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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Feasibility of Correlation-Aware Inference and Universal Precision Scaling in Bonse–Hart Ultra-Small-Angle Neutron Scattering

Bonse–Hart ultra-small-angle neutron scattering (USANS) provides access to micrometre-scale structure, but useful measurements often require long counting times. In this work, we test whether the expected smoothness of the scattering profile can be exploited to improve data quality at lower counting statistics. We apply a Gaussian-process-based method to Bonse–Hart USANS data and evaluate its performance on pseudo-measurements generated from high-statistics experiments under Poisson statistics. This provides a stringent test of how well the underlying I(Q) profile can be reconstructed when the available counts are substantially reduced. We further show that, in the counting-limited regime, the reconstruction error follows a universal scaling behaviour that differs from the usual independent-counting expectation. At higher counts, the improvement crosses over to a resolution-limited regime set by analyser-angle discretization and rocking-curve width. These results clarify when correlation-aware inference is useful in USANS and provide a practical basis for improving measurement efficiency and beam-time usage.

Tung, Chi-Huan [ORNL] (ORCID:0000000221972074)↗
DOE OSTI2025

Explainable multi-fidelity Bayesian neural network for distribution system state estimation

Distribution System State Estimation (DSSE) is frequently constrained by limited real-time measurements, the uncertainties introduced by distributed energy resources, and the presence of bad data. To address them, this paper proposes an enhanced Multi-Fidelity Bayesian Neural Network (MFBNN) DSSE approach. A low-fidelity layer based on a Deep Neural Network (DNN) is first pre-trained on pseudo-measurement data to learn fundamental state features. Subsequently, a high-fidelity Bayesian Neural Network (BNN) layer leverages limited but high-quality real-time measurements to refine these features, thereby achieving accurate DSSE. Additionally, the deep SHapley Additive exPlanation (SHAP) is developed to quantify the influence of measurement data on DSSE through dual perspectives of global feature importance and local nodal contributions, establishing a hierarchical explainability framework for machine learning-based DSSE. Comparative studies conducted on the IEEE 13-bus system and a real-world 2135-node system from Dominion Energy demonstrate that the proposed method excels in estimation accuracy, even under situations of high noise levels, bad data, and missing data. Further comparisons with Weighted Least Squares (WLS) and other machine learning-based DSSE approaches verify that the proposed framework offers higher accuracy, improved interpretability, and enhanced robustness.

Bad data↗
NASA NTRS2011

Simulation Studies of Satellite Laser CO2 Mission Concepts

Results of mission simulation studies are presented for a laser-based atmospheric CO2 sounder. The simulations are based on real-time carbon cycle process modeling and data analysis. The mission concept corresponds to ASCENDS as recommended by the US National Academy of Sciences Decadal Survey. Compared to passive sensors, active (lidar) sensing of CO2 from space has several potentially significant advantages that hold promise to advance CO2 measurement capability in the next decade. Although the precision and accuracy requirements remain at unprecedented levels of stringency, analysis of possible instrument technology indicates that such sensors are more than feasible. Radiative transfer model calculations, an instrument model with representative errors, and a simple retrieval approach complete the cycle from "nature" run to "pseudodata" CO2. Several mission and instrument configuration options are examined, and the sensitivity to key design variables is shown. Examples are also shown of how the resulting pseudo-measurements might be used to address key carbon cycle science questions.

Kawa, Stephan Randy↗
DOE OSTI2026

Risk-Aware Measurement Synchronization and Recovery for DSSE With Heterogeneous Data Sources

Power distribution systems are increasingly integrating heterogeneous sensors with varying data reporting rates and types, which pose challenges to achieving observability at the desired temporal resolution of distribution system state estimation (DSSE). Multisensor failures caused by extreme events exacerbate these issues, introducing substantial uncertainties into DSSE. This article proposes a novel solution to these challenges by ensuring high-resolution system observability despite heterogeneous data sources and multisensor failures. First, a deep learning architecture combining long short-term memory (LSTM) and graph convolutional network (GCN) is employed to synchronize meters with different reporting rates, aiming to achieve system observability. A random-walk-model-based approach is introduced to generate pseudo-measurements while properly characterizing their uncertainties under multisensor failures. Finally, a disaster-risk-informed observability metric (RiOM) is defined to quantify the uncertainty associated with state estimation results. The proposed framework offers deeper insights into the system observability on the fly compared with conventional analysis. The effectiveness of the framework is demonstrated on an IEEE standard test case and a large-scale real-world distribution feeder in mid-Minnesota in the U.S.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Report for Task 10: Controllability and Observability Analysis (Deliverable D7))

It is common to have less than full observability for distribution systems, as the number of available measurements are not sufficient. Considering increasing penetration of distributed energy resources (DERs), it is imperative to understand and control distribution systems better. Developed for the transmission system, the original numerical observability analysis methods were based on the canonical DC Power Flow (DC-PF) model. However, the DC-PF model is ill-suited for the distribution system in which line resistance to reactance (R/X) ratios can be near unity. In this report, we apply the non-iterative Observability Test (OT) and Observable Island Identification Procedure (OIIP) in to the gain matrix from the distribution system state estimator. Because sensors are few in distribution systems, pseudo-measurements based on historical load profiles and zero-injection virtual measurements are often employed to ensure observability. However, both the observability and the accuracy of the state estimates are uncertain when historical data is limited/unavailable.

42 ENGINEERING↗
DOE OSTI2023

System state estimation with asynchronous measurements

The present disclosure provides techniques for estimating network states using asynchronous measurements by leveraging network inertia. For example, a device configured in accordance with the techniques of the present disclosure may receive electrical parameter values corresponding to at least one first location within a power network and determine, based on the electrical parameter values and a previous estimated state of the power network, an estimated value of unknown electrical parameters that correspond to a second location within the power network. The device may further cause at least one device within the power network to modify operation based on the estimated value of the unknown electrical parameters. The leveraging of network inertia may obviate the need for probabilistic models or pseudo-measurements.

Cavraro, Guido↗
DOE OSTI2021

State Estimation-Based Distributed Energy Resource Optimization for Distribution Voltage Regulation in Telemetry-Sparse Environments Using a Real-Time Digital Twin

Real-time state estimation using a digital twin can overcome the lack of in-field measurements inside an electric feeder to optimize grid services provided by distributed energy resources (DERs). Optimal reactive power control of DERs can be used to mitigate distribution system voltage violations caused by increased penetrations of photovoltaic (PV) systems. In this work, a new technology called the Programmable Distribution Resource Open Management Optimization System (ProDROMOS) issued optimized DER reactive power setpoints based-on results from a particle swarm optimization (PSO) algorithm wrapped around OpenDSS time-series feeder simulations. This paper demonstrates the use of the ProDROMOS in a RT simulated environment using a power hardware-in-the-loop PV inverter and in a field demonstration, using a 678 kW PV system in Grafton (MA, USA). The primary contribution of the work is demonstrating a RT digital twin effectively provides state estimation pseudo-measurements that can be used to optimize DER operations for distribution voltage regulation.

Darbali-Zamora, Rachid↗
DOE OSTI2020

Physics-Informed Deep Neural Network Method for Limited Observability State Estimation

The precise knowledge regarding the state of the power grid is important in order to ensure optimal and reliable grid operation. Specifically, knowing the state of the distribution grid becomes increasingly important as more renewable energy sources are connected directly into the distribution network, increasing the fluctuations of the injected power. In this paper, we consider the case when the distribution grid becomes partially observable, due to for example cyber attacks, and the state estimation problem is under-determined. We present a new methodology that leverages a deep neural network (DNN) to estimate the grid state. The standard DNN training method is modified to explicitly incorporate the physical information of the grid topology and line/shunt admittance. We show that our method leads to a superior accuracy of the estimation when compared to the case when no physical information is provided. Finally, we compare the performance of our method to the standard state estimation approach, which is based on the weighted least squares with pseudo-measurements, and show that our method performs significantly better with respect to the estimation accuracy.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1974

Space shuttle entry and landing navigation analysis

A navigation system for the entry phase of a Space Shuttle mission which is an aided-inertial system which uses a Kalman filter to mix IMU data with data derived from external navigation aids is evaluated. A drag pseudo-measurement used during radio blackout is treated as an additional external aid. A comprehensive truth model with 101 states is formulated and used to generate detailed error budgets at several significant time points -- end-of-blackout, start of final approach, over runway threshold, and touchdown. Sensitivity curves illustrating the effect of variations in the size of individual error sources on navigation accuracy are presented. The sensitivity of the navigation system performance to filter modifications is analyzed. The projected overall performance is shown in the form of time histories of position and velocity error components. The detailed results are summarized and interpreted, and suggestions are made concerning possible software improvements.

Jones, H. L.↗
NASA NTRS1994

Testing and Performance Analysis of a 650 Mbps QPPM Modem for Free-space Laser Communications

The testing and performance of a prototype modem developed at NASA Lewis Research Center for high-speed free-space direct detection optical communications is described. The testing was performed under laboratory conditions using computer control with specially developed test equipment that simulates free-space link conditions. The modem employs quaternary pulse position modulation (QPPM) at 325 Megabits per second (Mbps) on two optical channels, which are multiplexed to transmit a single 650 Mbps data stream. The measured results indicate that the receiver's automatic gain control (AGC), phased-locked-loop slot clock recovery, digital symbol clock recovery, matched filtering, and maximum likelihood data recovery circuits were found to have only 1.5 dB combined implementation loss during bit-error-rate (BER) performance measurements. Pseudo random bit sequences and real-time high quality video sources were used to supply 650 Mbps and 325 Mbps data streams to the modem. Additional testing revealed that Doppler frequency shifting can be easily tracked by the receiver, that simulated pointing errors are readily compensated for by the AGC circuits, and that channel timing skew affects the BER performance in an expected manner. Overall, the needed technologies for a high-speed laser communications modem were demonstrated.

Mortensen, Dale J.↗
NASA NTRSDate not supplied

Hybrid Flush and Synthetic Air Data Filter for Entry Vehicle Atmospheric State Estimation

A hybrid flush/synthetic air data sensing filter for entry vehicle atmosphere estimation is developed. The approach makes use of a Kalman-Schmidt and Rauch-Tung-Streibel smoother. The filter/smoother blends information from pressure sensors distributed on the heatshield with pseudo-measurements of the vehicle aerodynamic forces and moments computed from mass properties and inertial measurement unit data, and prior estimates of the atmosphere. The filter produces estimates of the atmospheric conditions along the entry trajectory, and systematic error estimates to reconcile differences between the pressure and aerodynamic data sources. The filter is applied to data acquired during the Mars 2020 entry, descent, and landing at Jezero crater on February 18th, 2021. The final paper will also include results from the Mars Science Laboratory entry, descent, and landing.

Chris D. Karlgaard↗
NASA NTRS1976

Flow and heat transfer measurements in a pseudo-shock region with surface cooling

An experimental investigation was conducted to acquire information on the flow structure, mean flowfield, and temperature distributions in a pseudo-shock region in a supersonic diffuser with surface cooling. The Mach number upstream was 2.9, and the wall to stagnation temperature ratio was 0.44. A Mach-disk-like shock wave emanated from the thin separated flow region near the beginning of the compression region, and reattachment occurred one diameter downstream so that the flow was not separated over most of the pseudo-shock region. The flow compression was a shock-free, predominantly viscous process. Along the pseudo-shock region the measured heat-transfer coefficient increased approximately as the 0.8 power of the measured wall static pressure. The estimated wall shear stress increased downstream of flow attachment, but was still considerably less than the upstream value.

Cuffel, R. F.↗
NASA NTRS1993

A comparison of the near-infrared spectral features of early-type galaxies in the Coma Cluster, the Virgo cluster and the field

Earlier researchers derived the relative distance between the Coma and Virgo clusters from color-magnitude relations of the early-type galaxies in each cluster. They found that the derived distance was color-dependent and concluded that the galaxies of similar luminosity in the two clusters differ in their red stellar populations. More recently, the color-dependence of the Coma-Virgo distance modulus has been called into question. However, because these two clusters differ so dramatically in their morphologies and kinematics, it is plausible that the star formation histories of the member galaxies also differed. If the conclusions of earlier researchers are indeed correct, then some signature of the resulting stellar population differences should appear in the near-infrared and/or infrared light of the respective galaxies. We have collected near-infrared spectra of 17 Virgo and 10 Coma early-type galaxies; this sample spans about four magnitudes in luminosity in each cluster. Seven field E/S0 galaxies have been observed for comparison. Pseudo-equivalent widths have been measured for all of the field galaxies, all but one of the Virgo members, and five of the Coma galaxies. The features examined are sensitive to the temperature, metallicity, and surface gravity of the reddest stars. A preliminary analysis of these spectral features has been performed, and, with a few notable exceptions, the measured pseudo-equivalent widths agree well with previously published values.

Houdashelt, Mark L.↗
NASA NTRS1978

Application of global positioning system to determination of tectonic plate movements and crustal deformations

It is shown that pseudo-range measurements to four GPS satellites based on correlation of the pseudo random code transmissions from the satellites can be used to determine the relative position of ground stations which are separated by several hundred kilometers to a precision at the centimeter level. Carrier signal measurements during the course of passage of satellites over a pair of stations also yield centimeter precision in the relative position, but oscillator instabilities limit the accuracy. The accuracy of solutions based on either type of data is limited by unmodeled tropospheric refraction effects which would reach 5 centimeters at low elevation angles for widely separated stations.

Anderle, R. J.↗
DOE OSTI2022

Dynamic Parameter Estimation with Physics-based Neural Ordinary Differential Equations

Accurate estimation of dynamic parameters of gen-erators is crucial to building a reliable model for dynamical studies and reliable operation of the power system. This paper develops a physics-based neural ordinary differential equations (ODE) approach to learn the parameters of generator dynamic model using phasor measurement units (PMU) data. We design a physics-based neural network to represent the swing equations of the power system dynamics. A loss function is defined as the difference between dynamic simulation results from the physics-based neural networks and pseudo PMU measurements. The parameters of generator dynamic model are iteratively updated using the neural ODEs and the adjoint method. By exploiting the mini-batch scheme in neural ODE training, the parameter estimation performance is significantly improved. Numerical study results on a 3-machine 9-bus system show that the proposed algorithm outperforms state-of-the-art baseline method in both computation time and dynamic parameter estimation accuracy.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2005

A Kinetic and Product Study of the Cl + HO2 Reaction

Absolute rate data and product branching ratios for the reactions Cl + HO2 to HCl + O2 (k1a) and Cl + HO2 to OH + ClO (k1b) have been measured from 226 to 336 K at a total pressure of 1 Torr of helium using the discharge flow resonance fluorescence technique coupled with infrared diode laser spectroscopy. For kinetic measurements, pseudo-first-order conditions were used with both reagents in excess in separate experiments. HO2 was produced by two methods: through the termolecular reaction of H atoms with O2 and also by the reaction of F atoms with H2O2. Cl atoms were produced by a microwave discharge of Cl2 in He. HO2 radicals were converted to OH radicals prior to detection by resonance fluorescence at 308 nm. Cl atoms were detected directly at 138 nm also by resonance fluorescence. Measurement of the consumption of HO2 in excess Cl yielded k1a and measurement of the consumption of Cl in excess HO2 yielded the total rate coefficient, k1. Values of k1a and k1 derived from kinetic experiments expressed in Arrhenius form are (1.6 +/- 0.2) x 10-11 exp[(249 +/- 34)/T] and (2.8 +/- 0.1) x 10-11 exp[(123 +/- 15)/T] cm3 molecule-1 s-1, respectively. As the expression for k1 is only weakly temperature dependent, we report a temperature-independent value of k1 = (4.5 +/- 0.4) x 10-11 cm3 molecule-1 s-1. Additionally, an Arrhenius expression for k1b can also be derived: k1b = (7.7 +/- 0.8) x 10-11 exp[-(708 +/- 29)/T] cm3 molecule-1 s-1. These expressions for k1a and k1b are valid for 226 K T 336 and 256 K T 296 K, respectively. The cited errors are at the level of a single standard deviation. For the product measurements, an excess of Cl was added to known concentrations of HO2 and the reaction was allowed to reach completion. HCl product concentrations were determined by IR absorption yielding the ratio k1a/k1 over the temperature range 236 K T 296 K. OH product concentrations were determined by resonance fluorescence giving rise to the ratio k1b/k1 over the temperature range 226 K T 336 K. Both of these ratios were subsequently converted to absolute numbers. Values of k1a and k1b from the product experiments expressed in Arrhenius form are (1.5 +/- 0.1) x 10-11 exp[(222 +/- 17)/T] and (10.6 +/- 1.5) x 10-11 exp[-(733 +/- 41)/T] cm3 molecule-1 s-1, respectively. These expressions for k1a and k1b are valid for 256 K T 296 and 226 K T 336 K, respectively. A combination of the kinetic and product data results in the following Arrhenius expressions for k1a and k1b of (1.4 +/- 0.3) x 10-11 exp[(269 +/- 58)/T] and (12.7 +/- 4.1) x 10-11 exp[-(801 +/- 94)/T] cm3 molecule-1 s-1, respectively. Numerical simulations were used to check for interferences from secondary chemistry in both the kinetic and product experiments and also to quantify the losses incurred during the conversion process HO2 to OH for detection purposes.

rate constants↗