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Polanskey, Carol A.

Publications and source records attributed to Polanskey, Carol A..

13 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2021

Psyche Science Planning with the Science Opportunity Analyzer

Psyche is a NASA Discovery mission intent on solving mysteries surrounding early planetary formation. The mission spacecraft will journey to (16) Psyche: a metallic asteroid believed to be the exposed core of an early planetesimal. Despite the unique nature of the target asteroid and the mission’s novel science goals, a significant portion of the project’s science planning needs may be met through the use of legacy tools. In particular, the adoption of the Jet Propulsion Laboratory’s (JPL) Science Opportunity Analyzer (SOA) promises to satisfy mission requirements with minimal development effort. Originally developed as a multi-mission science planning tool, SOA can design and visualize observations, perform geometric flight rule checking, model physical phenomena, and much more. The software has been used by the mission since its proposal phase and is expected to continue providing valuable capabilities throughout operations.

Elkins-Tanton, Linda T.↗
NASA NTRS2013

Science Opportunity Analyzer (SOA) Version 8

SOA allows scientists to plan spacecraft observations. It facilitates the identification of geometrically interesting times in a spacecraft s orbit that a user can use to plan observations or instrument-driven spacecraft maneuvers. These observations can then be visualized multiple ways in both two- and three-dimensional views. When observations have been optimized within a spacecraft's flight rules, the resulting plans can be output for use by other JPL uplink tools. Now in its eighth major version, SOA improves on these capabilities in a modern and integrated fashion. SOA consists of five major functions: Opportunity Search, Visualization, Observation Design, Constraint Checking, and Data Output. Opportunity Search is a GUI-driven interface to existing search engines that can be used to identify times when a spacecraft is in a specific geometrical relationship with other bodies in the solar system. This function can be used for advanced mission planning as well as for making last-minute adjustments to mission sequences in response to trajectory modifications. Visualization is a key aspect of SOA. The user can view observation opportunities in either a 3D representation or as a 2D map projection. Observation Design allows the user to orient the spacecraft and visualize the projection of the instrument field of view for that orientation using the same views as Opportunity Search. Constraint Checking is provided to validate various geometrical and physical aspects of an observation design. The user has the ability to easily create custom rules or to use official project-generated flight rules. This capability may also allow scientists to easily assess the cost to science if flight rule changes occur. Data Output allows the user to compute ancillary data related to an observation or to a given position of the spacecraft along its trajectory. The data can be saved as a tab-delimited text file or viewed as a graph. SOA combines science planning functionality unique to both JPL and the sponsoring spacecraft. SOA is able to ingest JPL SPICE Kernels that are used to drive the tool and its computations. A Percy search engine is then included that identifies interesting time periods for the user to build observations. When observations are then built, flight-like orientation algorithms replicate spacecraft dynamics to closely simulate the flight spacecraft s dynamics. SOA v8 represents large steps forward from SOA v7 in terms of quality, reliability, maintainability, efficiency, and user experience. A tailored agile development environment has been built around SOA that provides automated unit testing, continuous build and integration, a consolidated Web-based code and documentation storage environment, modern Java enhancements, and a focus on usability

Witoff, Robert J.↗
NASA NTRS2006

Mars Odyssey: Off-nadir Imaging

Science Objectives for off-nadir imaging: a) Daily observations of high activity and high interest targets in the Polar Regions; b) Daily imaging of regions of gas jetting through vents and the formation of dark spots and fans; c) Increases likelihood of observing these processes in an active phase; d) Stereo imaging for geographical analysis and landing site characterization; and e) Fill in existing gaps and gores.

off nadir imaging↗
NASA NTRS2004

Observation Planning Made Simple with Science Opportunity Analyzer (SOA)

As NASA undertakes the exploration of the Moon and Mars as well as the rest of the Solar System while continuing to investigate Earth's oceans, winds, atmosphere, weather, etc., the ever-existing need to allow operations users to easily define their observations increases. Operation teams need to be able to determine the best time to perform an observation, as well as its duration and other parameters such as the observation target. In addition, operations teams need to be able to check the observation for validity against objectives and intent as well as spacecraft constraints such as turn rates and acceleration or pointing exclusion zones. Science Opportunity Analyzer (SOA), in development for the last six years, is a multi-mission toolset that has been built to meet those needs. The operations team can follow six simple steps and define his/her observation without having to know the complexities of orbital mechanics, coordinate transformations, or the spacecraft itself.

observation planning operations↗
NASA NTRS2004

Science Opportunity Analyzer (SOA): Science Planning Made Simple

.For the first time at JPL, the Cassini mission to Saturn is using distributed science operations for developing their experiments. Remote scientists needed the ability to: a) Identify observation opportunities; b) Create accurate, detailed designs for their observations; c) Verify that their designs meet their objectives; d) Check their observations against project flight rules and constraints; e) Communicate their observations to other scientists. Many existing tools provide one or more of these functions, but Science Opportunity Analyzer (SOA) has been built to unify these tasks into a single application. Accurate: Utilizes JPL Navigation and Ancillary Information Facility (NAIF) SPICE* software tool kit - Provides high fidelity modeling. - Facilitates rapid adaptation to other flight projects. Portable: Available in Unix, Windows and Linux. Adaptable: Designed to be a multi-mission tool so it can be readily adapted to other flight projects. Implemented in Java, Java 3D and other innovative technologies. Conclusion: SOA is easy to use. It only requires 6 simple steps. SOA's ability to show the same accurate information in multiple ways (multiple visualization formats, data plots, listings and file output) is essential to meet the needs of a diverse, distributed science operations environment.

observation planning operations↗
NASA NTRS2004

Science Opportunity Analyzer (SOA): Not Just Another Pretty Face

This viewgraph presentation reviews the Science Opportunity Analyzer (SOA). For the first time at JPL, the Cassini mission to Saturn is using distributed science operations for sequence generation. This means that scientist at other institutions has more responsibility to build the spacecraft sequence. Tools are required to support the sequence development. JPL tools required a complete configuration behind a firewall, and the tools that the user community had developed did not interface with the JPL tools. Therefore the SOA was created to bridge the gap between the remote scientists and the JPL operations teams. The presentation reviews the development of the SOA, and what was required of the system. The presentation reviews the functions that the SOA performed.

mission planning↗
NASA NTRS2003

Create your own science planning tool in 3 days with SOA

Scientific discovery and advancement of knowledge has been, and continues to be, the goal for space missions at Jet Propulsion Laboratory. Scientist must plan their observation/experiments to get the maximum data return in order to make those discoveries. However, each mission has different science objectives, a different spacecraft and different instrument payloads, as well as, different routes to different destinations with different spacecraft restrictions and characteristics. In the current reduced cost environment, manageable cost for mission planning software is a must. Science Opportunity Analyzer (SOA), a planning tool for scientists and mission planners, utilizes a simple approach to reduce cost and promote reusability.

Science Opportunity Analyzer (SOA).↗
NASA NTRS1994

Scaling craters in carbonates: Electron paramagnetic resonance analysis of shock damage

Carbonate samples from the 8.9-Mt nuclear (near-surface explosion) crater, OAK, and a terrestrial impact crater, Meteor Crater, were analyzed for shock damage using electron paramagnetic resonance (EPR). Samples from below the OAK apparent crater floor were obtained from six boreholes, as well as ejecta recovered from the crater floor. The degree of shock damage in the carbonate material was assessed by comparing the sample spectra to the spectra of Solenhofen and Kaibab limestone, which had been skocked to known pressures. Analysis of the OAK Crater borehole samples has identified a thin zone of allocthonous highly shocked (10-13 GPa) carbonate material underneath the apparent crater floor. This approx. 5- to 15-m-thick zone occurs at a maximum depth of approx. 125 m below current seafloor at the borehole, sited at the initial position of the OAK explosive, and decreases in depth towards the apparent crater edge. Because this zone of allocthonous shocked rock delineates deformed rock below, and a breccia of mobilized sand and collapse debris above, it appears to outline the transient crater. The transient crater volume inferred in this way is found to by 3.2 +/- 0.2 times 10(exp 6)cu m, which is in good agreement with a volume of 5.3 times 10(exp 6)cu m inferred from gravity scaling of laboratory experiments. A layer of highly shocked material is also found near the surface outside the crater. The latter material could represent a fallout ejecta layer. The ejecta boulders recovered from the present crater floor experienced a range of shock pressures from approx. 0 to 15 GPa with the more heavily shocked samples all occurring between radii of 360 and approx. 600 m. Moreover, the fossil content, lithology and Sr isotopic composition all demonstrate that the initial position of the bulk of the heavily shocked rock ejecta sampled was originally near surface rock at initial depths in the 32 to 45-m depth (below sea level) range. The EPR technique is also sensitive to prehistoric shock damage. This is demonstrated by our study of shocked Kaibab limestone from the 49,000-year-old Meteor (Barringer) Crater Arizona.

Polanskey, Carol A.↗
NASA NTRS1990

Impact spallation experiments - Fracture patterns and spall velocities

The spall velocities produced by nine experimental impacts of 1 to 6.5 km/sec into San Marcos gabbro targets, using projectiles of Fe, Al, Pb, and basalt of various sizes, have been measured in conjunction with fragment-velocity high-speed filmings of the events. A detailed comparison is made between measured spall velocities and those predicted by the model of Melosh (1984), with a view to the compatibility of small-scale results and large planetary impacts. Attention is also given to the patterns of internal fracture generated by impact within the targets.

Polanskey, Carol A.↗
NASA NTRS1986

Spall velocity measurements from laboratory impact craters

Spall velocities were measured for a series of impacts into San Marcos gabbro. Impact velocities ranged from 1 to 6.5 km/sec. Projectiles varied in material and size with a maximum mass of 4g for a lead bullet to a minimum of 0.04 g for an aluminum sphere. The spall velocities were calculated both from measurements taken from films of the events and from estimates based on range measurements of the spall fragments. The maximum spall velocity observed was 27 m/sec, or 0.5 percent of the impact velocity. The measured spall velocities were within the range predicted by the Melosh (1984) spallation model for the given experimental parameters. The compatability between the Melosh model for large planetary impacts and the results of these small scale experiments is considered in detail. The targets were also bisected to observe the internal fractures. A series of fractures were observed whose location coincided with the boundary of the theoretical near surface zone predicted by Melosh. Above this boundary the target material should receive reduced levels of compressive stress as compared to the more highly shocked region below.

Polanskey, Carol A.↗