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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Intracycle RPM control for vertical axis wind turbines

The wind energy market is currently dominated by horizontal axis wind turbines (HAWTs); however, vertical axis wind turbines (VAWTs) are emerging as a design alternative, especially for deep-water offshore siting due to their low center of gravity, ease of access to drivetrain components, and overall simplicity. Due to the absence of a pitch mechanism in large-scale Darrieus VAWTs, stall control has often been used to manage power and loads. Introducing a pitching mechanism in H-type VAWTs has been studied, but this diminishes the mechanical simplicity advantage, and the use of a pitching mechanism in a large-scale Darrieus-type VAWT is not practical. This work examines an innovative, alternative method to control the rotor dynamics of a large-scale 5 MW VAWT to maximize power while constraining loads without introducing any new or complex mechanical elements. This control strategy is termed intracycle revolution per minute (RPM) control, where the rotational speed of the turbine is allowed to vary in an optimal fashion with the azimuthal location of blades as opposed to typical constant RPM operation. An optimization framework is formulated for an open-loop optimal control problem and solved to maximize power subject to constraints on aerodynamic design loads. Results are presented to demonstrate the benefits and the performance limits of intracycle RPM control for large-scale 5 MW Darrieus VAWTs, namely, (1) power production (quantified in terms of AEP) that can be increased subject to baseline load limits and (2) opportunities to significantly increase AEP or decrease loads via intracycle RPM control that are examined for both two-bladed and three-bladed VAWTs.

17 WIND ENERGY↗
DOE OSTI2025

Uncertainty quantification of a physics-informed model based on sparse identification of a Thermal Energy Distribution System

Integrated energy systems (IES)s are crucial for enhancing the economy and efficiency of power generation sources (e.g., nuclear energy) necessary to unleash American energy dominance. These systems can be integrated with thermal energy storage (TES) and intermittent renewable energies to optimize overall energy use, peak-load regulation, and demand-side responses. However, the stabilization of energy generation, transport, and utilization introduces operational complexities that exceed the challenges of managing each sub-component individually. Currently, though IESs rely on human operators for efficiency and stability, reducing human error risk and enhancing performance through automation is highly desirable. Recent advances at Idaho National Laboratory have demonstrated successful control of the Thermal Energy Distributed System (TEDS). However, the automatic control system depends on a deterministic Sparse Identification of Nonlinear Dynamics with Control (SINDyC) model, which are trained based on simulation data from physics-based simulations. Because of uncertainties in physics-based simulation, SINDyC model results in large discrepancies against experimental data and cannot be reliably used in automatic control. In this paper, we present an innovative approach to address these discrepancies by quantifying uncertainties and developing a more robust model. We first generated trajectories by using first-principles physics codes to encapsulate the experiment. Next, we trained thousands of models by randomly sampling these trajectories. We then collapsed all those models into one probabilistic SINDyC by fitting a multivariate Gaussian distribution onto the resulting coefficient’s distribution. Despite its simplicity, our approach successfully produced 95% confidence intervals that captured the experimental trajectories. It even did so with a higher probability and better U-pooling score across six of the seven relevant quantities of interest (QoIs), as compared to other classical approaches. In conclusion, ongoing research is focusing on generating new experimental trajectories to validate this approach, and on employing Bayesian calibration to refine parametric uncertainties and guide future model development efforts.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Demand response event simulator and risk-aware bidding tool for industrial customers

Incentive Based Demand Response (IBDR) program participation delivers financial benefits to the consumers and resiliency benefits to the electricity grid. Effectively participating in these programs as an industrial consumer requires bidding strategies that balance financial risk with operational constraints. Existing bidding tools tend not to fully incorporate stochastic IBDR event modeling, program specific baseline and payment/penalty calculations, or demand reduction process control schemes that account for the cascading impacts of shutdown in complex facilities. Here, this work presents an IBDR event simulator and risk-aware bidding framework tool integrating three key components: a flexible, parameterized demand response event generator that rigorously accounts for program structures and stochasticity, a demand response operational simulation model that generates explicit control strategies for load reduction, and a Monte Carlo simulator to evaluate financial risk for varied capacity bids. A case study at a wastewater treatment plant participating in PG&E's Capacity Bidding Program demonstrates the framework's utility. In the peak capacity price month of August, optimal bidding by the wastewater treatment plant nets a mean IBDR benefit of $101,000 (67% of the August electricity bill) with 0.4% probability of a financial loss. This framework enables industrial operators to make informed bidding decisions, negotiate better program terms with demand response load aggregators, and analyze energy flexibility investments at their facilities. Ultimately, this work reduces participation barriers in IBDR programs and supports the broader goal of enhancing grid reliability and renewable energy integration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

MHD flow in liquid metal blankets: Major design issues, MHD guidelines and numerical analysis

The design of breeding blankets represents the major challenge for fusion reactor engineering because of performance requirements and severe operating conditions in terms of heat load and neutron flux. Liquid metal alloys such as lead-lithium, due to their lithium content, can be used to breed tritium, one of the plasma fuel components, and owing to their high thermal conductivity, they may serve as coolants. On the other hand, there are technical issues related to the fact that the liquid metals are electrically conducting and interact with the plasma-confining magnetic field. Induced electric currents and generated electromagnetic forces affect velocity and pressure distribution in the blankets. Magnetohydrodynamic (MHD) flows for fusion applications have been often investigated in simplified geometries, such as pipes, ducts, bends, with focus on their fundamental features. These analyses are essential, since results remain valid as background for the development of blanket designs, even when a concept is dismissed. However, the conceptual study of fusion blankets requires to take into account the global multiple effects, that arise when the full system is considered. Progress made in fusion-related MHD research results from combined numerical and experimental activities. In this paper we review and summarize features of 2D and 3D MHD flows that are typical in liquid metal blankets, together with available correlations for MHD pressure losses. This knowledge can provide simple design MHD guidelines that support a preliminary estimate of MHD effects in a blanket concept, in terms of pressure drop and flow distribution.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Analysis of fast-ion losses measured in MAST-U via infrared thermography and a Fast Ion Loss Detector

Fast-ion losses need to be monitored to avoid damage to plasma facing components. In existing experimental devices, the scintillator-based fast-ion loss detector (FILD) is the most advanced diagnostic for measuring fast-ion losses. However, FILDs provide only local information about the losses. Infrared (IR) thermography can be used as a complementary tool for more global monitoring of the deposition of fast-ion losses on the wall, at the expense of no velocity-space resolution. IR cameras measure the temperature of the plasma facing components. This measurement, determined by a combined effect of the thermal plasma, radiation, neutrons and fast-ion losses, can be decomposed to infer the fast-ion load on the tokamak wall. In this manuscript, a workflow to estimate fast-ion losses via IR thermography is applied to the MAST-U spherical tokamak, using a 1D approximation to extract the experimental heat flux on the FILD front face from IR data. To numerically estimate the different contributions to this total heat flux, the field-line tracing environment SMITER is used to calculate the thermal plasma contribution, the orbit-following Monte-Carlo code ASCOT to estimate the fast-ion losses, and bolometry measurements for the radiation. To validate the workflow, two discharges, L-mode plasmas with low MHD activity, were executed using on and off-axis beams, respectively. The experimentally and numerically estimated heat flux are of the same order of magnitude for the on-axis heated scenario, with a strong dependence of the estimated fast-ion losses contribution on the fit to the kinetic profiles used as input. This is also true for the off-axis heated scenario, where the total numerically estimated heat flux is 2.1 or 1.3 times higher than the maximum experimentally estimated heat flux, depending on the ASCOT input used.

FILD↗
DOE OSTI2022

Machine learning changes the rules for flux limiters

Learning to integrate non-linear equations from highly resolved direct numerical simulations has seen recent interest for reducing the computational load for fluid simulations. Here, we focus on determining a flux-limiter for shock capturing methods. Focusing on flux limiters provides a specific plug-and-play component for existing numerical methods. Since their introduction, an array of flux limiters has been designed. Using the coarse-grained Burgers' equation, we show that flux-limiters may be rank-ordered in terms of their log-error relative to high-resolution data. We then develop a theory to find an optimal flux-limiter and present flux-limiters that outperform others tested for integrating Burgers' equation on lattices with [Formula: see text], and 2x, 3x, 4x, and 8x coarse-grainings. We train a continuous piecewise linear limiter by minimizing the mean-squared misfit to six-grid point segments of high-resolution data, averaged over all segments. While flux limiters are generally designed to have an output of φ(r) = 1 at a flux ratio of r = 1, our limiters are not bound by this rule and yet produce a smaller error than standard limiters. Here we find that our machine learned limiters have distinctive features that may provide new rules-of-thumb for the development of improved limiters. Additionally, we use our theory to learn flux-limiters that outperform standard limiters across a range of values (as opposed to at a specific fixed value) of coarse-graining, number of discretized bins, and diffusion parameter. This demonstrates the ability to produce flux limiters that should be more broadly useful than standard limiters for general applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Structural Design and Modeling of MARVEL Primary Coolant System Using the ASME Section III, Division 5, Code

This paper presents the structural design and supporting analysis for the Microreactor Applications Research Validation and Evaluation (MARVEL) primary coolant system (PCS) using the American Society of Mechanical Engineers (ASME) Boiler and Pressure Vessel Code Section III, Division 5, rules. MARVEL is a liquid metal–cooled microreactor intended to provide experimental capabilities for the rapid testing and development of microreactor technologies. The PCS utilizes high-temperature sodium-potassium liquid metal as the primary coolant and operates at a design temperature of 570°C, necessitating the consideration of creep-related failure mechanisms. The base metal for the PCS is 316H stainless steel, and the weldments are made with a 16-8-2 filler. The design approach incorporates the current base code rules along with ASME code cases N-924, N-861, and N-862 to address primary load, ratcheting, and creep-fatigue evaluations, respectively. The reactor’s operation involves complex thermal and mechanical interactions due to natural convective flow and differential thermal expansion between components. In conclusion, this paper discusses the structural engineering challenges encountered, such as managing thermal stresses in the distribution plenum and guard vessel, and outlines the strategies implemented to meet the code requirements, including design modifications and operational constraints.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
DOE OSTI2020

Mitigating Cascading Outages in Severe Weather Using Simulation-Based Optimization

Severe weather events can trigger cascading power outages and lead to significant losses. In this work, we investigate cascading outage mitigation under severe weather conditions. Given day-ahead weather forecasts and component failure models, we aim to identify a set of power lines that can be hardened to minimize the expected impact of potential cascading outages. Since the expected load shedding cannot be expressed as an explicit function of line hardening decisions and system states, we developed a cascading outage simulator to estimate the expected value of load shedding under various initial weather-related disruption scenarios generated using a weather forecast. To avoid massive enumeration of all possible combinations of line hardening decisions and reduce the simulation efforts, we employed an efficient simulation-based optimization approach that quickly identifies the (near) optimal line hardening decisions in the presence of both large simulation noises due to the highly variable initial disturbances and system states, and significant randomness in the subsequent cascades. Furthermore, the algorithm is also able to utilize parallel computing to dramatically reduce computation time to support decision making in preparation for severe weather conditions. We performed a case study on the Northeast Power Coordinating Council (NPCC) 140-bus system model to demonstrate that our approach can significantly improve power grid resilience to adverse weather events.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Adverse Effects of Trace Non-polar Binder on Ion Transport in Free-standing Sulfide Solid Electrolyte Separators

Sulfide solid-state electrolyte (SE) possesses high room-temperature ionic conductivity. However, fabrication of the free-standing, sheet-type thin sulfide SE film electrolyte to enable all-solid-state batteries to deliver high energy and power density remains challenging. Herein we show that argyrodite sulfide (Li 6 PS 5 Cl) SE can be slurry cast to form free-standing films with low (≤5 wt%) loadings of poly(isobutylene) (PIB) binder. Two factors contribute to a lower areal specific resistance (ASR) of the thin film SEs benchmarked to the pristine powder pellet SSE counterparts: i) 1–2 orders reduced thickness and ii) reasonably comparable ionic conductivity at room temperature after the isostatic pressing process. Nevertheless, an increasing polymer binder loading inevitably introduced voids in the thin film SEs, compromising anode/electrolyte interfacial ion transport. Our findings highlight that electrolyte/electrode interfacial stability, as well as the selection of slurry components, including sulfide SE, binder, and solvent, play essential roles in thin film sulfide electrolyte development.

25 ENERGY STORAGE↗
DOE OSTI2025

High-Power Electric Vehicle Charging Hub Integration Platform (eCHIP): Site Energy Management System Platform Development

A site energy management system is a critical component of future high-power EV charging hubs. It monitors and supervises all inter-hub operations, coordinates grid interactions, and implements energy management strategies and load-sharing controls at various levels and time scales. This report provides a comprehensive high-level overview and guidelines on the essential elements of such energy management systems. These elements primarily focus on the core functions, architecture, and monitoring aspects of site energy management. The core functions define the grid services and operational objectives that a charging hub is expected to provide and achieve. The architectural section investigates the coordination between hub assets, different control schemes, and their potential benefits and drawbacks. Lastly, the report discusses the needs, types, and functionalities of a monitoring and visualization system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Modal Analysis of Ultrasonic Spot Welding for Lightweight Metals Joining

Ultrasonic spot welding (USW) represents one of the unique solid-state joining methods for lightweight materials such as magnesium alloy and aluminum alloy. However, the sonotrode vibration may have a detrimental impact on the sheet material and the existing welds, depending on the component geometry and vibration frequency. In this study, a modal analysis tool based on steady-state dynamics was developed for ultrasonic spot welding which features a cyclic load applied to the sheets during the joining process. Through predicting relative motion and shear stress at the faying surfaces, coupon geometry and weld spacing are identified as two major factors that affect the welding reliability and joint quality in USW. The model was validated via welding experiments on aluminum alloy and magnesium alloy and relevant characterization of temperature distribution, joint strength as well as fracture location.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Sealability Qualification of Material Extruded Zytel Gaskets at Extreme Temperatures

In this work, an in-depth qualification of additively manufactured Zytel for gasketing proton exchange membrane fuel cells (PEMFC’s) subject to extreme temperature conditions. The temperature cycling of the PEMFC from 55°C to 100°C accelerates the deterioration of these gaskets compared to that of conventional operation. The additive manufacturing process employed to print these gaskets is material extrusion using Zytel filament. In order to see the effects of the temperature of interest on the printed specimen, each specimen was thermally soaked and then charactered and tested according to ASTM standard F37B. ASTM F37B tests a materials ability to seal and maintain it while bearing both a compressive load and internal pressure load to simulate being in static operation. This process of thermally soaking and sealability testing is shown to show the validity of both this material and additive manufactured components for other applications as well. It is observed that soaking the gaskets at 100°C corrects some of the defects that are present after printing such as missing layers and small voids on the surface of the samples. This allowed for the hot soaked materials to perform better than the samples at room temperature and cold soaked.

Sealability↗
DOE OSTI2020

Direct Envelope Modeling of Load-Resonant Inverter for Wireless Power Transfer Applications

This paper presents the application of direct envelope modeling technique to primary side LCC tuned resonant wireless power transfer system. The method adapted here decomposes the HF resonant inverter output to a fundamental component and two dominant sidebands. The small-signal dutycycle-to-primary-coil-current-envelope transfer function of a primary side LCC tuned WPT system is then derived as the summation of the responses to the fundamental and the sideband components. The theoretical and simulation results are in good agreement indicating the validity of the approach to be applied to WPT systems.

Galigekere, Veda Prakash↗
DOE OSTI2024

Delamination and Buckling Analysis of a Laminated Component in a High-speed Permanent Magnet Motor

High-speed permanent magnet (PM) machines are widely used because of their high-power density and high efficiency. The high rotation speed also inevitably subjects the PMs to high centrifugal load, which might damage them due to their inherent mechanical vulnerability, such as a much lower tensile strength than the compressive strength. To robustly transfer the torque from the magnet to the shaft, the outer diameter of the laminated rotor core is larger than the inner diameter of the rotor frame to ensure tight contact while working at 20,000 rpm. Motor manufacturing requires the shrink-fit method to assemble the rotor frame and rotor core. However, after the shrink-fit assembly, unexpected local delamination and buckling are observed on the rotor core part. Utilizing finite element simulation, we study the internal stress of assembling these two parts at the provided interference. Simulation results indicate the reasons for the delamination and buckling of the rotor core part and provide suggestions for improving the assembly.

Lin, Lianshan↗
DOE OSTI2020

Analysis of Electric Vehicle Charging Behavior Patterns with Function Principal Component Analysis Approach

This manuscript focused on analyzing electric vehicles’ (EV) charging behavior patterns with a functional data analysis (FDA) approach, with the goal of providing theoretical support to the EV infrastructure planning and regulation, as well as the power grid load management. 5-year real-world charging log data from a total of 455 charging stations in Kansas City, Missouri, was used. The focuses were placed on analyzing the daily usage occupancy variability, daily energy consumption variability, and station-level usage variability. Compared with the traditional discrete-based analysis models, the proposed FDA modeling approach had unique advantages in preserving the smooth function behavior of the data, bringing more flexibility in the modeling process with little required assumptions or background knowledge on independent variables, as well as the capability of handling time series data with different lengths or sizes. In addition to the patterns revealed in the EV charging station’s occupancy and energy consumption, the differences between EV driver’s charging time and parking time were analyzed and called for the needs for parking regulation and enforcement. The different usage patterns observed at charging stations located on different land-use types were also analyzed.

Engineering↗
DOE OSTI2021

Weather and Random Forest-based Load Profiling Approximation Models and its Transferability across Climate Zones

This study is to provide predictive understanding of the associations of various weather attributes with residential and commercial load profiles, for a variety of climate zones and seasons. In this work, machine learning (ML) approaches were used to identify and quantify the impacts of various weather attributes on residential and commercial electricity demand and its components across the western United States. Performance and transferability of the developed ML models were then evaluated across different temperate zones (e.g., southern, middle, and northern US) and across coastal, mid-continent, and wet zones, with inputs of weather condition data from the National Oceanic and Atmospheric Administration (NOAA) at representative weather stations. The predictive models were developed based on the ranked/screened factors using the regression tree (RT) and random forest (RF) approaches, for five different scenarios (seasons).

load composite, Random Forest, regression tree, lo↗
DOE OSTI2022

Steady state thermo-mechanics and material property definition framework for analyzing DCLL blanket in the fusion nuclear science facility

In this work, a thermo-mechanics model that relies on creating the material property definition framework (MPDF) and multiphysics coupling of the heat transfer and the solid mechanics modules is developed to determine the structural integrity of the recently designed dual cooled lead lithium (DCLL) inboard blanket (IB) for the Fusion Nuclear Science Facility under steady state loads. The MPDF is called to supply fusion relevant neutron irradiation and temperature induced changes in material properties during multiphysics finite element runs, and PbLi temperature profiles are used to approximate Magnetohydrodynamics effect and the nuclear volumetric heating on the PbLi. Neutron irradiation and temperature induced reduction of the yield and ultimate strengths of F82H steel at the first wall (FW) are quantified for one year. A blanket in an assembly with gaps between blanket sectors and another blanket in an assembly with no gaps between blanket sectors, both exposed to radiation damage that lasted for one year are analyzed. Analysis using the elastic ITER structural design criteria for in-vessel components (ITER SDC-IC) design rules and a linear isotropic-hardening-type elastoplastic material model are used where most appropriate. The IB blanket with gaps between blanket sectors will withstand the steady state combined thermal and coolant loads for one year operational period but will fail if no gaps are allowed between blanket sectors. It is recommended that a gap of about 7.62 mm should be provided between IB blanket sectors during assembly which would close up during service, stop neutron streaming, reduce stresses and reduce bending of the FW into the scrape-off layer.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Burning magnesium in carbon dioxide for highly effective phosphate removal

Magnesium oxide was found to have high-phosphate-affinity as an effective component to enhance the phosphate removal ability of common adsorbent materials. However, the currently prepared MgO-based hybrid adsorbents by conventional methods still suffer from the limited low loading of MgO and inferior removal performances, much far away from practical application. In this study, an ingenious carbon coated MgO nanocomposite is designed by directly burning magnesium in CO 2 , a well-known textbook reaction. X-ray diffraction analysis, scanning electron microscope and aberration-corrected high-resolution transmission electron microscope demonstrate the sample is well prepared. Consequently, the high content of nanosized MgO combined with defect-rich carbon layer brings unprecedented phosphate removal capacity of 1135.0 mg/g, removal rate of 99% and benign compatibility with coexisting anions and solution pH. Furthermore, the removal mechanism is also investigated in detail by characterizing the sample before and after adsorption.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗