopy after hydrogen loading. The kinetics of experimental hydride formation was compared to the diffusion-limited Mintz–Bloch model. While the Mintz–Bloch model showed good fit with the experimental loadings, the model overpredicted the loading kinetics starting at 250 °C and at higher temperatures. In conclusion, The overprediction was either caused by lithium hydride outgassing due to some reduction with some residual lithium hydroxide created from brief air exposure when sealing the lithium in the reactor or a transition from diffusion-limited hydride growth to surface or metal–hydride interface-limited hydride growth.

25 ENERGY STORAGE↗
DOE OSTI2014

The Heuristic Static Load-Balancing Algorithm Applied to the Community Earth System Model

We propose to use the heuristic static loadbalancing (HSLB) algorithm for solving load-balancing problems in the Community Earth System Model (CESM), a climate model, using fitted benchmark data as an alternative to the current manual approach. The problem of allocating the optimal number of CPU cores to CESM components is formulated as a mixed-integer nonlinear optimization problem which is solved by using an optimization branch-and-bound solver implemented in the MINLP package MINOTAUR. The key feature of the branch-and- bound method is that it guarantees to provide an optimal solution or show that none exists. Our algorithm was tested for the 1 degrees and 1/8 degrees resolution simulations on 32,768 nodes (131,072 cores) of IBM Blue Gene/P where we consistently achieved well load-balanced results. This work is a part of a broader effort to eliminate the need for manual tuning of the code for each platform and simulation type, improve the performance and scalability of CESM, and develop automated tools to achieve these goals.

Alekseev, Yury↗
DOE OSTI2018

Discrete element modeling of deformable pinewood chips in cyclic loading test

The design of efficient lignocellulosic biomass feedstock systems is challenging, as current laboratory characterization and design methods were developed primarily for fine powders with relatively low compressibility. Here, the discrete element method (DEM) is gaining prominence as an alternative method for modeling the bulk flow and transport of particulate materials in hoppers and feeders. However, prior DEM simulations investigating the flow of wood chips modeled the particles as simple rigid geometries such as spheres, rods or blocks, and neglected the effects of particle deformability and irregular shapes. As a consequence, those simplified DEM models may not provide enough key diagnosis to help improve the design of biomass feeding and handling equipment. This work presents a bonded-sphere DEM approach for characterizing the mechanical behavior of bulk flexible, deformable pinewood chips in a cyclic stress loading test. Clustered spheres that can bend and twist via elastic bonds are used to model irregular-shape particles in real pinewood chip samples. An axial compression tester, which contains 0.06 million bonded-sphere particles (1.35 million spheres) in a quarter cylinder, is simulated with a domain size similar to the experiments. With careful calibration, the simulations have delivered the bulk densities and the bulk moduli of elasticity that are in good agreement with those measured in the corresponding experiments. However, it is also been found challenging for the present DEM model to accurately predict the overall stress-strain behavior of bulk pinewood chips, especially the large sustained plastic deformation during unloading. Additional numerical tests have shown that the adjustment in certain contact parameters (e.g. bond stiffness) can lead to profound solution improvement, but meanwhile will induce extra challenges such as increased computing time. Future work will include an elasto-plastic particle bond model to enhance the simulation fidelity.

42 ENGINEERING↗
DOE OSTI2024

Understanding early HIV-1 rebound dynamics following antiretroviral therapy interruption: The importance of effector cell expansion

Most people living with HIV-1 experience rapid viral rebound once antiretroviral therapy is interrupted; however, a small fraction remain in viral remission for an extended duration. Understanding the factors that determine whether viral rebound is likely after treatment interruption can enable the development of optimal treatment regimens and therapeutic interventions to potentially achieve a functional cure for HIV-1. We built upon the theoretical framework proposed by Conway and Perelson to construct dynamic models of virus-immune interactions to study factors that influence viral rebound dynamics. We evaluated these models using viral load data from 24 individuals following antiretroviral therapy interruption. The best-performing model accurately captures the heterogeneity of viral dynamics and highlights the importance of the effector cell expansion rate. Our results show that post-treatment controllers and non-controllers can be distinguished based on the effector cell expansion rate in our models. Furthermore, these results demonstrate the potential of using dynamic models incorporating an effector cell response to understand early viral rebound dynamics post-antiretroviral therapy interruption.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

District-Scale Analysis of Electricity Load and Strategies to Improve Energy Reliability Using Prototype District Models

Projected increases in electricity demand in the U.S. highlight the urgent need for effective load management to ensure grid reliability. As the building sector accounts for approximately 75% of electricity usage, enhancing energy efficiency and flexibility in this sector is crucial. Adopting district-level approaches offers significant advantages over traditional individual building analyses by enabling shared infrastructure and economies of scale. To navigate the data and computational challenges associated with modeling energy at the district level, prototype district models have been proposed as holistic, system-level solutions that capture complex interactions within typical configurations. This study presents these models as a reference tool for analyzing district-scale energy systems across various climate zones in the U.S. Developed with input from stakeholders, these models integrate varied building characteristics, inter-building connections, and energy system interactions. A case study utilizing the Urban Edge prototype district model, implemented on the URBANopt™ platform, evaluates multiple demand scenarios and the impact of distributed energy resources such as fuel-fired backup generators, photovoltaic systems, and batteries. Findings suggest that while new electric systems can significantly reduce annual energy use, they may also elevate peak electricity loads, with a notable 43% increase in heating-dominant climate zone 5B. The optimal backup power solutions vary based on location, influenced by factors such as utility rates and incentives. For example, PV and batteries perform well in high-cost regions like New York City, while diesel backup generators are more suitable for backup needs in climate zone 3A, such as Atlanta. Thus, this research highlights the importance of prototype district models for future district-scale energy planning.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2012

Seismic Loading for FAST: May 2011 — August 2011

As more wind farms are constructed in seismically active regions, earthquake loading increases in prominence for design and analysis of wind turbines. Early investigation of seismic load tended to simplify the rotor and nacelle as a lumped mass on top of the turbine tower. This simplification allowed the use of techniques developed for conventional civil structures, such as buildings, to beeasily applied to wind turbines. However, interest is shifting to more detailed models that consider loads for turbine components other than the tower. These improved models offer three key capabilities in consideration of base shaking for turbines: 1) The inclusion of aerodynamics and turbine control; 2) The ability to consider component loads other than just tower loads; and 3) An improvedrepresentation of turbine response in higher modes by reducing modeling simplifications. Both experimental and numerical investigations have shown that, especially for large modern turbines, it is important to consider interaction between earthquake input, aerodynamics, and operational loads. These investigations further show that consideration of higher mode activity may be necessary in theanalysis of the seismic response of turbines. Since the FAST code is already capable of considering these factors, modifications were developed that allow simulation of base shaking. This approach allows consideration of this additional load source within a framework, the FAST code that is already familiar to many researchers and practitioners.

17 WIND ENERGY↗
DOE OSTI2019

Within-host infectious disease models accommodating cellular coinfection, with an application to influenza

Within-host models are useful tools for understanding the processes regulating viral load dynamics. While existing models have considered a wide range of within-host processes, at their core these models have shown remarkable structural similarity. Specifically, the structure of these models generally consider target cells to be either uninfected or infected, with the possibility of accommodating further resolution (e.g. cells that are in an eclipse phase). Recent findings, however, indicate that cellular coinfection is the norm rather than the exception for many viral infectious diseases, and that cells with high multiplicity of infection are present over at least some duration of an infection. The reality of these cellular coinfection dynamics is not accommodated in current within-host models although it may be critical for understanding within-host dynamics. This is particularly the case if multiplicity of infection impacts infected cell phenotypes such as their death rate and their viral production rates. Here, we present a new class of within-host disease models that allow for cellular coinfection in a scalable manner by retaining the low-dimensionality that is a desirable feature of many current within-host models. The models we propose adopt the general structure of epidemiological ‘macroparasite’ models that allow hosts to be variably infected by parasites such as nematodes and host phenotypes to flexibly depend on parasite burden. Specifically, our within-host models consider target cells as ‘hosts’ and viral particles as ‘macroparasites’, and allow viral output and infected cell lifespans, among other phenotypes, to depend on a cell’s multiplicity of infection. We show with an application to influenza that these models can be statistically fit to viral load and other within-host data, and demonstrate using model selection approaches that they have the ability to outperform traditional within-host viral dynamic models. Important in vivo quantities such as the mean multiplicity of cellular infection and time-evolving reassortant frequencies can also be quantified in a straightforward manner once these macroparasite models have been parameterized. The within-host model structure we develop here provides a mathematical way forward to address questions related to the roles of cellular coinfection, collective viral interactions, and viral complementation in within-host viral dynamics and evolution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

3D-FE Modeling of 316 SS under Strain-Controlled Fatigue Loading and CFD Simulation of PWR Surge Line

In financial year 2017, we are focusing on developing a mechanistic fatigue model of surge line pipes for pressurized water reactors (PWRs). To that end, we plan to perform the following tasks: (1) conduct stress- and strain-controlled fatigue testing of surge-line base metal such as 316 stainless steel (SS) under constant, variable, and random fatigue loading, (2) develop cyclic plasticity material models of 316 SS, (3) develop one-dimensional (1D) analytical or closed-form model to validate the material models and to understand the mechanics associated with 316 SS cyclic hardening and/or softening, (4) develop three-dimensional (3D) finite element (FE) models with implementation of evolutionary cyclic plasticity, and (5) develop computational fluid dynamics (CFD) model for thermal stratification, thermal-mechanical stress, and fatigue of example reactor components, such as a PWR surge line under plant heat-up, cool-down, and normal operation with/without grid-load-following. This semi-annual progress report presents the work completed on the above tasks for a 316 SS laboratory-scale specimen subjected to strain-controlled cyclic loading with constant, variable, and random amplitude. This is the first time that the accurate 3D-FE modeling of the specimen for its entire fatigue life, including the hardening and softening behavior, has been achieved. We anticipate that this work will pave the way for the development of a fully mechanistic-computer model that can be used for fatigue evaluation of safety-critical metallic components, which are traditionally evaluated by heavy reliance on time-consuming and costly test-based approaches. This basic research will not only help the nuclear reactor industry for fatigue evaluation of reactor components in a cost effective and less time-consuming way, but will also help other safety-related industries, such as aerospace, which is heavily dependent on test-based approaches, where a single full-scale fatigue test can cost millions of dollars and require years of effort to conduct. Toward our goal of demonstration of fully mechanistic fatigue evaluation of reactor components, we also started work on developing a component-level computer model of reactor components, such as 316 SS surge line pipe. This requires developing a thermal-mechanical stress analysis model of the reactor surge line, which, in turn, requires time-dependent temperature and stratification information along the boundary of the pipe. Toward that goal, CFD models of surge lines are being developed. In this report, we also present some preliminary results showing the temperature conditions along the surge line wall under reactor heat-up, cool-down, and steady-state power operation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Experimental Evaluation of PV Inverter Anti-Islanding with Grid Support Functions in Multi-Inverter Island Scenarios

As PV and other DER systems are connected to the grid at increased penetration levels, island detection may become more challenging for two reasons: 1.) In islands containing many DERs, active inverter-based anti-islanding methods may have more difficulty detecting islands because each individual inverter's efforts to detect the island may be interfered with by the other inverters in the island. 2.) The increasing numbers of DERs are leading to new requirements that DERs ride through grid disturbances and even actively try to regulate grid voltage and frequency back towards nominal operating conditions. These new grid support requirements may directly or indirectly interfere with anti-islanding controls. This report describes a series of tests designed to examine the impacts of both grid support functions and multi-inverter islands on anti-islanding effectiveness. Crucially, the multi-inverter anti-islanding tests described in this report examine scenarios with multiple inverters connected to multiple different points on the grid. While this so-called 'solar subdivision' scenario has been examined to some extent through simulation, this is the first known work to test it using hardware inverters. This was accomplished through the use of power hardware-in-the-loop (PHIL) simulation, which allows the hardware inverters to be connected to a real-time transient simulation of an electric power system that can be easily reconfigured to test various distribution circuit scenarios. The anti-islanding test design was a modified version of the unintentional islanding test in IEEE Standard 1547.1, which creates a balanced, resonant island with the intent of creating a highly challenging condition for island detection. Three common, commercially available single-phase PV inverters from three different manufacturers were tested. The first part of this work examined each inverter individually using a series of pure hardware resistive-inductive-capacitive (RLC) resonant load based anti-islanding tests to determine the worst-case configuration of grid support functions for each inverter. A grid support function is a function an inverter performs to help stabilize the grid or drive the grid back towards its nominal operating point. The four grid support functions examined here were voltage ride-through, frequency ride-through, Volt-VAr control, and frequency-Watt control. The worst-case grid support configuration was defined as the configuration that led to the maximum island duration (or run-on time, ROT) out of 50 tests of each inverter. For each of the three inverters, it was observed that maximum ROT increased when voltage and frequency ride-through were activated. No conclusive evidence was found that Volt-VAr control or frequency-Watt control increased maximum ROT. Over all single-inverter test cases, the maximum ROT was 711 ms, well below the two-second limit currently imposed by IEEE Standard 1547-2003. A subsequent series of 244 experiments tested all three inverters simultaneously in the same island. These tests again used a procedure based on the IEEE 1547.1 unintentional islanding test to create a difficult-to-detect island condition. For these tests, which used the two worst-case grid support function configurations from the single-inverter tests, the inverters were connected to a variety of island circuit topologies designed to represent the variety of multiple-inverter islands that may occur on real distribution circuits. The interconnecting circuits and the resonant island load itself were represented in the real-time PHIL model. PHIL techniques similar to those employed here have been previously used and validated for anti-islanding tests, and the PHIL resonant load model used in this test was successfully validated by comparing single-inverter PHIL tests to conventional tests using an RLC load bank.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Operating a commercial building HVAC load as a virtual battery through airflow control

Virtual battery (VB) is an innovative method to model flexibility of building loads and effectively coordinate them with other resources at a system level. Unlike a real battery with a dedicated power conversion system for charging control, methods are required for operating building loads to deviate from the baseline to respond to grid signals. This paper presents a VB control for a commercial heating, ventilation, and air conditioning (HVAC) system to follow the desired power consumption in real-time by adjusting zonal airflow rates. The proposed method consists of two parts. At the system level, a mixed feedforward and feedback control is used to estimate the desired total airflow rate. At the zone level, two priority-based algorithms are then proposed to distribute the total airflow rate to individual zones. In particular, a zonal airflow limit estimation method is proposed using machine-learning techniques, in contrast to physics-based thermal models in existing studies, to more accurately capture zonal thermal dynamics and improve temperature control performance. An office building on the Pacific Northwest National Laboratory campus is implemented in EnergyPlus, and used to illustrate and validate the proposed control.

Wang, Jiyu↗
DOE OSTI2020

Thermal Overloading Risk Mitigation With a Semi-Analytical Probabilistic Model on Branch Current

A semi-analytical formulation is presented in this paper for the probability computation of branch current in multiphase systems. The developed formula is derived based on the linear power flow model in rectangular coordinates. The system uncertainty injections can be renewable energy resources or loads and are modeled using a Gaussian mixture model (GMM). The developed formula can be used to compute the line current violation probability as well as integrate into optimal power flow problem as chance-constraint relaxation. Here, the proposed formula is first compared with the Matlab embedded numerical integration function to show its performance. Besides, the semi-analytical formula is validated and compared with the Monte Carlo simulation method using the IEEE 123-bus system, EPRI Ckt5, and Ckt7 systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Building thermal load prediction through shallow machine learning and deep learning

Building thermal load prediction informs the optimization of cooling plant and thermal energy storage. Physics-based prediction models of building thermal load are constrained by the model and input complexity. In this study, we developed 12 data-driven models (7 shallow learning, 2 deep learning, and 3 heuristic methods) to predict building thermal load and compared shallow machine learning and deep learning. The 12 prediction models were compared with the measured cooling demand. It was found XGBoost (Extreme Gradient Boost) and LSTM (Long Short Term Memory) provided the most accurate load prediction in the shallow and deep learning category, and both outperformed the best baseline model, which uses the previous day's data for prediction. Then, we discussed how the prediction horizon and input uncertainty would influence the load prediction accuracy. Major conclusions are twofold: first, LSTM performs well in short-term prediction (1 h ahead) but not in long term prediction (24 h ahead), because the sequential information becomes less relevant and accordingly not so useful when the prediction horizon is long. Second, the presence of weather forecast uncertainty deteriorates XGBoost's accuracy and favors LSTM, because the sequential information makes the model more robust to input uncertainty. Training the model with the uncertain rather than accurate weather data could enhance the model's robustness. Finally, our findings have two implications for practice. First, LSTM is recommended for short-term load prediction given that weather forecast uncertainty is unavoidable. Second, XGBoost is recommended for long term prediction, and the model should be trained with the presence of input uncertainty.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Identification Uncertainty in Inverse Material Model Parameter Determination: A Sensitivity‐Based Decision Process for Load Path Selection

This research proposes a sensitivity-based framework for selecting the optimal prescribed loading path for a biaxial cruciform specimen. Optimality here is determined by the direction and magnitude of the prescribed displacement that minimizes the influence of random noise on the material model parameter identification. Using simulated experimental data based on finite element simulation, in this work, we identify the material model parameters of a Ludwik hardening model and plane stress implementation of the Hill-48 yield criterion using finite element model updating (FEMU). Our analysis reveals that the identification (or estimator) uncertainty of model parameters depends on the displacement boundary conditions (i.e., loading sequence) and the ground-truth value of the individual parameters. Optimal experimental design (OED) criteria based on the Fisher information matrix were investigated to mitigate indecision in the choice of optimal load path when the identification uncertainty of different material model parameters optimized at different load paths. The determinant of the Fisher information matrix was chosen here as the more useful metric due to its ability to capture uncertainty of the most influential material model parameters. The proposed framework demonstrates potential for real-time automated load step selection using scalar criteria derived prior to mechanical loading. The framework can be generalized to other geometries, boundary conditions and material models, allowing this procedure to be utilized for different experimental configurations and materials.

Fayad, Samuel S. [University of Illinois at Urbana↗
DOE OSTI2023

Simulink Model of a New Energy EVG-005 5kW Hydropower Turbine

Simulink model for a New Energy 5kW hydropower turbine. ADCP data ("ds_streamwise_7_13.nc") and DC voltage, DC current, and rotor rotation observed from the New Energy EVG-005 Current Energy Converter (CEC) ("electrical_7_13_10ohms.nc") were collected at the Tanana River Test Site (TRTS) near Nenana Alaska. - Data was collected on July 13th, 2023 with a constant 10 ohms resistance applied with a DC load bank. - Simulink model is meant to resemble the electrical setup at the TRTS. - Model is initialized by running the "NewEnergy_2023_10hz.m" Matlab script. Then the Simulink model ("New_Energy_Model_PMSM.slx") can be run. - Results are processed with the "NewEnergy_2023_processing.m" Matlab code. The Matlab results are also saved in the "New_Energy_7_13_model_validation_results.mat" Matlab file. This can be directly loaded into the Matlab Workspace using the "Load()" command. - The timetable variables "electrical_model_downsampled" is the model results and the "electrical_limited" is the experimental data from the TRTS.

16 TIDAL AND WAVE POWER↗
DOE OSTI2022

Hierarchical Model-Free Transactive Control of Residential Building Loads: An Actual Deployment

The transformation of electricity systems into more sustainable configurations brought some new challenges. The uncertain, intermittent, and variable nature of renewable energy sources require a significant amount of load demand flexibility, in which grid-interactive buildings (GEBs) are important flexible assets for electricity systems. In this regard, many demand response (DR) tools have been developed to harness this demand flexibility. However, such tools are mostly simulation-based or deal with a single load, which may not be sufficient to demonstrate their effectiveness. Towards this end, this paper presents a real-world field implementation and testing of a hierarchical model-free transactive DR control approach on actual GEBs. The control implementation incorporates elements of virtual battery, game theory, and model-free control mechanisms. The proposed approach was tested using a total of five GEBs, each having three zones. The results show that the proposed approach can mostly achieve all intended objectives, including flexibility estimation, peak load reduction, power tracking, and controlling GEBs while maintaining occupants’ comfort.

Amasyali, Kadir↗
DOE OSTI2011

Nuclear Graphite - Fracture Behavior and Modeling

Evidence for the graphite fracture mechanism is reviewed and discussed. The roles of certain microstructural features in the graphite fracture process are reported. The Burchell fracture model is described and its derivation reported. The successful application of the fracture model to uniaxial tensile data from several graphites with widely ranging structure and texture is reported. The extension of the model to multiaxial loading scenarios using two criteria is discussed. Initially, multiaxial strength data for H-451 graphite were modeled using the fracture model and the Principle of Independent Action. The predicted 4th stress quadrant failure envelope was satisfactory but the 1st quadrant predictions were not conservative and thus were unsatisfactory. Multiaxial strength data from the 1st and 4th stress quadrant for NBG-18 graphite are reported. To improve the conservatism of the predicted 1st quadrant failure envelope for NBG-18 the Shetty criterion has been applied to obtain the equivalent critical stress intensity factor, KIc (Equi), for each applied biaxial stress ratio. The equivalent KIc value is used in the Burchell fracture model to predict the failure envelope. The predicted 1st stress quadrant failure envelope is conservative and thus more satisfactory than achieved previously using the fracture model combined with the Principle of Independent Action.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Gearbox Reliability Collaborative: Test and Model Investigation of Sun Orbit and Planet Load Share in a Wind Turbine Gearbox; Preprint

This paper analyzes experimental measurement of the sun gear orbit in dynamometer testing and describes its relation to the other measured responses of the planetary stage. The relation of the sun orbit to component runout, component flexibility, gear coupling alignment, planet load share, and planet position error will be investigated. Equations describing the orbit of the sun gear in the testcases are derived. Rigid and flexible multibody models of the full gearbox are investigated and compared to sun and planet measurements. This paper shows that the sun gear's path may be influenced by gear coupling responses and gearbox structural flexibilities.

17 WIND ENERGY↗