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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Magnetic Field Sensing via Multi-Material Acoustic Sensing Optical Fibers with Magnetostrictive Cladding Inclusions

In this conducted research, optical fiber sensors are used to measure low strength alternating magnetic fields. Various fiber sensor configurations are tested and investigated to demonstrate sensing capabilities at different field magnitudes and frequencies. Distributed acoustic sensing fibers (DAS) have been largely studied and documented across a variety of applications and sensing systems. This research uses the DAS technology in tandem with magnetostrictive materials to create a distributed multi-material optical fiber magnetic sensor. Magnetic sensing has high demand across different fields and often runs into challenges of extreme environments including high temperature, corrosion, and areas with poor accessibility. The robust and distributed nature of optical fiber sensors which can be cheaply produced for long lengths is an attractive option over other single point magnetic sensors. In down hole applications specifically, having a distributed sensor able to be deployed easily and over long distances for magnetic sensing would be a large improvement to bulkier traditional magnetometers. In the conducted study, different magnetostrictive materials are implemented in distributed optical fiber sensors to analyze and compare the effective sensitivity and potential commercial viability. Nickel, galfenol alloy, and MetGlas alloy inclusions are drawn into fused silica optical fibers with Bragg gratings inscribed later on for DAS capability. Each was investigated for its response to varying AC magnetic fields to determine relative sensitivity and resolution for distributed magnetic field sensing.

Dejneka, Zach↗
DOE OSTI2021

Cement sensors with acoustic bandgaps using carbon nanotubes

Cement is widely used in wellbores to stabilize the steel casing used in wellbore operations for oil and gas production, enhanced geothermal systems and carbon sequestration, and to limit fluid movement between sub-surface strata. Flaws such as microcracks in wellbore cement can lead to leakage along the wellbore compromising wellbore integrity. There is an increasing need for methods to monitor cement crack propagation in wellbore environments. In this study, we develop and report the first cementitious sensors capable of exhibiting high frequency acoustic bandgaps (ABGs) using carbon nanotubes (CNTs). Computational simulations of a sensor unit cell are used to design cement-multi walled carbon nanotubes (MWCNTs) sensors that show a wide bandgap. When the cement-MWCNTs sensors is embedded in cement specimens, bandgaps were measured experimentally under 300 kHz and under 600 kHz, consistent with the computationally predicted bandgaps in the range of 290–360 kHz, 410–460 kHz and 515–585 kHz. These bandgap features were absent in homogeneous cement specimens. X-ray tomographic reconstructions showed microscopic debonding at cement-MWCNTs sensor interface. Frequency response analysis of a three-dimensional computational model indicated a shift of frequency of minimum transmission due to the interface debonding, but no perturbation of bandgap response was observed. Here, the cement-MWCNTs sensors developed in this study show the potential of a packed CNT inclusion material in cementitious matrix to create ABGs in a cement matrix.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Additive Manufacturing of Frequency-Agile W-Band Packaging

Abstract —In this paper we demonstrate a fully additively manufactured packaged W-band amplifier with integrated bypass capacitors. This package was fabricated using a chip-first approach and aerosol jet printing. Package substrates (dielectrics), conductors and interconnects are printed around a bare die attached to a carrier. This package uses shaped ramp interconnects, allowing for frequency agnostic package performance of the interconnect with no impedance discontinuity, within the physical limits of the printer. High dielectric constant thin films of a polymer-matrix nanocomposite for bypass capacitors were printed using multi-material aerosol jet printing. The maximum measured packaged gain is 14.9 dB in the W-band, compared to the maximum bare die gain of 15.5 dB in the same frequency range. From 75 - 92 GHz, the average package loss is 1.1 dB including 3 mm transmission line, interconnects, and a GSG launch structure correlating to an average loss of 0.37 dB/mm.

Additive manufacturing, aerosol jet printing, hete↗
DOE OSTI2021

Multiple Grid-Forming Inverters in Black-Start: The Challenges

Black-start is a major challenge toward the successful operation of an islanded inverter-based system. In this article, the technical challenges for the black-start of multiple grid-forming inverters are reported. Specifically, this article discusses inverter synchronization, voltage and frequency regulation, and power-sharing between the grid-forming inverters. Experiment results from a multi-inverter test-bed have been provided to support the discussion. Furthermore, a grid-forming inverter controller for black-start operation is developed and presented in this article that addresses the discussed technical challenges. The performance of the developed controller in black-start operation is verified through experiment results.

Sadeque, Fahmid↗
DOE OSTI2022

Distributed Secondary Control of Grid-Forming Inverters and AC Microgrids: Impacts of Voltage Feedback Choices

In this paper, the operational choices in distributed secondary control are examined, and their impacts on grid-forming (GFM) inverters and grid operation are investigated. In particular, the effects of feedback voltage choices, either average voltage feedback (AVF) or terminal voltage feedback (TVF), are studied with respect to reactive power sharing, voltage regulation, and grid-forming operation during black start. The secondary control used is a subgradient-based distributed cooperative control, and it provides the voltage, angle, and frequency references to the GFM inverters and their primary tracking controls. The overall control architecture employs multi-rate sampling such that the secondary control is slower than the primary control. The operational choices and their control performance are illustrated using a four-GFM-inverter microgrid in MATLAB/SIMULINK. Furthermore, the results show the effectiveness of the secondary controller, and several conclusions are drawn on the voltage feedback signals as the design choices.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Efficient multi-scale representation of visual objects using a biologically plausible spike-latency code and winner-take-all inhibition

Deep neural networks have surpassed human performance in key visual challenges such as object recognition, but require a large amount of energy, computation, and memory. In contrast, spiking neural networks (SNNs) have the potential to improve both the efficiency and biological plausibility of object recognition systems. Here we present a SNN model that uses spike-latency coding and winner-take-all inhibition (WTA-I) to efficiently represent visual stimuli using multi-scale parallel processing. Mimicking neuronal response properties in early visual cortex, images were preprocessed with three different spatial frequency (SF) channels, before they were fed to a layer of spiking neurons whose synaptic weights were updated using spike-timing-dependent-plasticity. We investigate how the quality of the represented objects changes under different SF bands and WTA-I schemes. We demonstrate that a network of 200 spiking neurons tuned to three SFs can efficiently represent objects with as little as 15 spikes per neuron. Furthermore, studying how core object recognition may be implemented using biologically plausible learning rules in SNNs may not only further our understanding of the brain, but also lead to novel and efficient artificial vision systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Characterizing a supernova’s standing accretion shock instability with neutrinos and gravitational waves

Here, we perform a novel multi-messenger analysis for the identification and parameter estimation of the Standing Accretion Shock Instability (SASI) in a core collapse supernova with neutrino and gravitational wave (GW) signals. In the neutrino channel, this method performs a likelihood ratio test for the presence of SASI in the frequency domain. For gravitational wave signals we process an event with a modified constrained likelihood method. Using simulated supernova signals, the properties of the Hyper-Kamiokande neutrino detector, and O3 LIGO Interferometric data, we produce the two-dimensional probability density distribution (PDF) of the SASI activity indicator and calculate the probability of detection P D as well as the false identification probability P FI . We discuss the probability to establish the presence of the SASI as a function of the source distance in each observational channel, as well as jointly. Compared to a single-messenger approach, the joint analysis results in P D (at P FI = 0.1) of SASI activities that is larger by up to ≈ 40% for a distance to the supernova of 5 kpc. We also discuss how accurately the frequency and duration of the SASI activity can be estimated in each channel separately. Our methodology is suitable for implementation in a realistic data analysis and a multi-messenger setting.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Probability Density Function Control of Frequency Fluctuations in Renewable-Rich Power Systems

The stochastic nature of renewable energy sources (RESs) necessitates treating power system frequency response as a random process with a nonstationary probability density function (PDF). Here, based upon the stochastic distribution control theory originated by the second author, this paper proposes a novel stochastic controller to improve the frequency PDF in power grids when integrating a large amount of RESs, thereby minimizing the effects of uncertainties and enhancing overall system stability. The key idea is to manipulate the controllable power generation resources so that the frequency PDF is make to follow a target PDF by using the stochastic distribution control theory originated by the second author. The proposed method can easily be plugged into existing automatic generation controls for multi-area transmission grids. The proposed method is validated via a modified Kundar's two area system and 240-bus Western Electricity Coordinating Council systems. The simulation results show that the proposed control shapes the frequency PDF narrower and sharper, leading to a notable improvement toward minimizing the effects of randomness and uncertainty during grid operation.

frequency↗
DOE OSTI2025

Asymptotic Relaxation of Moment Equations for a Multi-species, Homogeneous BGK Model

Multi-species BGK models describe the dynamics of rarefied gases with constituent particles of different elements or compounds with potentially nontrivial velocity distributions. Here, in this paper, moment equations for the bulk velocities, energies, and temperatures of a spatially homogeneous multi-species BGK model are examined. A key challenge in analyzing these equations is the fact that the collision frequencies are allowed to depend on the species temperatures, which allows for more realistic simulations of dilute gas flow. Therefore, a positive lower bound is established for the species temperatures. With this lower bound, a global existence and uniqueness of solutions to the coupled velocity-energy ODE system is established. The lower bound also enables a proof of exponential decay to a unique steady-state solution. Numerical results are presented to demonstrate how the bulk velocities and temperatures relax for large times.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Non-degenerate parametric mixing and Q-enhancement in ALN Lamb wave resonator

In this Letter, we explore a non-degenerate phase independent parametric quality factor (Q)-enhancement technique for aluminum nitride (AlN) Lamb wave resonators. Unlike other active Q-enhancement techniques which require precise phase control of the electronic feedback loop, this technique is implemented by parametrically pumping AlN material stiffness to realize a negative resistance seen at the signal path. The negative resistance is dependent on the nonlinear material modulation and multi-resonance coupling in the device. A nonlinear circuit model is developed to simulate the parametric coupling of each resonance and extract the nonlinearity of AlN from experimental data. With proper pump frequency and pump power, the device quality factor is boosted in both simulation and experiment. The demonstrated Q-enhancement method is simple to implement and can be applied to other types of resonators that have nonlinear behavior and support multi-resonance operation.

42 ENGINEERING↗
DOE OSTI2023

Lateral Variations Across the Southern San Andreas Fault Zone Revealed From Analysis of Traffic Signals at a Dense Seismic Array

Abstract We image the shallow seismic structure across the Southern San Andreas Fault (SSAF) using signals from freight trains and trucks recorded by a dense nodal array, with a linear component perpendicular to SSAF and two 2D subarrays centered on the Banning Fault and Mission Creek Fault (MCF). Particle motion analysis in the frequency band 2–5 Hz shows that the examined traffic sources can be approximated as moving single‐ or multi‐point sources that primarily induce Rayleigh waves. Using several techniques, we resolve strong lateral variations of Rayleigh wave velocities and Q ‐values across the SSAF, including 35% velocity reduction across MCF toward the northeast and strong attenuation around the two fault strands. We further resolve 10% mass density reduction and 45% shear modulus decrease across the MCF. These findings suggest that the MCF is currently the main strand of the SSAF in the area with important implications for seismic hazard assessments.

58 GEOSCIENCES↗
DOE OSTI2026

Adaptive Reinforcement Learning (ARL) Control of a Multi-port Resonant Converter in UAV Systems

This study presents an adaptive reinforcement learning (ARL) control framework for a multi-port resonant converter used in hybrid unmanned aerial vehicle (UAV) power systems. The converter integrates high-frequency half-bridge input ports connected to a rectified engine–generator set and a battery energy storage system, along with a semi-bridgeless active rectifier supplying the propulsion load. A deep RL agent is trained to dynamically regulate inter-port phase-shift commands in real time based on flight conditions and load power demand. The ARL controller autonomously identifies phase-shift combinations that maximize conversion efficiency while maintaining stable and coordinated power flow, even under rapidly varying operating scenarios. This data-driven approach eliminates the need for explicit system modeling or extensive manual tuning and enables coordinated control among multiple power ports without inter-port communication. Experimental results validate that the ARL based strategy achieves reliable power sharing and consistently high-efficiency operation across diverse UAV operating conditions.

Asa, Erdem [ORNL] (ORCID:0000000190884812)↗
DOE OSTI2021

Simulated Changes in Tropical Cyclone Size, Accumulated Cyclone Energy and Power Dissipation Index in a Warmer Climate

Detection, attribution and projection of changes in tropical cyclone intensity statistics are made difficult from the potentially decreasing overall storm frequency combined with increases in the peak winds of the most intense storms as the climate warms. Multi-decadal simulations of stabilized climate scenarios from a high-resolution tropical cyclone permitting atmospheric general circulation model are used to examine simulated global changes from warmer temperatures, if any, in estimates of tropical cyclone size, accumulated cyclonic energy and power dissipation index. Changes in these metrics are found to be complicated functions of storm categorization and global averages of them are unlikely to easily reveal the impact of climate change on future tropical cyclone intensity statistics.

Wehner, Michael (ORCID:0000000159910082)↗
DOE OSTI2020

Orchestrating Fault Prediction with Live Migration and Checkpointing

Checkpoint/Restart (C/R) is widely used to provide fault tolerance on High-Performance Computing (HPC) systems. However, Parallel File System (PFS) overhead and failure uncertainty cause significant application overhead. This paper develops an adaptive multi-level C/R model that incorporates a failure prediction and analysis model, which orchestrates failure prediction, checkpointing, checkpoint frequency, and proactive live migration along with the additional benefit of Burst Buffers (BB). It effectively reduces the overheads due to failures, checkpointing, and recovery. Simulation results for the Summit supercomputer yield a reduction of ~20%-86% in application overhead due to BBs, orchestrated failure prediction, and migration. We also observe a ~29% decrease in checkpoint writes to BBs, which can increase the longevity of the BB storage devices.

Behera, Subhendu↗
DOE OSTI2026

Pareto-optimal target definition for multi-axis random vibration testing

In random vibration testing with multiple control channels, existing control laws require specification of a complete spectral density matrix at each control frequency. Spectral density matrices include autospectral densities on the diagonal and cross-spectral densities on the off-diagonal. In practice, the off-diagonal terms are often unknown, and recent vibration testing research has focused on fixing the diagonal and specifying the off-diagonal to minimize the required control energy, subject to a constraint that the target matrix is positive semidefinite. This paper shows that, even with a fixed diagonal, off-diagonal terms strongly affect control residuals. This overlooked effect occurs in both square and rectangular systems. By jointly considering input energy and control residuals, open-loop inputs are derived directly from the diagonal without specifying the off-diagonal terms. Vibration targets that can be used in closed-loop control are then derived using the optimal inputs, with positive semidefinite constraints applied during the derivation. The result is a set of Pareto-optimal control solutions. For each solution in the set, any other possible solution produces greater control error, greater input energy, or both. A balanced solution is selected automatically, though others can be chosen based on test needs. Simulations and experiments show that the proposed method outperforms state-of-the-art energy-minimizing approaches, achieving significant reductions in both control error and input energy.

Autospectral density↗
DOE OSTI2025

Detecting isolated resonance curves using fixed frequency voltage control tests

Isolated resonance curves, or isolas, are resonance branches of the harmonically forced system that exist separately from the main nonlinear forced response curve, leading to excessive vibrations. Traditional stepped or swept sine simulations and tests rely on continuation along the frequency parameter, typically resulting in a jump phenomenon along the primary resonance branch, prior to the disconnected isola. The main objective of this research is to propose an approach to identify isolated resonance curves by performing continuation along the input amplitude that initializes the response from a low-amplitude solution in the linear regime. Furthermore, this is achieved with the open-loop fixed frequency voltage control method that continues along the shaker voltage parameter and measures the so-called S-curves, which are theoretically a continuous solution branch that connect to the isola. The methodology is demonstrated on a fixture-wing-pylon assembly with a vibro-impact nonlinearity localized in a pylon subcomponent attachment. Multi-harmonic balance simulations are deployed to compute both the nonlinear forced response curves and S-curves to demonstrate the isola detection strategy on a reduced-order finite element model of the nonlinear system. Swept sine and fixed frequency voltage control tests are then conducted on the physical structure to demonstrate the isola detection experimentally, revealing the existence of the large amplitude vibrations that are undetected in the forces levels and frequencies measured with traditional frequency sweeping.

Characterization and Analytical Technique↗
DOE OSTI2021

Hierarchical Tactile Sensation Integration from Prosthetic Fingertips Enables Multi-Texture Surface Recognition

Multifunctional flexible tactile sensors could be useful to improve the control of prosthetic hands. To that end, highly stretchable liquid metal tactile sensors (LMS) were designed, manufactured via photolithography, and incorporated into the fingertips of a prosthetic hand. Three novel contributions were made with the LMS. First, individual fingertips were used to distinguish between different speeds of sliding contact with different surfaces. Second, differences in surface textures were reliably detected during sliding contact. Third, the capacity for hierarchical tactile sensor integration was demonstrated by using four LMS signals simultaneously to distinguish between ten complex multi-textured surfaces. Four different machine learning algorithms were compared for their successful classification capabilities: K-nearest neighbor (KNN), support vector machine (SVM), random forest (RF), and neural network (NN). The time-frequency features of the LMSs were extracted to train and test the machine learning algorithms. The NN generally performed the best at the speed and texture detection with a single finger and had a 99.2 ± 0.8% accuracy to distinguish between ten different multi-textured surfaces using four LMSs from four fingers simultaneously. The capability for hierarchical multi-finger tactile sensation integration could be useful to provide a higher level of intelligence for artificial hands.

Abd, Moaed A. (ORCID:0000000284954244)↗
DOE OSTI2022

Alternative Ratemaking in the US: A Prerequisite for Grid Modernization or an Unwarranted Shift of Risk to Customers?

With increasing frequency, investor-owned electric utilities are requesting preferred cost recovery for "grid modernization" in multiple forms, from multi-year rate plans to riders. Utilities' claims that massive grid investment is necessary, and that exceptional investment requires exceptional cost recovery, are typically accepted by policymakers with little challenge. It is difficult for policymakers to resist the siren call of grid modernization's perceived outcomes, from improved reliability and resilience to reduced risks to safety and new customer technology adoption (electric vehicles, distributed energy resources, and more). This paper provides a contrarian viewpoint that is virtually absent as policymakers consider alternative ratemaking practices. It introduces the possibility that excess grid investment in the name of modernization is not only possible, and economically harmful, but has already occurred, encouraged by alternative ratemaking. It provides examples of common grid modernization expenditures the authors have identified as cost-ineffective in the course of their work. It also describes traditional grid planning practices with proven ability to address changing requirements over time, calling into question the need for exceptional grid modernization investment plans. Most important, the paper explains the moral hazard inherent in alternative ratemaking, and the fundamental shift in ratemaking risks and responsibilities from utilities to customers that results. The perspectives this paper presents are critical for policymakers to understand before adopting, extending, or expanding alternative ratemaking practices in their respective jurisdictions.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗