SEARCH · Search NASA

Results for “Output”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 541 records · Page 30

All sources NASA NTRS DOE OSTI

DOE OSTI2026

A Unified Design Theory for Multi-Port Polyphase Transformers Enabling Scalable Power-Multiplexed EV Fleet Charging Systems

This paper presents a unified analytical design theory for multi-port polyphase transformers, targeting scalable and isolated high-power Electric Vehicle (EV) fleet charging systems with power multiplexing capability. As fleet electrification accelerates, conventional one-to-one charger architectures face significant challenges in infrastructure cost, peak power demand, and low utilization of installed power electronics. Power-multiplexed charging architectures, which dynamically distribute power from a shared pool of converter modules across multiple vehicles, have emerged as a promising solution. However, such architectures require scalable, isolated multi-port power interfaces capable of routing energy among multiple inputs and outputs, whose design remains complex and dependent on iterative modeling. To address this gap, the proposed theory provides closed-form expressions for self-inductance, leakage inductance, and mutual coupling terms for arbitrary multi-phase, multi-port transformer structures. The formulation enables direct synthesis of isolated multi-input and multi-output resonant converter systems without reliance on geometry-specific finite-element analysis or extensive parameter extraction. This capability is particularly critical for power-multiplexed systems, where modular converter structures must interface with multiple vehicles while maintaining galvanic isolation and flexible power allocation. The effectiveness of the proposed framework is demonstrated through the design of a 360 kW multi-phase system operating over a 700–900 VDC input and 400–1250 VDC output range. PLECS simulation results confirm accurate prediction of system behavior and validate the applicability of the approach to multi-port, power-multiplexed charging scenarios. The proposed method significantly reduces design complexity while enabling scalable, cost-effective, and fully utilized EV fleet charging infrastructure.

Asa, Erdem [ORNL] (ORCID:0000000190884812)↗

DOE OSTI2024

Analysis and Control of a Three-Port Converter with High-Frequency AC Link for Hybrid Unmanned/Autonomous Aerial Vehicles

In this study, a three-port resonant converter with a high-frequency isolation link for hybrid unmanned/autonomous aerial vehicle (UAV/AAV) applications is analyzed. The rectified engine-generator set output supplies the first input ports while the other is connected to a battery energy storage system. Input ports consist of half-bridge high-frequency inverters, whereas output port utilizes a semi-bridgeless active rectifier. This rectifier is formed by replacing rectifier low-side diodes with active switching devices. A phase-shift duty-cycle control is implemented for switching signals to regulate the power share and flow between ports. The proposed control system implemented achieves zero voltage switching (ZVS), reduces switching losses, and minimum current flow optimization ensures regulation in a wide range of output power. Compared to the existing bidirectional pulse width modulation (PWM) converters, the proposed system decreases the number of power conversion stages and provides centralized control without needing communications between the ports. The proposed control technique operating in closed-loop control achieves the power flow between ports under various load conditions. Finally, theoretical analysis demonstrates the proposed converter’s viability and laboratory experimental validations at 500 W full power.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Wavelength Scaling of Widely-Tunable Terahertz Quantum-Cascade Metasurface Lasers

Terahertz (THz) external-cavity lasers based on quantum-cascade (QC) metasurfaces are emerging as widely-tunable, single-mode sources with the potential to cover the 1--6 THz range in discrete bands with milliwatt-level output power. By operating on an ultra-short cavity with a length on the order of the wavelength, the QC vertical-external-cavity surface-emitting-laser (VECSEL) architecture enables continuous, broadband tuning while producing high quality beam patterns and scalable power output. The methods and challenges for designing the metasurface at different frequencies are discussed. As the QC-VECSEL is scaled below 2 THz, the primary challenges are reduced gain from the QC active region, increased metasurface quality factor and its effect on tunable bandwidth, and larger power consumption due to a correspondingly scaled metasurface area. At frequencies above 4.5 THz, challenges arise from a reduced metasurface quality factor and the excess absorption that occurs from proximity to the Reststrahlen band. The results of four different devices — with center frequencies 1.8 THz, 2.8 THz, 3.5 THz, and 4.5 THz — are reported. Each device demonstrated at least 200 GHz of continuous single-mode tuning, with the largest being 650 GHz around 3.5 THz. The limitations of the tuning range are well modeled by a Fabry-Pérot cavity which accounts for the reflection phase of the metasurface and the effect of the metasurface quality factor on laser threshold. Lastly, the effect of different output couplers on device performance is studied, demonstrating a significant trade-off between the slope efficiency and tuning bandwidth.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Improving Robustness of Spectrogram Classifiers with Neural Stochastic Differential Equations

Signal analysis and classification is fraught with high levels of noise and perturbation. Computer-vision-based deep learning models applied to spectrograms have proven useful in the field of signal classification and detection; however, these methods aren't designed to handle the low signal-to-noise ratios inherent within non-vision signal processing tasks. While they are powerful, they are currently not the method of choice in the inherently noisy and dynamic critical infrastructure domain, such as smart-grid sensing, anomaly detection, and non-intrusive load monitoring. Currently, these models can be brittle, which makes them susceptible to noisy input. This also means they have sub-optimal stability of explanation outputs. Experts and technicians using these models to make decisions in real world scenarios need assurance that a model is performing as it is supposed to. The classification or prediction outputs it generates should be sound and grounded, not likely to change in the presence of shifting noise landscapes. In this work, we explore the idea of Neural Stochastic Differential Equations (NSDE's) to improve the robustness of models trained to classify time series data and the effect of NSDE's on the explainability of outputs. We then test the effectiveness of these approaches by applying them to a non-intrusive load monitoring (NILM) dataset that consists of simulated harmonic signals injected into a real building.

Brogan, Joel↗

DOE OSTI2022

A Novel Grid-forming Voltage Control Strategy for Supplying Unbalanced Microgrid Loads Using Inverter-based Resources

This paper presents a novel grid-forming voltage control strategy for a battery energy storage system to maintain balanced three-phase output voltages when serving unbalanced loads. A stationary reference frame (αβ) based control scheme is proposed to regulate positive-sequence and negative-sequence voltages. Compared with the conventional rotating reference frame (dq) based control scheme, the proposed scheme shows better dynamic performance. Then, we analyze the system zero-sequence network and propose adding a grounding transformer to the Y/Yg connected output transformer to further reduce the voltage unbalance at the point of common coupling. The simulation results demonstrate the effective performance of the proposed voltage control scheme. Based on the results, the power-voltage unbalance curve is derived for different output transformer configurations to establish the relationship between the power unbalance limit and the voltage unbalance limit for microgrid power scheduling.

Xu, Bei↗

DOE OSTI2024

Preventive Power Outage Estimation Based on a Novel Scenario Clustering Strategy

The increasing occurrence of extreme weather events is challenging power grid operation. For extreme weather events, the system operator is responsible for estimating the power outages and scheduling the restoration resources. This paper proposes an outage evaluation framework to identify the possible unserved load profiles, vulnerable areas, and mobile energy adequacy. The outputs of an outage prediction model tool are used to generate numerous faulted line scenarios. Next, each scenario's nodal unserved load profile is obtained by solving a three-phase restoration model that considers repair crews and mobile energy resources (MERs). Then, a novel scenario clustering strategy is developed to cluster the unserved load profiles into multiple representative profiles which the system operator can focus on. Finally, case studies on a distribution system evaluate the damage caused by an extreme weather event and verify the effectiveness of the proposed scenario clustering strategy.

MATHEMATICS AND COMPUTING,POWER TRANSMISSION AND D↗

DOE OSTI2025

A High-Current Pulsed Prototype Power Supply

The Accelerator Controls Operations Research Network (ACORN) project aims to modernize the accelerator control system and replace aging power supplies at Fermilab. As part of this effort, outdated RF ferrite bias power supplies will be redesigned. These power supplies are essential for tuning the resonant frequency of RF cavities by delivering programmable current outputs of up to 2500 A and voltages ranging from −10 V to +35 V. They operate at a repetition rate of 15 Hz in the Booster ring, and 1 Hz at the Main Injector ring. The power supplies utilize a bank of transistors in the linear region, connected in parallel with the load, to actively regulate the output current from a 12-pulse SCR bridge. To support this upgrade, a new bias power supply topology was developed as proof of concept. The design utilizes an IGBT Hbridge operating in Pulse Width Modulation (PWM) mode, controlled by a microcontroller. A prototype, constructed using spare components, successfully delivered an output current of 500 A at a repetition rate of 15 Hz during initial testing. The circuit's bandwidth was measured at 480 Hz, highlighting opportunities for further optimization in the controller design to achieve the target bandwidth of 2 kHz.

Bullman, Austin [ORNL]↗

DOE OSTI2025

Distributed Stochastic Optimization of a Neural Representation Network for Time-Space Tomography Reconstruction

4D time-space reconstruction of dynamic events or deforming objects using X-ray computed tomography (CT) is an important inverse problem in non-destructive evaluation. Conventional back-projection based reconstruction methods assume that the object remains static for the duration of several tens or hundreds of X-ray projection measurement images (reconstruction of consecutive limited-angle CT scans). However, this is an unrealistic assumption for many in-situ experiments that causes spurious artifacts and inaccurate morphological reconstructions of the object. To solve this problem, we propose to perform a 4D time-space reconstruction using a distributed implicit neural representation (DINR) network that is trained using a novel distributed stochastic training algorithm. Our DINR network learns to reconstruct the object at its output by iterative optimization of its network parameters such that the measured projection images best match the output of the CT forward measurement model. Here, we use a forward measurement model that is a function of the DINR outputs at a sparsely sampled set of continuous valued 4D object coordinates. Unlike previous neural representation architectures that forward and back propagate through dense voxel grids that sample the object's entire time-space coordinates, we only propagate through the DINR at a small subset of object coordinates in each iteration resulting in an order-of-magnitude reduction in memory and compute for training. DINR leverages distributed computation across several compute nodes and GPUs to produce high-fidelity 4D time-space reconstructions. We use both simulated parallel-beam and experimental cone-beam X-ray CT datasets to demonstrate the superior performance of our approach.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Optimal Power Management for Large-Scale Battery Energy Storage Systems via Bayesian Inference

Large-scale battery energy storage systems (BESS) have found ever-increasing use across industry and society to accelerate clean energy transition and improve energy supply reliability and resilience. However, their optimal power management poses significant challenges: the underlying high-dimensional nonlinear nonconvex optimization lacks computational tractability in real-world implementation, and the uncertainty of the exogenous power demand makes exact optimization difficult. This paper presents a new solution framework to address these bottlenecks. The solution pivots on introducing power-sharing ratios to specify each cell’s power quota from the output power demand. To find the optimal power-sharing ratios, we formulate a nonlinear model predictive control (NMPC) problem to achieve power-loss-minimizing BESS operation while complying with safety, cell balancing, and power supply-demand constraints. We then propose a parameterized control policy for the power-sharing ratios, which utilizes only three parameters, to reduce the computational demand in solving the NMPC problem. This policy parameterization allows us to translate the NMPC problem into a Bayesian inference problem for the sake of 1) computational tractability, and 2) overcoming the nonconvexity of the optimization problem. We leverage the ensemble Kalman inversion technique to solve the parameter estimation problem. Concurrently, a low-level control loop is developed to seamlessly integrate our proposed approach with the BESS to ensure practical implementation. This low-level controller receives the optimal power-sharing ratios, generates output power references for the cells, and maintains a balance between power supply and demand despite uncertainty in output power. We conduct extensive simulations and experiments on a 20-cell prototype to validate the proposed approach.

Battery energy storage systems (BESSs)↗

DOE OSTI2025

Design Principles for Resonant Wave Energy Converters: Benchmarking Power Capture and Flow

Control co-design (CCD) in Wave Energy Converters (WECs) integrates the controller, power take-off (PTO), and buoy models during system design to optimize power output. Using the bi-conjugate impedance matching principle, this study models the PTO as a two-port network, revealing impedance matching conditions at the input and output ports as a function of the buoy, PTO, and controller. Here, this study examines the pairing of a flywheel-type pitch resonator PTO within a given buoy constrained by limited space and ballast capacity. The results show that physical constraints imposed by the buoy affect PTO performance. While controller tuning achieves optimal output impedance matching and flywheel inertia is maximized within the buoy's limitations, the PTO's input impedance remains smaller than the complex conjugate of the buoy's intrinsic impedance. This mismatch limits the PTO's ability to generate sufficient reaction torque, particularly outside the resonance frequency, resulting in narrow-band power transfer. The findings emphasize the need for PTO design modifications to improve input power transfer. Pendulum-based PTO mechanisms are proposed as alternatives to couple with multiple buoy motion modes and improve wave-to-wire efficiency while respecting system constraints.

Control Co-Design↗

DOE OSTI2022

A 4 kV/120 A SiC Solid-State DC Circuit Breaker Powered By a Load-Independent IPT System

This article introduces a 4 kV/120 A solid-state dc circuit breaker (DCCB) based on discrete SiC mosfets. The DCCB is designed in a five-layer tower structure. Each layer consists of a circular main conduction branch and an attached gate driver. There are two primary benefits of the proposed DCCB. First, it reduces conduction loss with multiple devices in parallel. Second, it achieves an ultrafast response speed with SiC mosfets. Moreover, the gate drivers of the DCCB are powered by a domino inductive power transfer (IPT) system. It achieves the load-independent constant-voltage output characteristics, which means the outputs are immune to load variations. Additionally, an IPT system prototype is implemented to test the power transfer performance. At 500-kHz frequency, the total output power reaches 15.73 W, which is sufficient to power on five gate drivers, with a peak transfer efficiency of 75.4%. The IPT system is tested to power a 4 kV/120 A DCCB prototype. It validates that the DCCB is effective to turn off 120 A current within 3.5 μs.

42 ENGINEERING↗

DOE OSTI2020

Thermal Characterization of Tl 2 LiYCl 6 :Ce (TLYC)

Tl 2 LiYCl 6 :Ce (TLYC) is a new dual-detection elpasolite scintillator that can detect and distinguish between gamma rays and neutrons using pulse shape discrimination (PSD). It has a higher density and Z -number than the more mature and well-known elpasolite Cs 2 LiYCl 6 :Ce (CLYC), causing it to have a significantly better gamma-ray stopping power. These properties make TLYC an attractive alternative to CLYC for resource-constrained applications where size and weight are important, such as space or national security applications. Such applications may be subjected to a wide range of temperatures, and therefore, TLYC's performance was characterized for the first time over a temperature range of -20 °C to +50 °C in 10 °C increments. TLYC's thermal response effects on light-output linearity with energy, gamma-ray photopeak energy resolution, detected neutron energy, pulse shapes, and figure of merit (FOM) is analyzed and reported. The light output of TLYC was found to be linear with energy over the tested temperature range and was observed to decrease with increasing temperature. The decay time of the scintillation light output was observed to decrease with decreasing temperature at short times, leading to a decreasing PSD FOM. The gamma-ray photopeak energy resolution was also observed to degrade with decreasing temperature, due to an asymmetric broadening of the photopeak at low temperatures.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Enhanced Performance of Dual Inverter with a Floating Capacitor for Motor Drive Applications

This paper studies a dual inverter supplied by a DC-link and a floating capacitor (FC), emerged as a promising inverter topology for motor drive applications. For this type of inverter, the voltage ratio between the DC-link and the FC can be actively controlled. This ratio design is crucial as it essentially defines both the DC-link voltage utilization and the inverter output quality. Several voltage ratios have previously been discussed to enhance the dual inverter performance, but only one aspect, either the voltage utilization or the output quality, is investigated. As a result, although one performance aspect can be improved, the other aspect has been adversely affected. In this work, a comparative study considering both aspects is carried out for all the possible voltage ratios. Based on this analysis, the optimal ratios for different inverter modulation indices are identified. This is followed by proposing a ratio selection strategy to double the voltage utilization without degrading the output quality. Furthermore, this strategy enables an electric drive to work at a higher maximum speed without flux weakening for a given DC-link voltage. The claimed advantages have been proved by experimental tests on an open-end windings induction motor drive.

42 ENGINEERING↗

DOE OSTI2021

An Investigation into High Voltage Spiral Generators Utilizing Thyristor Input Switches

High voltage nanosecond pulses are widely used in scientific research, but their wider adoption in industry requires compact, cost effective and easy to use generators to be developed. This paper presents modelling and experimental investigations into one method of producing such pulses – a spiral generator with a solid-state, thyristor-based input switch. It includes how the pulses are formed within the spiral, why a high speed input switch is required, how the geometry of the spiral dictates its output characteristics, and the effects of different loads. Using thyristors, often connected in series to increase the operating voltage of the spiral, enables the spiral generators to have low jitter, high repetition rate, and long lifetime. Modelling of the circuit used a combination of telegraph equations to account for the wave propagation along the spiral and a lumped circuit exchanging charge between the spiral, the input switch, and the load. The model is verified by detailed experimental results with the relative error being < 10% in most cases. Here, the output voltage pulse was often observed to have an initial peak of much lower magnitude than the subsequent peak(s) – which can only be fully explained by considering wave propagation effects. Lower input switch inductance, shorter switching time, larger mean diameter of the spiral, and increasing the width of the copper tape that makes up the spiral can all increase the voltage multiplication efficiency. Though increasing the number of turns that make up the spiral can increase the output voltage, it can also lower the multiplication efficiency. By understanding the effects of different geometries the spiral can be optimized to drive different loads - three applications of such spiral generators are then presented: pulses with 10 kV amplitude and 10 kHz repetition rate for driving DBD plasma, pulses with amplitude of 10 kV and 10 kV/ns rising rate for triggering of advanced solid state switches, and pulses with -50 kV amplitude and 50 ns rising time for triggering high current gas switches through field distortion.1 Index Terms—spiral generator, nanosecond pulses, telegraph equations, series-connected thyristor module, pulse forming process

42 ENGINEERING↗

DOE OSTI2021

Bidirectional LCC-LCC -Compensated 20 kW Wireless Power Transfer System for Medium-Duty Vehicle Charging

This paper presents the design and demonstration of a bidirectional 20 kW wireless charging system (WCS) with a significantly large airgap (11 inches) and asymmetrical input-output voltage levels. Analytical and experimental sensitivity analyses of the WCS resonant tank were conducted to verify the optimal operating region under the load and frequency variation. The inverter and rectifier were designed with switching components, the charging pads were designed with double-D (DD) coils, and the tuning networks were designed with an LCC-LCC tuning circuit. The grid and vehicle side tuning circuits were designed separately to achieve a ~1:2 gain for the asymmetrical input (800 V dc ) and output (350 V dc ) voltage. The proposed WCS was designed, simulated, and tested to verify the efficiency, power transfer capacity, and sensitivity under load variation. The experimental results show that, at 20-kW output power, the achieved grid to vehicle dc-dc efficiency was 96.1%, and vehicle to grid dc-dc efficiency was 96.2%. The proposed system is the largest-airgap bidirectional WCS with the highest efficiency and power density.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

SpotSDC: Revealing the Silent Data Corruption Propagation in High-Performance Computing Systems

We report the trend of rapid technology scaling is expected to make the hardware of high-performance computing (HPC) systems more susceptible to computational errors due to random bit flips. Some bit flips may cause a program to crash or have a minimal effect on the output, but others may lead to silent data corruption (SDC), i.e., undetected yet significant output errors. Classical fault injection analysis methods employ uniform sampling of random bit flips during program execution to derive a statistical resiliency profile. However, summarizing such fault injection result with sufficient detail is difficult, and understanding the behavior of the fault-corrupted program is still a challenge. In this article, we introduce SpotSDC, a visualization system to facilitate the analysis of a program's resilience to SDC. SpotSDC provides multiple perspectives at various levels of detail of the impact on the output relative to where in the source code the flipped bit occurs, which bit is flipped, and when during the execution it happens. SpotSDC also enables users to study the code protection and provide new insights to understand the behavior of a fault-injected program. Based on lessons learned, we demonstrate how what we found can improve the fault injection campaign method.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Sensitivity of modelled passive margin stratigraphy to variations in sea level, sediment supply and subsidence

Abstract We produced a 10 Myr synthetic stratigraphic section using a forward stratigraphic model that generates marine deltaic stratigraphy over geological timescales. We recursively fit the model using a Bayesian inversion algorithm to test: (1) if it could be accurately reconstructed; (2) if the parameters used to create it could be recovered; and (3) the sensitivity of the model output to given model parameters and the attendant physical processes. The original synthetic stratigraphic section was produced with cyclical sea‐level variations of 40 and 30 m with 2.4 and 10 Myr periods respectively. Sediment was also supplied cyclically, in 2.4 and 10 Myr cycles with amplitudes of 30 and 80 tons/100 kyr, respectively, varying from a mean of 232 tons/100 kyr. Parameter values were sampled to fit the model using a Markov chain Monte Carlo algorithm, resulting in a ±5 m (1σ) variation between the experimental output and the original. Sea level varied by ±7 m (1σ) within the posterior distribution of parameters. As a result, both the 10 Myr and 2.4 Myr sea‐level cycles could be extracted from the original output. The variation in sediment supply was approximately ±38 tons/100 kyr (1σ) and, as a result, only the larger long‐term supply variations could be accurately recovered in refitting the model. The variation in thermal, flexural and total subsidence across those parameter sets is less than ±10 m (1σ). The original section experienced 150 m of total subsidence at the depocentre. Our results demonstrate the distinct and interpretable imprint of sea level and subsidence on continental margin stratigraphy can be quantified. Moreover, we conclude that sea‐level change produces a defined effect on the geometries of stratigraphic architecture, and that techniques applied for the purpose of delineating sea‐level variation from continental margin strata have a well‐founded conceptual basis.

Schmelz, William J.↗

DOE OSTI2025

Uncertainty propagation and sensitivity analysis for constrained optimization of nuclear waste vitrification

Abstract The vitrification of high‐level waste (HLW) by heating a mixture of glass‐forming chemicals (GFCs) with the waste can be improved using a constrained optimization problem. This study explores how different uncertainty propagation (UP) methods implemented with the optimization process can affect the glass formulation of nuclear waste glasses. UP is the effort of propagating uncertain inputs through a system to understand and quantify output distributions. Uncertainty intervals are crafted from output distributions to inform the optimization algorithm. UP is often implemented with Monte Carlo (MC) sampling for large nonlinear systems, which can be difficult to implement within a constrained optimization algorithm that requires derivative information. Other UP methods often used for optimization under uncertainty (OUU) can be designed to work within an established constrained optimization framework. Methods of UP are evaluated in this study including iterative sampling approaches, first‐order approximations, and surrogate modeling with machine learning (ML). A method of dimensional reduction based on global sensitivity analysis is introduced to support the UP methods for the large dimensionality of the problem. Analytical UP methods able to achieve similar optimums 10 times faster than the baseline MC approach, and produce 93.9% similar output distributions are reported.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗