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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 1,027 records · Page 57
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Double Resonances and Spectral Scaling in the Weak Turbulence Theory of Rotating and Stratified Turbulence

In rotating turbulence, stably stratified turbulence, and in rotating stratified turbulence, heuristic arguments concerning the turbulent time scale suggest that the inertial range energy spectrum scales as k(exp -2). From the viewpoint of weak turbulence theory, there are three possibilities which might invalidate these arguments: four-wave interactions could dominate three-wave interactions leading to a modified inertial range energy balance, double resonances could alter the time scale, and the energy flux integral might not converge. It is shown that although double resonances exist in all of these problems, they do not influence overall energy transfer. However, the resonance conditions cause the flux integral for rotating turbulence to diverge logarithmically when evaluated for a k(exp -2) energy spectrum; therefore, this spectrum requires logarithmic corrections. Finally, the role of four-wave interactions is briefly discussed.

Rubinstein, Robert↗
DOE OSTI2021

Roadmap of Solid-State Lithium-Organic Batteries toward 500 Wh kg –1

Over the past few years, solid-state electrolytes (SSEs) have attracted tremendous attention due to their credible promise toward high-energy batteries. In parallel, organic battery electrode materials (OBEMs) are gaining momentum as strong candidates thanks to their lower environmental footprint, flexibility in molecular design and high energy metrics. Integration of the two constitutes a potential synergy to enable energy-dense solid-state batteries (SSBs) with high safety, low cost, and long-term sustainability. Here, we present the technological feasibility of combining OBEMs with SSEs along with the possible cell configurations that may result from this peculiar combination. We provide an overview of organic SSBs and discuss their main challenges. We analyze the performance-limiting factors and the critical cell design parameters governing cell-level specific energy and energy density. Lastly, we propose guidelines to achieve 500 Wh kg –1 cell-level specific energy with solid-state Li–organic batteries.

25 ENERGY STORAGE↗
DOE OSTI2024

Towards Sustainable Post-Exascale Leadership Computing

As computing systems approach the limits of traditional silicon technology, the diminishing returns in performance per watt present a significant barrier to sustaining growth in HPC. From a large-scale scientific supercomputing facility point of view, we propose a multifaceted strategy toward specialized hardware and architectures that are optimized for energy efficiency in specific applications. We also emphasize the need for integrating energy-aware practices across all levels of HPC, from system design and software development to operational policies. We discuss strategic opportunities such as the adoption of application-specific accelerators, the development of energy-efficient algorithms, and the implementation of data-driven operational analytics. Our goal is to develop a comprehensive roadmap ensuring that future leadership systems at OLCF can meet scientific demands while operating within stringent energy budgets, thereby supporting sustainable computing growth.

Shin, Woong↗
DOE OSTI2022

Integration of physiologically relevant photosynthetic energy flows into whole genome models of light‐driven metabolism

SUMMARY Characterizing photosynthetic productivity is necessary to understand the ecological contributions and biotechnology potential of plants, algae, and cyanobacteria. Light capture efficiency and photophysiology have long been characterized by measurements of chlorophyll fluorescence dynamics. However, these investigations typically do not consider the metabolic network downstream of light harvesting. By contrast, genome‐scale metabolic models capture species‐specific metabolic capabilities but have yet to incorporate the rapid regulation of the light harvesting apparatus. Here, we combine chlorophyll fluorescence parameters defining photosynthetic and non‐photosynthetic yield of absorbed light energy with a metabolic model of the pennate diatom Phaeodactylum tricornutum. This integration increases the model predictive accuracy regarding growth rate, intracellular oxygen production and consumption, and metabolic pathway usage. Through the quantification of excess electron transport, we uncover the sequential activation of non‐radiative energy dissipation processes, cross‐compartment electron shuttling, and non‐photochemical quenching as the rapid photoacclimation strategy in P. tricornutum. Interestingly, the photon absorption thresholds that trigger the transition between these mechanisms were consistent at low and high incident photon fluxes. We use this understanding to explore engineering strategies for rerouting cellular resources and excess light energy towards bioproducts in silico . Overall, we present a methodology for incorporating a common, informative data type into computational models of light‐driven metabolism and show its utilization within the design–build–test–learn cycle for engineering of photosynthetic organisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Functional Requirements for the WEIS Toolset to Enable Controls Co-Design of Floating Offshore Wind Turbines

The goal of the new Wind Energy with Integrated Servo-control (WEIS) toolset under development is to provide the offshore wind industry and research communities with an open-source, user-friendly, flexible tool to enable true controls co-design (CCD) of the physical design of a floating offshore wind turbine together with the controller. WEIS will use a multifidelity library of models built on the foundations of WISDEM® and OpenFAST formerly known as FAST). This paper presents the WEIS development plan, including the functional requirements of WEIS (including improvements to WISDEM and OpenFAST) together with associated rationale for their establishment and a qualitative description of the modeling approaches that will be implemented to address these functional requirements. The development of WEIS is a project under the Aerodynamic Turbines Lighter and Afloat with Nautical Technologies and Integrated Servo-control program funded by the U.S. Department of Energy Advanced Research Projects Agency – Energy.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2024

Emerging Technologies for Privacy Preservation in Energy Systems

This study explores the intersection of digitalization and privacy within the energy sector, focusing on the emerging challenges and opportunities presented by integrating Distributed Energy Resources (DERs) and advanced metering infrastructure. The need for robust digital privacy measures has become crucial as the energy industry evolves towards a more decentralized, digitalized, and decarbonized future. This study delves into four cutting-edge privacy-preserving technologies—Homomorphic Encryption (HE), Secure Multiparty Computation (SMPC), Differential Privacy (DP), and Federated Learning (FL)—each offering unique solutions to safeguard consumer data by increasing digital connectivity and data exchange. Through a detailed examination of these methods, the study explains how each technology operates, its applications within the energy sector, and the specific privacy challenges it addresses. Homomorphic Encryption allows for secure computations on encrypted data, enabling data analysis without compromising privacy. Secure Multiparty Computation enables collaborative data analysis across different entities while protecting the confidentiality of the inputs. Differential Privacy introduces randomness into the assembled data set, preventing the identification of individual records in statistical databases. Lastly, Federated Learning offers a paradigm shift in data analysis, where machine learning models are trained at the edge, minimizing the centralization of sensitive data. The research underscores the significance of implementing these privacy-enhancing technologies to comply with strict data protection regulations, foster consumer trust, and enhance the security of the energy infrastructure. By providing a comprehensive overview of these methodologies and their practical implications for the energy sector, this study aims to contribute to the ongoing discourse on digital privacy, offering insights into how the energy industry can navigate the complexities of data privacy in the digital age.

Cali, Umit↗
DOE OSTI2020

Numerical Modeling and Parametric Study of a Dual Purpose Underground Thermal Battery

Buildings’ thermal energy systems for providing space heating/cooling consume a considerable amount of electricity nationwide. Integrating thermal energy storage with buildings’ thermal systems has the potential to shave the peak electric demand and to overcome the mismatch between the intermittent renewable power and the fluctuating daily demand for electricity. A novel dual-purpose underground thermal battery (DPUTB) has been developed to provide diurnal thermal energy storage in conjunction with a dual-source heat pump (DSHP)system. A two-dimensional numerical model is developed to simulate the transient performance of the DPUTB. This model has similar accuracy as a detailed three-dimensional model developed with commercial heat transfer and fluid dynamics simulation program but with 1000 times faster computational speed. A parametric study is performed to identify a design of the DPUTB that can provide 14 kWh thermal storage capacity for each charging and discharging cycle. A system simulation has been developed to assess the performance of the designed DPUTB when it is integrated with a DSHP for conditioning a typical residential building in summer and winter. Simulation results indicate that the DPUTB can meet all the design requirements in both summer and winter with the simple rule-based control strategy and the overall integrated DPUTB and DSHP system can shift the electric load for meeting the thermal demand from the peak hours to off-peak hours during a day, which would result in considerable energy cost savings if a Time of Use electricity tariff is applicable.

25 ENERGY STORAGE↗
NASA NTRS1992

Botswana water and surface energy balance research program. Part 1: Integrated approach and field campaign results

The Botswana water and surface energy balance research program was developed to study and evaluate the integrated use of multispectral satellite remote sensing for monitoring the hydrological status of the Earth's surface. Results of the first part of the program (Botswana 1) which ran from 1 Jan. 1988 - 31 Dec. 1990 are summarized. Botswana 1 consisted of two major, mutually related components: a surface energy balance modeling component, built around an extensive field campaign; and a passive microwave research component which consisted of a retrospective study of large scale moisture conditions and Nimbus scanning multichannel microwave radiometer microwave signatures. The integrated approach of both components in general are described and activities performed during the surface energy modeling component including the extensive field campaign are summarized. The results of the passive microwave component are summarized. The key of the field campaign was a multilevel approach, whereby measurements by various similar sensors were made at several altitudes and resolution. Data collection was performed at two adjacent sites of contrasting surface character. The following measurements were made: micrometeorological measurements, surface temperatures, soil temperatures, soil moisture, vegetation (leaf area index and biomass), satellite data, aircraft data, atmospheric soundings, stomatal resistance, and surface emissivity.

Vandegriend, A. A.↗
DOE OSTI2023

Microgrid energy scheduling under uncertain extreme weather: Adaptation from parallelized reinforcement learning agents

Microgrids are useful solutions for integrating renewable energy resources and providing seamless green electricity to minimize carbon footprint. In recent years, extreme weather events happened often worldwide and caused significant economic and societal losses. Such events bring uncertainties to the microgrid energy scheduling problems and increase the challenges of microgrid operation. Traditional optimization approaches suffer from the inaccuracy of the uncertain microgrid model and the unseen events. Existing reinforcement learning (RL) - based approaches are also hampered by the limited generalization and the increasing computational burden when stochastic formulations are required to accommodate the uncertainties. This paper proposes a new parallelized reinforcement learning (PRL) method based on the probabilistic events to handle the microgrid energy uncertainties. Specifically, several local learning agents are employed to interact with pertinent microgrid environments in a distributed manner and report outcomes to the global agent, which will optimize microgrid energy resources online during extreme events. The stochastic microgrid energy optimization problem is reformulated to include all possible scenarios with probabilities. The advantage estimate functions of learning agents are designed with a backward sweep to transfer the outcomes to the value function updating process. Two simulation studies, stochastic optimization and online testing, are performed to compare with several existing RL approaches. Results substantiate that the proposed PRL method can achieve up to 20% optimization performance improvement with 4 and 28 times less computation cost than Q-learning with experience replay and multi-agent Q-learning approaches, respectively.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1992

The energy spectra of solar flare hydrogen, helium, oxygen, and iron - Evidence for stochastic acceleration

The time-integrated differential energy spectra of H, He, O, and Fe measured in 10 large flare events observed at 1 AU over the energy range of 0.3-80 MeV/nucleon showed consistent patterns in their spectral shapes: particles with larger mean mass-to-charge ratios were generally less abundant at higher energies. A steady state model of stochastic particle acceleration with rigidity-dependent diffusion coefficients fit the spectra best; spectra representative of diffusive shock acceleration also described the spectra of some events with the same number of free parameters, but often fell off faster in energy above 30 MeV per nucleon than the observations. The two model predictions differed most at energies near 0.1 MeV per nucleon, below the lowest energies observed in this study. The stochastic model quantitatively described the observed spectral ordering with less efficient acceleration of species with larger mean mass-to-charge ratios.

Mazur, J. E.↗
DOE OSTI2024

Multi-parametric analysis for mixed integer linear programming: An application to transmission upgrade and congestion management

Upgrading the capacity of existing transmission lines is essential for meeting the growing energy demands, facilitating the integration of renewable energy, and ensuring the security of the transmission system. This study focuses on the selection of lines whose capacities and by how much should be expanded from the perspective of the Independent System Operators (ISOs) to minimize the total system cost. We employ advanced multi-parametric programming and an enhanced branch-and-bound algorithm to address complex mixed-integer linear programming (MILP) problems, considering multi-period time constraints and physical limitations of generators and transmission lines. To characterize the various decisions in transmission expansion, we model the increased capacity of existing lines as parameters within a specified range. This study first relaxes the binary variables to continuous variables and applies the Lagrange method and Karush-Kuhn-Tucker (KKT) conditions to obtain optimal solutions and identify critical regions associated with active and inactive constraints. Moreover, we extend the traditional branch-and-bound (B&B) method by determining the problem’s upper and lower bounds at each node of the B&B decision tree, helping to manage computational challenges in large-scale MILP problems. Here, we compare the difference between the upper and lower bounds to obtain an approximate optimal solution within the decision-makers’ tolerable error range. In addition, the first derivative of the objective function on the parameters of each line is used to inform the selection of lines for easing congestion and maximizing social welfare. Finally, the capacity upgrades are selected by weighing the reductions in system costs against the expense of upgrading line capacities. The findings are supported by numerical simulations and provide transmission-line planners with decision-making guidance.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Probing the electronic properties of gap states near the surface of n -SrTiO 3-δ / i -Si (001) heterojunctions with high sensitivity

We have measured soft x-ray resonant photoemission for the n–SrTiO 3–δ /i–Si⁡(001) (δ=~0.0003) hybrid semiconductor heterojunction with the goal of probing occupied electronic states in the band gap near the surface. By utilizing both swept energy, angle-integrated and fixed-energy, and angle-resolved spectroscopies, we identify the atomic and orbital character of the in-gap state as well as the different electronic phases that contribute to it. Specifically, we isolate the state associated with trapped charge on the n–SrTiO 3–δ surface that causes surface depletion from the localized gap state resulting from electron correlation effects in the complex oxide. Using an x-ray energy close to select dipole allowed TiL 3 → 3⁢d x-ray absorption resonances results in a 40-fold increase in sensitivity. Furthermore, this feature makes photoemission possible when probing electrons from dopants at concentrations as low as a few hundredths of a percent.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Ocean Wave Energy Harvester with Oak Ridge Converter

Oceans can provide great potential for the American energy dominance. There is significant potential to utilize marine energy resources. In the United States, the total amount of marine energy available is equivalent to about 57% of the country's total power generation in 2019. Even if a fraction of this technical potential is harnessed, marine energy technologies could play a crucial role in fulfilling the nation's energy requirements. Marine energy resources are spread out geographically, and because more than 50% of the United States' population resides within 50 miles of the coastline, they are well-positioned to power local communities. These resources are also very dependable, making them a viable option for contributing to a consistent, trustworthy energy grid. Due to their predictable daily and seasonal patterns, marine energy resources can be integrated into our energy generation portfolio. On the other hand, ocean environment presents many challenges for cost-effective renewable energy conversion, including optimal control of ocean wave energy. This report presents a novel cost-effective energy conversion technique for ocean wave energy harvesters. The proposed system is simulated by using the Oak Ridge Converter to directly interface ocean wave energy source with the utility grid. The system description and simulation results are presented in detail. The results show that the proposed system is a cost effective and promising technology to reduce the infrastructure cost for ocean wave energy harvesters.

Sutton, Elizabeth [ORNL] (ORCID:0009000078885935)↗
DOE OSTI2023

Integrated Resource and System Plannning Based on Energy Costs and Emission Analysis for a Sustainable Future

Efficient integration of renewable energy sources (RES) - such as wind, solar, geothermal, tidal, and wave - into the electric power grids can help improve energy security and contribute toward a sustainable energy future. To date, however, electric power grids are critically dependent on conventional sources, such as fossil fuels. Given the increasing penetration of RES and dynamic loads, there is a need to thoroughly reanalyze the performance of power grids in terms of cost, efficiency, and energy security. This paper presents a comprehensive analysis in terms of energy costs and emissions estimates of dynamic power grids incorporating various power-generating sources.

distributed energy resources↗
DOE OSTI2020

Implementing Inertial Control for PMSG-WTG in Region 2 Using Virtual Synchronous Generator with Multiple Virtual Rotating Masses

With the increasing integration of renewable energy, the problems associated with a deteriorating grid frequency profile and potential power system instability have become more significant. In this paper, the inertial control algorithm using a virtual synchronous generator (VSG) is implemented on a Type 4 permanent magnet synchronous generator (PMSG) wind turbine generator (WTG). The overall nonlinear dynamic model and its small-signal linearization of the PMSG-WTG using a VSG is established and comprehensively analyzed. Inevitably, the direct application of the VSG introduces a large inertia, which causes conflict between the fast variance of available wind power and inverter control with slow dynamics, particularly in Region 2 of the wind turbine. Aiming to address such issues, a VSG with multiple virtual rotating masses is proposed to improve the active power tracking performance as well as to boost the inertial control of a VSG. The inertial responses are verified in a modified 10-MVA IEEE 14-bus microgrid system. The assessment of the simulation results demonstrates the applicability of the VSG on renewable energy generation units.

17 WIND ENERGY↗
DOE OSTI2022

Highlights for DOE ASCR Applied Math Office [Slides]

An efficient Picard-based solver is proposed for a novel energy conserving particle integrator preserving all first-order guiding center drifts and correct gyroradius for large time steps in arbitrary (non-uniform) magnetic fields. This research enables the efficient deployment of the novel asymptotic preserving (AP) particle orbit integrator into modern energy-conserving, implicit particle-in-cell codes, delivering a truly multiscale simulation capability.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗