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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 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Sci—Thur PM: Planning and Delivery — 02: Treatment planning workflow for very high-energy electron beam radiotherapy

Purpose: To develop treatment planning workflow for rapid radiotherapy delivered with very-high energy electron (VHEE) scanning beam. Methods: VHEE radiotherapy treatment planning was performed by linking Monte Carlo (MC) dose calculations with inverse optimization in a research version of RayStation. In order to study a number of treatment parameters, a Matlab graphical user interface (GUI) for calculation of VHEE beamlet dose was developed. Through the GUI, EGSnrc MC simulations were run for a number of beam energies, number of beams, beamlet spot and grid sizes, and machine bore sizes. VHEE plans for a pediatric patient with a 4.3 cm{sup 3} brain target optimized with spot-scanning algorithm in RayStation were compared to the clinically delivered 6 MV VMAT plan. Results and Discussion: VHEE beam energy had the largest effect on the quality of dose distributions. For the same target dose, the mean doses to critical organs decreased by 10–15% when planned with 100 MeV compared to 60 MeV. VHEE plans calculated with 36 beams outperformed plans calculated with 13 and 17 beams. While beamlet spacing and bore size had a small effect on VHEE dose distributions, 0.1-3mm beamlet sizes resulted in identical dose distributions. Critical organ doses were by up to 70% lower in the best VHEE plan compared to the clinical 6 MV VMAT plan. Conclusions: We have developed a GUI for MC beamlet generation for treatment planning of VHEE radiotherapy. We have demonstrated that pediatric VHEE plans resulted in significant critical organ dose sparing compared to the clinical VMAT plan.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1995

Computational analysis of forebody tangential slot blowing on the high alpha research vehicle

A numerical analysis of forebody tangential slot blowing as a means of generating side force and yawing moment is conducted using an aircraft geometry. The Reynolds-averaged, thin-layer, Navier-Stokes equations are solved using a partially flux-split, approximately-factored algorithm. An algebraic turbulence model is used to determine the turbulent eddy viscosity values. Solutions are obtained using both patched and overset grid systems. In the patched grid model, and actuator plane is used to introduce jet variables into the flow field. The overset grid model is used to model the physical slot geometry and facilitate modeling of the full aircraft configuration. A slot optimization study indicates that a short slot located close to the nose of the aircraft provided the most side force and yawing moment per unit blowing coefficient. Comparison of computed surface pressure with that obtained in full-scale wind tunnel tests produce good agreement, indicating the numerical method and grid system used in the study are valid. Full aircraft computations resolve the changes in vortex burst point due to blowing. A time-accurate full-aircraft solution shows the effect of blowing on the changes in the frequency of the aerodynamic loads over the vertical tails. A study of the effects of freestream Mach number and various jet parameters indicates blowing remains effective through the transonic Mach range. An investigation of the force onset time lag associated with forebody blowing shows the lag to be minimal. The knowledge obtained in this study may be applied to the design of a forebody tangential slot blowing system for use on flight aircraft.

Gee, Ken↗
DOE OSTI2023

The Empirical Effect of Fleet Optimization on Synchronization and Rebound Effects in Heat Pump Water Heaters

Demand response is a growing concept in light of the internet of things and an increasing need for grid flexibility. Water heaters are one of the preferred devices for providing demand response for grid services and peak management due to their capability to store energy. The efficient use of water heaters for demand response requires consideration of the associated load effects such as synchronization of device schedules and rebound effect. These effects present a significant challenge. Despite the importance of the mentioned effects for water heater queuing and scheduling, there has been no effort to quantify and empirically validate their impact. This study attempts to address this gap by offering two methods - Ward clustering and Euclidean K-means - to evaluate the extent of synchronization in a fleet of 42 water heaters in Atlanta, GA. Using the aforementioned methods on the measured data, we find evidence of convergence of water heater loads as a result of optimization compared to an idle period and analyzed their impact.

demand response↗
DOE OSTI2024

Microgrid design and multi-year dispatch optimization under climate-informed load and renewable resource uncertainty

Microgrids are an increasingly popular solution to provide energy resilience in response to increasing grid dependency and the growing impacts of climate change on grid operations. However, existing microgrid models do not currently consider the uncertain and long-term impacts of climate change when determining a set of design and operational decisions to minimize long-term costs or meet a resilience threshold. In this paper, we develop a novel scenario generation method that accounts for the uncertain effects of (i) climate change on variable renewable energy availability, (ii) extreme heat events on site load, and (iii) population and electrification trends on load growth. Additionally, we develop a two-stage stochastic programming extension of an existing microgrid design and dispatch optimization model to obtain uncertainty-informed and climate-resilient energy system decisions that minimizes long-term costs. Use of sample average approximation to validate our two case studies illustrates that the proposed methodology produces high-quality solutions that add resilience to systems with existing backup generation while reducing expected long-term costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Interleaved Cuk Converter Wave Energy System With Advanced Control and Grid Support Functions for Seamless Integration

This paper presents an innovative wave energy conversion system that integrates an interleaved Cuk converter with advanced nonlinear control for seamless grid integration. The system efficiently extracts power on the DC side using the interleaved Cuk converter, while an inverter manages power transfer to the grid or load on the AC side. A nonlinear control architecture, based on the Lyapunov energy function, ensures stable and optimal operation under varying wave conditions, effectively addressing the challenges of variability and unpredictability inherent in wave energy. The proposed system also incorporates features to enhance power quality and minimize losses, making it a robust solution for renewable energy integration. The system's effectiveness in harnessing wave energy and achieving smooth grid integration is validated through comprehensive computer simulations in MATLAB/Simulink, with case study results demonstrating its capabilities.

HYDRO ENERGY,TIDAL AND WAVE POWER↗
DOE OSTI2023

Multiphysics simulations of Self-Regulating performance of an optimized molten metal fuel microreactor design

Advanced microreactors are expected to play an indispensable role in reliable energy solutions for civilian/ military applications in off-grid regions and space applications such as power supplies for Lunar and Mars bases. An innovative fast neutron spectrum heat pipe microreactor (HP-MR) concept was recently proposed with two unique features: molten U-Mn fuel and heat pipes as the heat removal mechanism. The microreactor was designed to be self-regulated, solely relying on reactivity feedbacks from fuel temperature. The reactor design has been further optimized to provide sufficient engineering safety margin and effective heat removal. In this study, the self-regulating performance of the optimized molten metal fuel microreactor was investigated by multi-physics simulations (neutronics, heat-transfer and heat pipe modeling) based on the MOOSE MultiApps system. In conclusion, the responses of the reactor to a series of transient scenarios were simulated to demonstrate the exceptional and inherent safety features of the novel microreactor concept.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Impacts of Regional Coordination on Transmission Needs for Power System Resource Adequacy [Slides]

Resource adequacy (RA) is an important component of bulk power system reliability that addresses whether there are sufficient resources available to meet electricity demand at all times. RA analysis is used to assess whether the planned power system will provide reliable electricity to consumers while accounting for equipment outages, weather variability, and load uncertainty. Coordination between regions can enable resource sharing to meet RA needs if sufficient transmission capacity exists. Transmission's role in RA coordination can be particularly pronounced for large power systems like the U.S. electricity grid which contains geographically diverse demand and weather-dependent resources. Depending on the level of coordination desired, existing inter-regional transmission capacity may not be sufficient. This study is designed to assess optimal pathways for the development of inter-regional transmission in the U.S. under varying levels of RA coordination. Results can inform long-term grid infrastructure planning and provide insights into potential benefits of greater coordination for generation and transmission planning between regional U.S. power systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Robust Scheduling of Networked Microgrids for Economics and Resilience Improvement

The benefits of networked microgrids in terms of economics and resilience are investigated and validated in this work. Considering the stochastic unintentional islanding conditions and conventional forecast errors of both renewable generation and loads, a two-stage adaptive robust optimization is proposed to minimize the total operating cost of networked microgrids in the worst scenario of the modeled uncertainties. By coordinating the dispatch of distributed energy resources (DERs) and responsive demand among networked microgrids, the total operating cost is minimized, which includes the start-up and shut-down cost of distributed generators (DGs), the operation and maintenance (O&M) cost of DGs, the cost of buying/selling power from/to the utility grid, the degradation cost of energy storage systems (ESSs), and the cost associated with load shedding. The proposed optimization is solved with the column and constraint generation (C&CG) algorithm. The results of case studies demonstrate the advantages of networked microgrids over independent microgrids in terms of reducing total operating cost and improving the resilience of power supply.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2004

Investigation of Navier-Stokes Code Verification and Design Optimization

With rapid progress made in employing computational techniques for various complex Navier-Stokes fluid flow problems, design optimization problems traditionally based on empirical formulations and experiments are now being addressed with the aid of computational fluid dynamics (CFD). To be able to carry out an effective CFD-based optimization study, it is essential that the uncertainty and appropriate confidence limits of the CFD solutions be quantified over the chosen design space. The present dissertation investigates the issues related to code verification, surrogate model-based optimization and sensitivity evaluation. For Navier-Stokes (NS) CFD code verification a least square extrapolation (LSE) method is assessed. This method projects numerically computed NS solutions from multiple, coarser base grids onto a freer grid and improves solution accuracy by minimizing the residual of the discretized NS equations over the projected grid. In this dissertation, the finite volume (FV) formulation is focused on. The interplay between the xi concepts and the outcome of LSE, and the effects of solution gradients and singularities, nonlinear physics, and coupling of flow variables on the effectiveness of LSE are investigated. A CFD-based design optimization of a single element liquid rocket injector is conducted with surrogate models developed using response surface methodology (RSM) based on CFD solutions. The computational model consists of the NS equations, finite rate chemistry, and the k-6 turbulence closure. With the aid of these surrogate models, sensitivity and trade-off analyses are carried out for the injector design whose geometry (hydrogen flow angle, hydrogen and oxygen flow areas and oxygen post tip thickness) is optimized to attain desirable goals in performance (combustion length) and life/survivability (the maximum temperatures on the oxidizer post tip and injector face and a combustion chamber wall temperature). A preliminary multi-objective optimization study is carried out using a geometric mean approach. Following this, sensitivity analyses with the aid of variance-based non-parametric approach and partial correlation coefficients are conducted using data available from surrogate models of the objectives and the multi-objective optima to identify the contribution of the design variables to the objective variability and to analyze the variability of the design variables and the objectives. In summary the present dissertation offers insight into an improved coarse to fine grid extrapolation technique for Navier-Stokes computations and also suggests tools for a designer to conduct design optimization study and related sensitivity analyses for a given design problem.

Vaidyanathan, Rajkumar↗
NASA NTRS1995

Aerodynamic shape optimization of wing and wing-body configurations using control theory

This paper describes the implementation of optimization techniques based on control theory for wing and wing-body design. In previous studies it was shown that control theory could be used to devise an effective optimization procedure for airfoils and wings in which the shape and the surrounding body-fitted mesh are both generated analytically, and the control is the mapping function. Recently, the method has been implemented for both potential flows and flows governed by the Euler equations using an alternative formulation which employs numerically generated grids, so that it can more easily be extended to treat general configurations. Here results are presented both for the optimization of a swept wing using an analytic mapping, and for the optimization of wing and wing-body configurations using a general mesh.

Reuther, James↗
DOE OSTI2021

Controlling distributed energy resources via deep reinforcement learning for load flexibility and energy efficiency

Behind-the-meter distributed energy resources (DERs), including building solar photovoltaic (PV) technology and electric battery storage, are increasingly being considered as solutions to support carbon reduction goals and increase grid reliability and resiliency. However, dynamic control of these resources in concert with traditional building loads, to effect efficiency and demand flexibility, is not yet commonplace in commercial control products. Traditional rule-based control algorithms do not offer integrated closed-loop control to optimize across systems, and most often, PV and battery systems are operated for energy arbitrage and demand charge management, and not for the provision of grid services. More advanced control approaches, such as MPC control have not been widely adopted in industry because they require significant expertise to develop and deploy. Recent advances in deep reinforcement learning (DRL) offer a promising option to optimize the operation of DER systems and building loads with reduced setup effort. However, there are limited studies that evaluate the efficacy of these methods to control multiple building subsystems simultaneously. Additionally, most of the research has been conducted in simulated environments as opposed to real buildings. This paper proposes a DRL approach that uses a deep deterministic policy gradient algorithm for integrated control of HVAC and electric battery storage systems in the presence of on-site PV generation. The DRL algorithm, trained on synthetic data, was deployed in a physical test building and evaluated against a baseline that uses the current best-in-class rule-based control strategies. Performance in delivering energy efficiency, load shift, and load shed was tested using price-based signals. The results showed that the DRL-based controller can produce cost savings of up to 39.6% as compared to the baseline controller, while maintaining similar thermal comfort in the building. The project team has also integrated the simulation components developed during this work as an OpenAIGym environment and made it publicly available so that prospective DRL researchers can leverage this environment to evaluate alternate DRL algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Advanced Transmission Technologies (ATTs) Supplier Cohort Workshops Cohort Summary [Slides]

This Summary slide deck summarizes the key outcomes of the Advanced Transmission Technologies (ATTs) supplier cohort, part of Idaho National Laboratory’s (INL) Technical Assistance for Digital Assurance (TADA) program. The program aimed to strengthen grid resilience through cybersecurity controls, supply-chain security, and Cyber-Informed Engineering (CIE) for advanced transmission technologies. The cohort brought together vendors representing the full range of Grid-Enhancing Technologies (GETs), including providers of Dynamic Line Ratings (DLR), Advanced Power Flow Control (APFC), Transmission Topology Optimization (TTO), and High-Performance Conductors (HPCs). Discussions focused on institutional, integration, and operational barriers limiting GET adoption; cybersecurity risks at EMS/SCADA, cloud, and network integration points; and supply-chain transparency issues such as semiconductor dependence and SBOM/HBOM expectations. Participants also addressed operator trust, human-in-the-loop requirements, and challenges with utility adoption, while exploring how CIE can support secure deployment of GETs. This deck represents a consolidated summary of challenges and risks identified by vendors, cross-cutting themes and technology-specific insights from three cohort workshops, and actionable mitigations to guide utilities, vendors, and the Department of Energy in advancing secure, trusted deployment of GETs.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

PMU-data-driven Event Classification in Power Transmission Grids

This paper presents an event classification in transmission grids. The convolutional neural network (CNN)-based classifier is proposed to capture the temporal similarity of time-synchronized data stream from phasor measurement units (PMUs). The proposed CNN is trained using Bayesian optimization to search for the best hyperparameters. The effectiveness of the proposed event classification is validated through the real-world dataset from the U.S. transmission grids. This dataset includes line outage, transformer outage, frequency, and oscillation events. The validation process also includes different PMU outputs, such as voltage magnitude, phase angle, current magnitude, frequency, and rate of change of frequency (ROCOF). The results show that ROCOF gives the best classification performance compared to other PMU outputs. In addition, it is shown that the classifier trained with a larger dataset has higher accuracy. Moreover, the superiority of the proposed method is validated through comparison with other state-of-the-art classification methods.

Niazazari, Iman↗
DOE OSTI2015

SU-E-T-331: Dosimetric Impact of Multileaf Collimator Leaf Width On Stereotactic Radiosurgery (SRS) RapidArc Treatment Plans for Single and Multiple Brain Metastases

Purpose: To determine the effects of multileaf collimator (MLC) leaf width on normal-brain-tissue doses and dose conformity of SRS RapidArc treatment plans for brain tumors. Methods: Ten patients with 24 intracranial tumors (seven with 1–2 and three with 4–6 lesions) were planned using RapidArc for both Varian Millennium 120 MLC (5 mm leaf width) and high definition (HD) MLC (2.5 mm leaf width). Between 2 and 8 arcs were used with two full coplanar arcs and the rest non-coplanar half arcs. 6 MV beams were used and plans were optimized with a high priority to the Normal Tissue Objective (to achieve dose conformity and sharp dose fall-off) and normal brain tissue. Calculation was done using AAA on a 1 mm grid size. The prescription dose ranged from 14–22 Gy. Plans were normalized such that 99% of the target received the prescription dose. Identical beam geometries, optimizations, calculations, and normalizations were used for both plans. Paddick Conformity Index (PCI), V4, V8 and V12 Gy for normal brain tissue and Integral Dose were used for analysis. Results: In all cases, HD MLC plans performed better in sparing normal brain tissue, achieving a higher PCI with a lower Integral Dose. The average PCI for all 24 targets was 0.75±0.23 and 0.70±0.23 (p ≤0.0015) for HD MLC and Millennium MLC plans, respectively. The average ratio of normal brain doses for Millennium MLC to HD MLC plans was 1.30±0.16, 1.27±0.15, and 1.31±0.18 for the V4, V8, and V12, respectively. The differences in normal brain dose for all criteria were statistically significant with p-value < 0.02. On average Millennium MLC plans had a 16% higher integral dose than HD MLC plans. Conclusion: Significantly better dose conformity with reduced volume of normal brain tissue and integral dose was achieved with HD MLC plans compared to Millennium MLC plans.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Electrolyzers Enhancing Flexibility in Electric Grids

This paper presents a real-time simulation with hardware-in-the-loop (HIL) based approach for verifying the performance of electrolyzer systems in providing grid support. Hydrogen refueling stations premdominantly use electrolyzer systems to generate hydrogen, and are proposed to have the potential of becoming smarter loads which can pro-actively provide grid services. Based on experimental findings electrolyzer systems are observed to have a high level of controllability and hence can add flexibility to the grid from demand side. Greater awareness and controllability is proposed, developed, implemented, and tested by a 'frond end controller' in real-time environment. It can optimize the operation of electrolyzer systems based on the information collected by a communication module. Real-time tests are performed to verify the performance of front end controller driven electrolyzers to provide grid support that enables greater economic revenue and grid support for hydrogen producers under dynamic conditions. The front end controller proposed in this paper is tested with electrolyzers, however it is proposed as a generic control topology that is applicable to any load.

08 HYDROGEN↗
DOE OSTI2021

Design and dispatch optimization of packaged ice storage systems within a connected community

The traditional implementation of cool thermal energy storage (CTES) must be reimagined within the context of a dynamic grid and smart buildings operating as connected communities. As most buildings do not operate central chillers or connect to district cooling loops, this necessitates a broader use of packaged CTES. Our objective is to begin answering the question of how such packaged CTES should be implemented within a connected community. We do so by presenting a simulation–optimization workflow employing building energy modeling software and a mixed-integer linear program to design and dispatch a packaged CTES technology to achieve minimum total annual cost. We demonstrate this methodology on a seven-building case study using current utility rates and find that total annual cooling energy costs can be reduced by 17.8% compared to baseline, after accounting for the cost of storage. We perform three parametric sensitivity studies to evaluate modeling assumptions and obtain the prioritization of storage procurement as a function of annualized life-cycle cost of storage. We find that a community optimization approach provides significantly different results than individual building optimizations and provides greater savings compared to baseline.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Demand Response Resources for Energy and Ancillary Services (Presentation)

Demand response (DR) resources present a potentially important source of grid flexibility particularly on future systems with high penetrations of variable wind an solar power generation. However, DR in grid models is limited by data availability and modeling complexity. This presentation focuses on the co-optimization of DR resources to provide energy and ancillary services in a production cost model of the Colorado test system. We assume each DR resource can provide energy services by either shedding load or shifting its use between different times, as well as operating

14 SOLAR ENERGY↗