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NASA NTRS2012

3D Drop Size Distribution Extrapolation Algorithm Using a Single Disdrometer

Determining the Z-R relationship (where Z is the radar reflectivity factor and R is rainfall rate) from disdrometer data has been and is a common goal of cloud physicists and radar meteorology researchers. The usefulness of this quantity has traditionally been limited since radar represents a volume measurement, while a disdrometer corresponds to a point measurement. To solve that problem, a 3D-DSD (drop-size distribution) method of determining an equivalent 3D Z-R was developed at the University of Central Florida and tested at the Kennedy Space Center, FL. Unfortunately, that method required a minimum of three disdrometers clustered together within a microscale network (.1-km separation). Since most commercial disdrometers used by the radar meteorology/cloud physics community are high-cost instruments, three disdrometers located within a microscale area is generally not a practical strategy due to the limitations of these kinds of research budgets. A relatively simple modification to the 3D-DSD algorithm provides an estimate of the 3D-DSD and therefore, a 3D Z-R measurement using a single disdrometer. The basis of the horizontal extrapolation is mass conservation of a drop size increment, employing the mass conservation equation. For vertical extrapolation, convolution of a drop size increment using raindrop terminal velocity is used. Together, these two independent extrapolation techniques provide a complete 3DDSD estimate in a volume around and above a single disdrometer. The estimation error is lowest along a vertical plane intersecting the disdrometer position in the direction of wind advection. This work demonstrates that multiple sensors are not required for successful implementation of the 3D interpolation/extrapolation algorithm. This is a great benefit since it is seldom that multiple sensors in the required spatial arrangement are available for this type of analysis. The original software (developed at the University of Central Florida, 1998.- 2000) has also been modified to read standardized disdrometer data format (Joss-Waldvogel format). Other modifications to the software involve accounting for vertical ambient wind motion, as well as evaporation of the raindrop during its flight time.

Lane, John↗

NASA NTRS2006

Development of a Low-Cost Sub-Scale Aircraft for Flight Research: The FASER Project

An inexpensive unmanned sub-scale aircraft was developed to conduct frequent flight test experiments for research and demonstration of advanced dynamic modeling and control design concepts. This paper describes the aircraft, flight systems, flight operations, and data compatibility including details of some practical problems encountered and the solutions found. The aircraft, named Free-flying Aircraft for Sub-scale Experimental Research, or FASER, was outfitted with high-quality instrumentation to measure aircraft inputs and states, as well as vehicle health parameters. Flight data are stored onboard, but can also be telemetered to a ground station in real time for analysis. Commercial-off-the-shelf hardware and software were used as often as possible. The flight computer is based on the PC104 platform, and runs xPC-Target software. Extensive wind tunnel testing was conducted with the same aircraft used for flight testing, and a six degree-of-freedom simulation with nonlinear aerodynamics was developed to support flight tests. Flight tests to date have been conducted to mature the flight operations, validate the instrumentation, and check the flight data for kinematic consistency. Data compatibility analysis showed that the flight data are accurate and consistent after corrections are made for estimated systematic instrumentation errors.

Owens, Donald B.↗

NASA NTRS1990

Multiversion software reliability through fault-avoidance and fault-tolerance

In this project we have proposed to investigate a number of experimental and theoretical issues associated with the practical use of multi-version software in providing dependable software through fault-avoidance and fault-elimination, as well as run-time tolerance of software faults. In the period reported here we have working on the following: We have continued collection of data on the relationships between software faults and reliability, and the coverage provided by the testing process as measured by different metrics (including data flow metrics). We continued work on software reliability estimation methods based on non-random sampling, and the relationship between software reliability and code coverage provided through testing. We have continued studying back-to-back testing as an efficient mechanism for removal of uncorrelated faults, and common-cause faults of variable span. We have also been studying back-to-back testing as a tool for improvement of the software change process, including regression testing. We continued investigating existing, and worked on formulation of new fault-tolerance models. In particular, we have partly finished evaluation of Consensus Voting in the presence of correlated failures, and are in the process of finishing evaluation of Consensus Recovery Block (CRB) under failure correlation. We find both approaches far superior to commonly employed fixed agreement number voting (usually majority voting). We have also finished a cost analysis of the CRB approach.

Vouk, Mladen A.↗

NASA NTRS2022

Automatic variable selection in ecological niche modeling: A case study using Cassin’s Sparrow (Peucaea cassinii)

MERRA/Max provides a feature selection approach to dimensionality reduction that enables direct use of global climate model outputs in ecological niche modeling. The system accomplishes this reduction through a Monte Carlo optimization in which many independent MaxEnt runs, operating on a species occurrence file and a small set of randomly selected variables in a large collection of variables, converge on an estimate of the top contributing predictors in the larger collection. These top predictors can be viewed as potential candidates in the variable selection step of the ecological niche modeling process. MERRA/Max’s Monte Carlo algorithm operates on files stored in the underlying filesystem, making it scalable to large data sets. Its software components can run as parallel processes in a high-performance cloud computing environment to yield near real-time performance. In tests using Cassin’s Sparrow (Peucaea cassinii) as the target species, MERRA/Max selected a set of predictors from Worldclim’s Bioclim collection of 19 environmental variables that have been shown to be important determinants of the species’ bioclimatic niche. It also selected biologically and ecologically plausible predictors from a more diverse set of 86 environmental variables derived from NASA’s Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2) reanalysis, an output product of the Goddard Earth Observing System Version 5 (GEOS-5) modeling system. We believe these results point to a technological approach that could expand the use global climate model outputs in ecological niche modeling, foster exploratory experimentation with otherwise difficult-to-use climate data sets, streamline the modeling process, and, eventually, enable automated bioclimatic modeling as a practical, readily accessible, low-cost, commercial cloud service.

John L. Schnase↗

NASA NTRS2013

Mars Sample Return Landed with Red Dragon

A Mars Sample Return (MSR) mission is the highest priority science mission for the next decade as recommended by the recent Decadal Survey of Planetary Science. However, an affordable program to carry this out has not been defined. This paper describes a study that examined use of emerging commercial capabilities to land the sample return elements, with the goal of reducing mission cost. A team at NASA Ames examined the feasibility of the following scenario for MSR: A Falcon Heavy launcher injects a SpaceX Dragon crew capsule and trunk onto a Trans Mars Injection trajectory. The capsule is modified to carry all the hardware needed to return samples collected on Mars including a Mars Ascent Vehicle (MAV), an Earth Return Vehicle (ERV) and Sample Collection and Storage hardware. The Dragon descends to land on the surface of Mars using SuperSonic Retro Propulsion (SSRP) as described by Braun and Manning [IEEEAC paper 0076, 2005]. Samples are acquired and deliverd to the MAV by a prelanded asset, possibly the proposed 2020 rover. After samples are obtained and stored in the ERV, the MAV launches the sample-containing ERV from the surface of Mars. We examined cases where the ERV is delivered to either low Mars orbit (LMO), C3 = 0 (Mars escape), or an intermediate energy state. The ERV then provides the rest of the energy (delta V) required to perform trans-Earth injection (TEI), cruise, and insertion into a Moon-trailing Earth Orbit (MTEO). A later mission, possibly a crewed Dragon launched by a Falcon Heavy (not part of the current study) retrieves the sample container, packages the sample, and performs a controlled Earth re-entry to prevent Mars materials from accidentally contaminating Earth. The key analysis methods used in the study employed a set of parametric mass estimating relationships (MERs) and standard aerospace analysis software codes modified for the MAV class of launch vehicle to determine the range of performance parameters that produced converged spacecraft designs capable of meeting mission requirements. Subsystems modeled in this study included structures, power system, propulsion system, nose fairing, thermal insulation, actuation devices, and GN&C. Best practice application of loads and design margins for all resources were used. Both storable and cryogenic propellant systems were examined. The landed mass and lander capsule size provide boundary conditions for the MAV design and packaging. We estimated the maximum mass the Dragon capsule is capable of landing. This and the volume capability to store the MAV was deduced from publically available data from SpaceX as well as our own engineering and aerodynamic estimates. Minimum gross-liftoff mass (GLOM) for the MAV were obtained for configurations that used pump-fed storable bi-propellant rocket engines for both the MAV and the ERV stage. The GLOM required fits within our internal estimate of the mass that Dragon can land at low elevation/optimal seasons on Mars. Based on the analysis, we show that a single Mars launch sample return mission is feasible using current commercial capabilities to deliver the return spacecraft assets.

Mars Ascent Vehicle (MAV)↗