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All sourcesNASA NTRSDOE OSTI
NASA NTRS1984

Satellite tracking and Earth dynamics research programs

Following an upgrading program, ranging performance capabilities of a satellite-tracking pulsed laser system were assessed in terms of range accuracy, range noise, data yield, and reliability. With a shorter laser pulse duration (2.5 to 3.0 NSEC) and a new analog pulse processing system, the systematic range errors were reduced to 3 to 5 cm and range noise was reduced to 5 to 16 cm and range noise was reduced to 5 to 15 cm on Starlette and BE-C, and 10 to 18 cm on LAGEOS. Maximum pulse repetition rate was increased to 30 pulses per minute and significant improvement was made in signal to noise ratio by installing a 3 A interference filter and by reducing the range gate window to 200 to 400 nsec. The solution to a problem involving leakage of a fraction of the laser oscillator pulse through the pulse chopper was outlined.

Pearlman, M. R.↗
NASA NTRS2012

Integrated Analysis of Interferometric SAR, Satellite Altimetry and Hydraulic Modeling to Quantify Louisiana Wetland Dynamics

Wetland loss in Louisiana has been accelerating due primarily to anthropogenic and nature processes, and is being advocated as a problem with national importance. Accurate measurement or modeling of wetland-wide water level changes, its varying extent, its storage and discharge changes resulting in part from sediment loads, erosion and subsidence are fundamental to assessment of hurricane-induced flood hazards and wetland ecology. Here, we use innovative method to integrate interferometric SAR (InSAR) and satellite radar altimetry for measuring absolute or geocentric water level changes and applied the methodology to remote areas of swamp forest in coastal Louisiana. Coherence analysis of InSAR pairs suggested that the HH polarization is preferred for this type of observation, and polarimetric analysis can help to identi:fy double-bonnce backscattering areas in the wetland. Envisat radar altimeter-measured 18- Hz (along-track sampling of 417 m) water level data processed with regional stackfile method have been used to provide vertical references for water bodies separated by levees. The high-resolution (approx.40 m) relative water changes measured from ALOS PALSAR L-band and Radarsat-l C-band InSAR are then integrated with Envisat radar altimetry to obtain absolute water level. The resulting water level time series were validated with in situ gauge observations within the swamp forest. Furthermore, we compare our water elevation changes with 2D flood modeling from LISFLOOD hydrodynamic model. Our study demonstrates that this new technique allows retrospective reconstruction and concurrent monitoring of water conditions and flow dynamics in wetlands, especially those lacking gauge networks.

Lee, Hyongki↗
DOE OSTI2025

Advancing the Frontiers of Deep Learning for Low-Dose 3D Cone-Beam CT Reconstruction

X-ray computed tomography (CT) is an important noninvasive medical imaging modality for studying the structural details of internal organs. Image reconstruction in CT is an inverse problem of recovering an object's internal structure from the absorption profile of X-ray beams (sinogram) measured using a detector. The classical variational approach for CT reconstruction minimizes an energy functional using an appropriate iterative algorithm. Motivated by the success of deep learning (DL), researchers have begun to leverage training data and enhanced computing capabilities in recent years to produce high-fidelity reconstructed images. Nonetheless, much of the academic research in DL algorithms for CT has focused primarily on the two-dimensional setting (with simplified forward operators and noise model) for proofs-of-concept, and a comprehensive benchmarking of various classical and data-driven CT reconstruction approaches has not beenundertaken. The key objective of our CT reconstruction grand challenge was to promote methodological advancements for both classical and DL-based approaches for clinical CT with a reasonably accurately simulated 3D CT forward operator and noise model. We have utilized the publicly available LIDC-IDRI dataset and simulated sinograms and FDK images corresponding to two dose levels (clinical- and low-dose, constituting two tracks of the challenge) starting from the normal-dose images as the ground truth. In this paper, we summarize the motivation, context, and results of our challenge, and highlight the future research directions in DL for clinical CT.

X-ray tomography↗
DOE OSTI2024

The Uranium-Containing and Thorium-Containing Anions Studied by Photoelectron Spectroscopy

An in-depth knowledge of actinide chemistry is fundamental to many aspects of nuclear science and technology, including the synthesis and processing of materials and the remediation of waste disposal sites. Among the actinides, the chemical bonding behaviors of actinium and thorium resemble those of the transition metals; the 5f-electrons of protactinium, uranium, neptunium, and plutonium often play important roles in their bonding; and among the still heavier elements, their bonding tends to mimic the lanthanide elements in terms of electron shielding and their f-electron contributions. Bonding that involves 5f-electrons, however, is especially important, in part because of the significance of uranium and plutonium, but also because these elements are among the few where f-electron participation in bonding is relatively common. This work focused on studying uranium-containing and thorium-containing anions in the gas phase using negative ion photoelectron spectroscopy. Since this technique directly probed valence electrons, it was uniquely positioned to address open questions regarding molecular bonding and electron configurations. A particularly important issue concerned how bonding in actinide-containing molecules was affected by modifications to their actinide atoms’ environment, i.e., due to their interaction with ligands. A closely related question was how actinide atoms’ suborbitals were qualitatively reordered and their energies quantitatively shifted as a result of their ligated environments. These were especially relevant issues in regard to uranium due to it having multiple possible oxidation states (OS) and the potential for 5f electron participation in bonding. The effects of ligands on oxidation states and 5f-orbital energies in uranium bonding was expected to be pronounced. Both ligands and excess electrons were seen as probes of actinide atoms within actinide-containing molecules. Our strategy for advancing knowledge of chemical bonding in the actinide-containing species utilized the synergy between experiments and theory, where in some cases experimental results validated theory and where in others computational results assisted in interpreting experiments. Calculations on actinide systems are terrifically challenging due to large spin-orbit interactions, relativistic effects, and just the sheer number of electrons involved. Even in the simplest species, e.g., U and U2, the most sophisticated, modern calculations carried out by the most experienced theorists often only approximate experimentally-measured values, such as electron affinities. For theory to provide confident predictions that can be used to solve real problems it needed an iterative and ultimately corrective mechanism by which its methods can develop further. Experiments can be used to identify when theory has failed; whereupon the subsequent process of using the experiment-theory interplay can be used to find the cause of the failure. Upon fixing it in one case, different test species can be proposed and studied by the experiment-theory combination to determine whether the problem has been corrected. Thus, experiments not only measure the values of molecular properties, they also provide navigational 3 beacons that keep computations off the reefs in an otherwise dark sea with few reference points. Experimental measurements in the actinide field are not only important, they are in actuality essential to computational progress. While it was not always possible to compare the theoreticallydetermined quantity of interest directly with the same experimentally-measured observable, it was usually possible to compare consequential properties that are both calculable and measurable. In the work completed here electron affinities and electronic state spacings were often sensitive consequential parameters. Reasonable agreement between measured and computational values signaled that a calculation that was very likely to be on-track. We had established collaborative relationships with five computational groups, all of which have expertise in computational actinide chemistry. Their PI’s are L. Cheng, D. Dixon, L. Gagliardi, K. Peterson, and B. Vlaisavljevich. Our close interaction with our theory partners led to us suggesting systems to them and them to us. This reciprocal interaction between our experimental and their computational results was among the most important strengths of this work and was a thread woven throughout. Even though anion photoelectron spectroscopic studies are conducted on anions, much of the information that they provide, pertains to the electronic structure of the neutral counterparts of those anions; among these are electron affinities and electronically excited state spacings. Our experimental tools included several specialized ion sources for forming the anionic species of interest, a mass spectrometer for identifying and mass-selecting them, and an anion photoelectron spectrometer for determining their electron affinities (EA) and characterizing the electronic states of the selected anions’ neutral counterparts. Anion photoelectron spectroscopy is conducted by crossing a mass-selected beam of anions with a fixed-frequency laser beam and energy-analyzing the resultant photodetached electrons. The photodetachment process is governed by the energyconserving relationship: hν = EBE + EKE, where hν is the photon’s energy, EBE is the electron binding (photodetachment transition) energy, and EKE is the electron’s kinetic energy. In our apparatus mass-selection is accomplished via time-of-flight mass spectrometry (TOF-MS), electron energy analysis is achieved with either a magnetic bottle or by velocity mapped imaging. Photodetachment of electrons from anions is implemented via either Nd:YAG or excimer lasers. The photodetachment transition energy, i.e., the EBE, between the ground vibrational and electronic state of an anion and the ground vibrational and electronic state of that anion’s neutral counterpart is the adiabatic electron affinity (EA) of that neutral molecule. Likewise, photodetachment transitions between the ground vibrational and electronic state of an anion and the various electronically-excited states of that anion’s corresponding neutral map the electronic spectrum of that neutral species, i.e., the spectral spacings in the photoelectron spectrum are a mirror image of the neutral’s electronic spectrum. It was, of course, crucial to be able to form the anionic species of interest. There, we had a particularly broad field of anion sources from which to choose. These included several variants of pulsed laser vaporization (LV), laser photoemission, infrared desorption plus photoemission, pulsed arc discharge (PACIS), electrospray ionization (ESI), and Rydberg electron transfer (RET). Each of these anion sources were readily combined with, i.e., connected to, the anion photoelectron spectroscopic portion of our apparatus as described above. Among the sources that utilize lasers, visible light for LV sources as well as IR for desorption sources are provided by Nd:YAG lasers. Ultraviolet photons are provided by both Nd:YAG and excimer lasers, whereas the excitation wavelengths for RET experiments come from two Nd:YAG-pumped dye lasers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1988

Flood basalts and mass extinctions

There appears to be a correlation between the times of flood basalts and mass-extinction events. There is a correlation of flood basalts and hotspot tracks--flood basalts appear to mark the beginning of a new hotspot. Perhaps there is an initial instability in the mantle that bursts forth as a flood basalt but then becomes a steady trickle that persists for many tens of millions of years. Suppose that flood basalts and not impacts cause the environmental changes that lead to mass-extinctions. This is a very testable hypothesis: it predicts that the ages of the flows should agree exactly with the times of extinctions. The Deccan and K-T ages agree with this hypothesis; An iridium anomaly at extinction boundaries apparently can be explained by a scaled-up eruption of the Hawaiian type; the occurrence of shocked-quartz is more of a problem. However if the flood basalts are all well dated and their ages indeed agree with extinction times, then surely some mechanism to appropriately produce shocked-quartz will be found.

Morgan, W. Jason↗
NASA NTRS1992

Differenced Doppler tracking in interplanetary navigation - The Magellan cruise reconstruction

The Magellan mission was the first in which Doppler and differenced Doppler tracking data were acquired at X-band uplink/downlink frequencies from the Deep Space Network (DSN). This paper describes a reconstruction of the Venus approach-phase navigation investigating the capabilities of these data types, which are up to an order of magnitude more precise than similar data acquired at S-band frequencies in previous missions. Comparisons of orbit solutions obtained with Doppler, Doppler plus differenced Doppler, and Doppler plus delta-differential one-way Range (DeltaDOR) data indicate that both differenced Doppler and DeltaDOR yield improvements of factors of 3 to 5 over the accuracy of the Doppler-only solutions obtained during Venus approach operations, in which the Doppler data were deweighted from their inherent accuracy due to mismodeling problems.

Ryne, Mark S.↗
DOE OSTI2023

Tracing the Rain Formation Pathways in Numerical Simulations of Deep Convection

Quantifying the microphysical process contributions to surface precipitation in numerical simulations can be challenging. This is due to the fact that many microphysical processes contribute to the formation and depletion of rain drops and there is almost always a spatial/temporal mismatch between where/when rain is formed and where/when it strikes the surface. In this work, we develop a tracing method that tracks the sources and sinks of raindrop mass and number as they are advected by the Weather Research and Forecasting model. Applying the method to an idealized squall line confirms that convective precipitation is dominated by warm rain processes (autoconversion and accretion) while stratiform precipitation is dominated by the melting of rimed and unrimed ice crystals. Sensitivity experiments in which the prescribed cloud drop number concentration is increased confirm the conventional wisdom that weakened autoconversion increases the fraction of raindrops originating from cold rain processes. The method also reveals that when applied to deep convection the Khairoutdinov and Kogan autoconversion scheme produces an excessive number of raindrops which are subsequently clipped in P3 microphysics to keep the rain size distribution within prescribed limits. This problem can mostly be mitigated by increasing the assumed radius for raindrops created by autoconversion.

58 GEOSCIENCES↗
DOE OSTI2021

MOOSE Framework Meshing Enhancements to Support Reactor Analysis

MOOSE-based physics codes require an input finite element mesh on which the physics solution is calculated, reported, and transferred to other physics codes. The use of difficult-touse, external licensed software is often required to generate high quality meshes for reactor geometries. High-fidelity geometry modeling also requires elaborate tracking of groups of elements for material property assignment and output reporting which can be considerably complex for the user to identify and maintain. Under the U.S. Department of Energy Office of Nuclear Energy Advanced Modeling and Simulation (NEAMS) program, several meshingrelated enhancements have been developed for the MOOSE framework to address user challenges in creating finite element meshes for advanced reactor geometries. MOOSE mesh generators have been developed to mesh hexagonal geometries (pins, ducted assemblies, and cores) commonly found in liquid-metal cooled fast reactor concepts. The mesh generator used for hexagonal pin cells is generic for regular polygons and therefore may also be used for Cartesian pin cells. Hexagonal pin cells can be stitched into ducted assemblies, and assemblies can be stitched together into a core. The user may specify region ids, region names, and other preferences on the mesh. This control is useful for later material mapping in the MOOSE-based physics codes input. A capability was also developed for meshing rotating control drums including determination of material volume fractions in each mesh element as a function of time. Control drum meshes may be stitched to other hexagonal assemblies to create a core configuration. Additional mesh generators were developed that wrap around the hexagonal meshing capabilities and utilize “extra element integer” ID values on each element. In regular Cartesian or hexagonal assemblies or cores, the bookkeeping of element groups for both material assignment and output reporting can now be automated through assignment of pin, assembly, core, axial and depletion id values stored as extra element integers. The extra element tags on the mesh greatly speed the reactor analyst’s efforts to map materials to meshes, track depletion zones, and parse output such as axial pin power distributions. At the highest level, pin, assembly, and core mesh generators (with this reactor terminology) have also been developed to easily generate regular Cartesian and hexagonal cores, including axial extrusion. These reactor geometry builders call upon the previously mentioned capabilities to produce analysis-ready 3D meshes including material assignments. Open source mesh triangulation capabilities were also investigated for integration into the MOOSE framework to address the need for meshing the core periphery region which extends from the irregular outer assembly border to a cylindrical boundary. Options are limited due to licensing constraints, and the recommendation is pursue building a native MOOSE Delaunay triangulator routine with full functionality. Finally, a series of verification problems were performed with NEAMS physics tools. All developed capabilities will be available in the new open-source “Reactor” module of the MOOSE framework, which is accessible to any MOOSE-based NEAMS physics tool.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Updated SAM Model for the Molten Salt Reactor Experiment (MSRE)

The development of reference standard problems based on prototypical reactor designs is of particular importance to verify the adequacy of computer codes and evaluation models for specific reactor types. To support the multiphysics coupled simulation of molten-salt-fueled reactor (MSR) using SAM and Griffin computer codes for safety and licensing analysis, much efforts have been put into enhancing code capabilities and developing reference models for the MSR primary loop in SAM. In this work, a previously developed Molten Salt Reactor Experiment (MSRE) primary loop model was updated to include a two-dimensional (2-D) core region and external core components in one-dimension (1-D) or zero-dimension (0-D). To ensure accurate feedback calculation in multi-physics simulations, the delayed neutron precursor tracking model and solid graphite model were added in the SAM model. In addition, the 2-D and 1-D domains are tightly coupled using the recently developed single-solve approach in SAM. The updated model has been tested under both steady-state and transient scenarios to demonstrate its potential for the multi-physics simulation of MSRE with coupled SAM and Griffin.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1990

Modeling reality

Although powerful computers have allowed complex physical and manmade hardware systems to be modeled successfully, we have encountered persistent problems with the reliability of computer models for systems involving human learning, human action, and human organizations. This is not a misfortune; unlike physical and manmade systems, human systems do not operate under a fixed set of laws. The rules governing the actions allowable in the system can be changed without warning at any moment, and can evolve over time. That the governing laws are inherently unpredictable raises serious questions about the reliability of models when applied to human situations. In these domains, computers are better used, not for prediction and planning, but for aiding humans. Examples are systems that help humans speculate about possible futures, offer advice about possible actions in a domain, systems that gather information from the networks, and systems that track and support work flows in organizations.

Denning, Peter J.↗
DOE OSTI2024

Quantifying microbial roles in environmental iron oxidation via an integrated kinetics, `omics and metabolic modeling study (Final Report)

Iron oxyhydroxides are extremely reactive components of environmental systems, and therefore exert a strong influence on biogeochemical cycles. These oxyhydroxides strongly adsorb many biologically-relevant elements, including organic carbon and phosphate, as well as a wide range of metals including uranium and actinide species. Thus, the formation mechanism of iron oxyhydroxides are key to understanding both nutrient and contaminant cycling. Microorganisms can catalyze iron oxidation and promote the formation of Fe biominerals and thus are increasingly recognized as important players in biogeochemical cycling. However, it is completely unknown how much of environmental iron oxidation is biologically mediated versus abiotic, and various challenges in studying microbial iron oxidation have hindered accurate incorporation into hydrobiogeochemical models. The overarching goal of our work was to quantify and constrain microbial iron oxidation rates and use ‘omics to gain insight into the controls on this process, while developing tools to enable integration of biotic iron oxidation into hydrobiogeochemical models. Our work focused on the Savannah River Site (SRS) in South Carolina, where extensive microbial iron oxidation has been observed. At Tims Branch, part of the Argonne National Laboratory Wetland Hydrobiogeochemistry Science Focus Area (Argonne SFA), where groundwater discharges into a stream, iron-oxidizing microbial mats form and appear to be a major sink of uranium. In the wetlands that surround Tims Branch, there are wide swaths of iron microbial mats and flocs (mobilized mat). We measured biotic and abiotic iron oxidation rates using mats and water sampled from these sites and found that iron oxidation is primarily carried out by chemolithotrophic microorganisms. The resulting rate constants can be incorporated into models. These mats were characterized by metagenomics and metatranscriptomics, which showed that aerobic chemolithotrophs were the dominant iron-oxidizing bacteria (FeOB), and these included Gallionellaceae and Leptothrix, and possibly Rhodoferax, which is known as an Fe-reducer but may also oxidize Fe(II). This demonstrated that diverse FeOB can coexist and suggests that there are a range of niches and therefore drivers of chemolithotrophic iron oxidation. Analysis of reconstructed genomes strongly suggests that a major factor in diversity is carbon source, as genomes contained varied pathways for autotrophy and heterotrophy. We performed an in-depth analysis of Leptothrix ochracea genomes, since this sheath-former is one of the primary mat builders, yet its physiology remained unresolved. A combination of genomics, transcriptomics, and metabolic modeling suggest that L. ochracea grows mixotrophically using a combination of Fe(II) and organics for energy and both inorganic and organic carbon to create biomass. This contrasts with the largely autotrophic Gallionellaceae (Gallionella, Sideroxydans, and Ferriphaselus) also present in the mats and flocs. Remarkably, multiple FeOB, both Leptothrix and Gallionellaceae, showed activity in response to Fe(II) in live mat incubations. We tracked the gene expression of individual MAGs to Fe(II) and found that various autotrophic and heterotrophic FeOB responded to Fe(II), increasing expression of both carbon fixation and organic utilization genes. The results of the integrated field, kinetics, and omics studies give detailed insight into 1) the taxa that oxidize Fe, and 2) how they connect Fe, C, and N cycles. Towards the goal of connecting omics data to hydrobiogeochemical models, we worked with the KBase team to create a template metabolic model for chemolithotrophic iron oxidation. We initially modeled the well-characterized isolate Gallionellaceae Sideroxydans lithotrophicus, and also applied the model to the mixotroph L. ochracea. In all, we have characterized diverse FeOB in a representative wetland system and solved key problems that enable better incorporation of iron-oxidizing microbes into hydrobiogeochemical models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Limiter-aware adaptive excitation control for hydropower generators with legacy voltage regulation systems

Hydropower units often rely on legacy excitation systems with fixed automatic voltage regulator (AVR) settings, but parameter drift, changing operating conditions, and evolving grid-service demands can degrade terminal-voltage regulation over time. This problem should be addressed because poor voltage regulation affects reactive-power support, system stability, and reliable plant operation, and replacing installed AVR and limiter logic is costly and disruptive in practice. To address this issue, this paper proposes a retrofit-friendly enhancement for hydropower generator excitation systems that combines adaptive tuning of the AVR middle lead–lag branch with a small proportional-integral correction for removing steady bias and slow drift. The adaptive laws are normalized, projection-bounded, and equipped with leakage, while adaptation is enabled only in the middle branch. Thus, the intent of the underexcitation and overexcitation limiters, as well as legacy current and rate limits, remains unchanged. Stability is analyzed under incremental performance assumptions, yielding boundedness and asymptotic tracking in the absence of saturation. The method is evaluated using real operational data from a utility-scale hydropower unit at Rocky Reach Dam, Unit C-8. Compared with the fixed AVR baseline, the proposed method reduces terminal-voltage mean squared error by about 70%, removes long periods of steady-state bias, and improves transient tracking while coexisting with limiter actions. These results show that substantial voltage-control improvement can be achieved on existing hydropower units with minimal integration effort and without replacing the installed AVR structure.

ESST5B model↗
NASA NTRS1989

A real-time guidance algorithm for aerospace plane optimal ascent to low earth orbit

Problems of onboard trajectory optimization and synthesis of suitable guidance laws for ascent to low Earth orbit of an air-breathing, single-stage-to-orbit vehicle are addressed. A multimode propulsion system is assumed which incorporates turbojet, ramjet, Scramjet, and rocket engines. An algorithm for generating fuel-optimal climb profiles is presented. This algorithm results from the application of the minimum principle to a low-order dynamic model that includes angle-of-attack effects and the normal component of thrust. Maximum dynamic pressure and maximum aerodynamic heating rate constraints are considered. Switching conditions are derived which, under appropriate assumptions, govern optimal transition from one propulsion mode to another. A nonlinear transformation technique is employed to derived a feedback controller for tracking the computed trajectory. Numerical results illustrate the nature of the resulting fuel-optimal climb paths.

Calise, A. J.↗
NASA NTRS1991

Optimal control study for the Space Station Solar Dynamic power module

The authors present the design of an optimal control system for the Space Station Freedom's Solar Dynamic Fine Pointing and Tracking (SDFPT) module. A very large state model of six rigid body modes and 272 flexible modes is used in conjunction with classical LQG optimal control to produce a full-order controller which satisfies the requirements. The results obtained are compared with those of a classically designed PID (proportional plus integral plus derivative) controller that was implemented for a six-rigid-body-mode forty-flexible-mode model. A major difficulty with designing LQG controllers for large models is solving the Riccati equation that arises from the optimal formulation. A Riccati solver based on a Pade approximation to the matrix sign function is used. A symmetric version of this algorithm is derived for the special class of Hamiltonion matrices, thereby yielding, for large problems, a nearly twofold speed increase over a previous algorithm.

Papadopoulos, P. M.↗
NASA NTRS2008

Venus Quadrangle Geological Mapping: Use of Geoscience Data Visualization Systems in Mapping and Training

We are currently investigating new technological developments in computer visualization and analysis in order to assess their importance and utility in planetary geological analysis and mapping [1,2]. Last year we reported on the range of technologies available and on our application of these to various problems in planetary mapping [3]. In this contribution we focus on the application of these techniques and tools to Venus geological mapping at the 1:5M quadrangle scale. In our current Venus mapping projects we have utilized and tested the various platforms to understand their capabilities and assess their usefulness in defining units, establishing stratigraphic relationships, mapping structures, reaching consensus on interpretations and producing map products. We are specifically assessing how computer visualization display qualities (e.g., level of immersion, stereoscopic vs. monoscopic viewing, field of view, large vs. small display size, etc.) influence performance on scientific analysis and geological mapping. We have been exploring four different environments: 1) conventional desktops (DT), 2) semi-immersive Fishtank VR (FT) (i.e., a conventional desktop with head-tracked stereo and 6DOF input), 3) tiled wall displays (TW), and 4) fully immersive virtual reality (IVR) (e.g., "Cave Automatic Virtual Environment," or Cave system). Formal studies demonstrate that fully immersive Cave environments are superior to desktop systems for many tasks [e.g., 4].

Head, James W.↗
NASA NTRS2012

Achievable Performance and Effective Interrogator Design for SAW RFID Sensor Tags

For many NASA missions, remote sensing is a critical application that supports activities such as environmental monitoring, planetary science, structural shape and health monitoring, non-destructive evaluation, etc. The utility of the remote sensing devices themselves is greatly increased if they are passive V that is, they do not require any on-board power supply such as batteries V and if they can be identified uniquely during the sensor interrogation process. Additional passive sensor characteristics that enable greater utilization in space applications are small size and weight, long read ranges with low interrogator power, ruggedness, and operability in extreme environments (vacuum, extreme high/low temperature, high radiation, etc.) In this paper, we consider one very promising passive sensor technology, called surface acoustic wave (SAW) radio-frequency identification (RFID), that satisfies all of these criteria. In general, RFID is a method of identifying items using radio waves to interrogate tags encoded with a unique identifier that are affixed to the items of interest. In the case of passive tags, only the interrogator, which transmits power to the tags in the form of radio-frequency electromagnetic radiation, requires access to a power supply. Passive RFID technologies are used today in many applications, including asset tracking and management, security and access control, and remote sensing. To date, most of the development and application in RFID technology has focused on either asset/inventory tracking and control or security and access control because these are the largest commercial application areas. Recently however, there has been growing interest in using passive RFID technology for remote sensing applications, and SAW devices are at the forefront of RFID sensing technology development. Although SAW RFID tags have great potential for use in numerous space-based remote sensing applications, the limited collision resolution capability of current generation tags limits the performance in a cluttered sensing environment. That is, as more SAW-based sensors are added to the environment, numerous tag responses are superimposed at the receiver and decoding all or even a subset of the telemetry becomes increasingly difficult. Background clutter generated by reflectors other than the sensors themselves is also a problem, as is multipath interference and signal distortion, but the limiting factor in many remote sensing applications can be expected to be tag mutual interference. This problem may be greatly mitigated by proper design of the SAW tag waveform, but that remains an open research problem, and in the meantime, several other related questions remain to be answered including: (1) What are the fundamental relationships between tag parameters such as bit-rate, time-bandwidth-product, SNR, and achievable collision resolution? (2) What are the differences in optimal or near-optimal interrogator designs between noise-limited environments and interference-limited environments? (3) What are the performance characteristics of different interrogator designs in term of parameters such as transmitter power level, range, and number of interfering tags? In this paper, we will present the results of a research effort aimed at providing at least partial answers to all of these questions.

Barton Richard J.↗
DOE OSTI2024

Preserving Tracer Correlations in Moment-Based Atmospheric Transport Models

A linear non-diffusive algorithm for advective transport is developed that greatly improves the detail at which aerosols and clouds can be represented in atmospheric models. Linear advection schemes preserve tracer correlations but the most basic linear scheme is rarely used by atmospheric modelers on account of its excessive numerical diffusion. Higher-order schemes are in widespread use, but these present new problems as nonlinear adjustments are required to avoid occurrences of negative concentrations, spurious oscillations, and other non-physical effects. Generally successful at reducing numerical diffusion during the advection of individual tracers, for example, particle number or mass, the higher-order schemes fail to preserve even the simplest of correlations between interrelated tracers. As a result, important attributes of aerosol and cloud populations including radial moments of particle size distributions, molecular precursors related through chemical equilibria, aerosol mixing state, and distribution of cloud phase are poorly represented. We introduce a new transport scheme, minVAR, that is both non-diffusive and preservative of tracer correlations, thereby combining the best features of the basic and higher-order schemes while enabling new features such as the tracking of sub-grid information at arbitrarily fine scales with high computational efficiency.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2022

Neurosymbolic Hybrid Approach to Driver Collision Warning

There are two main algorithmic approaches to autonomous driving systems: (1) An end-to-end system in which a single deep neural network learns to map sensory input directly into appropriate warning and driving responses. (2) A mediated hybrid recognition system in which a system is created by combining independent modules that detect each semantic feature. While some researchers believe that deep learning can solve any problem, others believe that a more engineered and symbolic approach is needed to cope with complex environments with less data. Deep learning alone has achieved state-of-the-art results in many areas, from complex gameplay to predicting protein structures. In particular, in image classification and recognition, deep learning models have achieved accuracies as high as humans. But sometimes it can be very difficult to debug if the deep learning model doesn't work. Deep learning models can be vulnerable and are very sensitive to changes in data distribution. Generalization can be problematic. It's usually hard to prove why it works or doesn't. Deep learning models can also be vulnerable to adversarial attacks. Here, we combine deep learning-based object recognition and tracking with an adaptive neurosymbolic network agent, called the Non-Axiomatic Reasoning System (NARS), that can adapt to its environment by building concepts based on perceptual sequences. We achieved an improved intersection-over-union (IOU) object recognition performance of 0.65 in the adaptive retraining model compared to IOU 0.31 in the COCO data pre-trained model. We improved the object detection limits using RADAR sensors in a simulated environment, and demonstrated the weaving car detection capability by combining deep learning-based object detection and tracking with a neurosymbolic model.

Wang, Pei↗