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All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

NASA Tech Briefs, August 2006

Topics covered include: Measurement and Controls Data Acquisition System IMU/GPS System Provides Position and Attitude Data Using Artificial Intelligence to Inform Pilots of Weather Fast Lossless Compression of Multispectral-Image Data Developing Signal-Pattern-Recognition Programs Implementing Access to Data Distributed on Many Processors Compact, Efficient Drive Circuit for a Piezoelectric Pump; Dual Common Planes for Time Multiplexing of Dual-Color QWIPs; MMIC Power Amplifier Puts Out 40 mW From 75 to 110 GHz; 2D/3D Visual Tracker for Rover Mast; Adding Hierarchical Objects to Relational Database General-Purpose XML-Based Information Managements; Vaporizable Scaffolds for Fabricating Thermoelectric Modules; Producing Quantum Dots by Spray Pyrolysis; Mobile Robot for Exploring Cold Liquid/Solid Environments; System Would Acquire Core and Powder Samples of Rocks; Improved Fabrication of Lithium Films Having Micron Features; Manufacture of Regularly Shaped Sol-Gel Pellets; Regulating Glucose and pH, and Monitoring Oxygen in a Bioreactor; Satellite Multiangle Spectropolarimetric Imaging of Aerosols; Interferometric System for Measuring Thickness of Sea Ice; Microscale Regenerative Heat Exchanger Protocols for Handling Messages Between Simulation Computers Statistical Detection of Atypical Aircraft Flights NASA's Aviation Safety and Modeling Project Multimode-Guided-Wave Ultrasonic Scanning of Materials Algorithms for Maneuvering Spacecraft Around Small Bodies Improved Solar-Radiation-Pressure Models for GPS Satellites Measuring Attitude of a Large, Flexible, Orbiting Structure

Source record↗
NASA NTRS1999

Earth Science Data Archive and Access at the NASA/Goddard Space Flight Center Distributed Active Archive Center (DAAC)

The Goddard Distributed Active Archive Center (DAAC), as an integral part of the Earth Observing System Data and Information System (EOSDIS), is the official source of data for several important earth remote sensing missions. These include the Sea-viewing Wide-Field-of-view Sensor (SeaWiFS) launched in August 1997, the Tropical Rainfall Measuring Mission (TRMM) launched in November 1997, and the Moderate Resolution Imaging Spectroradiometer (MODIS) scheduled for launch in mid 1999 as part of the EOS AM-1 instrumentation package. The data generated from these missions supports a host of users in the hydrological, land biosphere and oceanographic research and applications communities. The volume and nature of the data present unique challenges to an Earth science data archive and distribution system such as the DAAC. The DAAC system receives, archives and distributes a large number of standard data products on a daily basis, including data files that have been reprocessed with updated calibration data or improved analytical algorithms. A World Wide Web interface is provided allowing interactive data selection and automatic data subscriptions as distribution options. The DAAC also creates customized and value-added data products, which allow additional user flexibility and reduced data volume. Another significant part of our overall mission is to provide ancillary data support services and archive support for worldwide field campaigns designed to validate the results from the various satellite-derived measurements. In addition to direct data services, accompanying documentation, WWW links to related resources, support for EOSDIS data formats, and informed response to inquiries are routinely provided to users. The current GDAAC WWW search and order system is being restructured to provide users with a simplified, hierarchical access to data. Data Browsers have been developed for several data sets to aid users in ordering data. These Browsers allow users to specify spatial, temporal, and other parameter criteria in searching for and previewing data.

Leptoukh, Gregory↗
NASA NTRS1992

ISE: An Integrated Search Environment. The manual

Integrated Search Environment (ISE), a software package that implements hierarchical searches with meta-control, is described in this manual. ISE is a collection of problem-independent routines to support solving searches. Mainly, these routines are core routines for solving a search problem and they handle the control of searches and maintain the statistics related to searches. By separating the problem-dependent and problem-independent components in ISE, new search methods based on a combination of existing methods can be developed by coding a single master control program. Further, new applications solved by searches can be developed by coding the problem-dependent parts and reusing the problem-independent parts already developed. Potential users of ISE are designers of new application solvers and new search algorithms, and users of experimental application solvers and search algorithms. The ISE is designed to be user-friendly and information rich. In this manual, the organization of ISE is described and several experiments carried out on ISE are also described.

Chu, Lon-Chan↗
NASA NTRS1990

Development of a knoweledge-based system for validating finite element models

The finite element modeling of an airframe structure requires knowledge of general purpose programs such as NASTRAN as well as a detailed understanding of the airframe structure. Due to the sophistication of general purpose programs such as NASTRAN, a substantial investment in time and effort is required to gain expertise in using them effectively. This paper describes the development of an expert system used in the validation of NASTRAN based finite element models. Experts in the NASTRAN based finite element modeling of airframe structures were interviewed to document, understand, and represent their knowledge and reasoning in the expert system. Finite element stress analysis and internal loads reports generated by the experts were reviewed to determine expert resolution of problem areas. As a result, areas requiring expert assistance in the modeling of the airframe structures were identified. The finite element input data is represented as a set of 'facts'. A rule based representation is used to code the expert knowledge. A hierarchical set of rules are applied. The expert system first acts as an intelligent front end to insure that all the prerequisites needed to perform the analysis are present. This includes material properties, boundary conditions, and connectivity information. The next step examines if incompatible sets of elements are connected. The succeeding step examines if the specific airframe component is modeled by the appropriate set of elements. The next and final step examines if the airframe members used are adequate to represent the anticipated state of stress. The expert system is designed to inform the user the severity of the error, the likely consequence and possible remedial action. The shell used in the development of the expert system is CLIPS. CLIPS contains a forward chaining inference engine based on the Rete algorithm. CLIPS may be implemented on most personal computers as well as mini computers and mainframes. The approach taken is general and can be implemented using commercially available expert system shells.

Munir, N. I.↗
NASA NTRS2017

Generating Real-Time Robotics Control Software from SysML

In this paper, we outline an approach for autogenerating real-time robotics control code from hierarchical state machines and hardware configurations encoded in Systems Modeling Language (SysML). We propose a software architecture that provides an abstract SysML layer with access to device state information and a set of primitive device commands, such as move actuator and release brake, allowing a user to build up a complete functional state machine directly in SysML. The SysML diagram is then exported to a standard SCXML file format and subsequently used to auto-generate hardware control code. Once this architecture is in place, the only explicit code elements that need to be written are the primitive device commands, which can be easily unit tested and reused across different systems. The motivation for this work was the need for a test bed that enables the rapid prototyping of mechanisms and control algorithms for a spacecraft that could ultimately be used for preparing Martian rock samples for their return to Earth. To this end, our software system was also designed to allow for the run-time specification of the hardware layout in SysML, with the hardware-level control functions kept agnostic to the specific parameters or communication bus of any particular device. Further, we outline a system for specifying both the state machine and hardware configuration in the MagicDraw IDE in such a way that the system can be simulated before any code is generated. The resultant software system is easy to debug, understand, and allows users to choose how much information is encoded as a visual or text-based representation.

Godart, Peter↗
NASA NTRSDate not supplied

U.S. IMERG Status

The U.S. Science Team’s Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG) product provides estimates of surface precipitation rate and related information on a global 0.1° half-hour grid. It is run three times at increasingly longer latency and higher information input to serve different communities. This presentation will briefly summarize the major upgrades included in Version 07. The Goddard Profiling (GPROF) algorithm (applied to passive microwave sensor data from the GPM virtual constellation) and the Combined Radar-Radiometer Algorithm (CORRA) that provide input to IMERG V07 are both improved, and the new Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Dynamic Infrared Rain Rate (PDIR) algorithm is being applied to infrared data, which employs an additional, warmer infrared temperature threshold than the previous infrared scheme and a deep neural network. V07 has improved bias performance as a result of calibrations that now employ the entire swath widths of CORRA and GPROF GPM Microwave Imager precipitation estimates. As well, time continuity in precipitation features is improved as a result of changes to the Kalman filter that approximately preserve the local histogram of precipitation rates (Scheme for Histogram Adjustment with Ranked Precipitation Estimates in the Neighborhood, or SHARPEN), and that better account for differences in sensor performance. A long-standing bug in the geolocation that shifted grid values 0.1° to the east in the latitude band 70°N-S has been corrected. Other changes in V07 include a hierarchical selection among motion vector sources to address deficiencies in the precipitation propagation near orography, an update to the precipitation phase specification for improved consistency with current inputs, and a renewed effort to implement climatological gauge adjustment to the near-real-time Runs. Early evaluations of V07 IMERG show interesting behavior across the TRMM orbit boost that is highly relevant to the planned orbit boost for the GPM Core observatory.

GPM↗
NASA NTRS2007

Decision-Tree Formulation With Order-1 Lateral Execution

A compact symbolic formulation enables mapping of an arbitrarily complex decision tree of a certain type into a highly computationally efficient multidimensional software object. The type of decision trees to which this formulation applies is that known in the art as the Boolean class of balanced decision trees. Parallel lateral slices of an object created by means of this formulation can be executed in constant time considerably less time than would otherwise be required. Decision trees of various forms are incorporated into almost all large software systems. A decision tree is a way of hierarchically solving a problem, proceeding through a set of true/false responses to a conclusion. By definition, a decision tree has a tree-like structure, wherein each internal node denotes a test on an attribute, each branch from an internal node represents an outcome of a test, and leaf nodes represent classes or class distributions that, in turn represent possible conclusions. The drawback of decision trees is that execution of them can be computationally expensive (and, hence, time-consuming) because each non-leaf node must be examined to determine whether to progress deeper into a tree structure or to examine an alternative. The present formulation was conceived as an efficient means of representing a decision tree and executing it in as little time as possible. The formulation involves the use of a set of symbolic algorithms to transform a decision tree into a multi-dimensional object, the rank of which equals the number of lateral non-leaf nodes. The tree can then be executed in constant time by means of an order-one table lookup. The sequence of operations performed by the algorithms is summarized as follows: 1. Determination of whether the tree under consideration can be encoded by means of this formulation. 2. Extraction of decision variables. 3. Symbolic optimization of the decision tree to minimize its form. 4. Expansion and transformation of all nested conjunctive-disjunctive paths to a flattened conjunctive form composed only of equality checks when possible. If each reduced conjunctive form contains only equality checks and all of these forms use the same variables, then the decision tree can be reduced to an order-one operation through a table lookup. The speedup to order one is accomplished by distributing each decision variable over a surface of a multidimensional object by mapping the equality constant to an index

James, Mark↗
NASA NTRS1996

SAM-FS: LSC's New Solaris-Based Storage Management Product

SAM-FS is a full featured hierarchical storage management (HSM) device that operates as a file system on Solaris-based machines. The SAM-FS file system provides the user with all of the standard UNIX system utilities and calls, and adds some new commands, i.e. archive, release, stage, sls, sfind, and a family of maintenance commands. The system also offers enhancements such as high performance virtual disk read and write, control of the disk through an extent array, and the ability to dynamically allocate block size. SAM-FS provides 'archive sets' which are groupings of data to be copied to secondary storage. In practice, as soon as a file is written to disk, SAM-FS will make copies onto secondary media. SAM-FS is a scalable storage management system. The system can manage millions of files per system, though this is limited today by the speed of UNIX and its utilities. In the future, a new search algorithm will be implemented that will remove logical and performance restrictions on the number of files managed.

Angell, Kent↗
NASA NTRS1995

Introduction to Penelope

A formal program verification is a (mathematical) proof that a program executed according to its intended model meets some specification. This proves that the algorithm defined by the program is correct in the precise technical sense of being consistent with a particular specification. A program correct in this sense is free from a large and important class of errors, even though its behavior may still produce unintended results--either because the implementation of the programming language itself does not match the model of execution, or because the specification does not correctly express the user's intentions. Penelope is a prototype system for interactively developing and verifying programs that are written in a rich subset of sequential Ada. Penelope can be used to develop a program and its correctness proof incrementally, and in concert with one another. Incrementality is used in a number of ways to help make verification more tractable and more productive. For example, if an already-verified program is modified, one can attempt to prove the modified version by replaying and modifying the original verification. Penelope's specification language, Larch/Ada, belongs to the family of Larch interface languages. Larch/Ada scales up properly, in the sense that it is demonstrably sound to decompose a system hierarchically and reason locally about the implementation of each piece. Penelope has been applied in various demonstration projects--for specification (guidance control, distributed operating systems), verification (of off-the-shelf code), and formal development (by non-expert as well as expert users). Some features of Penelope have been embodied in Ada Wise, a lint-like non-interactive tool that warns of the potential for certain dynamic semantic errors in Ada programs.

Guaspari, David↗
NASA NTRS1989

A Boltzmann machine for the organization of intelligent machines

In the present technological society, there is a major need to build machines that would execute intelligent tasks operating in uncertain environments with minimum interaction with a human operator. Although some designers have built smart robots, utilizing heuristic ideas, there is no systematic approach to design such machines in an engineering manner. Recently, cross-disciplinary research from the fields of computers, systems AI and information theory has served to set the foundations of the emerging area of the design of intelligent machines. Since 1977 Saridis has been developing an approach, defined as Hierarchical Intelligent Control, designed to organize, coordinate and execute anthropomorphic tasks by a machine with minimum interaction with a human operator. This approach utilizes analytical (probabilistic) models to describe and control the various functions of the intelligent machine structured by the intuitively defined principle of Increasing Precision with Decreasing Intelligence (IPDI) (Saridis 1979). This principle, even though resembles the managerial structure of organizational systems (Levis 1988), has been derived on an analytic basis by Saridis (1988). The purpose is to derive analytically a Boltzmann machine suitable for optimal connection of nodes in a neural net (Fahlman, Hinton, Sejnowski, 1985). Then this machine will serve to search for the optimal design of the organization level of an intelligent machine. In order to accomplish this, some mathematical theory of the intelligent machines will be first outlined. Then some definitions of the variables associated with the principle, like machine intelligence, machine knowledge, and precision will be made (Saridis, Valavanis 1988). Then a procedure to establish the Boltzmann machine on an analytic basis will be presented and illustrated by an example in designing the organization level of an Intelligent Machine. A new search technique, the Modified Genetic Algorithm, is presented and proved to converge to the minimum of a cost function. Finally, simulations will show the effectiveness of a variety of search techniques for the intelligent machine.

Moed, Michael C.↗
NASA NTRS2007

Generative Representations for Automated Design of Robots

A method of automated design of complex, modular robots involves an evolutionary process in which generative representations of designs are used. The term generative representations as used here signifies, loosely, representations that consist of or include algorithms, computer programs, and the like, wherein encoded designs can reuse elements of their encoding and thereby evolve toward greater complexity. Automated design of robots through synthetic evolutionary processes has already been demonstrated, but it is not clear whether genetically inspired search algorithms can yield designs that are sufficiently complex for practical engineering. The ultimate success of such algorithms as tools for automation of design depends on the scaling properties of representations of designs. A nongenerative representation (one in which each element of the encoded design is used at most once in translating to the design) scales linearly with the number of elements. Search algorithms that use nongenerative representations quickly become intractable (search times vary approximately exponentially with numbers of design elements), and thus are not amenable to scaling to complex designs. Generative representations are compact representations and were devised as means to circumvent the above-mentioned fundamental restriction on scalability. In the present method, a robot is defined by a compact programmatic form (its generative representation) and the evolutionary variation takes place on this form. The evolutionary process is an iterative one, wherein each cycle consists of the following steps: 1. Generative representations are generated in an evolutionary subprocess. 2. Each generative representation is a program that, when compiled, produces an assembly procedure. 3. In a computational simulation, a constructor executes an assembly procedure to generate a robot. 4. A physical-simulation program tests the performance of a simulated constructed robot, evaluating the performance according to a fitness criterion to yield a figure of merit that is fed back into the evolutionary subprocess of the next iteration. In comparison with prior approaches to automated evolutionary design of robots, the use of generative representations offers two advantages: First, a generative representation enables the reuse of components in regular and hierarchical ways and thereby serves a systematic means of creating more complex modules out of simpler ones. Second, the evolved generative representation may capture intrinsic properties of the design problem, so that variations in the representations move through the design space more effectively than do equivalent variations in a nongenerative representation. This method has been demonstrated by using it to design some robots that move, variously, by walking, rolling, or sliding. Some of the robots were built (see figure). Although these robots are very simple, in comparison with robots designed by humans, their structures are more regular, modular, hierarchical, and complex than are those of evolved designs of comparable functionality synthesized by use of nongenerative representations.

Homby, Gregory S.↗
NASA NTRS2012

HyDE Framework for Stochastic and Hybrid Model-Based Diagnosis

Hybrid Diagnosis Engine (HyDE) is a general framework for stochastic and hybrid model-based diagnosis that offers flexibility to the diagnosis application designer. The HyDE architecture supports the use of multiple modeling paradigms at the component and system level. Several alternative algorithms are available for the various steps in diagnostic reasoning. This approach is extensible, with support for the addition of new modeling paradigms as well as diagnostic reasoning algorithms for existing or new modeling paradigms. HyDE is a general framework for stochastic hybrid model-based diagnosis of discrete faults; that is, spontaneous changes in operating modes of components. HyDE combines ideas from consistency-based and stochastic approaches to model- based diagnosis using discrete and continuous models to create a flexible and extensible architecture for stochastic and hybrid diagnosis. HyDE supports the use of multiple paradigms and is extensible to support new paradigms. HyDE generates candidate diagnoses and checks them for consistency with the observations. It uses hybrid models built by the users and sensor data from the system to deduce the state of the system over time, including changes in state indicative of faults. At each time step when observations are available, HyDE checks each existing candidate for continued consistency with the new observations. If the candidate is consistent, it continues to remain in the candidate set. If it is not consistent, then the information about the inconsistency is used to generate successor candidates while discarding the candidate that was inconsistent. The models used by HyDE are similar to simulation models. They describe the expected behavior of the system under nominal and fault conditions. The model can be constructed in modular and hierarchical fashion by building component/subsystem models (which may themselves contain component/ subsystem models) and linking them through shared variables/parameters. The component model is expressed as operating modes of the component and conditions for transitions between these various modes. Faults are modeled as transitions whose conditions for transitions are unknown (and have to be inferred through the reasoning process). Finally, the behavior of the components is expressed as a set of variables/ parameters and relations governing the interaction between the variables. The hybrid nature of the systems being modeled is captured by a combination of the above transitional model and behavioral model. Stochasticity is captured as probabilities associated with transitions (indicating the likelihood of that transition being taken), as well as noise on the sensed variables.

Narasimhan, Sriram↗
NASA NTRS2013

Enigma Version 12

Enigma Version 12 software combines model building, animation, and engineering visualization into one concise software package. Enigma employs a versatile user interface to allow average users access to even the most complex pieces of the application. Using Enigma eliminates the need to buy and learn several software packages to create an engineering visualization. Models can be created and/or modified within Enigma down to the polygon level. Textures and materials can be applied for additional realism. Within Enigma, these models can be combined to create systems of models that have a hierarchical relationship to one another, such as a robotic arm. Then these systems can be animated within the program or controlled by an external application programming interface (API). In addition, Enigma provides the ability to use plug-ins. Plugins allow the user to create custom code for a specific application and access the Enigma model and system data, but still use the Enigma drawing functionality. CAD files can be imported into Enigma and combined to create systems of computer graphics models that can be manipulated with constraints. An API is available so that an engineer can write a simulation and drive the computer graphics models with no knowledge of computer graphics. An animation editor allows an engineer to set up sequences of animations generated by simulations or by conceptual trajectories in order to record these to highquality media for presentation. Enigma Version 12 Lyndon B. Johnson Space Center, Houston, Texas 28 NASA Tech Briefs, September 2013 Planetary Protection Bioburden Analysis Program NASA's Jet Propulsion Laboratory, Pasadena, California This program is a Microsoft Access program that performed statistical analysis of the colony counts from assays performed on the Mars Science Laboratory (MSL) spacecraft to determine the bioburden density, 3-sigma biodensity, and the total bioburdens required for the MSL prelaunch reports. It also contains numerous tools that report the data in various ways to simplify the reports required. The program performs all the calculations directly in the MS Access program. Prior to this development, the data was exported to large Excel files that had to be cut and pasted to provide the desired results. The program contains a main menu and a number of submenus. Analyses can be performed by using either all the assays, or only the accountable assays that will be used in the final analysis. There are three options on the first menu: either calculate using (1) the old MER (Mars Exploration Rover) statistics, (2) the MSL statistics for all the assays, or This software implements penetration limit equations for common micrometeoroid and orbital debris (MMOD) shield configurations, windows, and thermal protection systems. Allowable MMOD risk is formulated in terms of the probability of penetration (PNP) of the spacecraft pressure hull. For calculating the risk, spacecraft geometry models, mission profiles, debris environment models, and penetration limit equations for installed shielding configurations are required. Risk assessment software such as NASA's BUMPERII is used to calculate mission PNP; however, they are unsuitable for use in shield design and preliminary analysis studies. The software defines a single equation for the design and performance evaluation of common MMOD shielding configurations, windows, and thermal protection systems, along with a description of their validity range and guidelines for their application. Recommendations are based on preliminary reviews of fundamental assumptions, and accuracy in predicting experimental impact test results. The software is programmed in Visual Basic for Applications for installation as a simple add-in for Microsoft Excel. The user is directed to a graphical user interface (GUI) that requires user inputs and provides solutions directly in Microsoft Excel workbooks. This work was done by Shannon Ryan of the USRA Lunar and Planetary Institute for Johnson Space Center. Further information is contained in a TSP (see page 1). MSC- 24582-1 Micrometeoroid and Orbital Debris (MMOD) Shield Ballistic Limit Analysis Program Lyndon B. Johnson Space Center, Houston, Texas Commercially, because it is so generic, Enigma can be used for almost any project that requires engineering visualization, model building, or animation. Models in Enigma can be exported to many other formats for use in other applications as well. Educationally, Enigma is being used to allow university students to visualize robotic algorithms in a simulation mode before using them with actual hardware.

Shores, David↗