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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A Novel LCC-CLCC Resonant Tuning Network for Light-Load Conditions in Wireless Power Transfer Systems

In wireless power transfer (WPT) systems, voltage and current distortions are observed at the vehicle side rectifier when power flow is from grid to vehicle (G2V) under light load conditions. These distortions can increase switching losses and decrease the overall efficiency of the WPT system. To address this issue, this paper proposes adding a higher value inductor in series with the original LCC tuning network at the vehicle side. However, increasing the series inductance causes the input impedance and phase angle to move away from the resonant frequency. To solve this problem, a capacitor is added in series to tune out the difference between the original and modified inductor values. This series tuning capacitor also improves the power factor and brings the input impedance and phase angle back to the resonant frequency. The traditional LCC-LCC and proposed LCC-CLCC WPT systems are compared and analyzed analytically, and simulated in a MATLAB/Simulink environment to verify parameters such as efficiency and power transfer capacity. An experimental prototype is implemented and compared with the simulation. The obtained results confirm the validity of the proposed method.

Harave, Sudarshan↗
DOE OSTI2022

DenKv: Addressing Design Trade-offs of Key-value Stores for Scientific Applications

High-performance computing (HPC) facilities have employed flash-based storage tier near to compute nodes to absorb high I/O demand by HPC applications during periodic system-level checkpoints. To accelerate these checkpoints, proxy-based distributed key-value stores (PD-KVS) gained particular attention for their flexibility to support multiple backends and different network configurations. PD-KVS rely internally on monolithic KVS, such as LevelDB or RocksDB, to exploit the KV interface and query support. However, PD-KVS are unaware of the high redundancy factor in checkpoint data, which can be up to GBs to TBs, and therefore, tend to generate high write and space amplification on these storage layers. In this paper, we propose DenKv which is deduplication-extended node-local LSM-tree-based KVS. DenKv employs asynchronous partially inline dedup (APID) and aims to maintain the performance characteristics of LSM-tree-based KVS while reducing the write and space amplification problems. We implemented DenKv atop BlobDB and showed that our proposed solution maintains performance while reducing write amplification up to 2× and space amplification by 4× on average.

Khan, Awais↗
DOE OSTI2021

Geothermal Representation in Power System Models

Power system models generally fail to capture the range of characteristics geothermal resources provide and the value they potentially contribute to decarbonization and reliability of future electricity grids as firm, dispatchable, non-combustion power resources. This study reviews the results of power system modeling efforts to investigate geothermal deployment potential in the United States, including the U.S. DOE GeoVision analysis and ongoing modeling and analysis efforts to support planning and development of future grids with 100% renewable energy in California. Several themes are identified that could be implemented immediately to improve the accuracy of geothermal representation in power system models: consistency of model inputs, modeling of baseload and dispatchable geothermal resources, accurate valuation of grid services, improved representation of capacity factor, use of contemporary LCOE estimates, improved understanding of the evolution of geothermal value, and use of accurate resource potential constraints. Many of the models reviewed produced significantly different amounts of geothermal resource selection - even when modeling the same region and time period. This highlights the variability of inputs and assumptions among models, so creating a consistent set of geothermal inputs is a first step toward more accurate representation of geothermal in models. Research opportunities are identified that could help improve geothermal data inputs in modeling efforts, including analyses of historical data, sensitivity to model inputs, and comparative value of geothermal generators as baseload or dispatchable resources. Outcomes of such research can inform the geothermal community about how best to guide geothermal development toward wider deployment in support of future electricity grids through improved understanding of the evolution of geothermal value over time and the characteristics that contribute to that value.

capacity expansion models↗
DOE OSTI2021

Utility-Scale Solar, 2021 Edition: Empirical Trends in Deployment, Technology, Cost, Performance, PPA Pricing, and Value in the United States [Slides]

Berkeley Lab’s “Utility-Scale Solar, 2021 Edition” provides an overview of key trends in the U.S. market, with a focus on 2020. Highlights of this year’s update include: A record of nearly 9.6 GWAC of new utility-scale PV capacity came online in 2020, bringing cumulative installed capacity to more than 38.7 GWAC across 43 states. 89% of all new utility-scale PV capacity added in 2020 uses single-axis tracking. Median installed project costs declined to $\$$1.4/WAC (or $\$$1.1/WDC) in 2020. Project-level capacity factors vary widely, from 9% to 36% (on an AC basis), with a sample median of 24%. The report explores drivers of this variation. Utility-scale PV’s LCOE fell to $\$$34/MWh in 2020 ($\$$28/MWh if factoring in the federal investment tax credit, or ITC). PPA prices have largely followed the decline in solar’s LCOE over time, but have stagnated more recently. Prices from a sample of recent contracts average just above $\$$20/MWh (levelized). In 2020, solar’s average market value (defined in the report to include only energy and capacity value) exceeded average wholesale prices in 12 of the 17 balancing authorities analyzed (including 4 of the 7 independent system operators across the United States). Adding battery storage is one way to increase the value of solar. Our public data file tracks metadata for more than 150 PV+battery hybrid projects that are already online or that have secured offtake arrangements. At the end of 2020, there were at least 460 GW of utility-scale solar power capacity within the interconnection queues across the nation, 160 GW of which include batteries. For more information, and to explore related interactive data visualizations, go to utilityscalesolar.lbl.gov.

14 SOLAR ENERGY↗
DOE OSTI2023

Unlocking the Value of Deep Energy Retrofits

This publication is based on an extensive study conducted on behalf of the New York State Energy Research and Development Authority (NYSERDA) and the U S Department of Energy (DOE) to explore financial and risk products to accelerate the implementation of deep energy retrofit (DER) solutions to reduce costs These financial products are intended to speed market development via three fundamental themes: reallocating risk from building owners and lenders to insurers, quantifying and monetizing previously unrecognized value associated with DERs, and providing building owners and lenders with confidence in the performance of building systems Findings are based on a comprehensive analysis and characterization of 100+ existing DER case studies, and more than 40 qualitative interviews with industry experts, including insurers, researchers, building owners, and policymakers In addition, a quantitative model of overall project economics with baseline, high, and low cases was developed This data informed the analysis that resulted in three recommended financial product solutions, which were evaluated for their potential to raise projected cash flows and finance DERs: 1) Building System Performance and Energy Savings Guarantee; 2) Trade Credit Insurance; 3) Ancillary Revenue Contracts. This report identifies many value streams associated with DERs and introduces these three potential financial products, which aim to reallocate risks and reduce barriers to the adoption of advanced envelope DERs.

ancillary renenue contracts↗
DOE OSTI2020

Learning method and system for separating independent and dependent attacks

Streams of monitoring node signal values over time, representing a current operation of the industrial asset, are used to generate current monitoring node feature vectors. Each feature vector is compared with a corresponding decision boundary separating normal from abnormal states. When a first monitoring node passes a corresponding decision boundary, an attack is detected and classified as an independent attack. When a second monitoring node passes a decision boundary, an attack is detected and a first decision is generated based on a first set of inputs indicating if the attack is independent/dependent. From the beginning of the attack on the second monitoring node until a final time, the first decision is updated as new signal values are received for the second monitoring node. When the final time is reached, a second decision is generated based on a second set of inputs indicating if the attack is independent/dependent.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

The need for an integrated multi-OMICs approach in microbiome science in the food system

Microbiome science as an interdisciplinary research field has evolved rapidly over the past two decades, becoming a popular topic not only in the scientific community and among the general public, but also in the food industry due to the growing demand for microbiome-based technologies that provide added-value solutions. Microbiome research has expanded in the context of food systems, strongly driven by methodological advances in different -omics fields that leverage our understanding of microbial diversity and function. However, managing and integrating different complex -omics layers are still challenging. Within the Coordinated Support Action MicrobiomeSupport (https://www.microbiomesupport.eu/), a project supported by the European Commission, the workshop “Metagenomics, Metaproteomics and Metabolomics: the need for data integration in microbiome research” gathered 70 participants from different microbiome research fields relevant to food systems, to discuss challenges in microbiome research and to promote a switch from microbiome-based descriptive studies to functional studies, elucidating the biology and interactive roles of microbiomes in food systems. A combination of technologies is proposed. This will reduce the biases resulting from each individual technology and result in a more comprehensive view of the biological system as a whole. Although combinations of different datasets are still rare, advanced bioinformatics tools and artificial intelligence approaches can contribute to understanding, prediction, and management of the microbiome, thereby providing the basis for the improvement of food quality and safety.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Log-N/Period Power Offset Sensitivity Calculation

This study focused on the calculation of sensitivity values for Channels 4 and 5 in the Log-N/Period system at the Advanced Test Reactor (ATR). The Log-N/Period system provides an indication of reactor power generation between criticality and full power. This indication is determined by the power offset and the current produced by the detector. Sensitivity values for Channels 4 and 5 were calculated using existing equations, documents, reactor startup data.

42 - ENGINEERING↗
DOE OSTI2022

Towards sharp error analysis of extended Lagrangian molecular dynamics

The extended Lagrangian molecular dynamics (XLMD) method provides a useful framework for reducing the computational cost of a class of molecular dynamics simulations with constrained latent variables. The XLMD method relaxes the constraints by introducing a fictitious mass ε for the latent variables and solving a set of singularly perturbed ordinary differential equations. While favorable numerical performance of XLMD has been demonstrated in several different contexts in the past decade, mathematical analysis of the method remains scarce. Here, we propose the first error analysis of the XLMD method in the context of a classical polarizable force field model. While the dynamics with respect to the atomic degrees of freedom are general and nonlinear, the key mathematical simplification of the polarizable force field model is that the constraints on the latent variables are given by a linear system of equations. We prove that when the initial value of the latent variables is compatible in a sense that we define, XLMD converges as the fictitious mass ε is made small with $\mathscr{O}$(ε) error for the atomic degrees of freedom and with $\mathscr{O}$($\sqrt{ε}$) error for the latent variables, when the dimension of the latent variable d' is 1. Furthermore, when the initial value of the latent variables is improved to be optimally compatible in a certain sense, we prove that the convergence rate can be improved to $\mathscr{O}$(ε) for the latent variables as well. Numerical results verify that both estimates are sharp not only for d'=1, but also for arbitrary d'. In the setting of general d', we do obtain convergence, but with the non-sharp rate of $\mathscr{O}$($\sqrt{ε}$) for both the atomic and latent variables.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

Functional Assessment of Shell Recharge Solutions' SKY™ Platform OpenADR Capability

The project’s overall objective is to research, develop, and conduct a wide-scale demonstration of a utility smart charge management (SCM) system to develop optimal managed charging structures for grid value, evaluate the impact of EV charging on local distribution utility operations, and evaluate the utilities’ ability to control electronic vehicle (EV) charging load based on grid conditions. This report covers Argonne’s validation testing in the first period of the project, the objective of which was to determine the current managed charging functionality of the EVSE hardware, the network and the vehicle telematics software solution and understand gaps that need to be addressed prior to a large-scale demonstration.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Evaluating Utility Costs Savings and Resilience: A Case Study in Port Arthur, Texas

This study evaluates the techno-economic feasibility of integrating solar photovoltaics (PV), battery energy storage systems (BESS), and generators to enhance both cost savings and resilience in critical community facilities in Port Arthur, Texas. Using NREL's REopt model, we analyze four facilities: the Golden Triangle Empowerment Center (GTEC), Lamar State College (LSC), Port Arthur Independent School District (PAISD), and Port Arthur Transit (PAT). A key aspect of the analysis is the incorporation of the Value of Lost Load (VoLL) and microgrid upgrade costs to assess the hidden value of resilience during grid outages. While standalone PV scenarios show moderate cost reductions and a 10-15% decrease in CO2 emissions, the inclusion of resilience measures with BESS and generators significantly increases system costs. However, the hidden value of resilience - quantified through avoided outage costs - leads to a substantial improvement in financial outcomes, resulting in positive Net Present Value (NPV) at many sites. The study demonstrates that resilient solar and storage systems offer both economic and resilience benefits, particularly for underserved communities, by balancing energy savings and enhanced operational continuity during outages.

14 SOLAR ENERGY↗
DOE OSTI2025

Wide bandgap photoconductor (SiC:V)-based optically addressed light valve for high fluence operation

Optically addressable light valves based on wide bandgap 4H- and 6H-SiC as photoconductors were designed to withstand higher operational laser fluences than the state of-the-art bismuth silicon oxide (BSO; Bi 12 SiO 20 ) based devices. Vanadium-doped SiC was selected as the photoconductors due to their reasonable photoresponsivity while many fold improvement in laser induced damage threshold as compared to BSO. The laser induced damage threshold values of the materials were measured after exposing ~ 200 sites on the samples to increasing levels of fluence of a gaussian pulsed Nd: YAG laser system (1064 nm) with a 5 Hz repetition rate. The measured damage threshold values for BSO, 4H- and 6H-SiC were 0.4 J/cm 2 , 1.75 J/cm 2 and 1.8 J/cm 2 , respectively. Photoconductive switches based on 4H and 6H-SiC samples were characterized at wavelengths of 380 nm, 405 nm, and 447 nm. The peak photoresponsivity values of the 4H- and 6H-SiC materials were measured to be under 380 nm and 405 nm, respectively. The photoconductor was bonded to a BK7 optical window with 5 μm diameter microspheres as spacers. A twisted nematic type E7 liquid crystal (LC) was filled in the 5 μm gap in a vacuum chamber. The desired alignment of the liquid crystal was achieved by mutually orthogonal orientation of LC alignment layers on the two mating faces (SiC and BK7). The fabricated devices were modulated using address beams of wavelengths 380 nm, 405 nm, and 447 nm. In conclusion, required transmission levels of > 90% was achieved for the fabricated OALVs for a sinusoidal voltage waveform that meets the lifetime requirement of the device.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Learning Conservation Laws in Unknown Quantum Dynamics

We present a learning algorithm for discovering conservation laws given as sums of geometrically local observables in quantum dynamics. This includes conserved quantities that arise from local and global symmetries in closed and open quantum many-body systems. The algorithm combines the classical shadow formalism for estimating expectation values of observable and data analysis techniques based on singular value decompositions and robust polynomial interpolation to discover all such conservation laws in unknown quantum dynamics with rigorous performance guarantees. Our method can be directly realized in quantum experiments, which we illustrate with numerical simulations, using closed and open quantum system dynamics in a ℤ 2 gauge theory and in many-body localized spin chains.

Machine learning↗
DOE OSTI2026

Estimating the impact of tariff-driven behind-the-meter storage operation on distribution grid investments

Increasing growth of distributed solar photovoltaics (PV) and electric vehicles (EV) can strain local distribution networks and require costly upgrades. Distributed battery storage, often deployed alongside PV, can be used to mitigate those costs, depending on how batteries are operated. This study evaluates the potential deferral value of distributed battery storage across a range of tariff structures, focusing on the rate structures most commonly available to residential customers today and related variants. Deferrals are evaluated with a least-cost distribution grid expansion optimization model to identify requirements on line reconductoring, transformer upgrades, and voltage regulator installations under each tariff. Results show that TOU rates and net billing tariffs can yield meaningful deferral value, depending on specific tariff structure features. Under the best performing tariff structure tested, storage produced a median annualized deferral value of $7.18 per kW of storage capacity ( kW S ) across all feeders in the sample, though deferral values were considerably larger for feeders with peak loads that coincide with utility system peak, i.e., timing of TOU peak period. In contrast, under an unrestricted TOU design with no restrictions on grid charging or discharging, the median deferral value was $0/ kW S illustrating the critical importance of tariff structure details.

Rodriguez-Garcia, Luis↗
DOE OSTI2022

Forest regeneration within Earth system models: current process representations and ways forward

Earth system models must predict forest responses to global change in order to simulate future global climate, hydrology, and ecosystem dynamics. These models are increasingly adopting vegetation demographic approaches that explicitly represent tree growth, mortality, and recruitment, enabling advances in the projection of forest vulnerability and resilience, as well as evaluation with field data. To date, simulation of regeneration processes has received far less attention than simulation of processes that affect growth and mortality, in spite of their critical role maintaining forest structure, facilitating turnover in forest composition over space and time, enabling recovery from disturbance, and regulating climate-driven range shifts. Here, our critical review of regeneration process representations within current Earth system vegetation demographic models reveals the need to improve parameter values and algorithms for reproductive allocation, dispersal, seed survival and germination, environmental filtering in the seedling layer, and tree regeneration strategies adapted to wind, fire, and anthropogenic disturbance regimes. These improvements require synthesis of existing data, specific field data-collection protocols, and novel model algorithms compatible with global-scale simulations. Vegetation demographic models offer the opportunity to more fully integrate ecological understanding into Earth system prediction; regeneration processes need to be a critical part of the effort.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Intelligent driving passive pedal control

A method for assignment of vehicle control includes receiving route data indicating a route between a starting location of a vehicle and a destination location, and determining an optimal vehicle configuration for the route based on a target vehicle speed and a hybrid torque split. The method further includes receiving a driver requested torque value and determining a passive pedal torque value based on the route data and vehicle powertrain data. The method further includes selectively assigning control of the vehicle to a vehicle system or to a driver of the vehicle based on the driver requested torque value and the passive pedal torque value.

Aggoune, Karim↗
DOE OSTI2020

Performance Limits for Maritime Wide-Area Search (MWAS) Radar

One of the earliest applications for radar was to search for and find maritime vessels on the open sea. Proper design and operation of an airborne Maritime Wide Area Search (MWAS) radar requires an understanding of system performance characteristics and limitations, and furthermore understanding the trades amongst a large number of interdependent system parameters. This report identifies and explores those characteristics and limits, and how they depend on hardware system parameters and environmental conditions. Ultimately, this leads to a characterization of parameters that offer optimum performance for the overall MWAS radar system. While the information herein is not new to the literature, its collection into a single report hopes to offer some value in reducing the 'seek time'. Acknowledgements This report was funded by General Atomics Aeronautical Systems, Inc. (GA-ASI) Mission Systems under Cooperative Research and Development Agreement (CRADA) SC08/01749 between Sandia National Laboratories and GA-ASI. General Atomics Aeronautical Systems, Inc. (GA-ASI), an affiliate of privately-held General Atomics, is a leading manufacturer of Remotely Piloted Aircraft (RPA) systems, radars, and electro-optic and related mission systems, including the Predator/Gray Eagle-series and Lynx Multi-mode Radar. -

42 ENGINEERING↗
DOE OSTI2024

Cyber100 Compass: Quantification of Cybersecurity Risks for Systems Transitioning to High Levels of Renewables (Final Report)

The shift to high levels of renewable deployment will entail a significant re-engineering of the grid. As investors, utilities, customers, and others prepare for clean energy transitions, there is need to understand how restructuring the grid to accommodate renewables will change the attack surface of the grid and accompanying cyber risk. However, today the cyber-physical risks associated with electric grids incorporating high levels of renewable deployment remain largely unknown. The Cyber100 Compass proof-of-concept application attempts to quantify future cyber-physical security risks by combining risk data gathered from subject matter experts (SMEs) with input from system planners about conditions they expect to be true about their electric systems in the future. Users provide data about their organization’s tolerance for risk; the value they place on avoiding the consequences of different cyber events; and conditions that they expect to be true on their systems at some point in the future. The SMEs provide baseline probabilities for different cyber events; the probability that an event will be low-, moderate-, or high-impact; and the amount by which user-identified conditions on their systems will change the likelihood of the cyber events. The application takes both the user and SME input and performs a series of Monte Carlo simulations to arrive at a quantification of risk.

24 POWER TRANSMISSION AND DISTRIBUTION↗