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NASA NTRS2017

Diffusion of Redox-Sensitive Elements in Basalt at Different Oxygen Fugacities

The terrestrial planets and moons of our solar system have differentiated over a range of oxygen fugacity conditions. Basalts formed from magmas on the Earth cover a range of more oxidized states (from approximately IW (iron wustite) plus 2 to approximately FMQ (fayalite-magnetite-quartz) plus 3) than crustal rocks from Mars (IW to approximately IW plus 3), and basalts from the Moon are more reduced than both, ranging from IW to IW minus 2. The small body Vesta differentiated around IW minus 4. Characterization of redox sensitive elements' diffusivities will offer insight into behavior of these elements as a function of f (fugacity of) O2 for these planetary bodies. Here, we report a systematic study of the diffusion of redox-sensitive elements in basaltic melts with varying oxygen fugacities (fO2) for trace elements, V, Nb, W, Mo, La, Ce, Pr, Sm, Eu, Gd, Ta, and W. Since fO2 is an intensive variable that is different for the reservoirs of various planets and moons in our solar system, it is important to characterize how changes in redox states will affect diffusion. We conducted experiments in a piston cylinder device at 1300 degrees Centigrade and 1 gigapascal, at the University of Rochester and NASA Johnson Space Center. We buffered some experiments at Ru-RuO2 (FMQ plus 6.00), and conducted other experiments within either a graphite or Mo capsule, which corresponds to fO2s of either FMQ minus1.2, or FMQ minus 3.00, respectively. Characterizing the diffusivities of redox sensitive elements at different fO2s is important because some elements, like Eu, have varying valence states, such as Eu (sup 2 plus) and Eu (sup 3 plus). Differences in charge and ion radii may lead to differences in diffusivities within silicate melts. This could, lead to formation of a Eu anomaly by diffusion, the magnitude of which may be controlled by the fO2. Characterization of trace element diffusion is also important in understanding trace element fractionation. We found, during the course of our investigation, that not only did the diffusivities of the redox sensitive elements change with fO2, but that the diffusivities of all other analyzed elements also changed. This indicates that not only do changes in valence influence trace elements diffusivities but that the structure of melt may have changed with varying oxygen fugacity, probably due to changes in the speciation of the major element Fe.

Szumila, I.↗

NASA NTRS2017

Converging Climate Sensitivities of European Forests Between Observed Radial Tree Growth and Vegetation Models

The impacts of climate variability and trends on European forests are unevenly distributed across different bioclimatic zones and species. Extreme climate events are also becoming more frequent and it is unknown how they will affect feed backs of CO2 between forest ecosystems and the atmosphere. An improved understanding of species differences at the regional scale of the response of forest productivity to climate variation and extremes is thus important for forecasting forest dynamics. In this study, we evaluate the climate sensitivity of above ground net primary production (NPP) simulated by two dynamic global vegetation models (DGVM; ORCHIDEE and LPJ-wsl) against tree ring width (TRW) observations from about1000 sites distributed across Europe. In both the model simulations and the TRW observations, forests in northern Europe and the Alps respond positively to warmer spring and summer temperature, and their overall temperature sensitivity is larger than that of the soil-moisture-limited forests in central Europe and Mediterranean regions. Compared with TRW observations, simulated NPP from ORCHIDEE and LPJ-wsl appear to be overly sensitive to climatic factors. Our results indicate that the models lack biological processes that control time lags, such as carbohydrate storage and remobilization, that delay the effects of radial growth dynamics to climate. Our study highlights the need for re-evaluating the physiological controls on the climate sensitivity of NPP simulated by DGVMs. In particular, DGVMs could be further enhanced by a more detailed representation of carbon reserves and allocation that control year-to year variation in plant growth.

Zhang, Zhen↗

NASA NTRS2017

Experimental Verification of Buffet Calculation Procedure Using Unsteady Pressure-Sensitive Paint

Typically, a limited number of dynamic pressure sensors is employed to determine the unsteady aerodynamic forces on large, slender aerospace structures. This paper describes a robust calculation procedure based on frequency-specific correlation lengths and validation from an experiment conducted on a flat panel coated with fast response pressure-sensitive paint. The first part of the paper describes the procedure used to analyze the pressure sensitive paint images and a calibration method using dynamic pressure transducers. Excellent comparison in spectra, coherence, and phase, measured via pressure-sensitive paint and dynamic pressure sensors, validates the pressure-sensitive paint data. The second part of the paper describes the buffet validation process, the first step of which was to use pressure histories from all pixels to determine the true force fluctuations. In the next step, only a selected number of pixels was chosen as virtual sensors, and a correlation-length-based buffet calculation procedure was applied to determine modeled force fluctuations. By progressively decreasing the number of virtual sensors, it was observed that the present calculation procedure was able to make a close estimate of the true unsteady forces only from eight sensors. It is believed that the present work provides the first validation of a buffet calculation procedure.

Buffet↗

NASA NTRS2018

Methane on Mars: New Insights into the Sensitivity of CH4 with the NOMAD/ExoMars Spectrometer Through Its First In-Flight Calibration

The Nadir and Occultation for MArs Discovery instrument (NOMAD), onboard the ExoMars Trace Gas Orbiter (TGO) spacecraft was conceived to observe Mars in solar occultation, nadir, and limb geometries, and will be able to produce an outstanding amount of diverse data, mostly focused on properties of the atmosphere. The infrared channels of the instrument operate by combining an echelle grating spectrometer with an Acousto- Optical Tunable Filter (AOTF). Using in-flight data, we characterized the instrument performance and parameterized its calibration. In particular: an accurate frequency calibration was achieved, together with its variability due to thermal effects on the grating. The AOTF properties and transfer function were also quantified, and we developed and tested a realistic method to compute the spectral continuum transmitted through the coupled grating and AOTF system. The calibration results enabled unprecedented insights into the important problem of the sensitivity of NOMAD to methane abundances in the atmosphere. We also deeply characterized its performance under realistic conditions of varying aerosol abundances, diverse albedos and changing illumination conditions as foreseen over the nominal mission. The results show that, in low aerosol conditions, NOMAD single spectrum, 1σ sensitivity to CH4 is around 0.33 ppbv at 20 km of altitude when performing solar occultation's, and better than 1 ppbv below 30 km. In dusty conditions, we show that the sensitivity drops to 0 below 10 km. In Nadir geometry, results demonstrate that NOMAD will be able to produce seasonal maps of CH4 with a sensitivity around 5 ppbv over most of planet's surface with spatial integration over 5×5° bins. Results show also that such numbers can be improved by a factor of ~10 to ~30 by data binning. Overall, our results quantify NOMAD's capability to address the variable aspects of Martian climate.

Liuzzi, Giuliano↗

NASA NTRS2020

Observational Constraints on the Effective Climate Sensitivity from the Historical Period

The observed warming in the atmosphere and ocean can be used to estimate the climate sensitivity linked to present-day feedbacks, which is referred to as the effective climate sensitivity (Shist). However, such an estimate is affected by uncertainty in the radiative forcing, particularly aerosols, over the historical period. Here, we make use of detection and attribution techniques to derive the surface air temperature and ocean warming that can be attributed directly to greenhouse gas increases. These serve as inputs to a simple energy budget to infer the likelihood of Shist in response to observed greenhouse gases increases over two time periods (1862–2012 and 1955–2012). The benefit of using greenhouse gas attributable quantities is that they are not subject to uncertainties in the aerosol forcing (other than uncertainty in the attribution to greenhouse gas versus aerosol forcing not captured by the multi-model aerosol response pattern). The resulting effective climate sensitivity estimate, Shist, ranges from 1.3 °Cto 3.1 °C(5%–95% range) over the full instrumental period (1862–2012) for our best estimate, and gets slightly wider when considering further uncertainties. This estimate increases to 1.7 °C–4.6 °C if using the shorter period (1955–2012).We also evaluate the climate model simulated surface air temperature and ocean heat content increase in response to greenhouse gas forcing over the same periods, and compare them with the observationally-constrained values.We find that that the ocean warming simulated in greenhouse gas only simulations in models considered here is consistent with that attributed to greenhouse gas increases from observations, while one model simulates more greenhouse gas-induced surface air warming than observed. However, other models with sensitivity outside our range show greenhouse gas warming that is consistent with that attributed in observations, emphasising that feedbacks during the historical period may differ from the feedbacks at CO2 doubling and from those at true equilibrium.

Tokarska, Katarzyna B↗

NASA NTRSDate not supplied

Individual Variability and Predictive Biomarkers of Human Sensitivity to Ionizing Radiation

High-linear energy transfer (LET) ionizing radiation is a major health hazard for astronauts who will be exposed to galactic cosmic rays during upcoming lunar and Mars missions. Predicting and mitigating personalized health risks from space radiation exposure requires understanding the factors underlying individual radiation sensitivity, which currently remain unknown. We started to address this challenge by identifying the genomic and demographic associations with sensitivity to low and high-LET ionizing radiation in the largest human sample cohort to date and by evaluating baseline DNA damage as a potential predictor of radiation responses. We have collected and irradiated peripheral blood mononuclear cells (PBMCs) from 768 healthy donors of matched ethnicity, 50/50 male/female, 18-70 years old. We have analyzed the responses of 576 donor PBMCs to irradiation with simulated galactic cosmic ray components: 350MeV/n 28Si, 350MeV/n 40Ar and 600MeV/n 56Fe, at 1.1 and 3 particles/100μm2 fluences, as well as 0.1Gy and 1Gy doses of gamma rays, at 4 and 24 hours post irradiation. We quantified post-irradiation DNA repair based on radiation-induced 53BP1+ foci formation, together with oxidative stress and cell death using a flow cytometry-based assay. We also assessed baseline levels of DNA repair in PBMCs at the time of sample collection prior to irradiation experiments. We observed a wide variability of subject- and LET-dependent radiation responses, with radiation-induced DNA repair foci increasing with LET, though oxidative stress being notably reduced by high-LET irradiation, potentially due to a switch between hydrogen peroxide and oxygen radical-based mechanisms. We also identified a relationship between few DNA repair foci at baseline and increased DNA repair after irradiation, accompanied by an alteration in immunoregulatory cytokine secretion, which might be adapted as biomarkers to predict ionizing radiation sensitivity. Among demographic variables, baseline foci levels were positively associated with age and latent cytomegalovirus infection. Finally, we have performed low-throughput whole genome sequencing of all samples and are currently in process of identifying the genes and pathways associated with low and high-LET ionizing radiation sensitivity in humans.

Space radiation, human spaceflight, DNA damage↗

NASA NTRS1993

NASA Ultra-Sensitive Miniature Accelerometer

Using micro-machined silicon technology, an ultra-sensitive miniature accelerometer can be constructed which meets the requirements for microgravity experiments in the space environment. Such an accelerometer will have a full scale sensitivity of 10 -2 g, a resolution of 10 -8 g, low cross-axis sensitivity, and low temperature sensitivity. Mass of the device is approximately five grams and its footprint is 2 cm x 2 cm.

miniature↗

NASA NTRS2019

Assessment of VIIRS on-orbit polarization sensitivity and its impact on CLARREO pathfinder inter-calibration

The primary objective of the CLARREO Pathfinder (CPF) mission is to demonstrate essential measurement technologies to enable highly accurate decadal change observations traceable on-orbit to SI standards. Another important objective of the CPF is to demonstrate inter-calibration with the VIIRS sensor and to show that such high-accuracy reference inter-calibration is achievable. To satisfy this requirement, it is important to understand and quantify uncertainties in VIIRS sensor measurements. Based on prelaunch test results, the reflective solar bands of both SNPP and NOAA-20 VIIRS have exhibited polarization sensitivities in the shortest wavelength bands, with an unexpectedly larger sensitivity observed for NOAA-20 VIIRS, particularly in bands M1 to M4. In this study, we use VIIRS Level-1B reflectance data collected over the Pseudo-Invariant Calibration Sites over North African desert region to examine the polarization associated uncertainty for these four bands. Impact due to BRDF on the reflectance data is considered by comparing baseline results obtained from the same viewing and solar zenith angles under relatively low polarization sensitivity. Impact due to detector relative difference in polarization sensitivity is examined by normalizing reflectances by the value of the middle detector. Results of this study provide useful information on VIIRS uncertainty contribution due to polarization when conducting CPF and VIIRS inter-calibration.

VIIRS↗

NASA NTRSDate not supplied

Mars Entry, Descent, Landing, and Ascent Systems Sensitivities to Landing Site and Atmospheric Dust

Plans for human missions to Mars continue to go through several architectural changes, dating all the way back to the 1950s [1]. The continuous study, reformulation, and refinement of Mars architectures and system concepts is necessary in order to incorporate evolving mission objectives, technology advancements, and growth in the body of knowledge regarding human factors and the various environments of human space travel. This evolution has continued into the 21st century, with architectures concepts such as NASA’s Design Reference Architecture 5.0 in 2009 [2], The Evolvable Mars Campaign in 2016 [3], and as recently as 2020, an architecture focused on a crewed mission as early as the 2030s that aims to minimizing crewed duration and infrastructure investment for the first mission [4]. Within these architectures, numerous studies around the current concept designs for Mars entry, descent, landing, and ascent (EDLA) systems have been performed over the last half a decade [[5], [6], [7], [8], [9], [10]]. Despite the breadth and depth of these studies, landing site, a key design parameter relevant to the design of EDLA systems, has remained nebulous over the years, largely due to the ever evolving mission objectives and architecture concept over the decades. However, the specific landing site has direct impact on the altitude and atmospheric conditions, which subsequently impact the design of EDLA systems. To accommodate the lack of a specific landing site, a baseline reference altitude of 0 km relative to the Mars Orbiter Laser Altimeter (MOLA), which is similar to an Earth sea level reference, has typically been selected and fixed for these past studies. Similarly, a baseline reference atmosphere has typically been utilized in these studies, either the Mars Global Reference Atmospheric Model [11], or a general 1982 standard warm, high pressure atmosphere model derived from Viking lander data [12]. Fig. 1 shows the range of elevations across the surface of Mars. Current architectures are focused on latitudes greater than 30 degrees north in an effort to ensure access to frozen water ice. From the figure, it is quickly evident that elevations over the range of longitudes at or above this latitude are significantly varied between roughly -4 to +4 km MOLA. Based on these observations, initial qualitative assessments of the impacts of landing site elevation on EDLA systems were performed. Fig. 2 depicts the expected trends in EDLA system mass for variations in both land site latitude and elevation. The background coloring is a qualitative evaluation of the current knowledge on ice water availability at the latitudes. Further modeling and simulation was performed to obtain numerical predictions of sensitivities to these parameters. Results indicate up to +2% to -4% mass variation from the current baseline Mars Ascent Vehicle concept, with the potential for greater than 6% mass variation at latitudes greater than 70 degrees north. However, variations in the descent system due to landing site were much more significant with mass variations in the range of -15% to +30% around the current baseline Mars Descent System concept. Additionally, Fig. 3 provides a depiction of potential Mars atmospheric density variations with both dust and Martian season. Though the Martian atmosphere is relatively thin compared to Earth’s atmosphere, it still poses significant impact on the design of EDLA systems. Variations in atmospheric density indicated by this slice of data would have significant impact on the design of EDLA systems. However, due to the highly complex nature of atmospheric flight, a qualitative assessment could not be performed. Rather, sensitivity results relied on modeling and simulation to provide numerical results for sensitivities on the current EDLA design concepts under consideration. Understanding these sensitivities is vital to the overall systems design of a Mars architecture. The resulting mass impacts on EDLA systems, driven by landing site elevation and dust level variations, has rippling impacts throughout the architecture that, ultimately, impact the viability of the architecture. Results showed fairly minor mass impacts to the current Mars Ascent Vehicle baseline configuration, roughly -0.6% to + 0.4% mass variations, while the Mars Descent System say greater variations due to dust, roughly -4% to +6% around the baseline concept.

EDLA↗

NASA NTRS2022

Satellite Soil Moisture Data Assimilation Impacts on Modeling Weather Variables and Ozone in the Southeastern US – Part 2: Sensitivity to Dry-Deposition Parameterizations

Ozone (O3) dry deposition is a major O3 sink. As a follow-up study of Huang et al. (2021), we quantify the impact of satellite soil moisture (SM) on model representations of this process when different dry-deposition parameterizations are implemented, based on which the implications for interpreting O3 air pollution levels and assessing the O3 impacts on human and ecosystem health are provided. The SM data from NASA's Soil Moisture Active Passive mission are assimilated into the Noah-Multiparameterization (Noah-MP) land surface model within the NASA Land Information System framework, semicoupled with Weather Research and Forecasting model with online Chemistry (WRF-Chem) regional-scale simulations covering the southeastern US. Major changes in the modeling system used include enabling the dynamic vegetation option, adding the irrigation process, and updating the scheme for the surface exchange coefficient. Two dry-deposition schemes are implemented, i.e., the Wesely scheme and a “dynamic” scheme, in the latter of which dry-deposition parameterization is coupled with photosynthesis and vegetation dynamics. It is demonstrated that, when the dynamic scheme is applied, the simulated O3 dry-deposition velocities vd and their stomatal and cuticular portions, as well as the total O3 fluxes Ft, are larger overall; vd and Ft are 2–3 times more sensitive to the SM changes due to the data assimilation (DA). Further, through case studies at two forested sites with different soil types and hydrological regimes, we highlight that, applying the Community Land Model type of SM factor controlling stomatal resistance (i.e., β factor) scheme in replacement of the Noah-type β factor scheme reduced the v(d) sensitivity to SM changes by ∼75 % at one site, while it doubled this sensitivity at the other site. Referring to multiple evaluation datasets, which may be associated with variable extents of uncertainty, the model performance of vegetation, surface fluxes, weather, and surface O3 concentrations shows mixed responses to the DA, some of which display land cover dependency. Finally, using model-derived concentration- and flux-based policy-relevant O3 metrics as well as their matching exposure–response functions, the relative biomass/crop yield losses for several types of vegetation/crops are estimated to be within a wide range of 1 %–17 %. Their sensitivities to the model's dry-deposition scheme and the implementation of SM DA are discussed.

Min Huang↗

NASA NTRSDate not supplied

Low-cost Quantification of Fluid Flow Parameter Sensitivity using Reduced-order Modeling

Uncertainty quantification of computational fluid dynamics (CFD) simulations is a complicated procedure which still relies in many cases on engineering judgment and factors of safety. This is in part because the computational cost of measuring the simulation's sensitivity to all meaningful parameters (e.g., body surface roughness) and hyperparameters (e.g., subiteration convergence criterion) is intractable for even a single simulation. Reduced-order modeling dramatically lowers this computational cost of simulating fluid flows, but usually only where similar data is already available. In this work, fluid reduced-order models are utilized to quantify a flow's sensitivity to certain physical parameters for the purposes of improved uncertainty quantification. Characteristic observability and sensitivity are both explored. The resulting sensitivity quantifications enable more informed CFD frameworks and more rigorous uncertainty bounds on the resulting data.

uncertainty quantification↗

NASA NTRSDate not supplied

Low-cost Quantification of Fluid Flow Parameter Sensitivity using Reduced-order Modeling

uncertainty quantification↗

NASA NTRSDate not supplied

Camera Setup for Unsteady Pressure Sensitive Paint at NASA Ames Research Center

The unsteady Pressure-Sensitive Paint Development Team at NASA Ames Research Center is conducting a Launch Vehicle Demo Test in the Unitary Plan Wind Tunnel’s 11-ft Transonic Wind Tunnel in the first half of 2024 to showcase improvements made to unsteady Pressure-Sensitive Paint technology. The unsteady Pressure-Sensitive Paint setup has upgraded from a four-camera system to an eight-camera system, prompting analysis to maximize the system performance and overall data quality. Additional analysis was performed to maximize the system resolving power when subject to test constraints such as model size and model tunnel positions. These analyses have uncovered new opportunities to improve the unsteady Pressure-Sensitive Paint technology and will allow the system to collect higher quality data with simple changes to the setup procedure.

Camera Calibration↗

NASA NTRSDate not supplied

Sensitivity Analysis of Heat Rejection and Propellant Management Technologies for Nuclear Thermal Propulsion Architectures

Cryogenic fluid management (CFM) technologies are very important for enabling a wider range of missions to utilize space nuclear propulsion (SNP) concepts such as nuclear thermal propulsion (NTP). Technologies for thermal and cryogenic propellant management allow for vehicles to take full advantage of the higher efficiency NTP systems for longer duration human interplanetary and deep space robotic missions. Currently, the CFM Portfolio Project at NASA’s Marshall Space Flight Center (MSFC) is developing thermal and propellant management technologies needed for SNP. When developing these technologies, it is important to understand the sensitivities of key performance parameters (KPPs) at the system and overall mission level due to the ways the technologies interact with each other, other subsystems, and influence the overall vehicle. The Advanced Concepts Office (ACO) at NASA-MSFC was tasked with building an integrated system model of a human Mars NTP mission to evaluate the impacts and sensitivities of CFM technologies on the overall vehicle and mission. This paper will cover the buildup of the model and highlight major sensitivities and breakpoints encountered, as well as future work in improving the existing models and sensitivities being evaluated.

Robert J. Hetterich↗

NASA NTRSDate not supplied

Fluid-Structure Interaction Simulations Of Supersonic Parachute Inflation: Model Sensitivities

Fluid-structure interaction simulations have the potential to accelerate the certification process of parachute systems for interplanetary robotic exploration missions while helping to mitigate risks by covering a wider range of scenarios than can be flight tested. The Launch, Ascent, and Vehicle Aerodynamics team is working toward actualizing this potential by further developing the capability to perform such fluid-structure interaction simulations and validating it with the best supersonic parachute flight test data available. We perform several simulations of the Advanced Supersonic Parachute Inflation Research Experiments’ third flight test (SR03) where we independently vary several parameters to determine their sensitivity on the predicted drag. We investigate sensitivity of the drag to the added mass of the confluence fitting, to the effective porosity, to how the gore seams are modeled, to viscous effects, and to deceleration. Modeling the added mass of the confluence fitting has virtually no impact on the drag, but is worthwhile to include to better match the overall system’s mass, which is important for the simulations with deceleration. Parachute drag is only marginally sensitive to porosity and viscous effects. Maximum parachute drag is most sensitive to how the gore seams are modeled, causing a nearly 20% drop when they are modeled as stiffer radials, and to deceleration, causing an additional 10% reduction. Results show improved agreement with flight test measurements when the FSI model is closest to the as-built configuration and physics experienced in flight: with the confluence fitting, viscous effects, the gore seams modeled as stiff radials, and including deceleration.

ESM↗

NASA NTRSDate not supplied

Sensitivity Analysis of Heat Rejection and Propellant Management Technologies for Nuclear Thermal Propulsion Architectures

Robert J Hetterich↗

NASA NTRS2024

Global Sensitivity Analysis of Simulated Remote Sensing Polarimetric Observations Over Snow

This study presents a detailed theoretical assessment of the information content of passive polarimetric observations over snow scenes, using a global sensitivity analysis (GSA) method. Conventional sensitivity studies focus on varying a single parameter while keeping all other parameters fixed. In contrast, the GSA correctly addresses the covariance of state parameters across their entire parameter space, hence favoring a more correct interpretation of inversion algorithms and the optimal design of their state vectors. The forward simulations exploit a vector radiative transfer model to obtain the Stokes vector emerging at the top of the atmosphere for different solar zenith angles, when the bottom boundary consists of a vertically resolved snowpack of non-spherical grains. The presence of light-absorbing particulates (LAPs), either embedded in the snow or aloft in the atmosphere above in the form of aerosols, is also considered. The results are presented for a set of wavelengths spanning the visible (VIS), near-infrared (NIR), and shortwave infrared (SWIR) region of the spectrum. The GSA correctly captures the expected, high sensitivity of the reflectance to LAPs in the VIS–NIR and to grain size at different depths in the snowpack in the NIR–SWIR. With adequate viewing geometries, mono-angle measurements of total reflectance in the VIS–SWIR (akin to those of the Moderate Resolution Imaging Spectroradiometer, MODIS) resolve grain size in the top layer of the snowpack sufficiently well. The addition of multi-angle polarimetric observations in the VIS–NIR provides information on grain shape and microscale roughness. The simultaneous sensitivity in the VIS–NIR to both aerosols and snow-embedded impurities can be disentangled by extending the spectral range to the SWIR, which contains information on aerosol optical depth while remaining essentially unaffected when the same particulates are mixed with the snow. Multi-angle polarimetric observations can therefore (i) effectively partition LAPs between the atmosphere and the surface, which represents a notorious challenge for snow remote sensing based on measurements of total reflectance only and (ii) lead to better estimates of grain shape and roughness and, in turn, the asymmetry parameter, which is critical for the determination of albedo. The retrieval uncertainties are minimized when the degree of linear polarization is used in place of the polarized reflectance. The Sobol indices, which are the main metric for the GSA, were used to select the state parameters in retrievals performed on data simulated for multiple instrument configurations. Improvements in retrieval quality with the addition of measurements of polarization, multi-angle views, and different spectral channels reflect the information content, identified by the Sobol indices, relative to each configuration. The results encourage the development of new remote sensing algorithms that fully leverage multi-angle and polarimetric capabilities of modern remote sensors. They can also aid flight planning activities, since the optimal exploitation of the information content of multi-angle measurements depends on the viewing geometry. The better characterization of surface and atmospheric parameters in snow-covered regions advances research opportunities for scientists of the cryosphere and ultimately benefits albedo estimates in climate models.

remote sensing↗

DOE OSTI2020

Sensitivity and Uncertainty Quantification of Transition Scenario Simulations

This report documents the first collective attempt at developing and applying capabilities to quantify uncertainties, assess parametric sensitivities, and optimize multiple parameters and metrics in fuel cycle simulations generated by the SA&I Campaign. To do this, external codes that were designed to perform sensitivity analysis and uncertainty quantification (SA&UQ) needed to be coupled to the SA&I Campaign’s nuclear fuel cycle simulators (NFCS). In FY20, two approaches were pursued: 1) coupling Cyclus to an ORNL-internal code called MOT (Metaheuristic Optimization Tool) and 2) coupling DYMOND to the opensource SA&UQ tool kit Dakota. The primary objective of having these NFCS/SA&UQ coupled capabilities is to better inform DOE-NE and other stakeholders on the results generated from the NFCS. For a given set of fuel cycle strategies, policies, and technology assumptions that make up a fuel cycle scenario, these NFCS have traditionally been used by the SA&I Campaign to provide quantitative answers in terms of year-by-year mass flows, infrastructure requirements, costs, etc. With these newly developed coupled capabilities, the SA&I Campaign can now efficiently simulate hundreds or thousands of these scenarios, sample large ranges of parameters and assumptions, and use the unique features of the SA&UQ tools to process the data. This enables providing answers with known and propagated uncertainties, determining the sensitivity of important metrics to different parameters and assumptions, quantifying how much fuel cycle and technology parameters impact each other, and producing optimized fuel cycle strategies for single and multiple variables. To demonstrate these new capabilities, the Cyclus/MOT was used to model several scenarios ranging from simple fleet retirements to transitions to advanced reactors. Specifically, for a transition scenario from LWRs to SFRs and advanced LWRs, uncertainty quantification, sensitivity analysis, and optimization studies were applied to cases involving single and multiple parameter (input) and single and multiple metric (output) variations. In addition, a similar transition scenario was modeled to demonstrate how to optimize the reprocessing capacity parameter to minimize two performance metrics while taking into account uncertainties from two other parameters. Lastly, a depletion module based on SCALE/ORIGEN was added in Cyclus to simulate the third scenario that was designed to quantify the impact of the modeling assumption that all LWR used nuclear fuel have the same burnup. The newly developed DYMOND/Dakota capability was also applied to a transition scenario from the existing fleet to small modular reactors and fast reactors. This particular scenario involves not only explicit isotopic depletion via ORIGEN-2, but also includes multirecycling and utilizing the criticality search feature to determine the fresh fuel composition of recycled fuel, a feature unique to the DYMOND NFCS. A large database of simulations were run with 4 main parameters that were sampled: start date of reprocessing, reprocessing capacity, energy demand growth rate, and advanced reactor share of the fleet. The 4 main metrics were uranium consumption, enrichment requirements, waste generation, and levelized cost of electricity using data from the Cost Basis Report. The demonstrated SA&UQ results include those that inform on how to choose parameters to avoid “failed” scenarios, Sobol’ indices that inform on the importance of various parameters individually and synergistically, and Analysis of Variance (ANOVA) studies that decompose parameter ranges into groups and informs on whether variations are statistically significant.

Feng, B.↗