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At least 1,297 records · Page 72

Constraining nuclear mass models using 𝑟-process observables with multiobjective optimization

Modeling nuclear masses, particularly for nuclei far from stability, remains a key objective in nuclear physics. One contemporary approach is machine learning (ML), which trains on experimental data, but can suffer large errors when extrapolating toward neutron-rich species. In nature, such masses shape observables for the rapid neutron capture process (𝑟 process), which in principle could inform ML models. Here, we introduce a multiobjective optimization approach using the Pareto front algorithm. We show that this technique, capable of identifying models that generate 𝑟-process abundances aligning with both solar and stellar data, is a promising method to select ML models with reliable extrapolation power.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Strain-Gauge Measurement of Weight of Fluid in a Tank

A method of determining the amount of fluid in a tank is based on measurement of strains induced in tank supports by the weight of the fluid. Unlike most prior methods, this method is nonintrusive: there is no need to insert instrumentation in the tank and, hence, no need to run wires, cables, or tubes through the tank wall. Also unlike most prior methods, this method is applicable even if the fluid in the tank is at supercritical pressure and temperature, because it does not depend on the presence of a liquid/gas interface (as in liquid-level-measuring methods). The strain gauges used in this method may be of two types: foil and fiber-optic. Four foil gauges (full bridge) are mounted on each of the tank-supporting legs. As the tank is filled or emptied, the deformation in each leg increases or decreases, respectively. Measured deformations of all legs are added to obtain a composite deformation indicative of the change in weight of the tank plus fluid. An initial calibration is performed by recording data at two points (usually, empty and full) for which the mass or weight of fluid is known. It is assumed that the deformations are elastic, so that the line passing through the two points can be used as a calibration curve of mass (or weight) of fluid versus deformation. One or more fiber-optic gauges may be used instead of the foil gauges. The resolution of the fiber-optic and foil gauges is approximately the same, but the fiber-optic gauges are immune to EMI (electromagnetic interference), are linear with respect to temperature over their entire dynamic range (as defined by the behavior of the sample), and measure thermally induced deformations as predictable signals. Conversely, long term testing has demonstrated that the foil gauges exhibit an erratic behavior whenever subjected to direct sun radiation (even if protected with a rubberized cover). Henceforth, for deployment in outdoor conditions, fiber-optic gauges are the only option if one is to rely on the system for an extended period of time when a recalibration procedure may not be acceptable. A set of foil gauges had been tested on the supports of a 500-gallon (1,900-liter) tank. The gauges were found to be capable of measuring the deformations (up to 22 micro-strain) that occurred during filling and emptying of the tank. The fluid masses calculated from the gauge readings were found to be accurate within 4.5 percent. However, the reliability of the foil gauges over a few hours was not acceptable. Therefore, the foil sensor system is acceptable for use only in controlled environments (complete shade, or indoors).

Figueroa, Jorge↗

A comparative analysis of loop heat pipe based thermal architectures for spacecraft thermal control

Loop Heat Pipes (LHP) have gained acceptance as a viable means of heat transport in many spacecraft in recent years. However, applications using LHP technology tend to only remove waste heat from a single component to an external radiator. Removing heat from multiple components has been done by using multiple LHPs. This paper discusses the development and implementation of a Loop Heat Pipe based thermal architecture for spacecraft. In this architecture, a Loop Heat Pipe with multiple evaporators and condensers is described in which heat load sharing and thermal control of multiple components can be achieved. A key element in using a LHP thermal architecture is defining the need for such an architecture early in the spacecraft design process. This paper describes an example in which a LHP based thermal architecture can be used and how such a system can have advantages in weight, cost and reliability over other kinds of distributed thermal control systems. The example used in this paper focuses on a Mars Rover Thermal Architecture. However, the principles described here are applicable to Earth orbiting spacecraft as well.

loop heat pipes↗

Atomic Decay Data for Modeling K Lines of Iron Peak and Light Odd-Z Elements*

Complete data sets of level energies, transition wavelengths, A-values, radiative and Auger widths and fluorescence yields for K-vacancy levels of the F, Na, P, Cl, K, Sc, Ti, V, Cr, Mn, Co, Cu and Zn isonuclear sequences have been computed by a Hartree-Fock method that includes relativistic corrections as implemented in Cowan's atomic structure computer suite. The atomic parameters for more than 3 million fine-structure K lines have been determined. Ions with electron number N greater than 9 are treated for the first time, and detailed comparisons with available measurements and theoretical data for ions with N less than or equal to 9 are carried out in order to estimate reliable accuracy ratings.

modeling K lines↗

Cloud Detection over Snow and Ice with Oxygen A- and B-band Observations from the Earth Polychromatic Imaging Camera (EPIC)

Satellite cloud detection over snow and ice has been difficult for passive remote sensing instruments due to the lack of contrast between clouds and cold/bright surfaces; cloud mask algorithms often heavily rely on shortwave infrared (IR) channels over such surfaces. The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) does not have infrared channels, which makes cloud detection over snow and ice surfaces even more challenging. This study investigates the methodology of applying EPIC's two oxygen absorption band pair ratios in the A band (764, 780 nm) and B band (688, 680 nm) for cloud detection over the snow and ice surfaces. We develop a novel elevation and zenith-angle-dependent threshold scheme based on radiative transfer model simulations that achieves significant improvements over the existing algorithm. When compared against a composite cloud mask based on geosynchronous Earth orbit (GEO) and low Earth orbit (LEO) sensors, the positive detection rate over snow and ice surfaces increased from around 36 % to 65 % while the false detection rate dropped from 50 % to 10 % for observations of January 2016 and 2017. The improvement in July is less substantial due to relatively better performance in the current algorithm. The new algorithm is applicable for all snow and ice surfaces including Antarctic, sea ice, high-latitude snow, and high-altitude glacier regions. This method is less reliable when clouds are optically thin or below 3 km because the sensitivity is low in oxygen band ratios for these cases.

EPIC↗

Evaluation of UAV-derived multimodal remote sensing data for biomass prediction and drought tolerance assessment in bioenergy sorghum

Screening for drought tolerance is critical to ensure high biomass production of bioenergy sorghum in arid or semi-arid environments. The bottleneck in drought tolerance selection is the challenge of accurately predicting biomass for a large number of genotypes. Although biomass prediction by low-altitude remote sensing has been widely investigated on various crops, the performance of the predictions are not consistent, especially when applied in a breeding context with hundreds of genotypes. In some cases, biomass prediction of a large group of genotypes benefited from multimodal remote sensing data; while in other cases, the benefits were not obvious. In this study, we evaluated the performance of single and multimodal data (thermal, RGB, and multispectral) derived from an unmanned aerial vehicle (UAV) for biomass prediction for drought tolerance assessments within a context of bioenergy sorghum breeding. The biomass of 360 sorghum genotypes grown under well-watered and water-stressed regimes was predicted with a series of UAV-derived canopy features, including canopy structure, spectral reflectance, and thermal radiation features. Biomass predictions using canopy features derived from the multimodal data showed comparable performance with the best results obtained with the single modal data with coefficients of determination (R 2 ) ranging from 0.40 to 0.53 under water-stressed environment and 0.11 to 0.35 under well-watered environment. The significance in biomass prediction was highest with multispectral followed by RGB and lowest with the thermal sensor. Finally, two well-recognized yield-based drought tolerance indices were calculated from ground truth biomass data and UAV predicted biomass, respectively. Results showed that the geometric mean productivity index outperformed the yield stability index in terms of the potential for reliable predictions by the remotely sensed data. Collectively, this study demonstrated a promising strategy for the use of different UAV-based imaging sensors to quantify yield-based drought tolerance.

09 BIOMASS FUELS↗

Robotic control and inspection verification

Three areas of possible commercialization involving robots at the Kennedy Space Center (KSC) are discussed: a six degree-of-freedom target tracking system for remote umbilical operations; an intelligent torque sensing end effector for operating hand valves in hazardous locations; and an automatic radiator inspection device, a 13 by 65 foot robotic mechanism involving completely redundant motors, drives, and controls. Aspects concerning the first two innovations can be integrated to enable robots or teleoperators to perform tasks involving orientation and panal actuation operations that can be done with existing technology rather than waiting for telerobots to incorporate artificial intelligence (AI) to perform 'smart' autonomous operations. The third robot involves the application of complete control hardware redundancy to enable performance of work over and near expensive Space Shuttle hardware. The consumer marketplace may wish to explore commercialization of similiar component redundancy techniques for applications when a robot would not normally be used because of reliability concerns.

Davis, Virgil Leon↗

A physiological signal derived from sun-induced chlorophyll fluorescence quantifies crop physiological response to environmental stresses in the U.S. Corn Belt

Sun-induced chlorophyll fluorescence (SIF) measurements have shown unique potential for quantifying plant physiological stress. However, recent investigations found canopy structure and radiation largely control SIF, and physiological relevance of SIF remains yet to be fully understood. This study aims to evaluate whether the SIF-derived physiological signal improves quantification of crop responses to environmental stresses, by analyzing data at three different spatial scales within the U.S. Corn Belt, i.e. experiment plot, field, and regional scales, where ground-based portable, stationary and space-borne hyperspectral sensing systems are used, respectively. We found that, when controlling for variations in incoming radiation and canopy structure, crop SIF signals can be decomposed into non-physiological (i.e. canopy structure and radiation, 60% ~ 82%) and physiological information (i.e. physiological SIF yield, Φ F , 17% ~ 31%), which confirms the contribution of physiological variation to SIF. We further evaluated whether Φ F indicated plant responses under high-temperature and high vapor pressure deficit (VPD) stresses. The plot-scale data showed that Φ F responded to the proxy for physiological stress (partial correlation coefficient, r p = 0.40, p < 0.001) while non-physiological signals of SIF did not respond ( p > 0.1). The field-scale Φ F data showed water deficit stress from the comparison between irrigated and rainfed fields, and Φ F was positively correlated with canopy-scale stomatal conductance, a reliable indicator of plant physiological condition (correlation coefficient r = 0.60 and 0.56 for an irrigated and rainfed sites, respectively). The regional-scale data showed Φ F was more strongly correlated spatially with air temperature and VPD ( r = 0.23 and 0.39) than SIF ( r = 0.11 and 0.34) for the U.S. Corn Belt. The lines of evidence suggested that Φ F reflects crop physiological responses to environmental stresses with greater sensitivity to stress factors than SIF, and the stress quantification capability of Φ F is spatially scalable. Utilizing Φ F for physiological investigations will contribute to improve our understanding of vegetation responses to high-temperature and high-VPD stresses.

54 ENVIRONMENTAL SCIENCES↗

Theoretical tools for neutrino scattering: interplay between lattice QCD, EFTs, nuclear physics, phenomenology, and neutrino event generators

Maximizing the discovery potential of increasingly precise neutrino experiments will require an improved theoretical understanding of neutrino-nucleus cross sections over a wide range of energies. Low-energy interactions are needed to reconstruct the energies of astrophysical neutrinos from supernovae bursts and search for new physics using increasingly precise measurement of coherent elastic neutrino scattering. Higher-energy interactions involve a variety of reaction mechanisms including quasi-elastic scattering, resonance production, and deep inelastic scattering that must all be included to reliably predict cross sections for energies relevant to DUNE and other accelerator neutrino experiments. This white paper discusses the theoretical status, challenges, required resources, and path forward for achieving precise predictions of neutrino-nucleus scattering and emphasizes the need for a coordinated theoretical effort involved lattice QCD, nuclear effective theories, phenomenological models of the transition region, and event generators.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Space Qualification of Laser Diode Arrays

Laser instruments have great potential in enabling a new generation of remote-sensing scientific instruments. NASA s desire to employ laser instruments aboard satellites, imposes stringent reliability requirements under severe conditions. As a result of these requirements, NASA has a research program to understand, quantify and reduce the risk of failure to these instruments when deployed on satellites. Most of NASA s proposed laser missions have base-lined diode-pumped Nd:YAG lasers that generally use quasi-constant wave (QCW), 808 nm Laser Diode Arrays (LDAs). Our group has an on-going test program to measure the performance of these LDAs when operated in conditions replicating launch and orbit. In this paper, we report on the results of tests designed to measure the effect of vibration loads simulating launch into space and the radiation environment encountered on orbit. Our primary objective is to quantify the performance of the LDAs in conditions replicating those of a satellite instrument, determine their limitations and strengths which will enable better and more robust designs. To this end we have developed a systematic testing strategy to quantify the effect of environmental stresses on the optical and electrical properties of the LDA.

Troupaki, Elisavet↗

Issues and Design Drivers for Deep Space Habitats

A cross-disciplinary team of scientists and engineers applied expertise gained in Lunar Lander development to the conceptual design of a long-duration, deep space habitat for Near Earth Asteroid (NEA) missions. The design reference mission involved two launches to assemble a 5-module vehicle for a 380-day round trip mission carrying 4 crew members. The conceptual design process yielded a number of interesting debates, some of which could be significant design drivers in a detailed Deep Space Habitat (DSH) design. These issues include: a) Launch loads: Potentially drives layout of equipment mounted to module floors or walls, and whether temporary internal structure is required to distribute launch loads to minimize shell mass; b) Unmanned loiter time: When added to an already lengthy mission, loiter time further drives risk and reliability, and poses issues for equipment shelf life such as material degradation or cryogenic fluids boil-off; c) Pointing and Visibility: A habitat embedded in a 5-module stack may drive Communications, Tracking, Guidance, and Navigation equipment out onto long booms to maintain line-of-sight visibility with targets. However, long booms will be more susceptible to disruption from exercise-induced vibration, potential damage during docking/undocking operations, and increased power distribution mass; d) Water: although it is assumed that a water processor will collect and recycle water, several interesting question were posed, such as: How much water to start with? Should potable water serve double-duty as radiation protection? And if so, should it be stowed in a single large tank, or smaller, portable containers? e) Design for repairability: one of the worst-case scenarios identified was a cabin depressurization that required suited repair from inside the module, potentially driving the need for long umbilical hoses or special equipment to allow smaller, mated modules to be used as safe havens for up to 180 days;

Anderson, Molly S.↗

Comparison of simulated and experimentally measured detector impulse responses to pulsed x-rays

The Gamma Array Simulation Toolkit (GAST) is a multi-physics software stack comprised of Geant4, MATLAB, and experimentally measured photomultiplier tube (PMT) impulse response waveforms that is used to model and inform the end-toend performance of radiation detector systems. In order to validate the ability of GAST to predict the impulse response of a modeled detector configuration operated in current mode, experimental measurements using the Nevada National Security Site Transformational Diagnostics and Imaging 2 MeV endpoint energy electron linear accelerator (linac) with a tungsten target were performed. Seven different detector configurations consisting of unique combinations of scintillator material, size, reflectivity conditions, presence or absence of light guide, and PMT were evaluated. The resultant impulse response of each detector configuration was recorded and compared to a GAST simulation that emulated the respective linac experiment conditions. The comparison of the experimental and simulated detector impulse responses indicated that GAST can reliably predict detector impulse responses.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A Compact Electron-Proton Spectrometer for Moon / Mars Surface Space Weather Monitoring and Crew Protection (CEPS)

Small mass/low-power sensors are needed for autonomous Moon/Mars surface ops that provide alerts to impending adverse space weather conditions. In order to use current operational forecasting tools, a sensor capable of measuring both high-energy electrons and protons is needed. By combining high-TRL Timepix technology with a CdTe layer, this project leverages known technology to fill a critical gap for surface operations. Typical space weather sensors are at least an order of magnitude higher in mass than is expected from Timepix-based devices and are deployed on robotic assets away from human crews. High fidelity measurements at the crew location and subsequent ability are needed to provide warnings to crews to shelter with a device that can easily be carried on the Lunar and Martian surfaces.​ The aim of this project is the development of compact, low power space weather sensors for crew protection based on the combination of AES flight heritage Timepix hardware with novel CdTe (Cadmium Telluride) sensors. CdTe technology has only recently matured to a point where it can be reliably used with Timepix detectors. These detectors will be able to measure electron spectra in an energy range relevant to the RELEASE model, which is used operationally by NASA to provide crew early warning of Solar Energetic Particle Events as well as protons in the energy ranges relevant to human health allowing for event ‘nowcasting’ and total event crew dose prediction. Compared to existing solutions these detectors will be compact enough to travel with crew, providing a significant advantage to space environment situation awareness. Project results indicate that CdTe-based Timepix sensors respond well to energetic electrons, and particle tracks are sufficiently distinct to be able to measure in a mixed radiation field. Thermal testing results point to a needed design modification to mitigate high temperatures the detector will see in space. Radiation susceptibility testing was conducted to assess the radiation hardness of the CdTe-Timepix assembly. Overall, the assembly continued to operate up to 100 kRad of gamma-ray exposure. The system calibration did show drift over time but recovered once exposure was complete.

Dan James Fry↗

CEPS – A Compact Electron-Proton Spectrometer

Small mass/low-power sensors are needed for autonomous Moon/Mars surface ops that provide alerts to impending adverse space weather conditions. In order to use current operational forecasting tools, a sensor capable of measuring both high-energy electrons and protons is needed. By combining high-TRL Timepix technology with a CdTe layer, this project leverages known technology to fill a critical gap for surface operations. Typical space weather sensors are at least an order of magnitude higher in mass than is expected from Timepix-based devices and are deployed on robotic assets away from human crews. High fidelity measurements at the crew location and subsequent ability are needed to provide warnings to crews to shelter with a device that can easily be carried on the Lunar and Martian surfaces.​ The aim of this project is the development of compact, low power space weather sensors for crew protection based on the combination of AES flight heritage Timepix hardware with novel CdTe (Cadmium Telluride) sensors. CdTe technology has only recently matured to a point where it can be reliably used with Timepix detectors. These detectors will be able to measure electron spectra in an energy range relevant to the RELEASE model, which is used operationally by NASA to provide crew early warning of Solar Energetic Particle Events as well as protons in the energy ranges relevant to human health allowing for event ‘nowcasting’ and total event crew dose prediction. Compared to existing solutions these detectors will be compact enough to travel with crew, providing a significant advantage to space environment situation awareness. Project results indicate that CdTe-based Timepix sensors respond well to energetic electrons, and particle tracks are sufficiently distinct to be able to measure in a mixed radiation field. Detector response functions were developed for both electrons and protons. Measurement results showed response to both electrons and protons in the energy range of interest for human space flight.

Radiation↗

BioSentinel: Leading the Way for Deep Space CubeSat Missions

Flagship science missions are not alone in Deep Space thanks to BioSentinel, a 6U spacecraft launched on Artemis-1. BioSentinel is one of the longest operating CubeSats beyond cislunar space. The subsystems and COTS components of the BioSentinel bus are a template for future deep space missions, and the lessons learned from over a year of operations will enable improved performance for the next missions. BioSentinel achieved its unprecedented performance for an SLS secondary payload due to preparation, planning, and a robust design. Pre-launch antenna and interface testing with both DSN and ESA confirmed command and data pathways and allowed for operational flexibility in the critical early hours post-deployment. Mission Operations simulations prior to launch identified potential risks and primed operators to respond in flight, preparing the team to react quickly to successfully detumble the spacecraft and enter a power-positive state. The spacecraft would not have survived without the inclusion of the trailblazing 3D-printed composite cold gas propulsion system. The non-standard tank geometry enabled efficient use of the limited space available in the CubeSat, as well as the capability to detumble the spacecraft and manage momentum, while providing sufficient margin to execute potential delta-V maneuvers. The Iris radio has operated for over 18 months with no significant issues. Initial Iris performance estimates have been accurate throughout the mission. BioSentinel continues to collect data on thermal conditions and to validate our performance models with real-world knowledge. We have received exemplary support from our DSN partners. Following the conclusion of the primary science mission, the Linear Energy Transfer (LET) Spectrometer continued to collect solar and galactic radiation data from its location in heliocentric orbit. The free space dataset offered by the BioSentinel LET is a valuable source of data for model validation and future mission planning. As the spacecraft travels farther from Earth it is poised to provide longitudinally distributed measurements of solar particle events during solar maximum. The lessons learned from BioSentinel suggest key areas to enhance performance. The ability to upload modified flight software can increase the stability of memory management. Additional heaters in the propulsion system design have already proven successful on the Starling mission. Streamlining mission operations can reduce costs, increase data return, and better utilize DSN time. Enhancements such as these will facilitate reliable, long-duration deep space exploration using the proven BioSentinel 6U CubeSat bus.

BioSentinel↗

Comparison of Simulated and Experimentally Measured Detector Impulse Responses to Pulsed X-rays

The Gamma Array Simulation Toolkit (GAST) is a multi-physics software stack comprised of Geant4, MATLAB, and experimentally measured photomultiplier tube (PMT) impulse response waveforms that is used to model and inform the end-to-end performance of radiation detector systems. In order to validate the ability of GAST to predict the impulse response of a modeled detector configuration operated in current mode, experimental measurements using the Nevada National Security Site Transformational Diagnostics and Imaging 2 MeV endpoint energy electron linear accelerator (linac) with a tungsten target were performed. Seven different detector configurations consisting of unique combinations of scintillator material, size, reflectivity conditions, presence or absence of light guide, and PMT were evaluated. The resultant impulse response of each detector configuration was recorded and compared to a GAST simulation that emulated the respective linac experiment conditions. The comparison of the experimental and simulated detector impulse responses indicated that GAST can reliably predict detector impulse responses.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Test Results for Checking Reliability of Selected ENDF/B-VIII.0 Evaluated Uncertainties

This report summarizes error messages obtained from counter-checking whether 1 H, 9 Be, 12 C, 27 Al, 235,238 U and 238–242 Pu relative uncertainties of ENDF/B-VIII.0 are realistic. Large parts of this report were generated automatically by the code CovVal. This code allows to test the reliability of relative uncertainties of any isotope. It gives generic error and warning messages if evaluated relative uncertainties of a particular reaction are likely under- or over-estimated. In addition to these error and warning messages, I added comments whether the flagged uncertainties are truly under- or overestimated. I call out these uncertainties that should be further investigated and corrected by an evaluator for an upcoming release of ENDF/B-VIII.1.

07 ISOTOPE AND RADIATION SOURCES↗

An efficient method to identify uncertainties of WRF-Solar variables in forecasting solar irradiance using a tangent linear sensitivity analysis

Uncertainty in predicting solar energy resources introduces major challenges in power system management and necessitates the development of reliable probabilistic solar forecasts. As the first part of the development of probabilistic forecasts based on the Weather Research and Forecasting model with solar extensions (WRF-Solar), this study presents a tangent linear approach to identify input variables responsible for the largest uncertainties in predicting surface solar irradiance and clouds. A tangent linear analysis is capable of efficiently investigating sensitivities of output variables with respect to various input variables of WRF-Solar because this approach avoids the computational burden of perturbing the initial conditions of individual input variables. We develop tangent linear models (TLMs) for six WRF-Solar physics packages that control the formation and dissipation of clouds and solar radiation, and we evaluate the validity of TLMs using a linearity test. The tangent linear sensitivity analysis is conducted under various scenarios based on satellite observations and model simulations to consider realistic input conditions. A simple method is used to quantify the impact of the uncertainty of input variables on the output variables from the TLMs. The results demonstrate that uncertainties in the output variables that are the focus of this study—including global horizontal irradiance, direct normal irradiance, cloud mixing ratio, cloud tendency, cloud fraction, and sensible and latent heat fluxes—are highly sensitive to uncertainties in 14 input variables. This study indicates that the tangent linear method can identify key variables of physics modules in WRF-Solar that can be stochastically perturbed to generate ensemble-based probabilistic forecasts.

14 SOLAR ENERGY↗