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DOE OSTI2020

Quantified uncertainties in fission yields from machine learning

As machine learning methods gain traction in the nuclear physics community, especially those methods that aim to propagate uncertainties to unmeasured quantities, it is important to understand how the uncertainty in the training data coming either from theory or experiment propagates to the uncertainty in the predicted values. Gaussian Processes and Bayesian Neural Networks are being more and more widely used, in particular to extrapolate beyond measured data. However, studies are typically not performed on the impact of the experimental errors on these extrapolated values. In this work, we focus on understanding how uncertainties propagate from input to prediction when using machine learning methods. We use a Mixture Density Network (MDN) to incorporate experimental error into the training of the network and construct uncertainties for the associated predicted quantities. Systematically, we study the effect of the size of the experimental error, both on the reproduced training data and extrapolated predictions for fission yields of actinides.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2022

A Cross-Domain Optimization Framework of PMU and Communication Placement for Multidomain Resiliency and Cost Reduction

Phasor measurement units (PMUs) play a crucial role in real-time monitoring and control of power grids. They rely on a communication network to transfer measurement data to the phasor data concentrator (PDC) for further processing and analysis. In this paper, a resilient cross-domain PMU and communication link placement method for minimizing the overall installation cost of the wide-area measurement system (WAMS) is proposed. Here, the main idea is to break down the barrier between the power grid domain and the communication domain, and consider the impact of one when design the other. The PMU placement in the power grid domain takes into account the cost of communication links by generating multiple solutions with equally minimum PMU costs for communication link placement evaluation. On the other hand, the communication link placement problem reduces the cost by customizing the routing policies based on the different roles of PMUs in grid observability. The proposed WAMS design is capable of withstanding any single component failure in the power domain (PMU failure or power branch failure) or in the communication domain (communication link failure or PDC failure). Numerical study on the IEEE 57-bus system reveals that the developed cross-domain optimization framework can significantly reduce the overall installation cost of WAMS while attaining multi-domain resiliency.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Ultra-Long Distance BOTDA Sensor System Employing Hybrid Amplification and Advanced Noise Reduction Techniques

Brillouin Optical Time Domain Analysis (BOTDA) sensor system play a pivotal role in distributed sensing, which enables precise measurements of strain and temperature across extensive fiber lengths. Nonetheless, challenges emerge as distances grow due to signal attenuation and noise interference resulting in measurement errors. This research offers a comprehensive strategy to extend the sensing range of BOTDA systems beyond 10’s of kilometers while maintaining high spatial resolutions. Such enhanced sensing is realized through the integration of distributed Raman amplification, inline amplification using erbium-doped fiber amplifiers (EDFA), and advanced noise reduction techniques. Leveraging inherent redundancy in measured data as a function of frequency and fiber distance, the non-local means (NLM) filter removes noise while preserving essential physical information. This approach proves particularly advantageous in BOTDA systems, where accurate measurement of Brillouin scattering signals is paramount for long-range sensing, while concurrently safeguarding high spatial resolutions. In summary, this research has shown a holistic exploration of extending BOTDA's distance sensing capabilities up to 150 km with spatial resolutions of 8 meters.

Bhatta, Hari↗

DOE OSTI2023

Fuel performance uncertainty quantification and sensitivity analysis in the presence of epistemic and aleatoric sources of uncertainties

Fuel performance modeling and simulation includes many uncertain parameters from models to boundary conditions, manufacturing parameters and material properties. These parameters exhibit large uncertainties and can have an epistemic or aleatoric nature, something that renders fuel performance code-to-code and code-to-measurements comparisons for complex phenomena such as the pellet cladding mechanical interaction (PCMI) very challenging. Additionally, PCMI and other complex phenomena found in fuel performance modeling and simulation induce strong discontinuities and non-linearities that can render difficult to extract meaningful conclusions form uncertainty quantification (UQ) and sensitivity analysis (SA) studies. In this work, we develop and apply a consistent treatment of epistemic and aleatoric uncertainties for both UQ and SA in fuel performance calculations and use historical benchmark-quality measurement data to demonstrate it. More specifically, the developed methodology is applied to the OECD/NEA Multi-physics Pellet Cladding Mechanical Interaction Validation benchmark. A cold ramp test leading to PCMI is modeled. Two measured quantities of interest are considered: the cladding axial elongation during the irradiations and the cladding outer diameter after the cold ramp. The fuel performance code used to perform the simulation is FAST. The developed methodology involves various steps including a Morris screening to decrease the number of uncertain inputs, a nested loop approach for propagating the epistemic and aleatoric sources of uncertainties, and a global SA using Sobol indices. The obtained results indicate that the fuel and cladding thermal conductivities as well as the cladding outer diameter uncertainties are the three inputs having the largest impact on the measured quantities. More importantly, it was found that the epistemic uncertainties can have a significant impact on the measured quantities and can affect the outcome of the global sensitivity analysis.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

Observational ozone datasets over the global oceans and polar regions (version 2024)

Studying tropospheric ozone over the remote areas of the planet, such as the open oceans and the polar regions, is crucial to understand the role of ozone as a global climate forcer and regulator of atmospheric oxidative capacity. A focus on the pristine oceanic and polar regions complements the available land-based datasets and provides insights into key photochemical and depositional loss processes that control the concentrations and spatiotemporal variability in ozone as well as the physicochemical mechanisms driving these patterns. However, an assessment of the role of ozone over the oceanic and polar regions has been hampered by a lack of comprehensive observational datasets. Here, we present the first comprehensive collection of ozone data over the oceans and the polar regions. The overall dataset consists of 77 ship cruises/buoy-based observations and 48 aircraft-based campaigns. The dataset, consisting of more than 630 000 independent ozone measurement data points covering the period from 1977 to 2022 and an altitude range from the surface to 5000 m (with a focus on the lowest 2000 m), allows systematic analyses of the spatiotemporal distribution and long-term trends over the 11 defined ocean/polar regions. The datasets from ships, buoys, and aircraft are complemented by ozonesonde data from 29 launch sites or field campaigns and by 21 non-polar and 17 polar ground-based station datasets. The datasets contain information on how long the observed air masses were isolated from land, as estimated by backward trajectories from the individual observation points. To extract observations representative of oceanic conditions, we recommend using a subset of the data with an isolation time of 72 h or longer, from the analysis with coincident radon observations. These filtered oceanic and polar data showed typically flat diurnal cycles at high latitudes, whereas daytime decreases in ozone (11 %–16 %) were observed at lower latitudes. The ship/buoy- and aircraft-based datasets presented here will supplement the land-based ones in the TOAR-II (Tropospheric Ozone Assessment Report Phase II) database to provide a fully global assessment of tropospheric ozone. The described dataset is available at https://doi.org/10.17596/0004044 (Kanaya et al., 2025).

Kanaya, Yugo [Japan Agency for Marine-Earth Scienc↗

NASA NTRS1977

Multilaterating the GEOS-3 satellite

It is demonstrated by means of rigorous simulations with an operational software system that multilateration of the GEOS-3 satellite is possible. This operation, i.e., the processing of simultaneous range measurements from the satellite to a real world constellation of stations using strictly geometric reduction of the observables, will result in the determination of the interstation coordinates to accuracies approaching those of the data measurements obtained at the stations. The satellite-to-satellite link between the GEOS-3 and ATS-6 can be used to further enhance the station covariance matrix.

Escobal, P. R.↗

NASA NTRS1978

A practical approach to helicopter internal noise prediction

A practical and well correlated procedure for predicting helicopter internal noise is presented. It accounts for the propagation of noise along multiple paths on an octave by octave basis. The method is sufficiently general to be applicable to conventional helicopters as well as other aircraft types, when the appropriate structural geometry, noise source strengths, and material acoustic properties are defined. A guide is provided for the prediction of various helicopter noise sources over a wide range of horsepower for use when measured data are not available. The method is applied to the prediction of the interior levels of the Civil Helicopter Research Aircraft (CHRA), both with and without soundproofing installed. Results include good correlation with measured levels and prediction of the speech interference level within 1.5 db at all conditions. A sample problem is also shown illustrating the use of the procedure. This example calculates the engine casing noise observed in the passenger cabin of the CHRA.

Levine, L. S.↗

NASA NTRS1979

Modern estimation techniques applied to microwave sensing of the marine boundary layer

Previous efforts in the area of satellite microwave sensing of the marine boundary layer have relied upon linear regression techniques to extract geophysical parameters from the microwave measurement data. The approach used in the present paper shifts emphasis away from the generation of regression weighting matrices which implicitly assume that the data are linear in the parameters to be determined and that the problem is statistically stationary. The idea is simply to employ modern computational estimation techniques to obtain parameter estimates from nonlinear noisy measurements. The approach is limited only to the region of validity of Grody's (1976) model. Attention is focused on documenting how estimation techniques, in particular the square root information filter (SRIF), are used to solve a nonlinear function optimization problem.

Bierman, G. J.↗

NASA NTRS2008

Investigation of an Anomaly Observed in Impedance Eduction Techniques

An intensive investigation into the cause of anomalous behavior commonly observed in impedance eduction techniques is performed. The investigation consists of grid refinement studies, detailed evaluation of results at and near anti-resonance frequencies, comparisons of different model results with synthesized and measured data, assessment or optimization techniques, and evaluation or boundary condition effects. Results show that the root cause of the anomalous behavior is the sensitivity of the educed impedance to small errors in the measured termination resistance at frequencies near anti-resonance or cut-on of a higher-order mode. Evidence is presented to show that the common usage of an anechoic, plane wave termination boundary condition in ducts where the "true" termination is reflective may act as a trigger for these anomalies. Replacing the exit impedance boundary condition by an exit pressure condition is shown to reduce the anomalous results.

Watson, W. R.↗

NASA NTRS2019

Thermal Fluctuation Noise in Mo/Au Superconducting Transition-Edge Sensor Microcalorimeters

In many superconducting transition-edge sensor (TES) microcalorimeters, the measured electrical noise exceeds theoretical estimates based on a thermal model of a single body thermally connected to a heat bath. Here, we report on noise and complex impedance measurements of a range of designs of TESs made with a Mo/Au bilayer. We have fitted the measured data using a two-body model, where the x-ray absorber and the TES are connected by an internal thermal conductance Gae. We find that the so-called excess noise measured in these devices is consistent with the noise generated from the internal thermal fluctuations between the x-ray absorber and the TES. Our fitted parameters are consistent with the origin of Gae being from the finite thermal conductance of the TES itself. These results suggest that even in these relatively low resistance Mo/Au TESs, the internal thermal conductance of the TES may add significant additional noise and could account for all the measured excess noise. Furthermore, we find that around regions of the superconducting transition with rapidly changing derivative of resistance with respect to temperature, an additional noise mechanism may dominate. These observations may lead to a greater understanding of TES devices and allow the design of TES microcalorimeters with improved performance.

Wakeham, N. A.↗

NASA NTRS2019

The Updated GEO Population for ORDEM 3.1

The limited availability of data for satellite fragmentations and debris in the geosynchronous orbit (GEO) region creates challenges to building accurate models for the orbital debris environment at such altitudes. Updated methods to properly incorporate and extrapolate measurement data have become a cornerstone of the GEO component in the newest version of the NASA Orbital Debris Engineering Model (ORDEM), ORDEM 3.1. For the GEO region, the Space Surveillance Network (SSN) catalog provides coverage down to a limit of approximately 1 m. A more statistically complete representation of the GEO population for smaller objects, which can pose a high risk to operational spacecraft, is thus dependent on dedicated observations by instruments optimized to observe debris smaller than the SSN cataloging threshold. For ORDEM 3.1, optical data from the Michigan Orbital DEbris Survey Telescope (MODEST) provided the input for building the GEO population down to approximately 30 cm (converting absolute magnitude to size). For smaller sizes, the size distribution of debris in the MODEST dataset was extrapolated down to 10 cm, and orbital parameters were estimated based on the orbits of the larger objects. When compared to previous versions of the model, significant improvements were made to the process of building the GEO population in ORDEM 3.1, both in the assessment of fragmentation debris in the data and assignment of orbital elements within the model. A so-called “debris ring filter,” based on a range of angles between an orbit’s angular momentum vector and that of the stable Laplace plane, was applied to the data to reduce biases from non- GEO objects, such as objects in a GEO-transfer orbit. In addition, a new approach was implemented to assign noncircular mean motions and eccentricities to the fragmentation debris observed by MODEST because the short observation window (5 min) in GEO limits orbit resolution to a circular orbit assumption for assigning orbital parameters. For ORDEM 3.1, non-circular orbital elements were assigned using relationships that were identified between mean motion and the angle between the orbit plane and the stable Laplace plane, as well as between mean motion and eccentricity, based on breakup clouds modeled by the NASA Standard Breakup Model. This approach has yielded a high-fidelity GEO model that has been validated with data from more recent MODEST observation campaigns.

Manis, A.↗

NASA NTRS2017

Summary of Propagation Cases of the Second AIAA Sonic Boom Prediction Workshop

A summary is provided for the propagation portion of the second AIAA Sonic Boom Workshop held January 8, 2017 in conjunction with the AIAA SciTech 2017 conference. Near-field pressure waveforms for two cases were supplied and ground signatures at multiple azimuthal angles as well as their corresponding loudness metrics were requested from 10 participants, representing 3 countries. Each case had some required, as well as some optional runs. The required cases included atmospheric profiles with measured data including winds, using Radiosonde balloon data at multiple geographically spread locations. The humidity profiles provided for the optional cases were taken from ANSI guidance, as the authors were unaware of an accepted standard at the time the cases were released to the participants. Participants provided ground signatures along with the requested data, including some loudness metrics using their best practices, which included lossy as well as lossless atmospheric propagation schemes. All the participants’ submissions, for each case, are compared and discussed. Noise or loudness measures are calculated and detailed comparisons and statistical analyses are performed and presented. It has been observed that the variation in the loudness measures and spread between participants’ submissions increased as the computation proceeded from under-track locations towards the lateral cut-off. Lessons learned during this workshop are discussed and recommendations are made for potential improvements and possible subsequent workshops as we collectively attempt to refine our analysis methods.

Rallabhandi, Sriram↗

DOE OSTI2026

A Physics-Based Digital Twin for Wave Elevation and Seabed Moment Estimation of Offshore Monopiles: Preprint

In this work, we present a proof of concept of a physics-based digital twin for a monopile structure (with overhead inertia) subjected to wave loading. The digital twin is formulated using reduced-order models derived from first principles and combined with a Kalman filter for state estimation. The proposed framework estimates the monopile top motion, the wave elevation, and the section forces and moments along the pile using primarily acceleration measurements at the monopile top. Key innovations include the use of a hydrodynamic shape function to represent distributed wave loading in a compact and computationally efficient manner, and the introduction of a shaping filter to augment the state-space with wave kinematics. Synthetic measurement data are generated using OpenFAST and used as a reference to assess the performance of the digital twin. Results demonstrate that the wave elevation can be accurately reconstructed without direct sea-state measurements as long as the wave regime is inertia-dominated. Under the ideal tested conditions, the total hydrodynamic force and sea-bed bending moment are estimated with relative errors on the order of 1% and correlation coefficients exceeding 96%. Future work will evaluate the estimator's performance under operational uncertainties and more complex loading conditions.

17 WIND ENERGY↗

DOE OSTI2024

Performance of plane wavefront Fizeau interferometers in power spectral density measurements with tilted plane optics

Binary pseudo-random array (BPRA) test samples are useful devices for calibrating the instrument transfer function (ITF) of Fizeau interferometers, interferometric microscopes, and other optical and non-optical surface and wavefront metrology instruments. The intrinsic white noise character of the power spectral density (PSD) function of the BPRA pattern simplifies the extraction of the ITF from the measured PSD. The ITF determined in a dedicated calibration experiment can be used to reconstruct the surface height profile from the measured data, effectively enhancing the instrument’s spatial resolution. For a high confidence reconstruction procedure, a reliable analytical model of the IFT is desirable. Usually, the model accounts for the contributions to the ITF related the imperfections of the instrument’s optical and detector systems. Here, we experimentally demonstrate that in the case of surface height metrology with Fizeau interferometers, the PSD measurements and, therefore, the efficacy of the ITF calibration of the tool, are strongly affected by the instrument data acquisition and processing procedures, as well as by the shape of the optic under test and its alignment with respect to the interferometer.

Yashchuk, V V↗

NASA NTRSDate not supplied

Nodal Modeling of Tank Pressurization and Draining using a Multi-Node-Ullage Approach

The purpose of the pressurization system in liquid rocket propulsion is to control the pressure in the gas space of the propellant tank (known as the ullage space) and the propellant mass flowrate to the engine. A mathematical model is required to predict the amount of pressurant necessary to ensure that pressure and temperature levels inside the tank remain within acceptable limits and that the propellant pressure leaving the tank satisfies the net positive suction pressure (NPSP) requirement of the pump feeding the engine. Nodal codes typically model tank pressurization and draining using a single node to represent the ullage and a single node to represent the propellant. As the tank drains, the ullage node grows and the propellant node shrinks. The heat transfer between ullage to wall and ullage to propellant is governed by natural convection. Designers of liquid propulsion systems often use empirical correlations to estimate the “Collapse Factor” which represents the ratio of pressurant required with heat transfer and the amount of pressurant required without heat transfer. A single node ullage model of tank pressurization was developed using GFSSP to compute the collapse factor reasonably well and later was used to model tank pressurization during test firing of the FASTRAC rocket engine. The predicted tank pressure compared well with the test data. In the early 1970’s, pressurization and drain tests with liquid methane were performed at NASA Lewis Research Center in a vacuum chamber. A 5 ft diameter spherical aluminum tank was tested to drain from 95% to 5% full using gaseous helium, hydrogen, nitrogen and methane as pressurant. Tests were conducted with different pressurant inlet temperatures and drain times. Measured data include pressurant requirement, amount of pressurant condensed, and ullage and wall temperatures at various heights in the ullage space at the end of draining. A single node GFSSP model was developed to simulate helium pressurization of the methane tank. Predicted helium consumption was 8-23% less than measured. The average error of the six test cases was 16%. A single ullage node with multiple solid node model was developed using Thermal Desktop. Predicted helium consumption compares with the test data within 2%. This paper describes the development of a GFSSP multi-node ullage model of the test configuration and compares the predicted pressurant consumption for both helium and autogenous pressurization using gaseous methane with experimental as well as TD predictions.

Nodal Model↗

DOE OSTI2022

β decay of neutron-rich 76 Cu and the structure of 76 Zn

In this work, the β decay of 76 Cu to the levels of 76 Zn was studied at the Holifield Radioactive Ion Beam Facility (HRIBF) at Oak Ridge National Lab (ORNL). A purified 76 Cu beam was developed and data were recorded for the decay of the A=76 decay chain using four high-purity germanium (HPGe) clover detectors at the Low-energy Radioactive Ion Beam Spectroscopy Station (LeRIBSS). In this measurement, data on γ-ray emission following β decay, including βγ and γγ coincidences, were collected and γγ spectra were analyzed to identify the statistically significant coincidences. From this analysis, we propose a level scheme for 76 Zn which contains a total of 59 energy levels up to 6.0 MeV containing 105 γ rays. We have identified an additional 53 γ rays associated with this decay which could not be place in the decay scheme due to insufficient coincidence information or no energy match to identified levels. No γ rays from states in 75 Zn fed in the delayed-neutron branch were observed even though other γ rays in the A=75 decay chain were observed. Spin and parity assignments are proposed for some levels based on comparison to systematics and shell model calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

New Baryon State N'(1720)3/2+ from the CLAS pi^+pi^--p Photo- and Electroproduction Data

Combined studies of exclusive meson photo- and electroproduction have extended the capabilities in the search for new excited states of the nucleon, the so called ?missing? resonances. New excited state of the nucleon, N?(1720)3/2+ has been observed in the combined studies of the pi^+pi^-p photo- and electroproduction off protons data measured with the CLAS detector at Jlab. The results on the new baryon state observation will be presented and discussed in the talk. A successful description of the pi^+pi^-p photo- and electroproduction data achieved with independent from photon virtualities (Q^2) mass, total and partial hadronic decay widths of N?(1720)3/2^+ state offers a strong evidence for the existence of this new resonance. Currently, N?(1720)3/2^+ resonance is the only observed new baryon state for which the results on Q^2-evolution of the electroexcitation amplitudes have become available. They offer an insight into the ?missing? resonance structure for the first time. Future analyses of the N?(1720)3/2^+ electroexcitation amplitudes will shed light on the particular structural features of ?missing? resonances which made their observation so challenging for decades

Mokeev, Viktor↗

DOE OSTI2026

Empirical Comparison of Machine Learning Approaches for Black-Box Modeling of Power Conversion System Dynamics

Inverter-based resources are key components in modern power systems, but accurately modeling their complex behavior can be challenging. Standard, generic converter models often oversimplify inverter dynamics, leading to significant errors in predicting performance. In this work, we compare several data-driven machine learning (ML) approaches for inverter modeling, performing experiments on power conversion systems, systematically varying input conditions, and recording the resulting voltages and currents. The ML models were then trained on this measured data to capture the inverter's dynamic response and to predict the inverter's output current. A performance comparison between the four ML models under study is conducted, laying the foundation for future work on hardware implementation for real-time inference.

30 DIRECT ENERGY CONVERSION↗