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DOE OSTI2021

Paclitaxel loading in cationic liposome vectors is enhanced by replacement of oleoyl with linoleoyl tails with distinct lipid shapes

Abstract Lipid carriers of hydrophobic paclitaxel (PTX) are used in clinical trials for cancer chemotherapy. Improving their loading capacity requires enhanced PTX solubilization. We compared the time-dependence of PTX membrane solubility as a function of PTX content in cationic liposomes (CLs) with lipid tails containing one (oleoyl; DOPC/DOTAP) or two (linoleoyl; DLinPC/newly synthesized DLinTAP) cis double bonds by using microscopy to generate kinetic phase diagrams. The DLin lipids displayed significantly increased PTX membrane solubility over DO lipids. Remarkably, 8 mol% PTX in DLinTAP/DLinPC CLs remained soluble for approximately as long as 3 mol% PTX (the solubility limit, which has been the focus of most previous studies and clinical trials) in DOTAP/DOPC CLs. The increase in solubility is likely caused by enhanced molecular affinity between lipid tails and PTX, rather than by the transition in membrane structure from bilayers to inverse cylindrical micelles observed with small-angle X-ray scattering. Importantly, the efficacy of PTX-loaded CLs against prostate cancer cells (their IC50 of PTX cytotoxicity) was unaffected by changing the lipid tails, and toxicity of the CL carrier was negligible. Moreover, efficacy was approximately doubled against melanoma cells for PTX-loaded DLinTAP/DLinPC over DOTAP/DOPC CLs. Our findings demonstrate the potential of chemical modifications of the lipid tails to increase the PTX membrane loading while maintaining (and in some cases even increasing) the efficacy of CLs. The increased PTX solubility will aid the development of liposomal PTX carriers that require significantly less lipid to deliver a given amount of PTX, reducing side effects and costs.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Climate change, malaria and neglected tropical diseases: a scoping review

Abstract To explore the effects of climate change on malaria and 20 neglected tropical diseases (NTDs), and potential effect amelioration through mitigation and adaptation, we searched for papers published from January 2010 to October 2023. We descriptively synthesised extracted data. We analysed numbers of papers meeting our inclusion criteria by country and national disease burden, healthcare access and quality index (HAQI), as well as by climate vulnerability score. From 42 693 retrieved records, 1543 full-text papers were assessed. Of 511 papers meeting the inclusion criteria, 185 studied malaria, 181 dengue and chikungunya and 53 leishmaniasis; other NTDs were relatively understudied. Mitigation was considered in 174 papers (34%) and adaption strategies in 24 (5%). Amplitude and direction of effects of climate change on malaria and NTDs are likely to vary by disease and location, be non-linear and evolve over time. Available analyses do not allow confident prediction of the overall global impact of climate change on these diseases. For dengue and chikungunya and the group of non-vector-borne NTDs, the literature privileged consideration of current low-burden countries with a high HAQI. No leishmaniasis papers considered outcomes in East Africa. Comprehensive, collaborative and standardised modelling efforts are needed to better understand how climate change will directly and indirectly affect malaria and NTDs.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1985

A fast, time-accurate unsteady full potential scheme

The unsteady form of the full potential equation is solved in conservation form by an implicit method based on approximate factorization. At each time level, internal Newton iterations are performed to achieve time accuracy and computational efficiency. A local time linearization procedure is introduced to provide a good initial guess for the Newton iteration. A novel flux-biasing technique is applied to generate proper forms of the artificial viscosity to treat hyperbolic regions with shocks and sonic lines present. The wake is properly modeled by accounting not only for jumps in phi, but also for jumps in higher derivatives of phi, obtained by imposing the density to be continuous across the wake. The far field is modeled using the Riemann invariants to simulate nonreflecting boundary conditions. The resulting unsteady method performs well which, even at low reduced frequency levels of 0.1 or less, requires fewer than 100 time steps per cycle at transonic Mach numbers. The code is fully vectorized for the CRAY-XMP and the VPS-32 computers.

Shankar, V.↗

NASA NTRS2001

MEMS-Based Satellite Micropropulsion Via Catalyzed Hydrogen Peroxide Decomposition

Micro-electromechanical systems (MEMS) techniques offer great potential in satisfying the mission requirements for the next generation of "micro-scale" satellites being designed by NASA and Department of Defense agencies. More commonly referred to as "nanosats", these miniature satellites feature masses in the range of 10-100 kg and therefore have unique propulsion requirements. The propulsion systems must be capable of providing extremely low levels of thrust and impulse while also satisfying stringent demands on size, mass, power consumption and cost. We begin with an overview of micropropulsion requirements and some current MEMS-based strategies being developed to meet these needs. The remainder of the article focuses the progress being made at NASA Goddard Space Flight Center towards the development of a prototype monopropellant MEMS thruster which uses the catalyzed chemical decomposition of high concentration hydrogen peroxide as a propulsion mechanism. The products of decomposition are delivered to a micro-scale converging/diverging supersonic nozzle which produces the thrust vector; the targeted thrust level approximately 500 N with a specific impulse of 140-180 seconds. Macro-scale hydrogen peroxide thrusters have been used for satellite propulsion for decades; however, the implementation of traditional thruster designs on a MEMS scale has uncovered new challenges in fabrication, materials compatibility, and combustion and hydrodynamic modeling. A summary of the achievements of the project to date is given, as is a discussion of remaining challenges and future prospects.

Hitt, Darren L.↗

NASA NTRS2018

A Common Probe Design for Multiple Planetary Destinations

Atmospheric probes have been successfully flown to planets and moons in the solar system to conduct in situ measurements. They include the Pioneer Venus multi-probes, the Galileo Jupiter probe, and Huygens probe. Probe mission concepts to five destinations, including Venus, Jupiter, Saturn, Uranus, and Neptune, have all utilized similar-shaped aeroshells and concept of operations, namely a 45-degree sphere cone shape with high density heatshield material and parachute system for extracting the descent vehicle from the aeroshell. Each concept designed its probe to meet specific mission requirements and to optimize mass, volume, and cost. At the 2017 International Planetary Probe Workshop (IPPW), NASA Headquarters postulated that a common aeroshell design could be used successfully for multiple destinations and missions. This "common probe" design could even be assembled with multiple copies, properly stored, and made available for future NASA missions, potentially realizing savings in cost and schedule and reducing the risk of losing technologies and skills difficult to sustain over decades. Thus the NASA Planetary Science Division funded a study to investigate whether a common probe design could meet most, if not all, mission needs to the five planetary destinations with extreme entry environments. The Common Probe study involved four NASA Centers and addressed these issues, including constraints and inefficiencies that occur in specifying a common design. Study methodology: First, a notional payload of instruments for each destination was defined based on priority measurements from the Planetary Science Decadal Survey. Steep and shallow entry flight path angles (EFPA) were defined for each planet based on qualification and operational g-load limits for current, state-of-the-art instruments. Interplanetary trajectories were then identified for a bounding range of EFPA. Next, 3-degrees-of-freedom simulations for entry trajectories were run using the entry state vectors from the interplanetary trajectories. Aeroheating correlations were used to generate stagnation point convective and radiative heat flux profiles for several aeroshell shapes and entry masses. High fidelity thermal response models for various Thermal Protection System (TPS) materials were used to size stagnation-point thicknesses, with margins based on previous studies. Backshell TPS masses were assumed based on scaled heat fluxes from the heatshield and also from previous mission concepts. Presentation: We will present an overview of the study scope, highlights of the trade studies and design driver analyses, and the final recommendations of a common probe design and assembly. We will also indicate limitations that the common probe design may have for the different destinations. Finally, recommended qualification approaches for missions will be presented.

Hwang, H. H.↗

DOE OSTI2023

Using machine learning to predict the correlation of spectra using SDSS magnitudes as an improvement to the Locus Algorithm

The Locus Algorithm is a new technique to improve the quality of differential photometry by optimising the choices of reference stars. At the heart of this algorithm is a routine to assess how good each potential reference star is by comparing its SDSS magnitude values to those of the target star. In this way, the difference in wavelength-dependent effects of the Earth’s atmospheric scattering between target and reference can be minimised. This paper sets out a new way to estimate the quality of each reference star using machine learning. A random subset of stars from SDSS with spectra was chosen. For each one, a suitable reference star, also with a spectrum, was chosen. The correlation between the two spectra in the SDSS r band (between 550 nm and 700 nm) was taken to be the gold-standard measure of how well they match up for differential photometry. The five SDSS magnitude values for each of these stars were used as predictors. A number of supervised machine learning models were constructed on a training set of the stars and were each evaluated on a testing set. The model using Support Vector Regression had the best performance of these models. It was then tested on a final, hold-out, validation set of stars to get an unbiased measure of its performance. With an R 2 of 0.62, the SVR model presents enhanced performance for the Locus Algorithm technique.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2021

Universal Monte Carlo Event Generator

With the Jefferson Lab 12 GeV physics program underway and plans for the future Electron-Ion Collider (EIC), the nuclear physics community is entering a new era of exploration of QCD phenomena involving extensive data taking and event-level processing. This brings with it the potential for unprecedented access to multidimensional particle momentum distributions (PMDs) that can be connected to various theoretical frameworks by unfolding the emergent quantum mechanical properties of QCD using the PMDs. In practice, the PMDs are rendered as discretized histograms (typically one- or two-dimensional projections), and detector effects must be taken into account to unfold the pure detector effect-free PMDs that can be connected with theory. One of the challenges in this new era is obtaining faithful reconstructions of the multidimensional PMDs that preserve all of the inherent particle correlations. In this LDRD project we developed a novel approach using machine learning (ML) that solves this challenge, by avoiding entirely the need to use histograms as the main numerical technique to obtain the detector effect-free PMDs. The new approach is, moreover, scalable to higher dimensional PMDs. The central idea involves training neural networks (NNs) to generate synthetic event-level data (momenta 4-vectors of final state particles) to preserve all correlations among the particles. This is achieved by converting the trial synthetic vertex-level events to detector-level events using detector simulators. The NNs are then tuned using a specialized distance metric between the synthetic detector events and the real detector events.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS2004

Automated Extraction of Flow Features

Computational Fluid Dynamics (CFD) simulations are routinely performed as part of the design process of most fluid handling devices. In order to efficiently and effectively use the results of a CFD simulation, visualization tools are often used. These tools are used in all stages of the CFD simulation including pre-processing, interim-processing, and post-processing, to interpret the results. Each of these stages requires visualization tools that allow one to examine the geometry of the device, as well as the partial or final results of the simulation. An engineer will typically generate a series of contour and vector plots to better understand the physics of how the fluid is interacting with the physical device. Of particular interest are detecting features such as shocks, recirculation zones, and vortices (which will highlight areas of stress and loss). As the demand for CFD analyses continues to increase the need for automated feature extraction capabilities has become vital. In the past, feature extraction and identification were interesting concepts, but not required in understanding the physics of a steady flow field. This is because the results of the more traditional tools like; iso-surface, cuts and streamlines, were more interactive and easily abstracted so they could be represented to the investigator. These tools worked and properly conveyed the collected information at the expense of a great deal of interaction. For unsteady flow-fields, the investigator does not have the luxury of spending time scanning only one "snapshot" of the simulation. Automated assistance is required in pointing out areas of potential interest contained within the flow. This must not require a heavy compute burden (the visualization should not significantly slow down the solution procedure for (co-processing environments). Methods must be developed to abstract the feature of interest and display it in a manner that physically makes sense.

Dorney, Suzanne↗

DOE OSTI2022

Pushing the Limits of Micro battery Capacity and Energy

Micro battery with higher energy density will extend the service life of the miniature sensors so that the scientists and engineers could be able to collect more data along with the time in ecological and environmental vectors, such as animal tracking. Within this project, a completely new cell design (Gen2) for micro batteries to further increase their cell capacity and energy is developed. The new cell design directly packages the active material in a hard aluminum case, decreasing the percentage of non-active components. The manufacturing process to improve wetting ability is studied and the trial run is finally given to evaluate the feasibility of the proposed technology. It’s found that both the capacity and energy with same battery size could be increased by 30% comparing with Gen1 micro battery technology previously developed by PNNL. The yield of Gen2 micro batteries is still lower due to the high degree of manual operation, especially for drilling process where more precise position control is needed. More effort is still required to improve the capability of automatic manufacturing processes. The new battery technology will support the development of smaller and lighter miniature sensors at PNNL and could potentially contribute to the large-scale manufacturing capabilities of micro batteries in US with reliable performances and long-term shelf life.

25 ENERGY STORAGE↗

NASA NTRS2010

Plasma IMS Composition Measurements for Europa and the Other Galilean Moons

NASA and ESA are planning the joint Europa Jupiter System Mission (EJSM) to the Jupiter system with specific emphasis to Europa and Ganymede, respectively. The Japanese Space Agency is also planning an orbiter mission to explore Jupiter's magnetosphere and the Galilean satellites. For NASA's Jupiter Europa Orbiter (JEO) we are developing the 3D Ion Mass Spectrometer (IMS) with two main goals which can also be applied to the other Galilean moons, 1) measure the plasma interaction between Europa and Jupiter's magnetosphere and 2) infer the 4 pi surface composition to trace elemental and significant isotopic levels. The first goal supports the magnetometer (MAG) measurements, primarily directed at detection of Europa's sub-surface ocean, while the second gives information about transfer of material between the Galilean moons, and between the moon surfaces and subsurface layers putatively including oceans. The measurement of the interactions for all the Galilean moons can be used to trace the in situ ion measurements of pickup ions back to either Europa's or Ganymede's surface from the respectively orbiting spacecraft. The IMS instrument, being developed under NASA's Astrobiology Instrument Development Program, would maximally achieve plasma measurement requirements for JEO and EJSM while moving forward our knowledge of Jupiter system composition and source processes to far higher levels than previously envisaged. The composition of the global surfaces of Europa and Ganymede can be inferred from the measurement of ejected neutrals and pick-up ions using at minimum an in situ payload including MAG and IMS also fully capable of meeting Level 1 mission requirements for ocean detection and survey. Elemental and isotopic analysis of potentially extruded oceanic materials at the moon surfaces would further support the ocean objectives. These measurements should be made from a polar orbiting spacecraft about Europa or Ganymede at height 100 km. The ejecta produced by sputtering of the surfaces of Europa and Ganymede has been shown to be representative of the surface composition. Level 2 science on surface geology and composition can then be further enhanced by addition of the following: 3D Ion Neutral Mass Spectrometer (INNS), 3D plasma electron spectrometer (ELS), and hot plasma energetic particle instrument. The measurement approach is to alternate between times measuring pickup ions and times measuring plasma and magnetic field parameters along the spacecraft trajectory. By measuring the pickup ion energy, arrival direction and mass-per-charge, the ion can be traced back along the ejection trajectory to the approximate area of origin if the 3-D electric field and magnetic field are known. In situ observations of plasma flow velocities and vector magnetic fields can be used to determine the local convective electric field (E = -VXB) along the spacecraft trajectory. By combining this information with models of the magnetospheric interaction with Europa, one can generate 3D maps of the electric and magnetic field and compute the trajectories of the pickup ions back to the surface or exospheric points of origin. In the case of Ganymede there is the additional complexity of its own internal dipole magnetic field, while Io's volcanic activity introduces the complexity of a highly structured denser atmosphere. Callisto with its less globally extended exosphere will have a simpler interaction than for Europa (i.e., more like our moon). We will discuss these differences in light of the above proposed technique. Finally, the INNS observations and neutral exosphere models are needed to estimate production rates of pickup ions. The hot plasma measurements are needed to correct for sputtering rates which can be time dependent and electron plasma observations for electron impact ionization rates. Instrument characteristics, field-of-view requirements, modes of operation and effects of radiation on instrument functionality will be discussed.

Sittler, Edward↗

NASA NTRS2005

Automated Extraction of Flow Features

Computational Fluid Dynamics (CFD) simulations are routinely performed as part of the design process of most fluid handling devices. In order to efficiently and effectively use the results of a CFD simulation, visualization tools are often used. These tools are used in all stages of the CFD simulation including pre-processing, interim-processing, and post-processing, to interpret the results. Each of these stages requires visualization tools that allow one to examine the geometry of the device, as well as the partial or final results of the simulation. An engineer will typically generate a series of contour and vector plots to better understand the physics of how the fluid is interacting with the physical device. Of particular interest are detecting features such as shocks, re-circulation zones, and vortices (which will highlight areas of stress and loss). As the demand for CFD analyses continues to increase the need for automated feature extraction capabilities has become vital. In the past, feature extraction and identification were interesting concepts, but not required in understanding the physics of a steady flow field. This is because the results of the more traditional tools like; isc-surface, cuts and streamlines, were more interactive and easily abstracted so they could be represented to the investigator. These tools worked and properly conveyed the collected information at the expense of a great deal of interaction. For unsteady flow-fields, the investigator does not have the luxury of spending time scanning only one "snapshot" of the simulation. Automated assistance is required in pointing out areas of potential interest contained within the flow. This must not require a heavy compute burden (the visualization should not significantly slow down the solution procedure for co-processing environments). Methods must be developed to abstract the feature of interest and display it in a manner that physically makes sense.

Dorney, Suzanne↗

DOE OSTI2021

Dispersion relation for gauge-free electromagnetic drift kinetics

Recently, a new approach to gyrokinetics, invariant under electromagnetic gauge transformations, was developed. The gyrocenter equations of motion are now expressed in terms of the perturbed fields instead of the potentials, in a form suitable for numerical simulations and analytic studies. In this paper, we verify that the long-wavelength limit, i.e., the drift-kinetic limit of the new gyrokinetic theory, is in line with existing work, providing a solid foundation for simulations. Here, we compute the dispersion relation of the new drift-kinetic theory in slab geometry and find agreement with a long-wavelength limit of the full Vlasov–Maxwell model.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2004

Reducing Errors by Use of Redundancy in Gravity Measurements

A methodology for improving gravity-gradient measurement data exploits the constraints imposed upon the components of the gravity-gradient tensor by the conditions of integrability needed for reconstruction of the gravitational potential. These constraints are derived from the basic equation for the gravitational potential and from mathematical identities that apply to the gravitational potential and its partial derivatives with respect to spatial coordinates. Consider the gravitational potential in a Cartesian coordinate system {x1,x2,x3}. If one measures all the components of the gravity-gradient tensor at all points of interest within a region of space in which one seeks to characterize the gravitational field, one obtains redundant information. One could utilize the constraints to select a minimum (that is, nonredundant) set of measurements from which the gravitational potential could be reconstructed. Alternatively, one could exploit the redundancy to reduce errors from noisy measurements. A convenient example is that of the selection of a minimum set of measurements to characterize the gravitational field at n3 points (where n is an integer) in a cube. Without the benefit of such a selection, it would be necessary to make 9n3 measurements because the gravitygradient tensor has 9 components at each point. The problem of utilizing the redundancy to reduce errors in noisy measurements is an optimization problem: Given a set of noisy values of the components of the gravity-gradient tensor at the measurement points, one seeks a set of corrected values - a set that is optimum in that it minimizes some measure of error (e.g., the sum of squares of the differences between the corrected and noisy measurement values) while taking account of the fact that the constraints must apply to the exact values. The problem as thus posed leads to a vector equation that can be solved to obtain the corrected values.

Kulikov, Igor↗

NASA NTRS1990

Hybrid Propulsion Technology Program

Future launch systems of the United States will require improvements in booster safety, reliability, and cost. In order to increase payload capabilities, performance improvements are also desirable. The hybrid rocket motor (HRM) offers the potential for improvements in all of these areas. The designs are presented for two sizes of hybrid boosters, a large 4.57 m (180 in.) diameter booster duplicating the Advanced Solid Rocket Motor (ASRM) vacuum thrust-time profile and smaller 2.44 m (96 in.), one-quater thrust level booster. The large booster would be used in tandem, while eight small boosters would be used to achieve the same total thrust. These preliminary designs were generated as part of the NASA Hybrid Propulsion Technology Program. This program is the first phase of an eventual three-phaes program culminating in the demonstration of a large subscale engine. The initial trade and sizing studies resulted in preferred motor diameters, operating pressures, nozzle geometry, and fuel grain systems for both the large and small boosters. The data were then used for specific performance predictions in terms of payload and the definition and selection of the requirements for the major components: the oxidizer feed system, nozzle, and thrust vector system. All of the parametric studies were performed using realistic fuel regression models based upon specific experimental data.

Jensen, G. E.↗

NASA NTRS1999

GH/IGF-I Transgene Expression on Muscle Homeostasis

We propose to test the hypothesis that the growth hormone/ insulin like growth factor-I axis through autocrine/paracrine mechanisms may provide long term muscle homeostasis under conditions of prolonged weightlessness. As a key alternative to hormone replacement therapy, ectopic production of hGH, growth hormone releasing hormone (GHRH), and IGF-I will be studied for its potential on muscle mass impact in transgenic mice under simulated microgravity. Expression of either hGH or IGF-I would provide a chronic source of a growth-promoting protein whose biosynthesis or secretion is shut down in space. Muscle expression of the IGF-I transgene has demonstrated about a 20% increase in hind limb muscle mass over control nontransgenic litter mates. These recent experiments, also establish the utility of hind-limb suspension in mice as a workable model to study atrophy in weight bearing muscles. Thus, transgenic mice will be used in hind-limb suspension models to determine the role of GH/IGF-I on maintenance of muscle mass and whether concentric exercises might act in synergy with hormone treatment. As a means to engineer and ensure long-term protein production that would be workable in humans, gene therapy technology will be used by to monitor muscle mass preservation during hind-limb suspension, after direct intramuscular injection of a genetically engineered muscle-specific vector expressing GHRH. Effects of this gene-based therapy will be assessed in both fast twitch (medial gastrocnemius) and slow twitch muscle (soleus). End-points include muscle size, ultrastructure, fiber type, and contractile function, in normal animals, hind limb suspension, and reambutation.

Schwartz, Robert J.↗

NASA NTRSDate not supplied

Utilization of Machine Learning Techniques for Managing the Tracking and Data Relay Satellite Constellation

National Aeronautics and Space Administration’s (NASA) Goddard Space Flight Center (GSFC) operates a constellation of ten geosynchronous Tracking and Data Relay Satellites (TDRS). The TDRS constellation consists of multiple geosynchronous communication relay satellites located around the equator so they can provide continual coverage of any mission in low earth orbit. The TDRS are located primarily in three oceanic regions around the earth. NASA’s White Sands Complex provides the ground communication support for TDRS located over the Atlantic and Pacific Oceans. Another TDRS ground station in Guam supports the TDRS over the Indian Ocean. With these satellites the TDRS network can provide continuous coverage of satellites in low-earth orbit. The NASA Space Network (SN) project office at GSFC manages the constellation of spacecraft. Major customers of the TDRS constellation include, but are not limited to, the International Space Station and the Hubble Space Telescope. The TDRS constellation has three generations of satellites and has been active for over 30 years providing reliable communication links between customer satellites and corresponding ground stations. However, one of the major concerns for TDRS, and in any space mission, is to ensure the health and safety of the spacecraft. Generally, engineers use telemetry data to monitor and analyze the performance and state of health of the spacecraft. Telemetry data contains hundreds of parameters that monitor each important component in the spacecraft, which can be utilized to recognize and characterize the behavior of the spacecraft. Each parameter contains considerable information to represent time-dependent properties of each spacecraft subsystem and component. During the entire life of a TDRS spacecraft, thousands of gigabytes of telemetry data are transmitted in real-time from the spacecraft to the ground station at the White Sands Complex in Las Cruces, New Mexico, and recorded as historical data sets for engineers to process and analyze the events that occurred on-orbit. These parameters contain the function of multiple spacecraft subsystems, such as the attitude control system (ACS), Thermal, Electrical Power Subsystem (EPS), etc. . The first and second generations have exceeded their required lifetime and NASA is keen to manage these spacecrafts carefully in order to maximize the remaining life using the spacecraft telemetry. The challenge is to know when the risk of losing a spacecraft in geosynchronous orbit exceeds the benefit of continued operations for customer support. In the TDRS fleet, the EPS is the most critical subsystem related to spacecraft operations. Failure of the EPS would strand a spacecraft in geosynchronous orbit. Since EPS provides power to the spacecraft, component failures ultimately lead to the inability to support the spacecraft loads and the communications payload. For instance, TDRS-8 has several anomalies in EPS including the Bus Voltage Limiter (BVL) shunt current, solar array loss of circuits, and failed battery cells. Any of these anomalies can cause critical issues to the spacecraft. Therefore, developing a system to analyze and perform early detection of a potential anomaly is an important issue in telemetry data analysis. In recent years, Telemetry Mining (TM) has been proposed to process telemetry data by using Data Mining (DM) techniques such as classification, clustering, regression and anomaly detection. Anomaly detection, also known as outlier detection, has been widely used in many data mining areas such as remote sensing, medical data processing and digital image processing. The goal of anomaly detection is to detect abnormal data, which contains a relatively low probability of occurrence among the entire data set. Early detection of anomalies is one of the most significant issues in managing the spacecraft configuration. If anomalies can be detected early enough, then the redundant resources can be used to extend the life of the operational spacecraft. We present an unsupervised anomaly detection method to process the EPS data extracted from TDRS-8. This is different from traditional analytical methods, which use telemetry data to illustrate behavior and physical meaning of each spacecraft component. TM connects multiple parameters as a vector and then conducts data analysis on this high dimension telemetry vector. This method is looking at the properties of a high dimensional vector that is able to consider the relationship between different parameters in the anomaly detection problem. This kind of method performs much better than the traditional limit checking method. In addition, we propose a new approach of real-time anomaly detection to process telemetry data in real-time, which can then be applied to spacecraft monitoring with high reliability, low cost and high accuracy.

Machine Learning (ML)↗

NASA NTRS2018

MAVEN Case Studies of Plasma Dynamics in Low‐Altitude Crustal Magnetic Field at Mars 1: Dayside Ion Spikes Associated With Radial Crustal Magnetic Fields

We report for the first time, simultaneous ion, electron, magnetic field vector and electric field wave measurements made possible by Mars Atmosphere and Volatile EvolutioN, during ion energy flux spikes in low‐altitude radial crustal magnetic fields on the Mars dayside. Observations show energetic electrons and ions (E > 25 eV) precipitating on magnetic field lines assumed as closed. Ions (E < 1.4 keV) display broad velocity distributions toward Mars, showing ions flowing from higher altitude possibly after magnetic reconnection or loss cone filling from pitch angle scattering effects. Precipitating ions (E < 1.4 keV) show nonadiabatic features depending on ion mass and energy and returning ions (E < 1.4 keV) show evidence of conserving the first adiabatic invariant in a mirror field. We observe magnetic field perturbations up to 60 nT, electric field wave amplitudes up to 38 mV/m, and brief periods of peaked electron spectra. At ∼175 km and at times Mars Atmosphere and Volatile EvolutioN is below the mirroring altitude of electrons, we observe mirroring and transverse heating of H+ ions alongside increased electric field wave amplitude fluctuations. It suggests field aligned potential drops result from different mirror altitudes of ions and electrons. Ions E > 1.4 keV (O+) occur as injected accelerated ion beams and ions heated after energization or deceleration. Energy dispersed kilo‐electron‐volt ions suggest a selection effect in radial magnetic fields for lower‐energy Marsward ions, compared to reflection of higher‐energy anti‐Sunward ions. Precipitating kilo‐electron‐volt ions show energy deposition rates of 3.6 ×10(exp -6) W/sq m and sputtering escape rates from precipitating O+ ions of 1.5 ×10(exp 5)/(sq cm.s) and 2.1 ×10(exp 6)/(sq cm.s) are calculated.

Plasma Dynamics↗

NASA NTRS2021

A Chlorophyll-a Algorithm for Landsat-8 Based on Mixture Density Networks

Retrieval of aquatic biogeochemical variables, such as the near-surface concentration of chlorophyll-a (Chla) in inland and coastal waters via remote observations, has long been regarded as a challenging task. This manuscript applies Mixture Density Networks (MDN) that use the visible spectral bands available by the Operational Land Imager (OLI) aboard Landsat-8 to estimate Chla. We utilize a database of co-located in situ radiometric and Chla measurements (N = 4,354), referred to as Type A data, to train and test an MDN model (MDN(A)). This algorithm’s performance, having been proven for other satellite missions, is further evaluated against other widely used machine learning models (e.g., support vector machines), as well as other domain-specific solutions (OC3), and shown to offer significant advancements in the field. Our performance assessment using a held-out test data set suggests that a 49% (median) accuracy with near-zero bias can be achieved via the MDN(A) model, offering improvements of 20 to 100% in retrievals with respect to other models. The sensitivity of the MDN(A) model and benchmarking methods to uncertainties from atmospheric correction (AC) methods, is further quantified through a semi-global matchup dataset (N = 3,337), referred to as Type B data. To tackle the increased uncertainties, alternative MDN models (MDN(B)) are developed through various features of the Type B data (e.g., Rayleigh-corrected reflectance spectra ρ(s)). Using held-out data, along with spatial and temporal analyses, we demonstrate that these alternative models show promise in enhancing the retrieval accuracy adversely influenced by the AC process. Results lend support for the adoption of MDN(B) models for regional and potentially global processing of OLI imagery, until a more robust AC method is developed. Index Terms—Chlorophyll-a, coastal water, inland water, Landsat-8, machine learning, ocean color, aquatic remote sensing.

Brandon Smith↗