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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Automating Component-Level Stress Measurements for Inverter Reliability Estimation

In the near future, grid operators are expected to regularly use advanced distributed energy resource (DER) functions, defined in IEEE 1547-2018, to perform a range of grid-support operations. Many of these functions adjust the active and reactive power of the device through commanded or autonomous operating modes which induce new stresses on the power electronics components. In this work, an experimental and theoretical framework is introduced which couples laboratory-measured component stress with advanced inverter functionality and derives a reduction in useful lifetime based on an applicable reliability model. Multiple DER devices were instrumented to calculate the additional component stress under multiple reactive power setpoints to estimate associated DER lifetime reductions. A clear increase in switch loss was demonstrated as a function of irradiance level and power factor. This is replicated in the system-level efficiency measurements, although magnitudes were different—suggesting other loss mechanisms exist. Using an approximate Arrhenius thermal model for the switches, the experimental data indicate a lifetime reduction of 1.5% when operating the inverter at 0.85 PF—compared to unity PF—assuming the DER failure mechanism thermally driven within the H-bridge. If other failure mechanisms are discovered for a set of power electronics devices, this testing and calculation framework can easily be tailored to those failure mechanisms.

Flicker, Jack (ORCID:0000000212232154)↗
DOE OSTI2021

Design of High-Deflection Foils MHK Applications - FEA models

The Ocean Renewable Power Company's (ORPC's) goal is to design, develop, and test hydrofoils with large deflections. The effects of the deflections on cross-flow turbine performance would be evaluated in order to inform design considerations for full-scale water turbines and other marine hydrokinetic devices. Finite element models - NASTRAN files Model scale turbines tested in UNH tow tank Model loads from CFD models

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Multi-physics modeling of tungsten collector probe samples during the WEST C4 He campaign

Abstract We describe the results of a multi-scale, multi-physics modeling assessment of SOLPS-ITER, hPIC2, RustBCA and Xolotl, in which five single-crystal tungsten (W) samples were placed in a reciprocating collector probe and exposed to helium (He) plasma in the WEST fusion device. In our models, we considered a pure (100 %) He plasma, as well as one with oxygen (O) present (95% He 5% O) corresponding to the impurity concentration estimated during the C4 He campaign in WEST. Our SOLPS simulations approximately match experimental reciprocating Langmuir probe plasma measurements of plasma density and temperature. Using these plasma parameters as input, hPIC2 and RustBCA predict that the presence of oxygen impurities lead to a 15%–20% decrease in ion and heat fluxes to the surface, and an order of magnitude higher sputtering yields (compared with a pure He plasma). Xolotl predictions for the response of tungsten to plasma surface interactions (PSIs) agree with experimental LAMS analysis, and indicate large near-surface He concentrations, which quickly decay with depth. Our model also shows an increasing role of erosion—in removing the near-surface He—with time. Overall, slightly higher retention is predicted for tungsten exposed to a pure He plasma, with the largest differences in the near-surface gas content caused by the large oxygen-induced erosion. This highlights the important role that impurities play in PSI. Therefore, future work will focus on providing a fully self-consistent description of oxygen (and oxides, etc.) in our models, through multi-species implementation in GITR and inclusion of oxygen and tungsten oxide formation in Xolotl.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Toward a Unified Framework for WEC Numerical Modeling

This presentation is about moving toward a united framework for WEC numerical modeling. A unified framework for WEC numerical modeling could help device developers on three fronts: 1) optimization; 2) more accurate load estimates; 3) validation.

modeling↗
DOE OSTI2021

D2U: Data Driven User Emulation for the Enhancement of Cyber Testing, Training, and Data Set Generation

Whether testing intrusion detection systems, conducting training exercises, or creating data sets to be used by the broader cybersecurity community, realistic user behavior is a critical component of a cyber range. Existing methods either rely on network level data or replay recorded user actions to approximate real users in a network. Our work is the first to produce generative models trained on actual user data (sequences of application usage) collected on endpoints. Once trained to the user's behavioral data, these models can generate novel sequences of actions %that appear to come from the same distribution as the training data. These sequences of actions are then fed to our custom software via configuration files, which replicate those behaviors on end devices. Notably, our models are platform agnostic and could generate behavior data for any emulation software package. In this paper we present our model generation process, software architecture, and an initial evaluation of the fidelity of our models. Our software is currently deployed in a cyber range to help evaluate the efficacy of defensive cyber technologies. We suggest additional ways that the cyber community as a whole can benefit from more realistic user behavior emulation. The data used to train our model, as well as sample configuration files produced by the model, are available at [redacted].

Oesch, T↗
DOE OSTI2023

High-bandwidth density silicon photonic resonators for energy-efficient optical interconnects

The growth of artificial intelligence applications demands ever larger and more complex deep learning models, dominating today's—and tomorrow's—data center and high-performance computing systems. While traditional electronics are failing to keep pace with application demands, silicon photonic (SiPh) interconnects have emerged as a necessary technology to support these systems. SiPh-driven wavelength-division multiplexing (WDM) offers a particularly promising path toward supporting incredibly high-aggregate link bandwidth in a compact and efficient form factor. One of the basic building blocks of these integrated WDM interconnects is the SiPh resonator. Their inherent wavelength selectivity and compact footprint allow for efficient data transmission multiplexed across dozens of carrier wavelengths. Used as add-drop (AD) filters, SiPh resonators are critical to constructing integrated tunable wavelength-selective optical circuit switches as well as for demultiplexing the different carrier wavelengths toward independent wavelength-insensitive photodiodes in a dense wavelength-division multiplexing receiver. Resonators in the all-pass (AP) configuration are widespread as well, allowing for wavelength-selective modulation to drive aggregate link bandwidths far beyond the individual channel data rate. Unlike SiPh Mach–Zehnder modulators (MZM), resonant modulators can be driven using low, complementary metal-oxide-semiconductor drive voltages, allowing for tight co-integration between photonic integrated circuits, fabricated with larger process node technologies, and electronic integrated circuits, designed to exploit the advantages of the latest node. To push toward practical peta-scale interconnects, a comprehensive review of SiPh resonators is required, addressing bottlenecks and design constraints at both the architecture and device levels. We first describe the predominant integrated link architectures and identify their limits. We then discuss the device-level design considerations that can be made for both AD and AP configuration resonators to overcome the system level limits with novel resonator device designs. Analytical models and numerical simulation of resonators are validated by experimental measurement of devices fabricated in a commercial 300-mm foundry, showing a clear path toward volume manufacturing. The demonstrated resonant modulators and filters support the feasibility of increasing the aggregate bandwidth of resonator-driven SiPh interconnects into the peta-scale regime.

42 ENGINEERING↗
DOE OSTI2021

Ocean Energy Systems Wave Energy Modeling Task 10.4: Numerical Modeling of a Fixed Oscillating Water Column

This paper reports on an ongoing international effort to establish guidelines for numerical modeling of wave energy converters, initiated by the International Energy Agency Technology Collaboration Program for Ocean Energy Systems. Initial results for point absorbers were presented in previous work, and here we present results for a breakwater-mounted Oscillating Water Column (OWC) device. The experimental model is at scale 1:4 relative to a full-scale installation in a water depth of 12.8 m. The power-extracting air turbine is modeled by an orifice plate of 1–2% of the internal chamber surface area. Measurements of chamber surface elevation, air flow through the orifice, and pressure difference across the orifice are compared with numerical calculations using both weakly-nonlinear potential flow theory and computational fluid dynamics. Both compressible- and incompressible-flow models are considered, and the effects of air compressibility are found to have a significant influence on the motion of the internal chamber surface. Recommendations are made for reducing uncertainties in future experimental campaigns, which are critical to enable firm conclusions to be drawn about the relative accuracy of the numerical models. It is well-known that boundary element method solutions of the linear potential flow problem (e.g., WAMIT) are singular at infinite frequency when panels are placed directly on the free surface. This is problematic for time-domain solutions where the value of the added mass matrix at infinite frequency is critical, especially for OWC chambers, which are modeled by zero-mass elements on the free surface. A straightforward rational procedure is described to replace ad-hoc solutions to this problem that have been proposed in the literature.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Quantum computer-enabled receivers for optical communication

Abstract Optical communication is the standard for high-bandwidth information transfer in today’s digital age. The increasing demand for bandwidth has led to the maturation of coherent transceivers that use phase- and amplitude-modulated optical signals to encode more bits of information per transmitted pulse. Such encoding schemes achieve higher information density, but also require more complicated receivers to discriminate the signaling states. In fact, achieving the ultimate limit of optical communication capacity, especially in the low light regime, requires coherent joint detection of multiple pulses. Despite their superiority, such joint detection receivers are not in widespread use because of the difficulty of constructing them in the optical domain. In this work we describe how optomechanical transduction of phase information from coherent optical pulses to superconducting qubit states followed by the execution of trained short-depth variational quantum circuits can perform joint detection of communication codewords with error probabilities that surpass all classical, individual pulse detection receivers. Importantly, we utilize a model of optomechanical transduction that captures non-idealities such as thermal noise and loss in order to understand the transduction performance necessary to achieve a quantum advantage with such a scheme. We also execute the trained variational circuits on an IBM-Q device with the modeled transduced states as input to demonstrate that a quantum advantage is possible even with current levels of quantum computing hardware noise.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Basic Physical Processes Involving Dust in Fusion Plasmas

This report presents the main outcomes of our research focused on understanding the behavior and effects of dust particles in fusion plasmas, particularly in the edge regions of tokamaks and stellarators. We conducted computer modeling studies of burst injections of carbon and tungsten dust particles in DIII-D like divertor plasmas. The studies investigated effects of transient influx of the low- and high-Z material plasma contaminants in form of dust on the edge plasma dynamics in a modern mid-size tokamak. We also performed theoretical and computational studies of the forces acting on non-spherical dust grains in magnetized and nonmagnetized plasmas. In addition, we cooperated with General Atomics slag management group on development of DIII-D dust injection experiments to measure trajectories of dust grains in the divertor plasma and compare them with DUSTT code predictions for validation of the dust modeling capabilities. We collaborated with JET experimentalists on evaluation of radiative losses induced by injection of mixed neon-deuterium ice pellets for disruption and run-away electron generation mitigation during thermal and current quench phases. We also cooperated with experimentalists at LHD fusion device (Japan) on modeling support of experiments on injection of boron granules in fusion plasma discharges to assess their dynamics and effectiveness for in situ dynamic wall conditioning.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2026

From IMT Device Measurements to Network-Level Consequences: When Learning Suppresses Beyond-LIF Neuron Dynamics

Emerging neuromorphic devices such as insulator--metal transition (IMT) devices exhibit complex temporal dynamics, including slow internal state memory, hysteresis, and burst-like firing, which are poorly captured by conventional leaky integrate-and-fire (LIF) neurons. However, it remains unclear when such dynamics influence learning and inference at the network level, particularly under commonly used unsupervised plasticity rules. We present a controlled, full-stack co-design study spanning experimental characterization of individual IMT devices, compact neuron model development, and large-scale spiking network simulations with identical architectures and learning rules. Rather than optimizing benchmark accuracy, our goal is to diagnose when neuron-level dynamics survive learning and competition, and when they are suppressed, to inform the co-design of devices, networks, and learning rules that can exploit beyond-LIF complexity.

42 ENGINEERING↗
DOE OSTI2020

A Novel Model of Thyristor in Reverse Recovery Process for Current Interruption Test of HVDC Circuit Breakers

The high voltage thyristor is widely used in high voltage DC (HVDC) grids due to its large current capability. Recently, the high voltage thyristor is implemented to produce a high current in the HVDC circuit breaker (CB) testing process. Unfortunately, the reverse recovery process (RRP) of a thyristor could induce significant turn-off overvoltage and power losses, jeopardizing the safety of the devices. The existing models of a thyristor cannot describe such hard-switching transient accurately. Therefore, this paper divides this process into four stages based on the physical mechanism and proposes a novel cosine exponential (CE), simulating the voltage and current of the thyristor with analytical equations, which are derived from the equivalent circuit. Moreover, the extraction procedure of the proposed model is illustrated in this paper. Finally, we develop an HVDC CB test platform to validate the proposed model. Experimental results show that the proposed CE model can accurately predict the overvoltage with a relative error of less than 8% at various current varying rates.

Dongye, Zhonghao↗
DOE OSTI2024

Toward High-Throughput Deposition of III-V Materials and Devices Using Halide Vapor Phase Epitaxy: Preprint

III-V devices are used in countless applications due to their excellent physical properties. They could become more prevalent, especially in area-intensive applications such as solar power, if they can achieve significant cost decreases through increasing scale. The development of high-throughput growth systems can help to achieve this scale, leading to the use of III-V devices in areas where they are not currently economically feasible. Here, we describe a pilot production, pseudo inline HVPE reactor with the potential to greatly increase the throughput of III-V devices. We show computational modeling results that both informed system design and the understanding of the impact of different process parameters on the deposition. We show the throughput possibilities of this reactor with an example solar cell device design but note that this system is agnostic to the device structure and can be used to increase the throughput of lasers, LEDs, transistors, and more III-V devices.

high throughput↗
DOE OSTI2022

Efficiency and Capacity Performance of a Stirling-Cycle Water-to-Water Heat Pump

The performance of a 10 kW (2.8 ton) heat pump has been modeled in preparation for evaluation in a controlled-atmosphere psychrometric facility. The heat pump uses an electrically driven Stirling engine with nitrogen as a working fluid. The appropriate standards for testing are ANSI/AHRI/ASHRAE ISO Standard 13256-2:1998 (RA 2012), Water-Source Heat Pumps—Testing and Rating for Performance—Part 2: Water-to-Water and Brine-to-Water Heat Pumps. The heating and cooling efficiency and capacity of the device has been modeled at different hot and cold sink temperatures spanning a wide range of possible operating conditions. The heat pump was designed for a seasonal efficiency energy ratio (SEER) of 22. The high efficiency of this product coupled with the use of nitrogen as a working fluid makes it an important tool for the decarbonization of residential, commercial, and industrial HVAC&R applications.

Kowalski, Steve↗
DOE OSTI2020

(Invited) Virtual Analysis of Gas-Diffusion-Electrode CO 2 Electrolyzers

The electrochemical reduction of CO 2 (CO 2 R) to value-added products is an attractive technology for tackling the rising atmospheric CO 2 levels and storing intermittent renewable energy into chemical bonds. Fundamental understanding of CO 2 R has progressed significantly in recent years and is critical in the development of CO 2 R to liquid-fuel electrolyzers, where gas-diffusion electrodes (GDEs) have been shown to be key enabling architectures. Various designs have been proposed and studied in the literature to enhance overall selectivity, rates, and maximize the conversion of CO 2 , the latter of which is only now being recognized as a critical issue. In this respect, there is a need to explore the governing phenomena inherent in these architectures to enable optimization. Mathematical modeling is ideally suited to tackle and explore these multiphysics interactions and provide virtual design analysis. In this talk, we discuss modeling methodologies and physics inherent in these devices and present our recent modeling of GDEs for CO 2 reduction. We specifically examine the impacts of multiphase flow and related phenomena on overall cell performance. We then explore the performance and limitations of various cell designs guided by simulation results and examine potential methods for improving water management and tuning catalyst selectivity including the use of different anion-exchange and bipolar membranes. Finally, we discuss the disparities in local environments between aqueous and GDE devices and propose strategies to reduce the gap in knowledge between the two systems.

42 ENGINEERING↗
DOE OSTI2020

Virtual Analysis of Gas-Diffusion-Electrode CO 2 Electrolyzers

The electrochemical reduction of CO 2 (CO2R) to value-added products is an attractive technology for tackling the rising atmospheric CO 2 levels and storing intermittent renewable energy into chemical bonds. Fundamental understanding of CO 2 R has progressed significantly in recent years and is critical in the development of CO 2 R to liquid-fuel electrolyzers, where gas-diffusion electrodes (GDEs) have been shown to be key enabling architectures. Various designs have been proposed and studied in the literature to enhance overall selectivity, rates, and maximize the conversion of CO 2 , the latter of which is only now being recognized as a critical issue. In this respect, there is a need to explore the governing phenomena inherent in these architectures to enable optimization. Mathematical modeling is ideally suited to tackle and explore these multiphysics interactions and provide virtual design analysis. In this talk, we discuss modeling methodologies and physics inherent in these devices and present our recent modeling of GDEs for CO 2 reduction. Here, we specifically examine the impacts of multiphase flow and related phenomena on overall cell performance. We then explore the performance and limitations of various cell designs guided by simulation results and examine potential methods for improving water management and tuning catalyst selectivity including the use of different anion-exchange and bipolar membranes. Finally, we discuss the disparities in local environments between aqueous and GDE devices and propose strategies to reduce the gap in knowledge between the two systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗