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NASA NTRS2010

Multivariate Methods for Prediction of Geologic Sample Composition with Laser-Induced Breakdown Spectroscopy

Laser-induced breakdown spectroscopy (LIBS) uses pulses of laser light to ablate a material from the surface of a sample and produce an expanding plasma. The optical emission from the plasma produces a spectrum which can be used to classify target materials and estimate their composition. The ChemCam instrument on the Mars Science Laboratory (MSL) mission will use LIBS to rapidly analyze targets remotely, allowing more resource- and time-intensive in-situ analyses to be reserved for targets of particular interest. ChemCam will also be used to analyze samples that are not reachable by the rover's in-situ instruments. Due to these tactical and scientific roles, it is important that ChemCam-derived sample compositions are as accurate as possible. We have compared the results of partial least squares (PLS), multilayer perceptron (MLP) artificial neural networks (ANNs), and cascade correlation (CC) ANNs to determine which technique yields better estimates of quantitative element abundances in rock and mineral samples. The number of hidden nodes in the MLP ANNs was optimized using a genetic algorithm. The influence of two data preprocessing techniques were also investigated: genetic algorithm feature selection and averaging the spectra for each training sample prior to training the PLS and ANN algorithms. We used a ChemCam-like laboratory stand-off LIBS system to collect spectra of 30 pressed powder geostandards and a diverse suite of 196 geologic slab samples of known bulk composition. We tested the performance of PLS and ANNs on a subset of these samples, choosing to focus on silicate rocks and minerals with a loss on ignition of less than 2 percent. This resulted in a set of 22 pressed powder geostandards and 80 geologic samples. Four of the geostandards were used as a validation set and 18 were used as the training set for the algorithms. We found that PLS typically resulted in the lowest average absolute error in its predictions, but that the optimized MLP ANN and the CC ANN often gave results comparable to PLS. Averaging the spectra for each training sample and/or using feature selection to choose a small subset of wavelengths to use for predictions gave mixed results, with degraded performance in some cases and similar or slightly improved performance in other cases. However, training time was significantly reduced for both PLS and ANN methods by implementing feature selection, making this a potentially appealing method for initial, rapid-turn-around analyses necessary for Chemcam's tactical role on MSL. Choice of training samples has a strong influence on the accuracy of predictions. We are currently investigating the use of clustering algorithms (e.g. k-means, neural gas, etc.) to identify training sets that are spectrally similar to the unknown samples that are being predicted, and therefore result in improved predictions

Morris, Richard↗

NASA NTRS2011

The SPASE Data Model for Heliophysics Data: Is it Working?

The Space Physics Archive Search and Extract (SPASE) Data Model was developed to provide a metadata standard for describing Heliophysics (Space and Solar Physics) data within that science discipline. The SPASE Data Model has matured over the many years of its creation and is presently represented by Version 2.2.1. Information about SPASE can be obtained from the website group.org. The Data Model defines terms and values as well as the relationships between them in order to describe the data resources in the Heliophysics data environment. This data environment is quite complex, consisting of Virtual Observatories, Resident Archives, Data Providers, Partnering Data Centers, Services, Final Archives, and a Deep Archive. SPASE is the metadata language standard intended to permeate the complexity and provide a common method of obtaining and understanding data. Is it working in this capacity? SPASE has been used to describe a wide range of data. Examples range from ground-based magnetometer data to interplanetary satellite measurements to space weather model results. Has it achieved the goal of making the data easier to find and use? To find data of interest it is necessary that all the data of importance be described using the SPASE Data Model. Within the part of the data community associated with NASA (supported through NASA funding) there are obligations to use SPASE and (0 describe the old and new data using the SPASE XML schema. Although this pan of the community is not near 100% compliance with the mandate, there is good progress being made and the goal should be reachable in the future. Outside of the NASA data community there is still work to be done to convince the international community that SPASE descriptions are w011h the cost of their generation. Some of these groups such as Cluster, HELlO, GAIA, NOAA/NGDe. CSSDP, VSTO, SuperMAG, and IUGONET have agreed to use SPASE. but there are still other groups of importance that need (0 be reached. It is also assumed that the terminology is sufficiently broad and the descriptions are sufficiently complete that researchers needing data of a specific type or from a specific period can find and acquire what they need. A valid SPASE description can be very brief or very thorough depending on the willingness of the author to spend the time necessary to make the description useful. There is evidence that users are finding what they need through the SPASE descriptions, and this standard is a big step forward in Heliophysics data location. Does SPASE make it easier to use the data once they are found,) Thorough descriptions of data using SPASE can describe the data down to the level of individual parameters and exactly how the data are organized and stored. Should the SPASE data descriptions be written in such a way that they can be automatically ingested and understood by software tools'? Heliophysics instruments are becoming morc versatile all the time and the complexity of the data makes it tedious and time consuming to write SPASE descriptions with this level of sophistication even with the improvement of the tools used to generate the descriptions. Is it better to just write human-readable descriptions of the data at the parameter level or to refer to references that provide this information? This is a debate that is presently taking place and software is being developed to test what is possible.

Thieman, James↗

NASA NTRS2011

Simulation and Verification of Synchronous Set Relations in Rewriting Logic

This paper presents a mathematical foundation and a rewriting logic infrastructure for the execution and property veri cation of synchronous set relations. The mathematical foundation is given in the language of abstract set relations. The infrastructure consists of an ordersorted rewrite theory in Maude, a rewriting logic system, that enables the synchronous execution of a set relation provided by the user. By using the infrastructure, existing algorithm veri cation techniques already available in Maude for traditional asynchronous rewriting, such as reachability analysis and model checking, are automatically available to synchronous set rewriting. The use of the infrastructure is illustrated with an executable operational semantics of a simple synchronous language and the veri cation of temporal properties of a synchronous system.

Rocha, Camilo↗

NASA NTRS2013

NASA Tech Briefs, January 2013

Topics include: Single-Photon-Sensitive HgCdTe Avalanche Photodiode Detector; Surface-Enhanced Raman Scattering Using Silica Whispering-Gallery Mode Resonators; 3D Hail Size Distribution Interpolation/Extrapolation Algorithm; Color-Changing Sensors for Detecting the Presence of Hypergolic Fuels; Artificial Intelligence Software for Assessing Postural Stability; Transformers: Shape-Changing Space Systems Built with Robotic Textiles; Fibrillar Adhesive for Climbing Robots; Using Pre-Melted Phase Change Material to Keep Payloads in Space Warm for Hours without Power; Development of a Centrifugal Technique for the Microbial Bioburden Analysis of Freon (CFC-11); Microwave Sinterator Freeform Additive Construction System (MS-FACS); DSP/FPGA Design for a High-Speed Programmable S-Band Space Transceiver; On-Chip Power-Combining for High-Power Schottky Diode-Based Frequency Multipliers; FPGA Vision Data Architecture; Memory Circuit Fault Simulator; Ultra-Compact Transputer-Based Controller for High-Level, Multi-Axis Coordination; Regolith Advanced Surface Systems Operations Robot Excavator; Magnetically Actuated Seal; Hybrid Electrostatic/Flextensional Mirror for Lightweight, Large-Aperture, and Cryogenic Space Telescopes; System for Contributing and Discovering Derived Mission and Science Data; Remote Viewer for Maritime Robotics Software; Stackfile Database; Reachability Maps for In Situ Operations; JPL Space Telecommunications Radio System Operating Environment; RFI-SIM: RFI Simulation Package; ION Configuration Editor; Dtest Testing Software; IMPaCT - Integration of Missions, Programs, and Core Technologies; Integrated Systems Health Management (ISHM) Toolkit; Wind-Driven Wireless Networked System of Mobile Sensors for Mars Exploration; In Situ Solid Particle Generator; Analysis of the Effects of Streamwise Lift Distribution on Sonic Boom Signature; Rad-Tolerant, Thermally Stable, High-Speed Fiber-Optic Network for Harsh Environments; Towed Subsurface Optical Communications Buoy; High-Collection-Efficiency Fluorescence Detection Cell; Ultra-Compact, Superconducting Spectrometer-on-a-Chip at Submillimeter Wavelengths; UV Resonant Raman Spectrometer with Multi-Line Laser Excitation; Medicine Delivery Device with Integrated Sterilization and Detection; Ionospheric Simulation System for Satellite Observations and Global Assimilative Model Experiments - ISOGAME; Airborne Tomographic Swath Ice Sounding Processing System; flexplan: Mission Planning System for the Lunar Reconnaissance Orbiter; Estimating Torque Imparted on Spacecraft Using Telemetry; PowderSim: Lagrangian Discrete and Mesh-Free Continuum Simulation Code for Cohesive Soils; Multiple-Frame Detection of Subpixel Targets in Thermal Image Sequences; Metric Learning to Enhance Hyperspectral Image Segmentation; Basic Operational Robotics Instructional System; Sheet Membrane Spacesuit Water Membrane Evaporator; Advanced Materials and Manufacturing for Low-Cost, High-Performance Liquid Rocket Combustion Chambers; Motor Qualification for Long-Duration Mars Missions.

Source record↗

NASA NTRS2010

Symbolic Analysis of Concurrent Programs with Polymorphism

The current trend of multi-core and multi-processor computing is causing a paradigm shift from inherently sequential to highly concurrent and parallel applications. Certain thread interleavings, data input values, or combinations of both often cause errors in the system. Systematic verification techniques such as explicit state model checking and symbolic execution are extensively used to detect errors in such systems [7, 9]. Explicit state model checking enumerates possible thread schedules and input data values of a program in order to check for errors [3, 9]. To partially mitigate the state space explosion from data input values, symbolic execution techniques substitute data input values with symbolic values [5, 7, 6]. Explicit state model checking and symbolic execution techniques used in conjunction with exhaustive search techniques such as depth-first search are unable to detect errors in medium to large-sized concurrent programs because the number of behaviors caused by data and thread non-determinism is extremely large. We present an overview of abstraction-guided symbolic execution for concurrent programs that detects errors manifested by a combination of thread schedules and data values [8]. The technique generates a set of key program locations relevant in testing the reachability of the target locations. The symbolic execution is then guided along these locations in an attempt to generate a feasible execution path to the error state. This allows the execution to focus in parts of the behavior space more likely to contain an error.

Rungta, Neha Shyam↗

NASA NTRS2013

Rewriting Modulo SMT

Combining symbolic techniques such as: (i) SMT solving, (ii) rewriting modulo theories, and (iii) model checking can enable the analysis of infinite-state systems outside the scope of each such technique. This paper proposes rewriting modulo SMT as a new technique combining the powers of (i)-(iii) and ideally suited to model and analyze infinite-state open systems; that is, systems that interact with a non-deterministic environment. Such systems exhibit both internal non-determinism due to the system, and external non-determinism due to the environment. They are not amenable to finite-state model checking analysis because they typically are infinite-state. By being reducible to standard rewriting using reflective techniques, rewriting modulo SMT can both naturally model and analyze open systems without requiring any changes to rewriting-based reachability analysis techniques for closed systems. This is illustrated by the analysis of a real-time system beyond the scope of timed automata methods.

Rocha, Camilo↗

NASA NTRS2013

Safe Maneuvering Envelope Estimation Based on a Physical Approach

This paper discusses a computationally efficient algorithm for estimating the safe maneuvering envelope of damaged aircraft. The algorithm performs a robust reachability analysis through an optimal control formulation while making use of time scale separation and taking into account uncertainties in the aerodynamic derivatives. This approach differs from others since it is physically inspired. This more transparent approach allows interpreting data in each step, and it is assumed that these physical models based upon flight dynamics theory will therefore facilitate certification for future real life applications.

aerodynamics↗

NASA NTRS2013

A Framework to Debug Diagnostic Matrices

Diagnostics is an important concept in system health and monitoring of space operations. Many of the existing diagnostic algorithms utilize system knowledge in the form of diagnostic matrix (D-matrix, also popularly known as diagnostic dictionary, fault signature matrix or reachability matrix) gleaned from physical models. But, sometimes, this may not be coherent to obtain high diagnostic performance. In such a case, it is important to modify this D-matrix based on knowledge obtained from other sources such as time-series data stream (simulated or maintenance data) within the context of a framework that includes the diagnostic/inference algorithm. A systematic and sequential update procedure, diagnostic modeling evaluator (DME) is proposed to modify D-matrix and wrapper logic considering least expensive solution first. This iterative procedure includes conditions ranging from modifying 0s and 1s in the matrix, or adding/removing the rows (failure sources) columns (tests). We will experiment this framework on datasets from DX challenge 2009.

Model-based↗

NASA NTRS2015

On-Line Safe Flight Envelope Determination for Impaired Aircraft

The design and simulation of an on-line algorithm which estimates the safe maneuvering envelope of aircraft is discussed in this paper. The trim envelope is estimated using probabilistic methods and efficient high-fidelity model based computations of attainable equilibrium sets. From this trim envelope, a robust reachability analysis provides the maneuverability limitations of the aircraft through an optimal control formulation. Both envelope limits are presented to the flight crew on the primary flight display. In the results section, scenarios are considered where this adaptive algorithm is capable of computing online changes to the maneuvering envelope due to impairment. Furthermore, corresponding updates to display features on the primary flight display are provided to potentially inform the flight crew of safety critical envelope alterations caused by the impairment.

algorithms↗

NASA NTRS2015

Piloted Simulator Evaluation of Maneuvering Envelope Information for Flight Crew Awareness

The implementation and evaluation of an efficient method for estimating safe aircraft maneuvering envelopes are discussed. A Bayesian approach is used to produce a deterministic algorithm for estimating aerodynamic system parameters from existing noisy sensor measurements, which are then used to estimate the trim envelope through efficient high- fidelity model-based computations of attainable equilibrium sets. The safe maneuverability limitations are extended beyond the trim envelope through a robust reachability analysis derived from an optimal control formulation. The trim and maneuvering envelope limits are then conveyed to pilots through three axes on the primary flight display. To evaluate the new display features, commercial airline crews flew multiple challenging approach and landing scenarios in the full motion Advanced Concepts Flight Simulator at NASA Ames Research Center, as part of a larger research initiative to investigate the impact on the energy state awareness of the crew. Results show that the additional display features have the potential to significantly improve situational awareness of the flight crew.

maneuvers↗

NASA NTRS2017

Applying Graph Theory to Problems in Air Traffic Management

Graph theory is used to investigate three different problems arising in air traffic management. First, using a polynomial reduction from a graph partitioning problem, it is shown that both the airspace sectorization problem and its incremental counterpart, the sector combination problem are NP-hard, in general, under several simple workload models. Second, using a polynomial time reduction from maximum independent set in graphs, it is shown that for any fixed e, the problem of finding a solution to the minimum delay scheduling problem in traffic flow management that is guaranteed to be within n1-e of the optimal, where n is the number of aircraft in the problem instance, is NP-hard. Finally, a problem arising in precision arrival scheduling is formulated and solved using graph reachability. These results demonstrate that graph theory provides a powerful framework for modeling, reasoning about, and devising algorithmic solutions to diverse problems arising in air traffic management.

precision arrival scheduling↗

NASA NTRS2017

Traverse Planning with Temporal-Spatial Constraints

We present an approach to planning rover traverses in a domain that includes temporal-spatial constraints. We are using the NASA Resource Prospector mission as a reference mission in our research. The objective of this mission is to explore permanently shadowed regions at a Lunar pole. Most of the time the rover is required to avoid being in shadow. This requirement depends on where the rover is located and when it is at that location. Such a temporal-spatial constraint makes traverse planning more challenging for both humans and machines. We present a mixed-initiative traverse planner which addresses this challenge. This traverse planner is part of the Exploration Ground Data Systems (xGDS), which we have enhanced with new visualization features, new analysis tools, and new automation for path planning, in order to be applicable to the Re-source Prospector mission. The key concept that is the basis of the analysis tools and that supports the automated path planning is reachability in this dynamic environment due to the temporal-spatial constraints.

temporal-spatial constraints↗

NASA NTRS2017

Applying Graph Theory to Problems in Air Traffic Management

Graph theory is used to investigate three different problems arising in air traffic management. First, using a polynomial reduction from a graph partitioning problem, it isshown that both the airspace sectorization problem and its incremental counterpart, the sector combination problem are NP-hard, in general, under several simple workload models. Second, using a polynomial time reduction from maximum independent set in graphs, it is shown that for any fixed e, the problem of finding a solution to the minimum delay scheduling problem in traffic flow management that is guaranteed to be within n1-e of the optimal, where n is the number of aircraft in the problem instance, is NP-hard. Finally, a problem arising in precision arrival scheduling is formulated and solved using graph reachability. These results demonstrate that graph theory provides a powerful framework for modeling, reasoning about, and devising algorithmic solutions to diverse problems arising in air traffic management.

computational complexity↗

NASA NTRS2019

Mission Design for the Lunar Pallet Lander

Due to lighting conditions, the program decided to only fly to the north pole in June 2022 and south pole in December 2022. Starting with the June 2022 landing sites at the north pole, a trajectory scan was run for one landing per day for the latitudes from 85 up to 88 degrees at 0.5 degree increments. Each landing site was at lunar dawn, which determined the landing site’s longitude as described in the previous section. The results of the June 2022 scan showed that LPL had the capability to reach a landing site at least once per day for the region examined as see in in Figure 12. There appears to be a correlation between the landing site’s altitude and the propellant remaining above the lander’s FPR, Figure 13. This is most likely due to the >10 km altitude constraint at SRM burnout. This constraint was applied to keep the lander high above the lunar terrain to avoid mountains, but can be relaxed when the full terrain data is added. Figure 12. June 2022 Nominal Usable Propellant Remaining vs Landing Date/time Similarly, the December 2022 landing sites were run showing that LPL was also capable of reaching a landing site at the Moon at least once per day. Figure 14 shows the results of the December scan, however, there were 3 landing sites that LPL could not reach. Two were very low in altitude (-5 and -4 km in altitude), which looking at the altitude trends in Figure 15, indicates that these sites may not be feasible with the current mission design. It may be possible to achieve the low altitude landing sites by lowering the SRM burnout altitude constraint, but that requires detailed terrain modeling, planned for a future phase of the analysis. The third non-reachable landing site is most likely due to an optimization error, as its altitude was high enough, at -2 km, that it should not have been a problem for the lander to arrive there. More analysis is required to verify this observation.

Craig, Scott↗

NASA NTRS2018

Mars Helicopter Technology Demonstrator

Aerial exploration of Mars with helicopters could provide mission capabilities that go beyond that of orbiting satellites, landed spacecraft and rovers. Helicopters allow examination of Mars at visual resolutions comparable to landers and rovers but over much longer ranges. They could access and land at designated targets in a controlled manner and could be used to carry or retrieve small payloads. Helicopters could enhance rover missions by quickly scouting out safe traverse routes or providing reconnaissance on possible science target destinations and, as standalone systems, could be used to explore areas that may not be reachable by rovers. Mars helicopters may also be considered as elements of a sample return architecture where they could be used for timely retrieval of small science samples back to a Mars ascent vehicle for return to Earth. The challenge to helicopter use on Mars is the thin carbon dioxide atmosphere with approximately 1% of the density of Earth’s atmosphere. Much like the Sojourner rover on the Pathfinder mission paved the way for the Spirit, Opportunity, Curiosity and the Mars 2020 rovers, an initial demonstration on Mars is desirable so as to inform the development of future helicopter missions. The Jet Propulsion Laboratory is leading a collaborative effort with AeroVironment Inc., and NASA centers Ames, Langley and Glenn to develop a small helicopter as a technology demonstrator. In this paper we briefly describe the results of this effort including results from controlled free-flight of a full-scale (approx 850 g) prototype flown in a test chamber under Mars conditions, the design and development of the 1800 g (not-to-exceed mass) technology demonstrator helicopter, and the operation of the helicopter.

Balaram, J. (Bob)↗

NASA NTRS2019

IKOS: Sound Static Program Analysis

IKOS (Inference Kernel for Open Static Analyzers) is a static analyzer for C/C++ based on the theory of Abstract Interpretation. It can detect or prove the absence of runtime errors (e.g, buffer overflows, integer overflows, null pointer dereferences, etc.) in the source code. IKOS uses Abstract Interpretation techniques to compute an over-approximation of all the reachable states of the program, thus it cannot miss a bug. In this talk, I will give an overview of the tool, then show how to apply it to a large software. I will present ikos-view, a web interface to examine the analysis results. I will discuss about methods to improve the analysis, such as adding code annotations, modeling library functions, and avoiding specific code patterns.

Arthaud, Maxime↗

NASA NTRS2019

Static Analysis Using Abstract Interpretation

Lecture about abstract interpretation. This lecture starts with a brief introduction to validation and verification using formal methods. It then demonstrates IKOS (Inference Kernel for Open Static Analyzers), a static analyzer for C/C++ based on Abstract Interpretation. Then, it describes in details the theory of Abstract Interpretation, a mathematical framework to over-approximate the reachable states of a program.

Arthaud, Maxime↗

NASA NTRSDate not supplied

Visualization and 3D Mesh Generation for ASSEMBLERS Range of Motion

In an effort to create a base and foundation for ASSEMBLERS with an informed layout, data representing the range of motion of varying heights of Stewart platforms were analyzed. 3D shapes were generated first to be approximately representative of these data in the form of rotationally symmetric shells, making use of 2D alpha shapes to create a border that did not account for asymmetry inherent in the true range of motion. Further work was performed to generate mesh files more fully representative of reach, creating 3D alpha shapes based directly on point clouds generated from uniformly random platform positions. These shapes were initially not representative of the entire range of motion of a platform stack due to the low likelihood of the most extreme positions being added to a given point cloud but were more representative of the asymmetry inherent in the possible positions of a Stewart platform as they no longer relied on a single 2D contour. The same algorithm for generating 3D alpha shapes was then applied to point clouds designed to represent extreme positions, generating larger smooth shells with six clear planes of symmetry. All shells were converted to STLs to aid in further modeling of range of motion for base layouts and in visualizing reachable area for varying stack heights, successfully creating closed shells representative of typical and extreme positions for platform stacks of varying heights.

Jonah DeGuire Vanke↗