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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Design and Production for Maximum Structural Efficiency With Respect to Fiber Orientation With Increased Understanding of Hybrid Fiber Flow Behavior

Discontinuous fiber-reinforced thermoplastic composites have gained considerable attention in automotive, aerospace, and other industries, due to their high-rate of production combined with their ability to attain complex and intricate shapes. Among other high-rate thermoplastic manufacturing processes, injection-molding is one of the most common manufacturing methods due to fast production and high surface finishing of complex geometries. Fiber orientation in discontinuous fiber composites plays a pivotal role in determining the mechanical, electrical, and thermomechanical properties, underscoring the necessity to comprehend fiber orientation in injection molded parts. Among different fiber types, glass and carbon fibers are most common in the composite industries. The recent trend of hybrid composites comprising both glass fiber (GF) and carbon fiber (CF) is also gaining importance in the automotive industry. Hybrid fiber options allow designers to optimize the balance between glass and carbon fibers by leveraging the high durability and low cost of GF while the strength and lightweight properties of CF. Consequently, comparing the fiber oriented distribution (FOD) of injection molded composites containing GF, CF, and a hybrid of GF/CF is critical to investigating the local mechanical properties of intricate structures for high-end applications. In Phase I of this project, FOD in injection-molded panels with respect to distance from the gate was analyzed using X-ray computed tomography (X-CT) for GF, CF, and hybrid CF/GF (CGF) reinforced nylon 66. To understand the reason behind the FOD with different fiber types, computational fluid dynamics (CFD) and rheology were performed. Samples were extracted at three locations: near the gate, center, and opposite end. Thickness of the layers of typical skin-shell-core type FOD varies with fiber type and location. GF achieved flow direction alignment (in shell) earlier than viscous CF and CGF near the gate, whereas CF showed the highest flow-direction alignment at the center due to shear induced orientation. At the opposite end, GF experienced more backflow than others indicating faster mold filling owing to its lower viscosity. Hybrid CGF exhibited GF-dominated center and CF-dominated end region. The numerical model used to obtain FOD and rheological predictions for the CF and GF composites served to corroborate the trends observed in the experimental trials. The FOD responses across fiber types and location were reflected in their longitudinal and transverse properties. Only GF showed higher longitudinal modulus over transverse modulus near the gate attributed to rapid alignment, whereas CF and CGF exhibited opposite trend. However, fountain flow enhanced the longitudinal modulus over transverse modulus with the distance for all, particularly for CF. This study offers insights into mold filling behavior of different fibers which are critical in optimizing injection molding conditions for tailored final properties.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Exact-two-component block-localized wave function: A simple scheme for the automatic computation of relativistic ΔSCF

Block-localized wave function is a useful method for optimizing constrained determinants. In this article, we extend the generalized block-localized wave function technique to relativistic two-component framework. Optimization of excited state determinants for two-component wave functions presents a unique challenge because the excited state manifold is often quite dense with degenerate states. Furthermore, we test the degree to which certain symmetries result naturally from the ΔSCF optimization such as time reversal symmetry and symmetry with respect to the total angular momentum operator on a series of atomic systems. Variational optimizations may often break symmetry in order to lower the overall energy, just as unrestricted Hartree-Fock breaks spin symmetry. Overall, we demonstrate that time reversal symmetry is roughly maintained when using Hartree-Fock, but less so when using Kohn-Sham density functional theory. Additionally, maintaining total angular momentum symmetry appears to be system dependent and not guaranteed. Finally, we were able to trace the breaking of total angular momentum symmetry to the relaxation of core electrons.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Emergent magnetism and exchange bias effect in iron oxide nanocubes with tunable phase and size

Abstract We report a systematic investigation of the magnetic properties including the exchange bias (EB) effect in an iron oxide nanocube system with tunable phase and average size (10, 15, 24, 34, and 43 nm). X-ray diffraction and Raman spectroscopy reveal the presence of Fe 3 O 4 , FeO, and α -Fe 2 O 3 phases in the nanocubes, in which the volume fraction of each phase varies depending upon particle size. While the Fe 3 O 4 phase is dominant in all and tends to grow with increasing particle size, the FeO phase appears to coexist with the Fe 3 O 4 phase in 10, 15, and 24 nm nanocubes but disappears in 34 and 43 nm nanocubes. The nanocubes exposed to air resulted in an α -Fe 2 O 3 oxidized surface layer whose thickness scaled with particle size resulting in a shell made of α -Fe 2 O 3 phase and a core containing Fe 3 O 4 or a mixture of both Fe 3 O 4 and FeO phases. Magnetometry indicates that the nanocubes undergo Morin (of the α -Fe 2 O 3 phase) and Verwey (of the Fe 3 O 4 phase) transitions at ∼250 K and ∼120 K, respectively. For smaller nanocubes (10, 15, and 24 nm), the EB effect is observed below 200 K, of which the 15 nm nanocubes showed the most prominent EB with optimal antiferromagnetic (AFM) FeO phase. No EB is reported for larger nanocubes (34 and 43 nm). The observed EB effect is ascribed to the strong interfacial coupling between the ferrimagnetic (FiM) Fe 3 O 4 phase and AFM FeO phase, while its absence is related to the disappearance of the FeO phase. The Fe 3 O 4 / α -Fe 2 O 3 (FiM/AFM) interfaces are found to have negligible influence on the EB. Our findings shed light on the complexity of the EB effect in mixed-phase iron oxide nanosystems and pave the way to design exchange-coupled nanomaterials with desirable magnetic properties for biomedical and spintronic applications.

Physics↗
DOE OSTI2025

MicroFisher: Fungal taxonomic classification for metatranscriptomic and metagenomic data using multiple short hypervariable markers

AbstractProfiling the taxonomic and functional composition of microbes using metagenomic (MG) and metatranscriptomic (MT) sequencing is advancing our understanding of microbial functions. However, the sensitivity and accuracy of microbial classification using genome– or core protein-based approaches, especially the classification of eukaryotic organisms, is limited by the availability of genomes and the resolution of sequence databases. To address this, we propose the MicroFisher, a novel approach that applies multiple hypervariable marker genes to profile fungal communities from MGs and MTs. This approach utilizes the hypervariable regions of ITS and large subunit (LSU) rRNA genes for fungal identification with high sensitivity and resolution. Simultaneously, we propose a computational pipeline (MicroFisher) to optimize and integrate the results from classifications using multiple hypervariable markers. To test the performance of our method, we applied MicroFisher to the synthetic community profiling and found high performance in fungal prediction and abundance estimation. In addition, we also used MGs from forest soil and MTs of root eukaryotic microbes to test our method and the results showed that MicroFisher provided more accurate profiling of environmental microbiomes compared to other classification tools. Overall, MicroFisher serves as a novel pipeline for classification of fungal communities from MGs and MTs.

Wang, Haihua↗
DOE OSTI2018

Predictively Coordinated Vehicle Acceleration and Lane Selection Using Mixed Integer Programming

Autonomous vehicle technology provides the means to optimize motion planning beyond human capacity. In particular, the problem of navigating multi-lane traffic optimally for trip time, energy efficiency, and collision avoidance presents challenges beyond those of single-lane roadways. For example, the host vehicle must simultaneously track multiple obstacles, the drivable region is non-convex, and automated vehicles must obey social expectations. Furthermore, reactive decision-making may result in becoming stuck in an undesirable traffic position. This paper presents a fundamental approach to these problems using model predictive control with a mixed integer quadratic program at its core. Lateral and longitudinal movements are coordinated to avoid collisions, track a velocity and lane, and minimize acceleration. Vehicle-to-vehicle connectivity provides a preview of surrounding vehicles’ motion. Simulation results show a 79% reduction in congestion-induced travel time and an 80% decrease in congestion-induced fuel consumption compared to a rule-based approach.

Dollar, Robert Austin↗
DOE OSTI2022

System and method for reasoning about the optimality of a configuration parameter of a distributed system

Embodiments provide a system and method for reasoning about the optimality of a configuration parameter of a distributed system. During operation, the system obtains a multi-layer graph for a system with a plurality of components, wherein the multi-layer graph comprises a configuration subgraph, a vulnerability subgraph, and a dependency subgraph. The system determines, based on the multi-layer graph, constraint relationships associated with configuration parameters for the components, wherein the constraint relationships include security constraints and functionality constraints. The system computes an unsatisfiable core which comprises a set of mutually incompatible constraints. The system resolves, based on a strategy and over multiple iterations, the unsatisfiable core by analyzing one pair of mutually incompatible constraints per a respective iteration, to obtain a new unsatisfiable core which comprises a smaller number of mutually incompatible constraints than the computed unsatisfiable core or a previously computed unsatisfiable core from a most recent iteration.

Soroush, Hamed↗
DOE OSTI2016

Adaptive Sparse-Grid Stochastic Collocation Uncertainty Quantification Convergence for Multigroup Diffusion

Advanced methods in uncertainty quantification for numerical models in computational physics continue to gain acceptance in nuclear modeling. Previously, the efficiency of sparse-grid stochastic collocation in comparison with Monte Carlo for uncertainty quantification through convergence studies was demonstrated. An adaptive method for anisotropic sparse grid collocation and its convergence compared to previous efforts is considered. The physical system in consideration is a two-dimensional quarter-core reactor, consisting of 5 materials distributed in 121 regions. The two-group neutron diffusion criticality approximation is solved. Vacuum boundaries are applied on the top and right, and reflecting boundaries on the bottom and left. The material cross sections, neutron multiplication factors, and diffusion coefficients are potential sources of uncertainty. Uniformly-distributed uncertainty within 5% of the reference values is introduced for material properties. The distribution of the uncertain parameters make up the uncertainty space Γ included in R{sup N}, where N is the number of uncertain parameters. The input parameter uncertainties are independently distributed. As expected, the convergence of Monte Carlo on the benchmark as a function of computational solves is nearly linear and lethargic compared to the other methods. The static isotropic index set, in which each input dimension is treated with equal importance, converges much more efficiently than Monte Carlo, but lacks the benefit of emphasizing some dimensions over others. The anisotropic case is most efficient, where first-order sensitivity information was used to determine anisotropic weights for polynomials to use in the polynomial chaos expansion. Interestingly, the adaptive algorithm converges slightly less efficiently than the anisotropic case, while still performing better than the isotropic case. Because the adaptive case has to determine the importance of each input dimension, it occasionally predicts inaccurately and wastes computation solves compared to the more ideal anisotropic case. However, in circumstances when an ideal anisotropy is not understood a priori, the adaptive algorithm may be optimally efficient in representing the original model. Given the potential loss of efficiency when using a poorly-chosen anisotropic weighting, the adaptive algorithm may be an effective choice for initial uncertainty quantification in problems with a low-dimensionality input space. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Safety Analysis for Accident-Tolerant Fuels with Increased Enrichment and Extended Burnup

The ERP research and development efforts in FY22 focused on the safety analysis of ATF with increased enrichment and extended burnup to provide scientific knowledge of the ATF fuel performance, failure mechanism and source term analysis during severe accident of the NPP. FeCrAl clad ATF was selected as basis of the reactor fuel. An optimized equilibrium cycle was developed for 24-months extended burnup operation. A 4-loop PWR model under loss-of-coolant accident (LOCA) was assessed and the behavior of the major source term from failed ATF has been analyzed. The result showed that grace to enhanced mechanical characteristics of ATF, the fuel failure starts up to 200~500 seconds later than conventional Zr clad fuel. This time gives sufficient buffer until low pressure safety injection (LPSI) of the emergency core cooling system (ECCS) restarted by the operator which reduces fuel fragmentation, relocation and dispersal (FFRD). As a consequence, the total amount of major radioactive materials released from FeCrAl clad fuel into the reactor containment was found up to three times less compare to Zr clad fuel.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Large Language Model for Validation, Optical Calibration, and Learning (VOCAL) Distributed Temperature Sensing Interface

Distributed temperature sensing (DTS) using fiber optic sensors (FOS) offers a promising method for temperature measurements in advanced reactors, such as sodium fast reactors and molten salt cooled reactors. To support the calibration and validation of DTS measurements, Argonne National Laboratory developed the Validation, Optical Calibration, and Learning (VOCAL) software package. This report describes the integration of a local large language model (LLM) with a retrieval-augmented generation (RAG) system into the VOCAL interface to serve as an interactive user assistant. The LLM framework enhances the VOCAL platform’s accessibility to users by explaining interface components, clarifying inputs and outputs, and answering user queries dynamically in real-time. The accuracy of the LLM assistant performance was evaluated with 20 queries regarding the interface and its parameters using experimental data from the Thermal Hydraulic Experimental Test Article (THETA) facility. Results demonstrate that the LLM achieved a 95% accuracy rate, with a BERTScore of 0.8816 and SBERT value of 0.7417. Furthermore, validation of the RAG system within the LLM framework showed optimal accuracy with k-values between 1 and 2 using the k-refinement convergence test. The prompt perturbation analysis demonstrated good initial consistency for the RAG system, exhibiting the highest accuracy under punctuation variations and the greatest sensitivity under query reordering. Notably, the model’s errors were limited to data retrieval failures rather than factual hallucinations, reinforcing its baseline reliability. The integration of LLM provides a highly accurate, userfriendly enhancement to the VOCAL platform without disrupting its core computational capabilities for FOS calibration and validation.

Hong, Evan↗
NASA NTRS2007

NASA Tech Briefs, December 2007

Topics include: Ka-Band TWT High-Efficiency Power Combiner for High-Rate Data Transmission; Reusable, Extensible High-Level Data-Distribution Concept; Processing Satellite Imagery To Detect Waste Tire Piles; Monitoring by Use of Clusters of Sensor-Data Vectors; Circuit and Method for Communication Over DC Power Line; Switched Band-Pass Filters for Adaptive Transceivers; Noncoherent DTTLs for Symbol Synchronization; High-Voltage Power Supply With Fast Rise and Fall Times; Waveguide Calibrator for Multi-Element Probe Calibration; Four-Way Ka-Band Power Combiner; Loss-of-Control-Inhibitor Systems for Aircraft; Improved Underwater Excitation-Emission Matrix Fluorometer; Metrology Camera System Using Two-Color Interferometry; Design and Fabrication of High-Efficiency CMOS/CCD Imagers; Foam Core Shielding for Spacecraft CHEM-Based Self-Deploying Planetary Storage Tanks Sequestration of Single-Walled Carbon Nanotubes in a Polymer PPC750 Performance Monitor Application-Program-Installer Builder Using Visual Odometry to Estimate Position and Attitude Design and Data Management System Simple, Script-Based Science Processing Archive Automated Rocket Propulsion Test Management Online Remote Sensing Interface Fusing Image Data for Calculating Position of an Object Implementation of a Point Algorithm for Real-Time Convex Optimization Handling Input and Output for COAMPS Modeling and Grid Generation of Iced Airfoils Automated Identification of Nucleotide Sequences Balloon Design Software Rocket Science 101 Interactive Educational Program Creep Forming of Carbon-Reinforced Ceramic-Matrix Composites Dog-Bone Horns for Piezoelectric Ultrasonic/Sonic Actuators Benchtop Detection of Proteins Recombinant Collagenlike Proteins Remote Sensing of Parasitic Nematodes in Plants Direct Coupling From WGM Resonator Disks to Photodetectors Using Digital Radiography To Image Liquid Nitrogen in Voids Multiple-Parameter, Low-False-Alarm Fire-Detection Systems Mosaic-Detector-Based Fluorescence Spectral Imager Plasmoid Thruster for High Specific-Impulse Propulsion Analysis Method for Quantifying Vehicle Design Goals Improved Tracking of Targets by Cameras on a Mars Rover Sample Caching Subsystem Multistage Passive Cooler for Spaceborne Instruments GVIPS Models and Software Stowable Energy-Absorbing Rocker-Bogie Suspensions

Source record↗
NASA NTRS2013

Auto-Gopher: A Wireline Deep Sampler Driven by Piezoelectric Percussive Actuator and EM Rotary Motor

The ability to penetrate subsurfaces and perform sample acquisition at depth of meters may be critical for future NASA in-situ exploration missions to bodies in the solar system, including Mars and Europa. A corer/sampler was developed with the goal of enabling acquisition of samples from depths of several meters where if used on Mars would be beyond the oxidized and sterilized zone. For this purpose, we developed a rotary-hammering coring drill, called Auto-Gopher, which employs a piezoelectric actuated percussive mechanism for breaking formations and an electric motor that rotates the bit to remove the powdered cuttings. This sampler is a wireline mechanism that can be fed into and retrieved from the drilled hole using a winch and a cable. It includes an inchworm anchoring mechanism allowing the drill advancement and weight on bit control without twisting the reeling and power cables. The penetration rate is being optimized by simultaneously activating the percussive and rotary motions of the Auto-Gopher. The percussive mechanism is based on the Ultrasonic/Sonic Drill/Corer (USDC) mechanism that is driven by piezoelectric stack and that was demonstrated to require low axial preload. The design and fabrication of this device were presented in previous publications. This paper presents the results of laboratory and field tests and lessons learned from this development.

piezoactuation↗
NASA NTRS2019

Atmospheric Mining in the Outer Solar System: Outer Planet Resource Processing, Moon Base Propulsion,and Vehicle Design Issues

Atmospheric mining in the outer solar system has been investigated as a means of fuel production for high energy propulsion and power. Fusion fuels such as Helium 3 (3He) and deuterium can be wrested from the atmospheres of Uranus and Neptune and either returned to Earth or used in-situ for energy production. Helium 3 and deuterium were the primary gases of interest with hydrogen being the primary propellant for nuclear thermal solid core and gas core rocket-based atmospheric flight. A series of analyses were undertaken to investigate resource capturing aspects of atmospheric mining in the outer solar system. This included the gas capturing rate, storage options, and different methods of direct use of the captured gases. While capturing 3He, large amounts of hydrogen and 4He are produced. Analyses of orbital transfer vehicles (OTVs), landers, and in-situ resource utilization (ISRU) mining factories are included. Preliminary observations are presented on near-optimal selections of moon base orbital locations, OTV power levels, and OTV and lander rendezvous points. Based on earlier propulsion investigations, the analyses of round trip OTV flights from Uranus and Neptune to their major moons with a 10- Megawatt electric (MWe) OTV power level and a 200 metric ton (MT) lander payload were selected. The OTV power level was based on delivering a relatively short OTV trip time and minimization of the number of lander flights. Moon base sites at Uranus and Neptune and the OTV requirements to support them will also be addressed. These analyses will include all of the major moons of Uranus and Neptune. In addition, the total masses and mass delivery schedules needed for atmospheric mining are presented.

nuclear propulsion↗
DOE OSTI2019

Optimization of lithium-glass fibers with lithium depleted coating for neutron detection

Neutron-detecting scintillating glass uses 6 Li to capture thermal neutrons to produce an a and triton particle, which have $a$ range of 6 $µm$ and 36 $µm$, respectively. Captures on the surface of the glass can cause one of the particles to not deposit their energy in the glass causing the neutron to not be detected. This effect can be mitigated in lithium glass scintillators by coating lithium- glass fibers with lithium depleted scintillating glass. Thus, the scintillator’s efficiency will be increased. Results from this work show that a 20-60% increase in neutron efficiency depending on core size can be achieved with scintillating glass coatings.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Development and Optimization of a Purification Process to Recover 99 Mo from Low-enriched Uranium

Supported by the DOE-NNSA Office of Material Management & Minimization (M3), a number of domestic entities are pursuing non-highly enriched uranium (non-HEU) production of 99 Mo. As the production technologies of 99Mo pivot toward low-enriched uranium (LEU) or molybdenum targets, new reaction channels and accelerators are being evaluated. Superconducting electron linear accelerators (LINACs) with high-Z converter targets can generate bremsstrahlung photons and neutron fluxes that are capable of inducing photonuclear reactions and LEU fission. A particular advantage of a LINAC is that it does not rely on HEU-fueled reactor cores (which are currently slated for LEU conversion) and can operate on an almost continuous basis. Regarding the chemical purification of 99 Mo from irradiated uranium targets under acidic digestion, there exists a procedure known as Cintichem or modifications thereof with respect to LEU (LEU Modified Cintichem process, LMC). The process relies on a number of selective precipitation steps and column chromatography to purify Mo. It is important to note that LMC prescribes the addition of stable Mo to carry 99 Mo on alpha benzoin oxime, which reduces the specific activity of 99 Mo. This is especially important for processing 99 Mo batches with lower activities (~33 Ci of 99 Mo per batch).

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2025

Collective neutrino oscillations in three flavors on qubit and qutrit processors

Collective neutrino flavor oscillations are of primary importance in understanding the dynamic evolution of core-collapse supernovae and subsequent terrestrial detection, but also among the most challenging aspects of numerical simulations. This situation is complicated by the quantum many-body nature of the problem due to neutrino-neutrino interactions, which demands a quantum treatment. An additional complication is the presence of three flavors, which often is approximated by the electron flavor and a heavy lepton flavor. In this work, we provide both qubit and qutrit encodings for all three flavors, and develop optimized quantum circuits for the time evolution and analyze the Trotter error. We conclude our study with a hardware experiment of a system of two neutrinos with superconducting hardware: the IBM Torino device for qubits and Advanced Quantum Testbed device at the Lawrence Berkeley National Laboratory for qutrits. We find that error mitigation greatly helps in obtaining a signal consistent with simulations. Finally, while hardware results are comparable at this stage, we expect the qutrit setup to be more convenient for large-scale simulations since it does not suffer from probability leakage into nonphysical qubit space, unlike the qubit setup.

Neutrino oscillations↗
DOE OSTI2022

Mitigate: An Adaptive Network Data Anonymization Tool Using Condensation-Based Differential Privacy

Modern network devices collect a large amount of data that can be analyzed to identify bottlenecks, anomalies, cyber-attacks, etc. Therefore, there is often a need to analyze such collections of network data quite often by an external expert or by the research community. However, these collections of data contain sensitive, proprietary information. In order for the network data to be shared, it must first be anonymized. The overall objective of this project is to develop an innovative privacy management tool to anonymize network data and achieve sufficient privacy, acceptable data utility, and efficient data analysis at the same time. No existing anonymization methods can achieve all of these at the same time. The core of this technology is a differential private clustering algorithm that provides strong privacy protection, preserves data properties important for subsequent analysis, and allows the party receiving the anonymized data to conduct analysis directly on anonymized data without the need of decryption or any extra processing. The research carried out was to design, implement and verify a solution to this problem by completing the following tasks: 1) developing the core technology; 2) developing a context based method that automatically recommends fields that must be anonymized; 3) conducted experiments showing superior results using our approach compared to existing tools, and 4) developed an intuitive but basic user interface. The research that was conducted generated novel algorithmic techniques that utilize state-of-the-art methods such as condensation, differential privacy preservation, clustering, automated tuning based on contextual awareness, and recommendation techniques to specify columns to users for anonymization leading to optimal privacy that allows research analysis on the dataset. Experiments were conducted to evaluate the efficacy of these novel algorithmic techniques by performing analysis on original non-anonymized datasets, then conducting analysis on the same yet anonymized datasets and comparing the results of the analyses. Overall, the anonymized analysis results were within 1% of the original results, verifying that the generated technology not only guarantees a high level of privacy but also enables research analysis as if it were conducted on the original dataset. Potential applications of this technology include anonymization of any type of structured network datasets that contain sensitive identifiers, such as IP addresses, that can be used in multiple applications. For example, to create an AI or machine learning model for cyber security, e.g., to detect attacks, or for performance analysis, e.g., identify bottlenecks or predict performance. In addition, a market analysis that was conducted for potential applications of this technology identified a broader range of applications of our anonymization technology beyond the network sector that includes healthcare, banking, insurance, securities, finance (FISB), data brokering, cloud services, ad sales, and government.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2009

Data Analysis for the LISA Pathfinder Mission

The LTP (LISA Technology Package) is the core part of the Laser Interferometer Space Antenna (LISA) Pathfinder mission. The main goal of the mission is to study the sources of any disturbances that perturb the motion of the freely-falling test masses from their geodesic trajectories as well as 10 test various technologies needed for LISA. The LTP experiment is designed as a sequence of experimental runs in which the performance of the instrument is studied and characterized under different operating conditions. In order to best optimize subsequent experimental runs, each run must be promptly analysed to ensure that the following ones make best use of the available knowledge of the instrument ' In order to do this, all analyses must be designed and tested in advance of the mission and have sufficient built-in flexibility to account for unexpected results or behaviour. To support this activity, a robust and flexible data analysis software package is also required. This poster presents two of the main components that make up the data analysis effort: the data analysis software and the mock-data challenges used to validate analysis procedures and experiment designs.

Thorpe, James Ira↗
NASA NTRS2022

Multi-Frequency Radiometer-Based Soil Moisture Retrieval and Algorithm Parameterization Using In Situ Sites

L-band brightness temperature (TB) has been shown to provide the best sensitivity to soil moisture (SM) although C- and X-band based products offer a longer time-series from satellite-based measurements. Currently, global coverage SM is routinely produced from spaceborne measurements using all three frequency bands, but despite continued validation efforts of the products, the relative characteristics and performance of these observations have not been fully established. Therefore, this study focused on the parametrization of SM retrieval algorithms at L-, C- and X-bands using TB observations from the L-band radiometer on NASA's SM Active Passive (SMAP) mission and the C- and X-band channels of JAXA's Advanced Microwave Scanning Radiometer 2 (AMSR2) onboard the GCOM-W satellite. These can be applied in global SM retrieval algorithms using either one of the frequencies or a combination of them. The reference in situ SM data was obtained from 12 core validation sites across various land cover types around the world. The investigation highlighted the known challenges of retrieving SM from C- and X-band data compared to the higher sensitivity of the L-band data. Even with a site-specific retrieval algorithm parameterization, the mean correlation of the C- and X-band retrievals for the core validation site SM measurement were much lower than that for L-band, being 0.52 (0.54) and 0.45 (0.47) for vertical (horizontal) polarization, respectively, while for the L-band retrieval the corresponding values were 0.81 (0.77). The parameterization exercise showed that matching the C- and X-band TB measurements with an emission model was not difficult; the problem was relating the observations to SM under the influence of large roughness and vegetation effects. As a result, parameter optimization produced values for some sites that were not realistic or did not allow any practical sensitivity to SM at C- and X-band. Considering the L-band observations, the parameter optimization resulted in superior bias performance as compared to the operational SMAP product parameterization, but the sensitivity to SM changes (R and unbiased root mean square difference) did not improve markedly, or in some cases degraded at the expense of a smaller bias.

passive microwave↗