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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Overbuilding & curtailment: The cost-effective enablers of firm PV generation

Current thinking considers that PV output curtailment is a last resort measure to be avoided. In this article, we argue that supply-shaping, achieved through proactive curtailment associated with PV oversupply, is actually critical to achieving intermittency mitigation and delivering firm PV generation at the lowest cost. We investigate the premium to transform a low-cost, but intermittent solar kWh into a firm, effectively dispatchable kWh. We show that a fundamental ingredient of minimizing this premium is to optimally overbuild and, as necessary and appropriate, curtail PV generation. Drawing on a case study in the State of Minnesota, we show that firm, high-penetration-ready PV generation could be achieved at a production cost at or below current conventional generation, especially when optimally coupled with wind generation. Here, we conclude with a recommendation that in order to achieve this lowest cost firm generation potential, proactive curtailment strategies should inform future transactional PV remuneration systems.

14 SOLAR ENERGY↗
DOE OSTI2022

Synchronization in electric power networks with inherent heterogeneity up to 100% inverter-based renewable generation

The synchronized operation of power generators is the foundation of electric power network stability and a key to the prevention of undesired power outages and blackouts. Here, we derive the conditions that guarantee synchronization in power networks with inherent generator heterogeneity when subjected to small perturbations, and perform a parametric sensitivity analysis to understand synchronization with varied types of generators. As inverter-based resources, which are the primary interfacing technology for many renewable sources of energy, have supplanted synchronous generators in ever growing numbers, the center of attention on associated integration challenges have resided primarily on the role of declining system inertia. Our results instead highlight the critical role of generator damping in achieving a stable state of synchronization. Additionally, we report the feasibility of operating interconnected electric grids with up to 100% power contribution from inverter-based renewable generation technologies. Our study has important implications as it sets the basis for the development of advanced control architectures and grid optimization methods that ensure synchronization and further pave the path towards the decarbonization of the electric power sector.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2011

Measurement of optical emission from the hydrogen plasma of the Linac4 ion source and the SPL plasma generator

At CERN, a non caesiated H{sup -} ion volume source derived from the DESY ion source is being commissioned. For a proposed High Power Superconducting Proton Linac (HP-SPL), a non caesiated plasma generator was designed to operate at the two orders of magnitude larger duty factor required by the SPL. The commissioning of the plasma generator test stand and the plasma generator prototype are completed and briefly described. The 2 MHz RF generators (100 kW, 50 Hz repetition rate) was successfully commissioned; its frequency and power will be controlled by arbitrary function generators during the 1 ms plasma pulse. In order to characterize the plasma, RF-coupling, optical spectrometer, rest gas analyzer and Langmuir probe measurements will be used. Optical spectrometry allows direct comparison with the currently commissioned Linac4 H{sup -} ion source plasma. The first measurements of the optical emission of the Linac4 ion source and of the SPL plasma generator plasmas are presented.

43 PARTICLE ACCELERATORS↗
DOE OSTI2013

Laser-induced breakdown and damage generation by nonlinear frequency conversion in ferroelectric crystals: Experiment and theory

Using our experimental data for ns pulsed second harmonic generation (SHG) by periodically poled stoichiometric LiTaO{sub 3} (PPSLT) crystals, we consider in detail the mechanism underlying laser-induced damage in ferroelectric crystals. This mechanism involves generation and heating of free electrons, providing an effective kinetic pathway for electric breakdown and crystal damage in ns pulsed operation via combined two-photon absorption (TPA) and induced pyroelectric field. In particular, a temperature increase in the lattice of ≈1 K induced initially by ns SHG and TPA at the rear of operating PPSLT crystal is found to induce a gradient of spontaneous polarization generating a pyroelectric field of ≈10 kV/cm, accelerating free electrons generated by TPA to an energy of ≈10 eV, followed by impact ionization and crystal damage. Under the damage threshold for ns operation, the impact ionization does not lead to the avalanche-like increase of free electron density, in contrast to the case of shorter ps and fs pulses. However, the total number of collisions by free electrons, ≈10{sup 18} cm{sup −3} (generated during the pulse and accelerated to the energy of ≈10 eV), can produce widespread structural defects, which by entrapping electrons dramatically increase linear absorption for both harmonics in subsequent pulses, creating a positive feedback for crystal lattice heating, pyroelectric field and crystal damage. Under pulse repetition, defect generation starting from the rear of the crystal can propagate towards its center and front side producing damage tracks along the laser beam and stopping SHG. Theoretical analysis leads to numerical estimates and analytical approximation for the threshold laser fluence for onset of this damage mechanism, which agree well with our (i) experiments for the input 1064 nm radiation in 6.8 kHz pulsed SHG by PPSLT crystal, (ii) pulsed low frequency 532 nm radiation transmission experiments, and also (iii) with the data published for other nonlinear crystals and operated wavelengths.

36 MATERIALS SCIENCE↗
DOE OSTI2014

An 8-GW long-pulse generator based on Tesla transformer and pulse forming network

A long-pulse generator TPG700L based on a Tesla transformer and a series pulse forming network (PFN) is constructed to generate intense electron beams for the purpose of high power microwave (HPM) generation. The TPG700L mainly consists of a 12-stage PFN, a built-in Tesla transformer in a pulse forming line, a three-electrode gas switch, a transmission line with a trigger, and a load. The Tesla transformer and the compact PFN are the key technologies for the development of the TPG700L. This generator can output electrical pulses with a width as long as 200 ns at a level of 8 GW and a repetition rate of 50 Hz. When used to drive a relative backward wave oscillator for HPM generation, the electrical pulse width is about 100 ns on a voltage level of 520 kV. Factors affecting the pulse waveform of the TPG700L are also discussed. At present, the TPG700L performs well for long-pulse HPM generation in our laboratory.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

Hydrogen-based power generation from bioethanol steam reforming

This paper is evaluating two power generation concepts based on hydrogen produced from bioethanol steam reforming at industrial scale without and with carbon capture. The power generation from bioethanol conversion is based on two important steps: hydrogen production from bioethanol catalytic steam reforming and electricity generation using a hydrogen-fuelled gas turbine. As carbon capture method to be assessed in hydrogen-based power generation from bioethanol steam reforming, the gas-liquid absorption using methyl-di-ethanol-amine (MDEA) was used. Bioethanol is a renewable energy carrier mainly produced from biomass fermentation. Steam reforming of bioethanol (SRE) provides a promising method for hydrogen and power production from renewable resources. SRE is performed at high temperatures (e.g. 800-900°C) to reduce the reforming by-products (e.g. ethane, ethene). The power generation from hydrogen was done with M701G2 gas turbine (334 MW net power output). Hydrogen was obtained through catalytic steam reforming of bioethanol without and with carbon capture. For the evaluated plant concepts the following key performance indicators were assessed: fuel consumption, gross and net power outputs, net electrical efficiency, ancillary consumptions, carbon capture rate, specific CO{sub 2} emission etc. As the results show, the power generation based on bioethanol conversion has high energy efficiency and low carbon footprint.

08 HYDROGEN↗
DOE OSTI2023

LHC hadronic jet generation using convolutional variational autoencoders with normalizing flows

Abstract In high energy physics, one of the most important processes for collider data analysis is the comparison of collected and simulated data. Nowadays the state-of-the-art for data generation is in the form of Monte Carlo (MC) generators. However, because of the upcoming high-luminosity upgrade of the Large Hadron Collider (LHC), there will not be enough computational power or time to match the amount of needed simulated data using MC methods. An alternative approach under study is the usage of machine learning generative methods to fulfill that task. Since the most common final-state objects of high-energy proton collisions are hadronic jets, which are collections of particles collimated in a given region of space, this work aims to develop a convolutional variational autoencoder (ConVAE) for the generation of particle-based LHC hadronic jets. Given the ConVAE’s limitations, a normalizing flow (NF) network is coupled to it in a two-step training process, which shows improvements on the results for the generated jets. The ConVAE+NF network is capable of generating a jet in 18.30 ± 0.04 μ s , making it one of the fastest methods for this task up to now.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Unified Medical Language System resources improve sieve-based generation and Bidirectional Encoder Representations from Transformers (BERT)–based ranking for concept normalization

Concept normalization, the task of linking phrases in text to concepts in an ontology, is useful for many downstream tasks including relation extraction, information retrieval, etc. We present a generate-and-rank concept normalization system based on our participation in the 2019 National NLP Clinical Challenges Shared Task Track 3 Concept Normalization. The shared task provided 13 609 concept mentions drawn from 100 discharge summaries. We first design a sieve-based system that uses Lucene indices over the training data, Unified Medical Language System (UMLS) preferred terms, and UMLS synonyms to generate a list of possible concepts for each mention. We then design a listwise classifier based on the BERT (Bidirectional Encoder Representations from Transformers) neural network to rank the candidate concepts, integrating UMLS semantic types through a regularizer. Our generate-and-rank system was third of 33 in the competition, outperforming the candidate generator alone (81.66% vs 79.44%) and the previous state of the art (76.35%). During postevaluation, the model’s accuracy was increased to 83.56% via improvements to how training data are generated from UMLS and incorporation of our UMLS semantic type regularizer. Analysis of the model shows that prioritizing UMLS preferred terms yields better performance, that the UMLS semantic type regularizer results in qualitatively better concept predictions, and that the model performs well even on concepts not seen during training. Our generate-and-rank framework for UMLS concept normalization integrates key UMLS features like preferred terms and semantic types with a neural network–based ranking model to accurately link phrases in text to UMLS concepts.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

TRIM: AI Guided Random Number Generation for Resource-Constrained IoT Systems

Random numbers often serve as the backbone for many security solutions in diverse domains such as cryptography, side channel leakage prevention, and moving target defense. However, generating true random numbers requires a physical source of entropy (e.g. hardware, quantum, environmental phenomenon) making it difficult to realize at a large scale and at a low cost. On the flip side, pseudorandom number generators (easy to implement) following a specific distribution (e.g. Gaussian) can be easily compromised given a sufficient amount of traces. In this work, we have developed a machine learning-guided generative approach that can be used to create portable, resource-efficient, and cost-effective random number generators with high throughput and true randomness characteristics. We implement the proposed approach as a highly parameterized framework and perform extensive evaluation for different settings. The framework was able to learn from true random sources such as irrational numbers and environmental audio noise and imitate those sources towards generating new good quality random numbers on demand. We have generated more than 1 billion bits and observed robust performance in terms of true randomness metrics obtained from NIST SP 800-22 and FIPS 140-1 randomness test suites achieving a throughput of up to 142.85 Mbps. Compared to the state-of-the-art (SOTA) technique, the iso-cost setup of our framework can achieve more than 500 Mbps in a distributed setting. We have evaluated the efficacy of running the true randomness imitation AI models on target edge devices such as Raspberry Pi 4 (Model B), Nvidia Jetson Nano, Nvidia Jetson Orin Nano and Nvidia Jetson Xavier. We have also looked at the security of the TRIM framework itself against different adversarial threat models.

Cybersecurity↗
DOE OSTI2022

System Resilience Benefits of Dual-Fuel Capable Generators

The growing dependency on natural gas (NG) for power generation raises challenges for ensuring the resilience of power systems during extreme cold weather. Dual-fuel capable generators that can switch from burning NG to distillate fuel oil during a NG shortage offer one way to alleviate these challenges. In this study, the impacts of gas unavailability on the IEEE 73- bus reliability test system (RTS) with 2019 updated generation mixture are explored. An extension to the standard production cost model formulation of unit commitment and economic dis- patch is proposed to allow representation of dual-fuel capable generators that can switch fuels between NG and distillate oil with a specified oil tank capacity and tank refueling capability. The operation of the system under gas unavailability with 0%, 25%, 50%, 75%, and 100% of combined cycle and combustion turbine generators as dual-fuel capable with a one-day supply of fuel oil are simulated using PLEXOS, a production cost model. The dual-fuel generator performance, unserved energy, and system costs are fully assessed.

duel-fuel generator performance↗
DOE OSTI2025

Stochastic Adaptive Droop Control in Frequency Regulation of Power Systems With Intermittent Generators

Modern power systems (MPSs), including microgrids (MGs), are increasingly incorporating multiple renewable energy sources (RESs) such as wind and solar power, as well as battery storage and controllable loads. While environmentally beneficial, these sources pose challenges for control and management due to their intermittent and stochastic nature, especially in maintaining frequency stability with multiple interconnected generators of varying capacities. Traditional droop control methods are effective in systems with generators that are dispatchable and have fixed generation capacities, but they fall short when applied to systems with RESs, where generation capacities are dynamic and affected by unpredictable environmental conditions. To address these challenges, this paper introduces a novel stochastic adaptive droop control (SADC) method for load frequency control (LFC). The proposed method adapts droop coefficients in real time, based on the measured stochastic data of power generation capacities, enabling more effective frequency regulation in systems with variable and intermittent power generation. Unlike traditional adaptive control methods, which assume constant or slowly-varying system parameters, this approach accounts for stochastic processes by modeling them as Markov chains, enabling robust performance under highly dynamic and unpredictable conditions. The key contributions of this work include the development of real-time droop coefficient adaptation algorithms, derivation of their stability and convergence properties, and the demonstration of the advantages of the method through simulations. Case studies highlight the improved performance of frequency regulation, particularly in addressing the impact of stochastic weather conditions and the benefits of reducing dependence on battery reserves in dealing with intermittency of RESs. Finally, this paper provides a comprehensive analysis of the theoretical foundations of the method, as well as practical implementation insights for future power systems with high penetration of RESs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Toward Improving the Generation Quality of Autoregressive Slot VAEs

Unconditional scene inference and generation are challenging to learn jointly with a single compositional model. Despite encouraging progress on models that extract object-centric representations (“slots”) from images, unconditional generation of scenes from slots has received less attention. This is primarily because learning the multiobject relations necessary to imagine coherent scenes is difficult. We hypothesize that most existing slot-based models have a limited ability to learn object correlations. We propose two improvements that strengthen object correlation learning. The first is to condition the slots on a global, scene-level variable that captures higher-order correlations between slots. Second, we address the fundamental lack of a canonical order for objects in images by proposing to learn a consistent order to use for the autoregressive generation of scene objects. Specifically, we train an autoregressive slot prior to sequentially generate scene objects following a learned order. Ordered slot inference entails first estimating a randomly ordered set of slots using existing approaches for extracting slots from images, then aligning those slots to ordered slots generated autoregressively with the slot prior. Our experiments across three multiobject environments demonstrate clear gains in unconditional scene generation quality. Detailed ablation studies are also provided that validate the two proposed improvements.

MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Developing an Automated Microscopic Traffic Simulation Scenario Generation Tool

Traffic simulation is an effective tool for urban planners, traffic engineers, and researchers to study traffic. In particular, microscopic traffic simulation, which simulates individual vehicles’ movements within a transportation network, has demonstrated its importance in analyzing and managing transportation systems. However, integrating data from various sources, generating traffic scenarios, and importing information into traffic simulators to conduct microscopic simulations have always been a challenge. This paper presents a solution to overcome this challenge: RealTwin, a comprehensive tool for automated scenario generation for microscopic traffic simulation. Following a streamlined scenario generation and calibration workflow, RealTwin effectively bridges gaps between traffic data from various sources and traffic simulators, making microscopic traffic simulation more accessible for researchers and engineers across various levels of expertise. Using RealTwin to generate a real-world traffic scenario in Simulation of Urban Mobility (SUMO), VISSIM, and AIMSUN, RealTwin’s ability is demonstrated in the construction of realistic and consistent traffic scenarios in different simulators. Furthermore, this paper introduces and illustrates RealTwin’s capability for technology (e.g., autonomous vehicle) scenario generation. This feature can contribute to more comprehensive microscopic simulations, facilitating the analysis of potential effects of various technological innovations on mobility, energy efficiency, and safety. Finally, RealTwin is used to calibrate a simulation in SUMO. In conclusion, the calibration module enhances RealTwin’s ability to generate consistent simulations across different platforms and more realistic simulations that reflect real-world traffic operations.

autonomous vehicle↗
DOE OSTI2019

Laboratory Foamed-Cement-Curing Evolution Using CT Scanning: Insights From Elevated-Pressure Generation

Computed-tomography (CT) scanning has become a mainstay among scientists (Wildenschild and Sheppard 2013) because it enables nondestructive observation of material processes and formation in real time. Foamed cement is a high-strength, low-density material containing nitrogen gas, and is used to stabilize wellbore casings both onshore and offshore. In-situ foamed cement is subject to pressure changes because the slurry is pumped downhole and cures at depth. To correlate the influence of pressure to the gas-void size and the curing evolution of a foamed cement, two laboratory foamed cements were generated and CT scanned as they cured. One cement was generated following the American Petroleum Institute (API) industry standard API RP 10B-4 (2015) at atmospheric conditions using a blender, and the other cement was created using a foamed-cement generator (FCG) (resembling that of de Rozières and Ferrière 1991) to produce a sample at an elevated pressure. FCG-generated cement qualities (in the range of 20, 25, 30, 35, and 40%) were scanned at their cured state for comparison. From the CT-image time series and the single FCG scans, the volumetric void properties were characterized and compared. The time-series blender voids were an order of magnitude larger than the FCG voids, and void growth was stagnant after a curing period of 100 minutes, whereas the FCG voids gradually increased in volume after 100 minutes. The Hsü-Nadai plots (Brandon 1995) reveal that the FCG and blender voids are weakly prolate, and all FCG voids, regardless of generation quality, relax to a greater final-magnitude strain than the blender voids. Furthermore, these findings confirm that both the void size and the curing process are influenced by the pressure at which a foamed cement is generated.

36 MATERIALS SCIENCE↗
DOE OSTI2012

Survey of Variable Generation Forecasting in the West: August 2011 - June 2012

This report surveyed Western Interconnection Balancing Authorities regarding their implementation of variable generation forecasting, the lessons learned to date, and recommendations they would offer to other Balancing Authorities who are considering variable generation forecasting. Our survey found that variable generation forecasting is at an early implementation stage in the West. Eight of theeleven Balancing Authorities interviewed began forecasting in 2008 or later. It also appears that less than one-half of the Balancing Authorities in the West are currently utilizing variable generation forecasting, suggesting that more Balancing Authorities in the West will engage in variable generation forecasting should more variable generation capacity be added.

17 WIND ENERGY↗
DOE OSTI2013

Low-temperature Stirling Engine for Geothermal Electricity Generation

Up to 2700 terawatt-hours per year of geothermal electricity generation capacity has been shown to be available within North America, typically with wells drilled into geologically active regions of the earth's crust where this energy is concentrated (Huttrer, 2001). Of this potential, about half is considered to have temperatures high enough for conventional (steam-based) power production, while the other half requires unconventional power conversion approaches, such as organic Rankine cycle systems or Stirling engines. If captured and converted effectively, geothermal power generation could replace up to 100GW of fossil fuel electric power generation, leading to a significant reduction of US power sector emissions. In addition, with the rapid growth of hydro-fracking in oil and gas production, there are smaller-scale distributed power generation opportunities in heated liquids that are co-produced with the main products. Since 2006, Cool Energy, Inc. (CEI) has designed, fabricated and tested four generations of low-temperature (100°C to 300°C) Stirling engine power conversion equipment. The electric power output of these engines has been demonstrated at over 2kWe and over 16% thermal conversion efficiency for an input temperature of 215°C and a rejection temperature of 15°C. Initial pilot units have been shipped to development partners for further testing and validation, and significantly larger engines (20+ kWe) have been shown to be feasible and conceptually designed. Originally intended for waste heat recovery (WHR) applications, these engines are easily adaptable to geothermal heat sources, as the heat supply temperatures are similar. Both the current and the 20+ kWe designs use novel approaches of self-lubricating, low-wear-rate bearing surfaces, non-metallic regenerators, and high-effectiveness heat exchangers. By extending CEI's current 3 kWe SolarHeart® Engine into the tens of kWe range, many additional applications are possible, as one 20 kWe design produces nearly seven times the power output of the 3 kWe unit but at only 2.5 times the estimated fabrication cost. Phase I of the proposed SBIR program will therefore study the feasibility of generating electricity with one or more 20 kWe or larger Stirling engines, powered by geothermal heat produced by current and possibly some forward-looking borehole extraction methods, and from producing oil and gas wells. The feasibility study will include full analysis of the thermodynamic and heat transfer processes within the engine (necessary to produce optimum theoretical designs and performance maps), the cost of pumping the geothermal heat recovery fluid, and how the system tradeoffs impact the overall system economics. The goal is a geothermal system design that could be demonstrated during a Phase II follow-on program at a field test site.

15 GEOTHERMAL ENERGY↗
DOE OSTI2016

Evaluation of CFD Methods for Simulation of Two-Phase Boiling Flow Phenomena in a Helical Coil Steam Generator

The U.S. Department of Energy, Office of Nuclear Energy charges participants in the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program with the development of advanced modeling and simulation capabilities that can be used to address design, performance and safety challenges in the development and deployment of advanced reactor technology. The NEAMS has established a high impact problem (HIP) team to demonstrate the applicability of these tools to identification and mitigation of sources of steam generator flow induced vibration (SGFIV). The SGFIV HIP team is working to evaluate vibration sources in an advanced helical coil steam generator using computational fluid dynamics (CFD) simulations of the turbulent primary coolant flow over the outside of the tubes and CFD simulations of the turbulent multiphase boiling secondary coolant flow inside the tubes integrated with high resolution finite element method assessments of the tubes and their associated structural supports. This report summarizes the demonstration of a methodology for the multiphase boiling flow analysis inside the helical coil steam generator tube. A helical coil steam generator configuration has been defined based on the experiments completed by Polytecnico di Milano in the SIET helical coil steam generator tube facility. Simulations of the defined problem have been completed using the Eulerian-Eulerian multi-fluid modeling capabilities of the commercial CFD code STAR-CCM+. Simulations suggest that the two phases will quickly stratify in the slightly inclined pipe of the helical coil steam generator. These results have been successfully benchmarked against both empirical correlations for pressure drop and simulations using an alternate CFD methodology, the dispersed phase mixture modeling capabilities of the open source CFD code Nek5000.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2014

A Lightweight, Direct-Drive, Fully Superconducting Generator for Large Wind Turbines

The current trend in the offshore wind turbine industry favors direct-drive generators based on permanent magnets, as they allow for a simple and reliable drivetrain without a gearbox. These generators, however, do not scale very well to high power levels beneficial for offshore wind, and their use in wind turbines over 6 MW is questionable in terms of mass and economic feasibility. Moreover, rare earth materials composing the permanent magnets are becoming less available, more costly and potentially unavailable in the foreseeable future. A stated goal of the DOE is a critical materials strategy that pursues the development of substitute materials and technology for rare earth materials to improve supply chain flexibility and meet the needs of the clean energy economy.Therefore, alternative solutions are needed, in terms of both favorable up-scaling and minimizing or eliminating the use of permanent magnets. The generator design presented in this document addresses both these issues with the development of a fully superconducting generator (FSG) with unprecedented high specific torque. A full-scale, 10-MW, 10-rpm generator will weigh less about 150 metric tons, compared to 300 metric tons for an equivalent direct-drive, permanent magnet generator. The developed concept does not use any rare earth materials in its critical drive components, but rather relies on a superconductor composed of mainly magnesium and boron (MgB2), both of which are in abundant supply from multiple global sources.

17 WIND ENERGY↗