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At least 1,531 records · Page 85

Toward Enhancing the Use of IASI and CrIS Surface-Sensitive Radiances Over Land in the NASA GMAO GEOS Data Assimilation Framework

Assimilating surface-sensitive radiances over land is still challenging for both infrared (IR) and microwave (WV) radiances essentially because of the large uncertainties of the land physical surface emissivity model used in the Community Radiative Transfer Model (CRTM) and the uncertainties of land surface state properties. Currently very few IR radiances are assimilated over land. Large number of IR radiances are rejected by the surface sensitivity checks as well as the cloud detection check. In this study, we identified the appropriate Infrared Atmospheric Sounding Interferometer (IASI) and Cross-track Infrared Sounder (CrIS) surface-sensitive channels to retrieve Land Surface Temperature (LST). Then, we studied the impacts of these retrieved LST and retuned cloud detection on the simulation and assimilation of IASI and CrIS in the NASA GEOS in clear sky conditions. The preliminary results are shown to enhance the rate of IASI and CrIS assimilated channels over land. The impacts on the quality of the resulting analysis and subsequent forecast will be presented at the meeting.

Niama Boukachaba↗

Starshade Rendezvous: Exoplanet Sensitivity and Observing Strategy

Launching a starshade to rendezvous with the Nancy Grace Roman Space Telescope (Roman) would provide the first opportunity to directly image the habitable zones (HZs) of nearby sunlike stars in the coming decade. A report on the science and feasibility of such a mission was recently submitted to NASA as a probe study concept. The driving objective of the concept is to determine whether Earth-like exoplanets exist in the HZs of the nearest sunlike stars and have biosignature gases in their atmospheres. With the sensitivity provided by this telescope, it is possible to measure the brightness of zodiacal dust disks around the nearest sunlike stars and establish how their population compares with our own. In addition, known gas-giant exoplanets can be targeted to measure their atmospheric metallicity and thereby determine if the correlation with planet mass follows the trend observed in the Solar System and hinted at by exoplanet transit spectroscopy data. We provide the details of the calculations used to estimate the sensitivity of Roman with a starshade and describe the publicly available Python-based source code used to make these calculations. Given the fixed capability of Roman and the constrained observing windows inherent for the starshade, we calculate the sensitivity of the combined observatory to detect these three types of targets, and we present an overall observing strategy that enables us to achieve these objectives.

Andrew Frederic Romero-wolf↗

PACE OCI Polarization Sensitivity Based on Pre-launch Testing

The Ocean Color Instrument (OCI) is a sensor on the upcoming Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, scheduled for launch in early 2024. OCI is a grating spectrometer with hyperspectral coverage from the ultraviolet (about 310 nm) to near-infrared (about 900 nm), with additional filtered channels in the short-wave infrared (940 nm – 2260 nm). This instrument will provide ocean color science data to continue the data sets collected by heritage sensors MODIS, SeaWiFs, and VIIRS, but with increased spectral coverage and improved accuracy. In order to achieve the high levels of accuracy demanded by the science community, a rigorous ground test program was conducted to calibrate the instrument and ensure that the calibration can be transferred to on-orbit operations. Some calibration parameters can only be measured during pre-launch testing; one such parameter is the polarization sensitivity. Polarization testing measured the Mueller matrix components needed to determine the polarization sensitivity for all spectral bands for a series of telescope scan angles covering the expected on-orbit scan range. Results indicate that the sensitivity is below 0.6 % except at the shortest wavelengths (less than 340 nm) and was characterized to better than 0.1 % above 340 nm. This indicates that any polarized scenes measured on orbit can be corrected for with a high degree of confidence.

PACE↗

PACE OCI Polarization Sensitivity Based on Pre-launch Testing

The Ocean Color Instrument (OCI) is a sensor on the upcoming Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, scheduled for launch in early 2024. OCI is a grating spectrometer with hyperspectral coverage from the ultraviolet (about 310 nm) to near-infrared (about 900 nm), with additional filtered channels in the short-wave infrared (940 nm – 2260 nm). This instrument will provide ocean color science data to continue the data sets collected by heritage sensors MODIS, SeaWiFs, and VIIRS, but with increased spectral coverage and improved accuracy. In order to achieve the high levels of accuracy demanded by the science community, a rigorous ground test program was conducted to calibrate the instrument and ensure that the calibration can be transferred to on-orbit operations. Some calibration parameters can only be measured during pre-launch testing; one such parameter is the polarization sensitivity. Polarization testing measured the Mueller matrix components needed to determine the polarization sensitivity for all spectral bands for a series of telescope scan angles covering the expected on-orbit scan range. Results indicate that the sensitivity is below 0.6 % except at the shortest wavelengths (less than 340 nm) and was characterized to better than 0.1 % above 340 nm. This indicates that any polarized scenes measured on orbit can be corrected for with a high degree of confidence.

PACE↗

Sensitivity of the MAR Regional Climate Model Snowpack to the Parameterization of the Assimilation of Satellite-Derived Wet-Snow Masks on the Antarctic Peninsula

Both regional climate models (RCMs) and remote sensing (RS) data are essential tools in understanding the response of polar regions to climate change. RCMs can simulate how certain climate variables, such as surface melt, runoff and snowfall, are likely to change in response to different climate scenarios but are subject to biases and errors. RS data can assist in reducing and quantifying model uncertainties by providing indirect observations of the modeled variables on the present climate. In this work, we improve on an existing scheme to assimilate RS wet snow occurrence data with the “Modèle Atmosphérique Régional” (MAR) RCM and investigate the sensitivity of the RCM to the parameters of the scheme. The assimilation is performed by nudging the MAR snowpack temperature to match the presence of liquid water observed by satellites. The sensitivity of the assimilation method is tested by modifying parameters such as the depth to which the MAR snowpack is warmed or cooled, the quantity of water required to qualify a MAR pixel as “wet” (0.1 % or 0.2 % of the snowpack mass being water), and assimilating different RS datasets. Data assimilation is carried out on the Antarctic Peninsula for the 2019–2021 period. The results show an increase in meltwater production (+66.7 % on average, or +95 Gt), along with a small decrease in surface mass balance (SMB) (−4.5 % on average, or −20 Gt) for the 2019–2020 melt season after assimilation. The model is sensitive to the tested parameters, albeit with varying orders of magnitude. The prescribed warming depth has a larger impact on the resulting surface melt production than the liquid water content (LWC) threshold due to strong refreezing occurring within the top layers of the snowpack. The values tested for the LWC threshold are lower than the LWC for typical melt days (approximately 1.2 %) and impact results mainly at the beginning and end of the melting period. The assimilation method will allow for the estimation of uncertainty in MAR meltwater production and will enable the identification of potential issues in modeling near-surface snowpack processes, paving the way for more accurate simulations of snow processes in model projections.

regional climate models↗

Atmosphere Modeling and Performance Sensitivity for the Mars Sample Return Earth Entry System

The Capture, Containment, and Return System (CCRS) mission is a key element of the joint NASA-European Space Agency (ESA) planned Mars Sample Return (MSR) Campaign. The CCRS assembled Earth Entry System (EES) will enter the mission’s final segment in its Approach, Entry, Descent, and Landing (AEDL) Phase. The EES AEDL aims to deliver a highly reliable, safe, and accurate return while maintaining strict containment assurance targets established by the campaign. As currently designed, the EES would be the first fully passive sample return capsule with no parachute or onboard control system, prompting a significant effort in Earth atmosphere characterization and modeling. Earth’s atmosphere, specifically winds, have a strong influence on EES flight mechanics and landing footprint during its free fall landing. This paper describes Earth atmosphere modeling, atmosphere characterization, and performance sensitivities incorporated into the teams’s efforts to ensure AEDL success. By utilizing high resolution balloon radiosondes, analyzing wind structural and distributional compositions, and investigating flight mechanics sensitivities, the AEDL atmosphere team has been able to better understand and simulate local wind conditions at the Utah Test and Training Range (UTTR). Utilizing tools such as horizontal turbulent kinetic energy, vertical wind shear, or integrated wind, the team have been able to reveal valuable information about wind profiles in a deeper context than previously conducted, ultimately improving understanding of AEDL flight mechanics sensitivity and EES design.

Kaustubh Ray↗

Global Sensitivity Analyses for Test Planning with Black-Box Models for Mars Sample Return

This work describes sensitivity analyses performed on complex black-box models used to support experimental test planning under limited resources in the context of the Mars Sample Return program, which aims at bringing to Earth rock and atmospheric samples from Mars. We develop a systematic workflow that allows the analysts to simultaneously obtain quantitative insights on key drivers of uncertainty, on the direction of impact, and the presence of interactions. We apply novel optimal transport-based global sensitivity measures to tackle the multivariate nature of the output. On the modeling side, we apply multi-fidelity techniques that leverage low-fidelity models to speed up the calculations and make up for the limited amount of high-fidelity samples, while keeping these in the loop for accuracy guarantees. The sensitivity analysis reveals insights useful for the analysts to understand the model's behavior and identify the factors to focus on during testing in order to maximize the value of information extracted from them to ensure mission success when limited resources are available.

Giuseppe Cataldo↗

Airburst & Blast Damage Modeling Sensitivities for Asteroid Impact Risk Assessment

Blast overpressure from a high-energy airburst or surface impact is the primary source of damage from potentially hazardous asteroid strikes. There are many sources of uncertainty in evaluating these potential damage risks, both in the approaches used to model the entry, breakup, and airburst behaviors of diverse asteroid properties, and in the blast modeling approaches used to estimate the ground damage from these very large-scale, high-energy events. In this study, we use NASA’s Probabilistic Asteroid Impact Risk (PAIR) model to investigate trends and sensitivities in asteroid airburst altitudes and the resulting blast damage estimates across a range of asteroid sizes. In particular, we show how uncertainties in asteroid breakup behavior and effective airburst altitudes combine with height-of-burst (HOB) blast damage models to produce key sensitivities and trends in the amount of damage expected from different asteroid sizes and airburst altitudes. We show airburst altitude ranges and probabilities stemming from asteroid entry and breakup modeling uncertainties, compare differences between traditional nuclear-based HOB blast models and simulation-based HOB models for larger asteroid energies, and show how the resulting interplay between likely burst altitudes and optimal burst heights affects blast damage trends across different asteroid sizes. Finally, we combine the relative likelihoods of asteroid sizes, airburst altitudes, and resulting blast damage severity to evaluate what airburst regimes pose the highest overall level of risk (when considering both the relative likelihood and scale of potential damage) for a mid-sized asteroid threat scenario. Results show what asteroid size regimes are most sensitive to airburst and blast modeling uncertainties, provide insight into nonintuitive trends in the size and severity of blast damage expected from different airburst events, and highlight where additional blast modeling studies or refinements may help improve future impact risk estimates

ATAP↗

Gas sensitive materials for gas detection and methods of making

A gas sensitive material comprising SnO.sub.2 nanocrystals doped with In.sub.2O.sub.3 and an oxide of a platinum group metal, and a method of making the same. The platinum group metal is preferably Pd, but also may include Pt, Ru, Ir, and combinations thereof. The SnO.sub.2 nanocrystals have a specific surface of 7 or greater, preferably about 20 m2/g, and a mean particle size of between about 10 nm and about 100 nm, preferably about 40 nm. A gas detection device made from the gas sensitive material deposited on a substrate, the gas sensitive material configured as a part of a current measuring circuit in communication with a heat source.

36 MATERIALS SCIENCE↗

Dynamic tuning of chemiresistor sensitivity using mechanical strain

The sensitivity of a chemiresistor sensor can be dynamically tuned using mechanical strain. The increase in sensitivity is a smooth, continuous function of the applied strain, and the effect can be reversible. Sensitivity tuning enables the response curve of the sensor to be dynamically optimized for sensing analytes, such as volatile organic compounds, over a wide concentration range.

47 OTHER INSTRUMENTATION↗

Adjusting the specificity of an engine map based on the sensitivity of an engine control parameter relative to a performance variable

Methods and systems for engine control optimization are provided. A first and a second operating condition of a vehicle engine are detected. An initial value is identified for a first and a second engine control parameter corresponding to a combination of the detected operating conditions according to a first and a second engine map look-up table. The initial values for the engine control parameters are adjusted based on a detected engine performance variable to cause the engine performance variable to approach a target value. A first and a second sensitivity of the engine performance variable are determined in response to changes in the engine control parameters. The first engine map look-up table is adjusted when the first sensitivity is greater than a threshold, and the second engine map look-up table is adjusted when the second sensitivity is greater than a threshold.

33 ADVANCED PROPULSION SYSTEMS↗

CONTINUOUS-ENERGY MONTE CARLO METHODS FOR CALCULATING GENERALIZED RESPONSE SENSITIVITIES USING TSUNAMI-3D

This work introduces a new approach for calculating sensitivity coefficients for generalized neutronic responses to nuclear data uncertainties using continuous-energy Monte Carlo methods. The approach presented in this paper, known as the GEAR-MC method, allows for the calculation of generalized sensitivity coefficients for multiple responses in a single Monte Carlo calculation with no nuclear data perturbations or knowledge of nuclear covariance data. The theory behind the GEAR-MC method is presented here, and proof of principle is demonstrated by using the GEAR-MC method to calculate sensitivity coefficients for responses in several 3D, continuous-energy Monte Carlo applications.

CLUTCH↗

Superconducting Accelerating Cavity Pressure Sensitivity Analysis and Stiffening

The Soreq Applied Research Accelerator Facility (SARAF) design is based on a 40 MeV 5 mA light ions superconducting RF linac. Phase-I of SARAF delivers up to 2 mA CW proton beams in an energy range of 1.5 - 4.0 MeV. The maximum beam power that we have reached is 5.7 kW. Today, the main limiting factor to reach higher ion energy and beam power is related to the HWR sensitivity to the liquid helium coolant pressure fluctuations. The HWR sensitivity to helium pressure is about 60 Hz/mbar. The cavities had been designed, a decade ago, to be soft in order to enable tuning of their novel shape. However, the cavities turned out to be too soft. In this work we found that increasing the rigidity of the cavities in the vicinity of the external drift tubes may reduce the cavity sensitivity by a factor of three. A preliminary design to increase the cavity rigidity is presented.

Rodnizki, J↗

Demonstration of Uncertainty Quantification and Sensitivity Analysis for PWR Fuel Performance with BISON

BISON is an advanced fuels performance code being developed at Idaho National Laboratory and is the code of choice for fuels performance by the U.S. Department of Energy (DOE)’s Consortium for Advanced Simulation of Light Water Reactors (CASL) Program. An approach to uncertainty quantification and sensitivity analysis with BISON was developed and a new toolkit was created. A PWR fuel rod model was developed and simulated by BISON, and uncertainty quantification and sensitivity analysis were performed with eighteen uncertain input parameters. The maximum fuel temperature and gap conductance were selected as the figures of merit (FOM). Pearson, Spearman, and partial correlation coefficients were considered for all of the figures of merit in sensitivity analysis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Energy sensitization of acceptors and donors in organic photovoltaics

Disclosed herein are organic photosensitive optoelectronic devices comprising acceptor and/or donor sensitizers to increase absorption and photoresponse of the photoactive layers of the devices. In particular, devices herein include at least one acceptor layer and at least one donor layer, wherein the acceptor layer may comprise a mixture of an acceptor material and at least one sensitizer, and the donor layer may comprise a mixture of a donor material and at least one sensitizer. Methods of fabricating the organic photosensitive optoelectronic devices are also disclosed.

14 SOLAR ENERGY↗

Enhancing the sensitivity of the LUX-ZEPLIN (LZ) dark matter experiment to low energy signals

Two-phase xenon detectors, such as that at the core of the forthcoming LZ dark matter experiment, use photomultiplier tubes to sense the primary (S1) and secondary (S2) scintillation signals resulting from particle interactions in their liquid xenon target. This paper describes a simulation study exploring two techniques to lower the energy threshold of LZ to gain sensitivity to low-mass dark matter and astrophysical neutrinos, which will be applicable to other liquid xenon detectors. The energy threshold is determined by the number of detected S1 photons; typically, these must be recorded in three or more photomultiplier channels to avoid dark count coincidences that mimic real signals. To lower this threshold: a) we take advantage of the double photoelectron emission effect, whereby a single vacuum ultraviolet photon has a $\sim20\%$ probability of ejecting two photoelectrons from a photomultiplier tube photocathode; and b) we drop the requirement of an S1 signal altogether, and use only the ionization signal, which can be detected more efficiently. For both techniques we develop signal and background models for the nominal exposure, and explore accompanying systematic effects, including the dependence on the free electron lifetime in the liquid xenon. When incorporating double photoelectron signals, we predict a factor of $\sim 4$ sensitivity improvement to the dark matter-nucleon scattering cross-section at $2.5$ GeV/c$^2$, and a factor of $\sim1.6$ increase in the solar $^8$B neutrino detection rate. Dropping the S1 requirement may allow sensitivity gains of two orders of magnitude in both cases. Finally, we apply these techniques to even lower masses by taking into account the atomic Migdal effect; this could lower the dark matter particle mass threshold to $80$ MeV/c$^2$.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Enhancing the sensitivity of the LUX-ZEPLIN (LZ) dark matter experiment to low energy signals

Two-phase xenon detectors, such as that at the core of the forthcoming LZ dark matter experiment, use photomultiplier tubes to sense the primary (S1) and secondary (S2) scintillation signals resulting from particle interactions in their liquid xenon target. This paper describes a simulation study exploring two techniques to lower the energy threshold of LZ to gain sensitivity to low-mass dark matter and astrophysical neutrinos, which will be applicable to other liquid xenon detectors. The energy threshold is determined by the number of detected S1 photons; typically, these must be recorded in three or more photomultiplier channels to avoid dark count coincidences that mimic real signals. To lower this threshold: a) we take advantage of the double photoelectron emission effect, whereby a single vacuum ultraviolet photon has a $\sim20\%$ probability of ejecting two photoelectrons from a photomultiplier tube photocathode; and b) we drop the requirement of an S1 signal altogether, and use only the ionization signal, which can be detected more efficiently. For both techniques we develop signal and background models for the nominal exposure, and explore accompanying systematic effects, including the dependence on the free electron lifetime in the liquid xenon. When incorporating double photoelectron signals, we predict a factor of $\sim 4$ sensitivity improvement to the dark matter-nucleon scattering cross-section at $2.5$ GeV/c$^2$, and a factor of $\sim1.6$ increase in the solar $^8$B neutrino detection rate. Dropping the S1 requirement may allow sensitivity gains of two orders of magnitude in both cases. Finally, we apply these techniques to even lower masses by taking into account the atomic Migdal effect; this could lower the dark matter particle mass threshold to $80$ MeV/c$^2$.

Akerib, DS↗

Enabling Computation on Sensitive Data in International Safeguards with Privacy-Preserving Encryption Techniques

Privacy-preserving machine learning is a field of study that explores how to protect and preserve the privacy of sensitive data while allowing the data to be used by machine learning algorithms. This field has had substantial industry investment due to heightened concerns about privacy in the technology industry, with a focus in two broad application areas: financial services and healthcare. Numerous privacy-preserving methods have also been proposed for international safeguards, but they have been difficult to enact because the data they require is con- sidered sensitive or proprietary by the nuclear facility operator. This work examines how current privacy-preserving approaches might be used to enable the International Atomic Energy Agency (IAEA) to use that data to contribute to a safeguards conclusion about a state while giving nuclear operators confidence that their sensitive data is adequately protected. This paper begins by exploring several broad categories of privacy-preserving techniques including homomorphic encryption, secure multiparty computation, secure enclaves, and zero-knowledge proofs. Then we discuss some of the security considerations related to using these methods, potential use cases, and a conceptual system design for applying privacy-preserving methods in international safeguards.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗