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We present results of continuing efforts to evaluate total dose bias dependency and ELDRS effects in bipolar linear microcircuits. Several devices were evaluated, each exhibiting moderate to significant bias and/or dose rate dependency.
We use state-of-the-art public-domain Fortran codes based on the T-matrix method to calculate orientation and ensemble averaged scattering matrix elements for a variety of morphologically complex black carbon (BC) and BC-containing aerosol particles, with a special emphasis on the linear depolarization ratio (LDR). We explain theoretically the quasi-Rayleigh LDR peak at side-scattering angles typical of low-density soot fractals and conclude that the measurement of this feature enables one to evaluate the compactness state of BC clusters and trace the evolution of low-density fluffy fractals into densely packed aggregates. We show that small backscattering LDRs measured with groundbased, airborne, and spaceborne lidars for fresh smoke generally agree with the values predicted theoretically for fluffy BC fractals and densely packed near-spheroidal BC aggregates. To reproduce higher lidar LDRs observed for aged smoke, one needs alternative particle models such as shape mixtures of BC spheroids or cylinders.
Vertical profiles of 0.532 μm aerosol particle extinction coefficient and linear volume depolarization ratio are described for Southeast Asia and the Maritime Continent. Quality-screened and cloud-cleared Version 3.01 Level 2 NASA Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) 5-km Aerosol Profile datasets are analyzed from 2007 to 2009. Numerical simulations from the U.S. Naval Aerosol Analysis and Predictive System (NAAPS), featuring two-dimensional variational assimilation of NASA Moderate Resolution Imaging Spectroradiometer and Multi-angle Imaging Spectro- Radiometer quality-assured datasets, combined with regional ground-based lidar measurements, are considered for assessing CALIOP retrieval performance, identifying bias, and evaluating regional representativeness. CALIOP retrievals of aerosol particle extinction coefficient and aerosol optical depth (AOD) are high over land and low over open waters relative to NAAPS (0.412/0.312 over land for all data points inclusive, 0.310/0.235 when the per bin average is used and each is treated as single data points; 0.102/0.151 and 0.086/0.124, respectively, over ocean). Regional means, however, are very similar (0.180/0.193 for all data points and 0.155/0.159 when averaged per normalized bin), as the two factors offset one another. The land/ocean offset is investigated, and discrepancies attributed to interpretation of particle composition and a-priori assignment of the extinction-to-backscatter ratio ("lidar ratio") necessary for retrieving the extinction coefficient from CALIOP signals. Over land, NAAPS indicates more dust present than CALIOP algorithms are identifying, indicating a likely assignment of a higher lidar ratio representative of more absorptive particles. NAAPS resolvesmore smoke overwater than identified with CALIOP, indicating likely usage of a lidar ratio characteristic of less absorptive particles to be applied that biases low AOD there. Over open waters except within the Bay of Bengal, aerosol particle scattering is largely capped below 1.5 km MSL, though ground-based lidar measurements at Singapore differ slightly from this finding. Significant aerosol particle presence over land is similarly capped near 3.0 km MSL over most regions. Particle presence at low levels regionally, except over India, is dominated by relatively non-depolarizing particles. Industrial haze, sea salt droplets and fresh smoke are thus most likely present.
The 2018 ExoMars rover mission includes the Mars Organic Molecule Analyzer (MOMA) investigation. MOMA will examine the chemical composition of samples acquired from depths of up to two meters below the martian surface, where organics may be protected from degradation derived from cosmic radiation and/or oxidative chemical reactions. When combined with the complement of instruments in the rover's Pasteur Payload, MOMA has the potential to reveal the presence of a wide range of organics preserved in a variety of mineralogical environments, and to begin to understand the structural character and potential origin of those compounds. The MOMA investigation is led by the Max Planck Institute for Solar System Research (MPS) with the mass spectrometer subsystem provided by NASA GSFC. MOMA's linear ion trap mass spectrometer (ITMS) is designed to analyze molecular composition of: (i) gas evolved from pyrolyzed powder samples and separated in a gas chromatograph; and, (ii) ions directly desorbed from crushed solid samples at Mars ambient pressure, as enabled by a pulsed UV laser system, fast-actuating aperture valve and capillary ion inlet. Breadboard ITMS and associated electronics have been advanced to high end-to-end fidelity in preparation for flight hardware delivery to Germany in 2015.
Two models of the linear alternator of the Advanced Stirling Convertor (ASC) have been developed using the Sage 1-D modeling software package. The first model relates the piston motion to electric current by means of a motor constant. The second uses electromagnetic model components to model the magnetic circuit of the alternator. The models are tuned and validated using test data and compared against each other. Results show both models can be tuned to achieve results within 7% of ASC test data under normal operating conditions. Using Sage enables the creation of a complete ASC model to be developed and simulations completed quickly compared to more complex multi-dimensional models. These models allow for better insight into overall Stirling convertor performance, aid with Stirling power system modeling, and in the future support NASA mission planning for Stirling-based power systems.
Two models of the linear alternator of the Advanced Stirling Convertor (ASC) have been developed using the Sage 1-D modeling software package. The first model relates the piston motion to electric current by means of a motor constant. The second uses electromagnetic model components to model the magnetic circuit of the alternator. The models are tuned and validated using test data and also compared against each other. Results show both models can be tuned to achieve results within 7 of ASC test data under normal operating conditions. Using Sage enables the creation of a complete ASC model to be developed and simulations completed quickly compared to more complex multi-dimensional models. These models allow for better insight into overall Stirling convertor performance, aid with Stirling power system modeling, and in the future support NASA mission planning for Stirling-based power systems.
Dose rate effects are examined in linear bipolar transistors at high and low dose rates. At high dose rates, approximately 50% of the damage anneals at room temperature, even though these devices exhibit enhanced damage at low dose rate. The unexpected recovery of a significant fraction of the damage after tests at high dose rate requires changes in existing test standards. Tests at low temperature with a one-second radiation pulse width show that damage continues to increase for more than 3000 seconds afterward, consistent with predictions of the CTRW model for oxides with a thickness of 700 nm.
Future surface missions to Mars and other planetary bodies will benefit from continued advances in miniature sensor and sample handling technologies that enable high-performance chemical analyses of natural samples. Fine-scale (approx.1 mm and below) analyses of rock surfaces and interiors, such as exposed on a drill core, will permit (1) the detection of habitability markers including complex organics in association with their original depositional environment, and (2) the characterization of successive layers and gradients that can reveal the time-evolution of those environments. In particular, if broad-based and highly-sensitive mass spectrometry techniques could be brought to such scales, the resulting planetary science capability would be truly powerful. The Linear Ion Trap Mass Spectrometer (LITMS) investigation is designed to conduct fine-scale organic and inorganic analyses of short (approx.5-10 cm) rock cores such as could be acquired by a planetary lander or rover arm-based drill. LITMS combines both pyrolysis/gas chromatograph mass spectrometry (GCMS) of sub-sampled core fines, and laser desorption mass spectrometry (LDMS) of the intact core surface, using a common mass analyzer, enhanced from the design used in the Mars Organic Molecule Analyzer (MOMA) instrument on the 2018 ExoMars rover. LITMS additionally features developments based on the Sample Analysis at Mars (SAM) investigation on MSL and recent NASA-funded prototype efforts in laser mass spectrometry, pyrolysis, and precision subsampling. LITMS brings these combined capabilities to achieve its four measurement objectives: (1) Organics: Broad Survey Detect organic molecules over a wide range of molecular weight, volatility, electronegativity, concentration, and host mineralogy. (2) Organic: Molecular Structure Characterize internal molecular structure to identify individual compounds, and reveal functionalization and processing. (3) Inorganic Host Environment Assess the local chemical/mineralogical makeup of organic host phases to help determine deposition and preservation factors. (4) Chemical Stratigraphy Analyze the fine spatial distribution and variation of key species with depth.
This paper extends in two directions the results of prior work on generalized linear covariance analysis of both batch least-squares and sequential estimators. The first is an improved treatment of process noise in the batch, or epoch state, estimator with an epoch time that may be later than some or all of the measurements in the batch. The second is to account for process noise in specifying the gains in the epoch state estimator. We establish the conditions under which the latter estimator is equivalent to the Kalman filter.
The Linear Technology (LT) LT2078 was tested for single event effect (SEE) at the Texas A&M University Cyclotron Facility (TAMU) on 11 April 2015. The device was exercised in varied load conditions to replicate its intended application with concerns about destructive effects on the commercial device.
New effects that complicate the application of linear devices in space are discussed, including enhanced damage at low dose rate and proton damage, which cause permanent degradtion.
Although many different processes can be used to manufacture linear integrated circuits, the process that is used for most circuits is optimized for high voltage -- a total power supply voltage of about 40 V -- and low cost.
Recent observations by two different nadir pointing airborne radars with some linear polarization
This paper describes the improvement in the architecture of the physics package used in the Linear-Ion -Trap-(LIT)-based frequency standard recently developed at JPL.
The technique of projective measurements in linear optics can provide an apparent, efficient nonlinear interaction between photons, which is technically problematic otherwise. We present an application of such a technique to prepare large photon-number path entanglement.
Simulation and analysis for modern engineering systems now routinely requires the merging of multiple disciplines, physical-domains, time-scales, and data sets — all at ever increasing levels. These capabilities are especially needed in the domain of Advanced Air Mobility, where rapidly emerging vehicle designs are significantly more complex, while having to be both cost-effective and safe. To meet these engineering challenges, machine learning methods are an attractive option for merging models and data across multiple areas while providing uncertainty quantification and maintaining computational efficiency. This paper examines the use of Gaussian process machine learning to generalize and enhance the commonly used class of quasi-Linear Parameter Varying models for fast full-envelope simulation while also supporting control system design and analysis with model uncertainty. Gaussian process machine learning is selected because it: can fuse multiple data sets, enables an easy trade-off between data fitting and smoothing, provides model uncertainty quantification, scales well with increasing complexity, and does not generally require starting from a large training data set. To demonstrate the benefits of the approach, a robust stability analysis with Gaussian process uncertainty is shown for a NASA reference design of an electric quad-rotor air-taxi concept vehicle with motor parameter uncertainty.
Typically for a rendezvous and docking scenario, only a single vehicle is considered the active vehicle. As a result, the target vehicle’s GN&C system is typically not a factor in the integrated performance analysis as it assumes a passive role. However, for upcoming NASA Artemis missions the active vehicle is both the chaser and target spacecraft. In addition, both vehicles are cooperating with one another, sharing telemetry data, and relying on data extracted from the GN&C system of the other. The process also includes a team of ground support personnel in mission control are tracking and monitoring each spacecraft uplinking state estimates and targeting solutions to support mission operations and enhance the onboard flight system performance. Being able to quickly analyze the impact of both vehicles with two different GN&C systems that also interact with the ground that does its own navigation and targeting uploads is critical. This paper outlines how to perform this rapid analysis using linear covariance techniques and applies them to a rendezvous scenario initiated in low lunar orbit and completed in a Near Rectilinear Halo Orbit (NRHO) representative of the NASA Artemis III mission.
The scope of the NASA Engineering and Safety Center (NESC) Unconservatism of Linear-Elastic Fracture Mechanics (LEFM) Analysis Post Autofrettage assessment was to evaluate the influence of the elastic-plastic autofrettage cycle on elastic cycles post autofrettage and generate data to support damage tolerance life analysis verification approach. The decision to include an elastic-plastic autofrettage cycle is informed by other factors beyond damage tolerance, including manufacturing and fatigue crack initiation. The results of the NESC assessment are contained in this report.