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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

TermGenie – a web-application for pattern-based ontology class generation

Biological ontologies are continually growing and improving from requests for new classes (terms) by biocurators. These ontology requests can frequently create bottlenecks in the biocuration process, as ontology developers struggle to keep up, while manually processing these requests and create classes. TermGenie allows biocurators to generate new classes based on formally specified design patterns or templates. The system is web-based and can be accessed by any authorized curator through a web browser. Automated rules and reasoning engines are used to ensure validity, uniqueness and relationship to pre-existing classes. In the last 4 years the Gene Ontology TermGenie generated 4715 new classes, about 51.4% of all new classes created. The immediate generation of permanent identifiers proved not to be an issue with only 70 (1.4%) obsoleted classes. Lastly, TermGenie is a web-based class-generation system that complements traditional ontology development tools. All classes added through pre-defined templates are guaranteed to have OWL equivalence axioms that are used for automatic classification and in some cases inter-ontology linkage. At the same time, the system is simple and intuitive and can be used by most biocurators without extensive training.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

New Two-Cylinder Prototype Demonstration and Concept Design of a Next Generation Class 3-6 Opposed Piston Engine (Final Report)

The objective of the project is to research, develop, and test an Opposed Piston (OP) engine prototype capable of ≥10% fuel economy improvement over a 2015 baseline diesel engine while meeting prevailing emissions standards and include a cost analysis of the proposed technologies that validates an operating cost payback of less than 2 years. Results: In direct comparison with the baseline Isuzu model, the OP engine exhibited a noteworthy average fuel economy improvement exceeding 12% across five distinct driving cycles, including the Interstate cycle, Congested interstate cycle, GM-city cycle, HWFET cycle, and FTP cycle, with Interstate cycle benefited the most.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

A first class constraint generates not a gauge transformation, but a bad physical change: The case of electromagnetism

In Dirac–Bergmann constrained dynamics, a first-class constraint typically does not alone generate a gauge transformation. By direct calculation it is found that each first-class constraint in Maxwell’s theory generates a change in the electric field E{sup →} by an arbitrary gradient, spoiling Gauss’s law. The secondary first-class constraint p{sup i},{sub i}=0 still holds, but being a function of derivatives of momenta (mere auxiliary fields), it is not directly about the observable electric field (a function of derivatives of A{sub μ}), which couples to charge. Only a special combination of the two first-class constraints, the Anderson–Bergmann–Castellani gauge generator G, leaves E{sup →} unchanged. Likewise only that combination leaves the canonical action invariant—an argument independent of observables. If one uses a first-class constraint to generate instead a canonical transformation, one partly strips the canonical coordinates of physical meaning as electromagnetic potentials, vindicating the Anderson–Bergmann Lagrangian orientation of interesting canonical transformations. The need to keep gauge-invariant the relation q-dot −(δH)/(δp) =−E{sub i}−p{sup i}=0 supports using the gauge generator and primary Hamiltonian rather than the separate first-class constraints and the extended Hamiltonian. Partly paralleling Pons’s criticism, it is shown that Dirac’s proof that a first-class primary constraint generates a gauge transformation, by comparing evolutions from identical initial data, cancels out and hence fails to detect the alterations made to the initial state. It also neglects the arbitrary coordinates multiplying the secondary constraints inside the canonical Hamiltonian. Thus the gauge-generating property has been ascribed to the primaries alone, not the primary–secondary team G. Hence the Dirac conjecture about secondary first-class constraints as generating gauge transformations rests upon a false presupposition about primary first-class constraints. Clarity about Hamiltonian electromagnetism will be useful for an analogous treatment of GR. - Highlights: • A first-class constraint changes the electric field E, spoiling Gauss’s law. • A first-class constraint does not leave the action invariant or preserve q,0−dH/dp. • The gauge generator preserves E,q,0−dH/dp, and the canonical action. • The error in proofs that first-class primaries generating gauge is shown. • Dirac’s conjecture about secondary first-class constraints is blocked.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Gigawatt-class radiation generated by a Ka-band overmoded Cherenkov-type high power millimeter wave generator

Particle simulation and experimental results are presented about a Ka-band overmoded Cherenkov-type high power millimeter wave generator in this paper. The relativistic electron beam with peak current of 8.4 kA was generated by a pulsed power accelerator working at the voltage of 625 kV, which was guided by an axial magnetic field of 1.05 T and transported through the beam-wave interaction structures. After careful calibration, the microwave power radiated in the far field was as high as about 500 MW, with a frequency of 32.1 GHz and a pulse width of 20 ns. The radiation mode was well controlled to be TM{sub 0n} mode.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS2009

Emittance Measurements Relevant to a 250 W(sub t) Class RTPV Generator for Space Exploration

A proposed 250 Wt Radioisotope Thermophotovoltaic (RTPV) power system for utilization in lunar exploration and the subsequent exploration of Mars is described. Details of emitter selection are outlined for use in a maintenance free power supply that is productive over a 14-year mission life. Thorough knowledge of a material s spectral emittance is essential for accurate modeling of the RTPV system. While sometimes treated as a surface effect, emittance involves radiation from within a material. This creates a complex thermal gradient which is a combination of conductive and radiative heat transfer mechanisms. Emittance data available in the literature is a valuable resource but it is particular to the test sample s physical characteristics and the test environment. Considerations for making spectral emittance measurements relevant to RTPV development are discussed. Measured spectral emittance data of refractory emitter materials is given. Planned measurement system modifications to improve relevance to the current project are presented.

Wolford, Dave↗
DOE OSTI2025

GridSTIX

SF-25-112 Grid-STIX is a comprehensive extension of the STIX (Structured Threat Information Expression) 2.1 ontology specifically designed for electrical grid cybersecurity applications. This ontology provides a standardized, machine-readable framework for modeling grid assets, operational technology devices, threats, vulnerabilities, supply chain risks, and security relationships in electrical power systems. ## Key Features - **Comprehensive Grid Coverage**: Physical assets, OT devices, grid components, sensors, and energy storage systems - **Zero Trust Architecture**: Policy decision points, enforcement points, trust brokers, and continuous monitoring - **AMI Infrastructure**: Advanced metering networks, head-end systems, mesh gateways, and MDM systems - **Advanced Security Modeling**: Attack patterns, vulnerabilities, mitigations, and supply chain risks - **Critical Grid Relationships**: Power flow, protection, control, and synchronization relationships - **Supply Chain Security**: Supplier modeling, country of origin tracking, and risk assessment - **Protocol Support**: DNP3, Modbus, IEC 61850, IEC 60870-5-104, OPC-UA, and IEEE standards - **Python Code Generation**: Automated STIX-compliant Python class generation from ontologies - **Interactive Visualization**: Enhanced HTML network graphs with grid-specific categorization - **STIX 2.1 Compliance**: Full compatibility with STIX threat intelligence ecosystem

Blakely, Benjamin [Argonne National Laboratory (AN↗
DOE OSTI2018

Performance Excellence Lean Six Sigma

Lean Six Sigma (LSS) organization at Y-12 sponsors the deployment of Performance Enterprise System (PES) and provides continuous improvement facilitation and training for the Y-12 site. Six- Question Survey was issued to 100 Y-12 employees at random, with the option to report one’s organization. Goals included: To gain an insight of Y-12 employees knowledge of PES & the Lean Six Sigma group • Generate employee desire to take PES class • Generate employee desire to perform continuous improvement.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2014

The Use of Redundancy to Improve Reliability of Deep Space Missions Using Stirling Radioisotope Generator Power Sources

This study will look at the 140 We class generator as originally envisioned for the ASRG and a larger generator that is scaled up to use four times the fuel. The results discussed below quantify the effect of the use of smaller generators and indicates that a scheme that makes use of several smaller generators enhances the system reliability and allows for more graceful degradation.

Bolotin, Gary↗
NASA NTRS1992

Membership generation using multilayer neural network

There has been intensive research in neural network applications to pattern recognition problems. Particularly, the back-propagation network has attracted many researchers because of its outstanding performance in pattern recognition applications. In this section, we describe a new method to generate membership functions from training data using a multilayer neural network. The basic idea behind the approach is as follows. The output values of a sigmoid activation function of a neuron bear remarkable resemblance to membership values. Therefore, we can regard the sigmoid activation values as the membership values in fuzzy set theory. Thus, in order to generate class membership values, we first train a suitable multilayer network using a training algorithm such as the back-propagation algorithm. After the training procedure converges, the resulting network can be treated as a membership generation network, where the inputs are feature values and the outputs are membership values in the different classes. This method allows fairly complex membership functions to be generated because the network is highly nonlinear in general. Also, it is to be noted that the membership functions are generated from a classification point of view. For pattern recognition applications, this is highly desirable, although the membership values may not be indicative of the degree of typicality of a feature value in a particular class.

Kim, Jaeseok↗
DOE OSTI2016

Collectively loading programs in a multiple program multiple data environment

Techniques are disclosed for loading programs efficiently in a parallel computing system. In one embodiment, nodes of the parallel computing system receive a load description file which indicates, for each program of a multiple program multiple data (MPMD) job, nodes which are to load the program. The nodes determine, using collective operations, a total number of programs to load and a number of programs to load in parallel. The nodes further generate a class route for each program to be loaded in parallel, where the class route generated for a particular program includes only those nodes on which the program needs to be loaded. For each class route, a node is selected using a collective operation to be a load leader which accesses a file system to load the program associated with a class route and broadcasts the program via the class route to other nodes which require the program.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Collectively loading programs in a multiple program multiple data environment

Techniques are disclosed for loading programs efficiently in a parallel computing system. In one embodiment, nodes of the parallel computing system receive a load description file which indicates, for each program of a multiple program multiple data (MPMD) job, nodes which are to load the program. The nodes determine, using collective operations, a total number of programs to load and a number of programs to load in parallel. The nodes further generate a class route for each program to be loaded in parallel, where the class route generated for a particular program includes only those nodes on which the program needs to be loaded. For each class route, a node is selected using a collective operation to be a load leader which accesses a file system to load the program associated with a class route and broadcasts the program via the class route to other nodes which require the program.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1979

Evaluation of three techniques for classifying urban land cover patterns using LANDSAT MSS data

Three computer quantitative techniques for determining urban land cover patterns are evaluated. The techniques examined deal with the selection of training samples by an automated process, the overlaying of two scenes from different seasons of the year, and the use of individual pixels as training points. Evaluation is based on the number and type of land cover classes generated and the marks obtained from an accuracy test. New Orleans, Louisiana and its environs form the study area.

Baumann, P. R.↗
NASA NTRS1971

A New All Solid State Approach to Gaseous Pollutant Detection

Recent efforts in our laboratories have concentrated on the development of an all solid state gas sensor, by combining solid electrolyte (ion exchange membrane) technology with advanced thin film deposition processes. With the proper bias magnitude and polarity these miniature electro-chemical,cells show remarkable current responses for many common pollution gases. Current activity is now focused on complementing a multiple array (matrix) of these solid state sensors, with a digital electronic scanner device possessing "scan-compare-identify-alarm: capability. This innovative approach to multi-component pollutant gas analysis may indeed be the advanced prototype for the "third generation" class of pollution analysis instrumentation so urgently needed in the decade ahead.

Brown, V.↗
NASA NTRS2010

FeatherSail - The Next Generation Nano-Class Sail Vehicle

Solar sail propulsion is a concept, which will soon become a reality. Solar sailing is a method of space flight propulsion, which utilizes the light photons to propel spacecrafts through the vacuum of space. Solar sail vehicles have generally been designed to have a very large area. This requires significant time and expenditures to develop, test and launch such a vehicle. Several notable solar propulsion missions and experiments have been performed and more are still in the development stage. This concept will be tested in the near future with the launch of the NanoSail-D satellite. NanoSail-D is a nano-class satellite, less than 10kg, which will deploy a thin lightweight sheet of reflective material used to propel the satellite in its low earth orbit. The NanoSail-D solar sail design is used for the basic design concept for the next generation of nanoclass solar sail vehicles. The FeatherSail project was started to develop a solar sail vehicle with the capability to perform attitude control via rotating or feathering the solar sails. In addition to using the robust deployment method of the NanoSail-D system, the FeatherSail design incorporates other novel technologies. These technologies include deployable thin film solar arrays and low power, low temperature Silicon-Germanium electronics. Together, these three technological advancements provide a starting point for smaller class sail vehicles. These smaller solar sail vehicles provide a capability for inexpensive missions to explore beyond the realms of low earth orbit.

Alhom, Dave C.↗
DOE OSTI2018

Factorization of generalized γ-generating matrices

The class of γ-generating matrices and its subclasses of regular and singular γ-generating matrices were introduced by D. Z. Arov in [8], where it was shown that every γ-generating matrix admits an essentially unique regular–singular factorization. The class of generalized γ-generating matrices was introduced in [14, 20]. In the present paper, subclasses of singular and regular generalized –generating matrices are introduced and studied. As the main result, a theorem of existence of the regular–singular factorization for a rational generalized γ-generating matrix is proved.

97 MATHEMATICS AND COMPUTING↗