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DOE OSTI2025

Embracing Uncertainty and Perseverance. A Brief Perspective on Conducting On-Site NDT Research

Dr. Judi E. See, a Systems Analyst and Human Factors Engineer at Sandia National Laboratories, reflects on her experience conducting NDT research in a male-dominated environment. She emphasizes the importance of persistence, flexibility, and persuasive skills in overcoming challenges, ranging from gaining access to test sites and equipment to building trust with inspectors. She shares her personal experience of navigating professional situations where gender disparities were evident, highlighting the need for women to adapt and overcome obstacles in traditionally male-dominated settings. See's journey demonstrates that perseverance and ingenuity can lead to significant contributions, process improvements, and recognition in the NDT field.

42 ENGINEERING↗

DOE OSTI2025

Decayheatml

This code is designed to predict and analyze the decay heat generated in molten salt reactors (MSRs) using a hybrid approach that combines machine learning and segmented polynomial fitting. The accurate prediction of decay heat is essential for reactor safety and the optimization of spent fuel storage. The code operates through several key components: 1) Data Architecture: It incorporates a modular data architecture that handles various MSR-specific operational parameters such as power density, humidity content, and air ingress. These parameters are sampled using Sobol sequences to ensure comprehensive coverage of operational uncertainties. 2) Machine Learning Framework: The code employs a diverse set of machine learning models, including polynomial regression, decision trees, random forests, gradient boosting, support vector regression, k-nearest neighbors, multi-layer perceptrons, and symbolic regression. These models are trained to predict decay heat over a wide temporal range, from immediate shutdown up to 10,000 years. 3) Region-Optimized Training: The temporal domain is divided into multiple regions, each modeled separately to capture distinct decay heat characteristics across different time scales. This approach significantly improves the accuracy and interpretability of predictions. 4) Segmented Polynomial Interpretation (SPI): The SPI method translates machine learning predictions into piecewise polynomial equations. These equations are physically interpretable and can be directly integrated into existing engineering workflows and safety analyses. 5) Front-End Interfaces: The code includes both a Jupyter notebook interface for research development and a Streamlit web application for operational deployment. These interfaces allow users to interactively explore decay heat predictions, adjust operational parameters, and visualize results in real-time. 6) Applications: The framework supports various applications, including safety system validation and spent fuel container optimization. It enables real-time evaluation of worst-case decay heat scenarios, informing the design of passive safety systems and optimizing container designs for long-term storage. Overall, this code provides a robust, accurate, and user-friendly tool for predicting decay heat in MSRs, enhancing reactor safety, and optimizing spent fuel management.

Retamales, Mauricio Eduardo Tano [Idaho National L↗

DOE OSTI2017

Research and Development Toward Massive Liquid Argon Time Projection Chambers for Neutrino Detection

Liquid argon (LAr) time projection chambers (TPC) have rapidly increased in importance as particle detectors throughout the past four decades. While much research has been completed, there are still many areas which require further development to build and operate the next generation LAr TPC experiment, such as the Deep Underground Neutrino Experiment (DUNE). These include high voltage breakdown, argon purification and purity monitoring, and vacuum ultraviolet (VUV) scintillation light measurement. Visual monitoring of high voltage breakdown is helpful in allowing assessment of the performance of high voltage component design. Thus, a system of cryogenic cameras, the first of its kind, was developed for use in a large LAr cryostat, without the need for additional electronics heating. The system functioned without problem for 50 days at cryogenic temperature, with some degradation of image quality, and provided a useful monitor for the DUNE 35-ton cryogenics systems. The system did not observe any high voltage breakdowns during the run. Further development of the concept is ongoing for future installation in other experiments. The monitoring of LAr purity using TPC data is a fundamental study for LAr TPC experiments. However, the study has not been performed for a large LAr TPC in the presence of high electronic noise. Custom software was developed and validated for the accurate reconstruction of signals in noisy TPC data. The results of the reconstruction were used to successfully measure the LAr electron lifetime with an uncertainty comparable to alternate methods of measurement. The electron lifetime of the 35-ton Phase II run is determined to be 4.12 ± 0.17 (stat.) ±0.40 (syst.) ms. For general purpose research and development of high purity LAr as a particle detection medium, a dedicated test stand was designed, constructed, and commissioned. The system is used to test the gaseous photomultiplier (GPM) performance at cryogenic temperatures. The GPM functions with photoelectron multiplication at 77 K, at a reduced gain. Further study is required to show the detector’s direct sensitivity to LAr VUV scintillation light.

Thiesse, Matthew↗

NASA NTRSDate not supplied

Olivine Dissolution and Formation of Secondary phases in Ultramafic Soils

Introduction: Olivine has been proposed as an indicator for the duration of water-rock interaction within Martian rocks and sediments [1-3]. The use of olivine as a mineralogical indicator for past aqueous alteration on Mars requires interpretation of a complex combination of factors including pH, temperature, and composition [5,6]. Here, we examine the persistence of natural olivine within terrestrial ultramafic soils (Fe/Mg-rich, Al-poor) developing under different climatic conditions and the incipient dissolution of emplaced forsterite (Fo) and fayalite (Fa) surfaces to investigate environmental effects on incipient olivine dissolution, olivine persistence in soils, and formation of secondary phases. Methods: Field Sites. We examined olivine weathering and secondary material formation in ultramafic soils at 6 sites in the Klamath Mountains (KM) of northern California with a mean annual temperature of ~12.8℃ and precipitation of ~55.7-95.4 cm/year [7], and soil pH of ~6.5-7.3; 4 sites in the Tablelands (TB) of Newfoundland, Canada with a mean annual temperature of <3.9℃ and precipitation of ~120.0 cm/year [8], and soil pH of ~7.7; and at 3 sites at Pickhandle Gulch (PG), Nevada with a mean annual temperature of ~14.4℃ and precipitation of ~14.1 cm/year [7], and soil pH of ~8.5. Sampling sites span an age range of ~12.1-50+ kya in the Klamath Mountains [9,10] and ~13-30 kya in the Tablelands [11]. Pickhandle Gulch sites are undated. Parent Material and Soil Analyses. Polished thin sections of bulk soil prepared by Wagner Petrographic, Inc were carbon-coated and analyzed on a JEOL 2100 SEM in back-scattered electron mode in the EMIL lab at UNLV and at the 13-ID-E synchrotron beamline at Argonne National Laboratory using µXRF, µXRD, and XAS. Soil and parent material samples were powdered in a Fritsch pulverisette and analyzed by XRD and soil by VNIR. Soil preparation is further described in [12]. Disk Preparation, Burial, and Collection. Fo disks were cut from a column prepared via hot-pressing and Fa disks by sintering synthetic fayalite powder, see [13] for detail. Disks were polished to a 0.25-micron level with diamond grit. Disks were buried in 3 KM soils, 4 TB soils, and 3 PG soils, collected after exactly 365 days, and washed gently with 100% reagent grade ethanol to remove potential adhered soil material. Weathered disks and soil samples were stored in a -20℃ freezer until analysis. Unaltered control disks prepared identically to the buried disks were stored at -20℃ for the duration of the experiment. Disk Analyses. One Fo and Fa disk from each climate zone was analyzed on a variable pressure Zeiss Supra 40VP SEM at Northern Arizona University. A separate Fo and Fa disk from each climate zone was analyzed by XPS using a Physical Electronics VersaProbe II at the Penn State Univ. Materials Characterization Lab after a Na-dodecyl sulfate wash and ozonation to remove carbon contamination as in [14]. VNIR measurements were conducted at Johnson Space Center using an ASD FieldSpec3 under ambient lab conditions on a separate Fo and Fa disk from each climate zone. One separate Fo and Fa control sample was analyzed for each technique for comparison with weathered samples. XPS uncertainty was determined from 5 repeat measurements on controls. Results: Bedrock and Soil Results Olivine is present in the parent material in the KM and TB. Olivine is found in ~12.1 ka KM soils but is absent from all older soils, while persisting into the oldest (>20 ka) TB soil (Figure 1). In both locations, olivine is found as cores surrounded by a serpentine rind (Figure 2). VNIR spectra from the analyzed soils possess strong OH-associated spectral features at ~2.33 µm indicating the presence of Mg-rich phyllosilicates as well as ferric-oxide features at ~0.92 µm in the KM (Figure 3). Primary crystalline silicate grains mostly incorporate Fe2+, while poorly crystalline weathering rinds are best fit by ferric oxide XAS standards (Figure 4). µXRF also shows that Fe and Ni concentrate in weathering rinds and Cr remains within interior silicate grains (Figure 4). Buried Sample Results All Fo surfaces exhibited formation of dissolution features including shallow pitting not observed on controls. Dissolution features were most visually widespread on the KM disk (Figure 5). Leaching of Mg from KM and TB Fo disks was evident from <1.6 Mg/Si ratios measured by XPS (Figure 6). Fe-rich precipitates in SEM (Figure 5) and Fe presence in XPS scans (Figure 6) indicate Fe deposition onto KM and TB Fo disk surfaces. The appearance of a spectral feature at 0.55 µm in the VNIR spectra from the TB Fo suggests this Fe is ferric (Figure 7). The PG Fo appears least altered, with minimal formation of dissolution features in SEM (Figure 5), a Mg/Si ratio inconsistent with leaching (~2) (Figure 6), and VNIR spectra almost identical to the control sample. Analysis of Fa surfaces is ongoing. The higher temperatures and more acidic pH in the KM soils likely drive the faster dissolution of the Fo disks described above. While the TB soils experience greater precipitation than in the KM, the cooler temperatures and more basic soil pH facilitate observable but more limited alteration. The dry climate and basic soil pH at PG lead to minimal dissolution of the PG disk surfaces.

A D Feldman↗

NASA NTRSDate not supplied

Status of Mars Retropropulsion Testing in the Langley Unitary Plan Wind Tunnel

Future Mars human landings will be enabled by a powered descent phase starting at supersonic conditions, something which has never been done before on a Mars mission. Significant aerosciences challenges exist due to jet interactions between the retrorocket engine plumes, freestream flow, and vehicle that will affect the aerodynamic behavior during powered descent. Historically, wind tunnel tests have been used to study the interactions with inert gas exhaust simulants in place of rocket engines. On the computational side, flowfield simulations have been completed at full-scale conditions, but the available ground and flight data are not appropriate for calibrating computational uncertainties for aerodynamic interference on proposed Mars descent vehicles, due to insufficient data, dissimilar vehicle geometries, and disparate operating conditions. A wind tunnel test has been designed to begin addressing powered descent aerodynamics risks for large-scale human Mars entry concepts and to identify gaps in computational predictive capabilities. The test will be conducted in the NASA Langley Unitary Plan Wind Tunnel and is designed with improvements in model design and data products over past tests. The test campaign will be run using sub-scale model geometries derived from NASA powered descent reference vehicles: a blunt low lift-to-drag vehicle and a more slender geometry that generates higher unpowered lift. Both models have been fabricated and are ready for testing. The blunt model is equipped with the flexibility to examine the effects of nozzle pointing direction, number, location, size, and area ratio. The main measurements are heatshield aerodynamic interference forces and moments with a custom flow-through balance, discrete and distributed heatshield pressure, and high-speed flowfield visualization. This paper covers the test objectives, facility, models and instrumentation, and planned test matrix.

Mars↗

NASA NTRSDate not supplied

Status of Mars Retropropulsion Testing in the Langley Unitary Plan Wind Tunnel

Supersonic Retropropulsion↗

DOE OSTI2019

Status of the NEAMS and ARC neutronic fast reactor tools integration to the NEAMS Workbench

The Workbench initiative was launched in FY-2017 within the Nuclear Energy Advanced Modeling and Simulation (NEAMS) Integration Product Line to facilitate the transition from conventional tools to high-fidelity tools. The Workbench provides a common user interface for model creation, real-time validation, execution, output processing, and visualization for integrated codes. The integration of the Argonne Reactor Computation (ARC) suite of codes into the NEAMS Workbench was initiated in FY-2017. The ARC codes contain both legacy codes like DIF3D and REBUS-3 that were developed with over 30 years of experience, and newer NEAMS additions like MC2-3, PERSENT and PROTEUS. The ARC integration into the NEAMS Workbench interface relies on the PyARC module which handles the pre- and post-processing of the native ARC codes input, and the runtime environment. The PyARC module together with the NEAMS Workbench interface are both released under Open Source Software licenses. In FY-2019, the effort focused on integrating the explicit assembly management logic of REBUS, the GAMSOR code for gamma heating transport, and of the NODAL solver of PROTEUS. Additional capabilities were also integrated in response to user requests, such as the assembly power peaking calculation and a 2D result plotting capability. For verification and demonstration purposes, the ARC codes were used through the Workbench for solving the Sodium-cooled Fast Reactor Uncertainty Analysis in Modelling (SFR-UAM) benchmark problems, including the newly proposed unit cells and ASTRID problem. Significant effort in FY-2019 focused on training new users from ANL, INL, NCSU, and Westinghouse. In particular, extensive training material was developed in the form of tutorials, including documentation, sample inputs, and associated presentations. The ARC codes are now actively used through the NEAMS Workbench by nuclear engineers at ANL, INL, NCSU, and Westinghouse, for LFR, MSR, micro-reactor, and SFR core design analyses. Future efforts will focus on adding new and existing modeling capabilities available with the ARC and NEAMS codes, training new users and supporting them to continue building user experience.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS2022

The Radiative Effect on Cloud Microphysics from the Arctic to the Tropics

Cloud representation is one of the largest uncertainties in the current weather and climate models. In this article, the observations and modeling of the radiative effect on (cloud) microphysics (REM) from the Arctic to the Tropics are overviewed, providing a new direction to meet the challenge of cloud representation. REM deals with the radiation-induced temperature difference between cloud particles and air. It leads to two common phenomena observed at the surface—dew and frost—and impacts clouds aloft significantly, which is noticed via the wide occurrence of horizontally oriented ice crystals (HOICs). However, REM has been overlooked by all of the operational weather and climate models. Based on the bin model of REM and the global distribution of radiative cooling/warming, the observations of REM from several platforms (e.g., aircrafts, field campaigns, and satellites) are coordinated in this article, yielding a global picture on REM. As a result, the picture is compatible with the global distribution of HOICs and other ice crystal characteristics obtained from various clouds on the globe, such as diamond dust (or clear-sky precipitation) in the Arctic, sub-visual cirrus clouds in the tropical tropopause layer, and other cirrus clouds from the low to high latitudes. In addition, ice crystals possess relatively strong REM compared to liquid drops because their aspect ratio is usually not one. The global picture on REM can be used by the weather and climate modelers to diagnose their cloud representation biases. It can also be used to improve the atmospheric ice retrieval algorithm from satellite observations.

cloud microphysics↗

DOE OSTI2020

An open source analysis framework for large-scale building energy modeling

Full integration of building energy modelling into the design and retrofit process has long been a goal of building scientists and practitioners. However, significant barriers still exist. Among them are the lack of available: (1) configurable technology stacks for performing both small- and large-scale analyses, (2) different classes of algorithms compatible with common design workflows, and (3) analysis tools for effectively visualizing large-scale simulation results. This article discusses the OpenStudio® Analysis Framework: a scalable analysis framework for building energy modelling that was developed to overcome the three barriers listed above. The framework is open-source and scalable to facilitate wider adoption and has a clearly defined application programming interface upon which other applications can be built. It runs on high-performance computing systems, within cloud infrastructure, and on laptops, and uses a common workflow to enable different classes of algorithms. Lessons learned from previous development efforts are also discussed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2018

Measurement of a Neutrino-Induced Charged Current Single Neutral Pion Cross Section at MicroBooNE

Micro Booster Neutrino Experiment (MicroBooNE) is a Liquid Argon Time Projection Chamber (LArTPC) operating in the Booster Neutrino Beamline at Fermi National Accelerator Laboratory. MicroBooNE's physics goals include studying short basline $\nu$ oscillation and performing a suite of low energy $\nu$ cross section measurements. Of particular interest to MicroBooNE, and the broader LArTPC community, are electromagnetic showers; these showers are at the heart of searches for charged current $\nu_e$ interactions, including MicroBooNE's flagship search for a MiniBooNE-like low energy excess (LEE). Neutral current $\pi^0$'s, which decay into 2 electromagnetic showers ($\gamma$'s), are the dominant source of non-$\nu_e$ backgrounds in searches for $\nu_{\mu}\rightarrow\nu_e$ oscillations in LArTPCs, such as the LEE. While precise measurements of this neutral current channel will provide a tight constraint on our modeling uncertainties, such events are particularly difficult to iden tify in data with our current tools, as there is often little or no activity at the neutrino interaction point. Charged current interactions, on the other hand, have simpler topologies with a long $\mu$ track that anchors to the interaction vertex. With a vertex in hand, we can develop automated reconstruction tools for neutrino-induced shower topologies (like the $\gamma$'s from $\pi^0$ decay). Thus, in studying charged current $\pi^0$ interactions, we are developing tools that can potentially be used to reconstruct an important LEE background, while also studying the physics of neutrino interactions, of which data is sparse for argon. This thesis reports the world's first measurement of the absolute, flux-averaged cross section of $\nu_{\mu}$-charged current single $\pi^0$ production on argon. The analysis chain begins with the selection of inclusive $\nu_\mu$ charged current events, where a candidate $\mu$ and neutrino interaction vertex are identified. These events are t hen passed to a reconstruction framework where electromagnet! ic shower candidates are reconstructed using computer visualization tools. Finally, the cross section is calculated on two reconstructed topologies: those with at least two reconstructed showers and those with at least one. Additionally, this work describes the first fully-automated electromagnetic shower reconstruction process employed by a LArTPC to perform a cross section analysis. We measure the flux averaged cross section on argon at 824 MeV via the two and one shower selections respectively to be \par \noindent $\sigma_{\geq2 Shower}$ = (2.56 $\pm$ $0.50_{stat}$ $\pm$ $0.31_{genie}$ $\pm$ $0.37_{flux}$ $\pm$ $0.31_{det}$) $\times$ $10^{-38}$ $\frac{cm^2}{Ar}$, \par \noindent $\sigma_{\geq 1 Shower}$ = (2.64 $\pm$ $0.33_{stat}$ $\pm$ $0.36_{genie}$ $\pm$ $0.38_{flux}$ $\pm$ $0.35_{det}$) $\times$ $10^{-38}$ $\frac{cm^2}{Ar}$.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2017

Economic Consequence Analysis of Disasters: The ECAT Software Tool

This study develops a methodology for rapidly obtaining approximate estimates of the economic consequences from numerous natural, man-made and technological threats. This software tool is intended for use by various decision makers and analysts to obtain estimates rapidly. It is programmed in Excel and Visual Basic for Applications (VBA) to facilitate its use. This tool is called E-CAT (Economic Consequence Analysis Tool) and accounts for the cumulative direct and indirect impacts (including resilience and behavioral factors that significantly affect base estimates) on the U.S. economy. E-CAT is intended to be a major step toward advancing the current state of economic consequence analysis (ECA) and also contributing to and developing interest in further research into complex but rapid turnaround approaches. The essence of the methodology involves running numerous simulations in a computable general equilibrium (CGE) model for each threat, yielding synthetic data for the estimation of a single regression equation based on the identification of key explanatory variables (threat characteristics and background conditions). This transforms the results of a complex model, which is beyond the reach of most users, into a "reduced form" model that is readily comprehensible. Functionality has been built into E-CAT so that its users can switch various consequence categories on and off in order to create customized profiles of economic consequences of numerous risk events. E-CAT incorporates uncertainty on both the input and output side in the course of the analysis.

Environmental Economics↗

DOE OSTI2024

Tau Positron Emission Tomography for Predicting Dementia in Individuals With Mild Cognitive Impairment

An accurate prognosis is especially pertinent in mild cognitive impairment (MCI), when individuals experience considerable uncertainty about future progression. To evaluate the prognostic value of tau positron emission tomography (PET) to predict clinical progression from MCI to dementia. This was a multicenter cohort study with external validation and a mean (SD) follow-up of 2.0 (1.1) years. Data were collected from centers in South Korea, Sweden, the US, and Switzerland from June 2014 to January 2024. Participant data were retrospectively collected and inclusion criteria were a baseline clinical diagnosis of MCI; longitudinal clinical follow-up; a Mini-Mental State Examination (MMSE) score greater than 22; and available tau PET, amyloid-β (Aβ) PET, and magnetic resonance imaging (MRI) scan less than 1 year from diagnosis. A total of 448 eligible individuals with MCI were included (331 in the discovery cohort and 117 in the validation cohort). None of these participants were excluded over the course of the study. Exposures included Tau PET, Aβ PET, and MRI. Positive results on tau PET (temporal meta–region of interest), Aβ PET (global; expressed in the standardized metric Centiloids), and MRI (Alzheimer disease [AD] signature region) was assessed using quantitative thresholds and visual reads. Clinical progression from MCI to all-cause dementia (regardless of suspected etiology) or to AD dementia (AD as suspected etiology) served as the primary outcomes. The primary analyses were receiver operating characteristics. In the discovery cohort, the mean (SD) age was 70.9 (8.5) years, 191 (58%) were male, the mean (SD) MMSE score was 27.1 (1.9), and 110 individuals with MCI (33%) converted to dementia (71 to AD dementia). Only the model with tau PET predicted all-cause dementia (area under the receiver operating characteristic curve [AUC], 0.75; 95% CI, 0.70-0.80) better than a base model including age, sex, education, and MMSE score (AUC, 0.71; 95% CI, 0.65-0.77; P = .02), while the models assessing the other neuroimaging markers did not improve prediction. In the validation cohort, tau PET replicated in predicting all-cause dementia. Compared to the base model (AUC, 0.75; 95% CI, 0.69-0.82), prediction of AD dementia in the discovery cohort was significantly improved by including tau PET (AUC, 0.84; 95% CI, 0.79-0.89; P < .001), tau PET visual read (AUC, 0.83; 95% CI, 0.78-0.88; P = .001), and Aβ PET Centiloids (AUC, 0.83; 95% CI, 0.78-0.88; P = .03). In the validation cohort, only the tau PET and the tau PET visual reads replicated in predicting AD dementia. In this study, tau-PET showed the best performance as a stand-alone marker to predict progression to dementia among individuals with MCI. This suggests that, for prognostic purposes in MCI, a tau PET scan may be the best currently available neuroimaging marker.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

The Sirius System and Its Astrophysical Puzzles: Hubble Space Telescope and Ground-based Astrometry

Sirius, the seventh-nearest stellar system, is a visual binary containing the metallic-line A1 V star Sirius A, the brightest star in the sky, orbited in a 50.13 year period by Sirius B, the brightest and nearest white dwarf (WD). Using images obtained over nearly two decades with the Hubble Space Telescope (HST), along with photographic observations covering almost 20 years and nearly 2300 historical measurements dating back to the 19th century, we determine precise orbital elements for the visual binary. Combined with the parallax and the motion of the A component, these elements yield dynamical masses of 2.063±0.023 M{sub ⊙} and 1.018±0.011 M{sub ⊙} for Sirius A and B, respectively. Our precise HST astrometry rules out third bodies orbiting either star in the system, down to masses of ∼15–25 M{sub Jup}. The location of Sirius B in the Hertzsprung–Russell diagram is in excellent agreement with theoretical cooling tracks for WDs of its dynamical mass, and implies a cooling age of ∼126 Myr. The position of Sirius B on the mass–radius plane is also consistent with WD theory, assuming a carbon–oxygen core. Including the pre-WD evolutionary timescale of the assumed progenitor, the total age of Sirius B is about 228 ± 10 Myr. We calculated evolutionary tracks for stars with the dynamical mass of Sirius A, using two independent codes. We find it necessary to assume a slightly subsolar metallicity, of about 0.85 Z{sub ⊙}, to fit its location on the luminosity–radius plane. The age of Sirius A based on these models is about 237–247 Myr, with uncertainties of ±15 Myr, consistent with that of the WD companion. We discuss astrophysical puzzles presented by the Sirius system, including the probability that the two stars must have interacted in the past, even though there is no direct evidence for this and the orbital eccentricity remains high.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2018

Fast Learning for Immersive Engagement in Energy Simulations

The fast computation which is critical for immersive engagement with and learning from energy simulations would be furthered by developing a general method for creating rapidly computed simplified versions of NREL's computation-intensive energy simulations. Created using machine learning techniques, these 'reduced form' simulations can provide statistically sound estimates of the results of the full simulations at a fraction of the computational cost with response times - typically less than one minute of wall-clock time - suitable for real-time human-in-the-loop design and analysis. Additionally, uncertainty quantification techniques can document the accuracy of the approximate models and their domain of validity. Approximation methods are applicable to a wide range of computational models, including supply-chain models, electric power grid simulations, and building models. These reduced-form representations cannot replace or re-implement existing simulations, but instead supplement them by enabling rapid scenario design and quality assurance for large sets of simulations. We present an overview of the framework and methods we have implemented for developing these reduced-form representations.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

MPC4CLR (Model-Predictive-Control-for-Critical-Load-Restoration-in-Power-Distribution-Systems) [SWR-22-24]

Model predictive control (MPC) is a system or process control technique for making decisions under uncertainty via rolling look-ahead optimizations at each control step where only the current step decisions are applied, and the rest are discarded. In this work, we developed an MPC for a critical load restoration (CLR) in power distribution systems to recover system service (electricity delivery) following an extreme event-triggered substation outage. The method considers the problem of controlling distributed energy resources (DERs) of the distribution system with the objective of achieving maximum load pick up while satisfying distribution network flow and voltage constraints. A linearized optimal power flow (OPF) model is employed to represent the physics of the network. The problem formulation is augmented with a ramping (up) reserve product for the DERs to ensure improved and upward monotonic load restoration as time evolves. Simulation analysis and performance tests are performed using a modified IEEE 13-bus test feeder integrated with wind, solar, microturbine, and energy storage battery. The software is developed using various software packages in Julia and Python. The MPC model is implemented using the JuMP optimization language in Julia while the data analytics including renewable generation and load demand forecasts, running the MPC simulation and visualizations is performed in Python.

Eseye, Abinet Tesfaye↗

NASA NTRS2015

Lunar Impact Flash Locations from NASA's Lunar Impact Monitoring Program

Meteoroids are small, natural bodies traveling through space, fragments from comets, asteroids, and impact debris from planets. Unlike the Earth, which has an atmosphere that slows, ablates, and disintegrates most meteoroids before they reach the ground, the Moon has little-to-no atmosphere to prevent meteoroids from impacting the lunar surface. Upon impact, the meteoroid's kinetic energy is partitioned into crater excavation, seismic wave production, and the generation of a debris plume. A flash of light associated with the plume is detectable by instruments on Earth. Following the initial observation of a probable Taurid impact flash on the Moon in November 2005,1 the NASA Meteoroid Environment Office (MEO) began a routine monitoring program to observe the Moon for meteoroid impact flashes in early 2006, resulting in the observation of over 330 impacts to date. The main objective of the MEO is to characterize the meteoroid environment for application to spacecraft engineering and operations. The Lunar Impact Monitoring Program provides information about the meteoroid flux in near-Earth space in a size range-tens of grams to a few kilograms-difficult to measure with statistical significance by other means. A bright impact flash detected by the program in March 2013 brought into focus the importance of determining the impact flash location. Prior to this time, the location was estimated to the nearest half-degree by visually comparing the impact imagery to maps of the Moon. Better accuracy was not needed because meteoroid flux calculations did not require high-accuracy impact locations. But such a bright event was thought to have produced a fresh crater detectable from lunar orbit by the NASA spacecraft Lunar Reconnaissance Orbiter (LRO). The idea of linking the observation of an impact flash with its crater was an appealing one, as it would validate NASA photometric calculations and crater scaling laws developed from hypervelocity gun testing. This idea was dependent upon LRO finding a fresh impact crater associated with one of the impact flashes recorded by Earth-based instruments, either the bright event of March 2013 or any other in the database of impact observations. To find the crater, LRO needed an accurate area to search. This Technical Memorandum (TM) describes the geolocation technique developed to accurately determine the impact flash location, and by association, the location of the crater, thought to lie directly beneath the brightest portion of the flash. The workflow and software tools used to geolocate the impact flashes are described in detail, along with sources of error and uncertainty and a case study applying the workflow to the bright impact flash in March 2013. Following the successful geolocation of the March 2013 flash, the technique was applied to all impact flashes detected by the MEO between November 7, 2005, and January 3, 2014.

Moser, D. E.↗

NASA NTRS2018

Analysis of the Honeywell Uncertified Research Engine (HURE) with Ice Crystal Cloud Ingestion at Simulated Altitudes: Public Version

The Honeywell Uncertified Research Engine (HURE), a research version of a turbofan engine that never entered production, was tested in the NASA Propulsion System Laboratory (PSL), an altitude test facility at the NASA Glenn Research Center. The PSL is a facility that is equipped with water spray bars capable of producing an ice cloud consisting of ice particles, having a controlled particle diameter and concentration in the air flow. In preparation for testing of the HURE, numerical analysis of flow and ice particle thermodynamics was performed on the compression system of the turbofan engine to predict operating conditions that could potentially result in a risk of ice accretion due to ice crystal ingestion. The results of those analyses formed the basis of the test matrix. The goal of the test matrix was to have ice accrete in two regions of the compression system: region one, which consists of the fan-stator through the inlet guide vane (IGV), and region two which is the first stator within the high pressure compressor. The predictive analyses were performed with the mean line compressor flow modeling code (COMDES-MELT) which includes an ice particle model. Together these comprise a one-dimensional icing tool. The HURE engine was tested in PSL with the ice cloud over the range of operating conditions of altitude, ambient temperature, simulated flight Mach number, and fan speed with guidance from the analytical predictions. The engine was fitted with video cameras at strategic locations within the engine compression system flow path where ice was predicted to accrete, in order to visually confirm ice accretion when it occurred. In addition, traditional compressor instrumentation such as total pressure and temperature probes, static pressure taps, and metal temperature thermocouples were installed in targeted areas where the risk of ice accretion was expected. The current research focuses on the analysis of the data that was obtained after testing the HURE engine in PSL with ice crystal ingestion. The computational method was enhanced by computing key parameters through the fan-stator at multiple spanwise locations, in order to increase the fidelity with the current mean-line method. In addition, other sources of heat (non-adiabatic walls) were suspected to be the cause of accretion near the splitter-lip and shroud. Since there were no thermocouples near the splitter, a simple order of magnitude heat transfer model was implemented to estimate the wall temperature. Future analyses will require a higher fidelity thermal analysis of the compression system metal walls to accurately calculate the total heat flux to the ice particle. For many data points analyzed, there were differences between the thermodynamic system model and the measured test data that may partially be responsible for uncertainties with the results of the current analyses.

Turbomachinery↗

DOE OSTI2024

Subsidence Measurements at the Teller 27 Field Site, Seward Peninsula, Alaska, 2021

In September 2021, differential GPS (dGPS) points were collected in areas of visual subsidence in the Teller watershed near mile marker 27 of the Bob Blodgett Nome-Teller Memorial Highway on the Seward Peninsula of Alaska. This study aimed to understand how structural permafrost loss is affecting meter-scale ground elevation. As ice thaws, heaving and slumping of the landscape creates new microtopographical features on the landscape that may alter surface hydrology and soil moisture and thus plant community composition and biogeochemical cycling. The Teller 27 field site is underlain with discontinuous permafrost, so the landscape features a variety of permafrost features. We collected ground elevations from eight subsidence areas in two forms: 1) Transects were sampled laterally through areas of ground subsidence to capture the high edges and low spots where the earth slumped. 2) The circumference of the subsidence area was sampled in order to measure the ground area affected by subsidence. These data were collected with an Emlid Reach RS2 dGPS and a base station. This dataset includes one *.csv of dGPS locations of the eight subsidence locations and one *.kml of measurement locations.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy’s Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy’s Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

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