Search NASA⌕ Search

SEARCH · Search NASA

Results for “Class generation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 433 records · Page 24

Fiber-optic rotation sensors

Possible approaches to the design of fiber optic inertial frame rotation sensors based on the Sagnac effect are reviewed under two general categories: (1) single frequency interferometers which generate a phase shift proportional to inertial rotation rate, and (2) dual frequency interferometers for which the beat frequency is proportional to rotation rate. The principal variations within the single frequency class involve the way in which the nonreciprocal phase bias is used and techniques for generating the nonreciprocal bias. Within the dual frequency class, the various approaches differ principally in the way in which the counter-circulating frequencies are established.

Goss, W. C.↗

Pioneer-class mission capabilities

Pioneer Jupiter spacecraft, noting low weight, radioisotope thermoelectric generators and gyroscopic stabilization by spinning with antenna pointed at earth

Jackson, R. W.↗

Candidate Formulary Development for Exploration Missions

An interdisciplinary team of clinician, pharmacist, and system engineer subject matter experts (SMEs) collaborated to match pharmaceutical resources to the medical conditions anticipated to occur during exploration class missions. This effort began by using a SME generated Exploration Medical Conditions List and the associated medical system capabilities necessary to treat them. Using the systems engineering software MagicDraw™ and knowledge of pharmaceutical use and efficacy in spaceflight, the team traced appropriate medications to the medical conditions. These traces were used to pilot the process for generating a candidate formulary for level of care 4 and level of care 5 medical systems. This presentation will discuss the collaborative efforts of the team as they developed the content, detail the challenges of utilizing systems engineering software to describe clinical resources, and provide an overview of how the candidate medication formulary for exploration class missions was developed. It will also discuss how the lessons learned from this pilot effort can be applied to streamline future work.

S. Kurian↗

Clang UPC Compiler (Clang UPC) v3.9.1-1

Clang Unified Parallel C (Clang UPC) provides a compilation and execution environment for programs written in the UPC (Unified Parallel C) language. The Clang UPC compiler extends the capabilities of the Clang LLVM C compiler to comply with the UPC Language Specification version 1.3. It includes support for UPC collectives and a configurable pointer-to-shared representation. The compiler generates programs that run on a wide variety of systems ranging from workstations to leadership-class supercomputers, in conjunction with the Berkeley UPC runtime and GASNet communication system. This compiler generates assembly code / object code directly for Intel processors and IBM PowerPC.

Hargrove, Paul↗

RockFlow: Fast Generation of Synthetic Source Rock Images Using Generative Flow Models

Image-based evaluation methods are a valuable tool for source rock characterization. The time and resources needed to obtain images has spurred development of machine-learning generative models to create synthetic images of pore structure and rock fabric from limited image data. While generative models have shown success, existing methods for generating 3D volumes from 2D training images are restricted to binary images and grayscale volume generation requires 3D training data. Shale characterization relies on 2D imaging techniques such as scanning electron microscopy (SEM), and grayscale values carry important information about porosity, kerogen content, and mineral composition of the shale. Here, we introduce RockFlow, a method based on generative flow models that creates grayscale volumes from 2D training data. We apply RockFlow to baseline binary micro-CT image volumes and compare performance to a previously proposed model. We also show the extension of our model to 2D grayscale data by generating grayscale image volumes from 2D SEM and dual modality nanoscale shale images. The results show that our method underestimates the porosity and surface area on the binary baseline datasets but is able to generate realistic grayscale image volumes for shales. With improved binary data preprocessing, we believe that our model is capable of generating synthetic porous media volumes for a very broad class of rocks from shale to carbonates to sandstone.

58 GEOSCIENCES↗

A possibilistic approach to clustering

Fuzzy clustering has been shown to be advantageous over crisp (or traditional) clustering methods in that total commitment of a vector to a given class is not required at each image pattern recognition iteration. Recently fuzzy clustering methods have shown spectacular ability to detect not only hypervolume clusters, but also clusters which are actually 'thin shells', i.e., curves and surfaces. Most analytic fuzzy clustering approaches are derived from the 'Fuzzy C-Means' (FCM) algorithm. The FCM uses the probabilistic constraint that the memberships of a data point across classes sum to one. This constraint was used to generate the membership update equations for an iterative algorithm. Recently, we cast the clustering problem into the framework of possibility theory using an approach in which the resulting partition of the data can be interpreted as a possibilistic partition, and the membership values may be interpreted as degrees of possibility of the points belonging to the classes. We show the ability of this approach to detect linear and quartic curves in the presence of considerable noise.

Krishnapuram, Raghu↗

Data-driven Minimum Entropy Control for Stochastic Nonlinear Systems using the Cumulant-Generating Function

Here, we present a novel minimum entropy control algorithm for a class of stochastic nonlinear systems subjected to non-Gaussian noises. The entropy control can be considered as an optimization problem for the system randomness attenuation, but the mean value has to be considered separately. To overcome this disadvantage, a new representation of the system stochastic properties was given using the cumulant-generating function based on the moment-generating function, in which the mean value and the entropy was reflected by the shape of the cumulant-generating function. Based on the samples of the system output and control input, a time-variant linear model was identified, and the minimum entropy optimization was transformed to system stabilization. Then, an optimal control strategy was developed to achieve the randomness attenuation, and the boundedness of the controlled system output was analyzed. The effectiveness of the presented control algorithm was demonstrated by a numerical example. In this paper, a data-driven minimum entropy design is presented without pre-knowledge of the system model; entropy optimization is achieved by the system stabilization approach in which the stochastic distribution control and minimum entropy are unified using the same identified structure; and a potential framework is obtained since all the existing system stabilization methods can be adopted to achieve the minimum entropy objective.

42 ENGINEERING↗

Seismic isolation: A pathway to standardized advanced nuclear reactors

Standardizing advanced nuclear reactors is a pathway to substantially reducing their overnight capital cost and achieving parity with other power sources, including renewables and fossil fuels. The seismic load case has thwarted standardization of nuclear power plants because site-specific seismic hazard and local near-surface geology has triggered soil-structure-interaction analysis, design, equipment qualification, regulatory review, and licensing, ensuring that each build is different. To achieve standardized or site-independent certified advanced reactor designs, the impact of the seismic load case on the engineering and construction cost and time must be substantially mitigated. Seismic isolation is a mature technology that has been used for more than 30 years in non-nuclear sectors to substantially reduce earthquake demands in buildings and other infrastructure. In this paper, seismic isolation is used to enable standardization of advanced reactor designs, aimed at the complete re-use of a site-independent, certified design and repeated procurement of safety-class equipment. A pathway to standardized designs using seismic isolation is demonstrated for two fundamentally different advanced reactors: a molten salt reactor and a high temperature gas reactor. Each reactor building is equipped with three specialized pieces of safety-class equipment, namely, a reactor vessel, a steam generator, and a control rod drive mechanism housing that is attached to the reactor head. Analysis is performed per ASCE and ASME standards to design the buildings and the equipment for two base conditions: conventional (fixed base) and base isolated. The impact of the seismic load case is characterized for the reinforced concrete walls in the buildings and for the equipment, measured using vessel wall thickness and horizontal accelerations. Here the analysis results show that the fixed-base buildings, designed for a site of low seismic hazard (peak ground acceleration, PGA = 0.15 g) could be constructed at a site of much greater seismic hazard (PGA = 0.7 g) if seismic base isolation is employed. Importantly, the scope of the site-specific analysis, design, and qualification would be limited to the seismic isolators and the isolated substructure, drastically reducing plant-specific engineering, review, and licensing, and time to construction start. Regulatory challenges and opportunities with standardized reactor designs are identified.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A Study on the Use of Solid-Oxide Fuel Cells for Increased Power Generation on Small Aircraft

A growing demand for higher-power electrical equipment on aircraft is driving the exploration of alternative electrical power generation devices. “Hybrid-electric” aircraft architectures that leverage multiple or alternative power sources are also becoming more popular with rising concerns over efficiency. Fuel cells are particularly interesting as auxiliary or secondary electrical power generation devices, due to their relative efficiency and longevity, and could be used as a “power pod” for vehicles without enough on-board electrical generation capability. This paper examines the feasibility and potential value of using an externally-mounted, hybridelectric, solid-oxide fuel cell (SOFC) power system on a Class IV unmanned aerial vehicle (UAV) for the purpose of power generation in excess of the baseline electrical load. Moreover, the paper will demonstrate that a SOFC auxiliary power unit (APU) provides significant value to an aircraft by producing a relatively large amount of additional electrical power for a relatively low initial investment when compared to producing additional power by scaling the engine.

Litherland, Brandon L.↗

Nonlinear Dispersion Relation and Out‐of‐Plane Second Harmonic Generation in MoSSe and WSSe Janus Monolayers

Janus transition metal dichalcogenides are an emerging class of atomically thin materials with engineered broken mirror symmetry that gives rise to long‐lived dipolar excitons, Rashba splitting, and topologically protected solitons. They hold great promise as a versatile nonlinear optical platform due to their broadband harmonic generation tunability, ease of integration on photonic structures, and nonlinearities beyond the basal crystal plane. Here, second and third harmonic generation in MoSSe and WSSe Janus monolayers is studied. Polarization‐resolved spectroscopy is used to map the full second‐order susceptibility tensor of MoSSe, including its out‐of‐plane components. In addition, the effective third‐order susceptibility and the second‐order nonlinear dispersion close to exciton resonances for both MoSSe and WSSe are measured at room and cryogenic temperatures. This work sets a bedrock for understanding the nonlinear optical properties of Janus transition metal dichalcogenides and probing their use in the next‐generation on‐chip multifaceted photonic devices.

36 MATERIALS SCIENCE↗

Electrostatic emissions between electron gyroharmonics in the outer magnetosphere

Electrostatic emissions are often observed by spacecraft in the outer magnetosphere at frequencies between low electron gyroharmonics. The emissions include the well-known odd half-harmonic emissions as well as weaker emissions which occur near the electron plasma frequency. A scheme is constructed for classifying the emissions, and it is shown that a theoretical model which has been previously used to explain '3/2' emissions can be extended to the other classes of emissions. All of the emissions therefore appear to be generated by the same basic mechanism: an unstable electron plasma distribution consisting of cold electrons (below 100 eV) and hot loss cone electrons (about 1 keV). Each emission class is associated with a particular range of model parameters; the wide-band electric field data can thus be used to infer the density and temperature of the cold plasma component. The model predicts that gyroharmonic emissions near the plasma frequency require large cold plasma densities.

Hubbard, R. F.↗

f‐ block MOFs: A Pathway to Heterometallic Transuranics

Abstract A novel series of heterometallic f ‐block‐frameworks including the first examples of transuranic heterometallic 238 U/ 239 Pu‐metal–organic frameworks (MOFs) and a novel monometallic 239 Pu‐analog are reported. In combination with theoretical calculations, we probed the kinetics and thermodynamics of heterometallic actinide(An)‐MOF formation and reported the first value of a U‐to‐Th transmetallation rate. We concluded that formation of uranyl species could be a driving force for solid‐state metathesis. Density of states near the Fermi edge, enthalpy of formation, band gap, proton affinity, and thermal/chemical stability were probed as a function of metal ratios. Furthermore, we achieved 97 % of the theoretical maximum capacity for An‐integration. These studies shed light on fundamental aspects of actinide chemistry and also foreshadow avenues for the development of emerging classes of An‐containing materials, including radioisotope thermoelectric generators or metalloradiopharmaceuticals.

Park, Kyoung Chul↗

f‐ block MOFs: A Pathway to Heterometallic Transuranics

Abstract A novel series of heterometallic f ‐block‐frameworks including the first examples of transuranic heterometallic 238 U/ 239 Pu‐metal–organic frameworks (MOFs) and a novel monometallic 239 Pu‐analog are reported. In combination with theoretical calculations, we probed the kinetics and thermodynamics of heterometallic actinide(An)‐MOF formation and reported the first value of a U‐to‐Th transmetallation rate. We concluded that formation of uranyl species could be a driving force for solid‐state metathesis. Density of states near the Fermi edge, enthalpy of formation, band gap, proton affinity, and thermal/chemical stability were probed as a function of metal ratios. Furthermore, we achieved 97 % of the theoretical maximum capacity for An‐integration. These studies shed light on fundamental aspects of actinide chemistry and also foreshadow avenues for the development of emerging classes of An‐containing materials, including radioisotope thermoelectric generators or metalloradiopharmaceuticals.

Park, Kyoung Chul↗

Learning non-Higgsable gauge groups in 4D F-theory

We apply machine learning techniques to solve a specific classification problem in 4D F-theory. For a divisor D on a given complex threefold base, we want to read out the non-Higgsable gauge group on it using local geometric information near D. The input features are the triple intersection numbers among divisors near D and the output label is the non-Higgsable gauge group. We use decision tree to solve this problem and achieved 85%-98% out-of-sample accuracies for different classes of divisors, where the data sets are generated from toric threefold bases without (4,6) curves. We have explicitly generated a large number of analytic rules directly from the decision tree and proved a small number of them. As a crosscheck, we applied these decision trees on bases with (4,6) curves as well and achieved high accuracies. Additionally, we have trained a decision tree to distinguish toric (4,6) curves as well. Finally, we present an application of these analytic rules to construct local base configurations with interesting gauge groups such as SU(3).

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

To the Theory of C{sub 0}-Operator Orthogonal Polynomials

Operator orthogonal polynomials are considered whose arguments are generators of strongly continuous semigroups of transformations of class C{sub 0} acting in a Banach space. Earlier such polynomials were considered by the authors in the case of the Chebyshev polynomials of the first and second kind. In this paper, more general classes of operator orthogonal polynomials are considered, which include the Jacobi and Aptekarev polynomials. Integral representations of operator fractional-rational functions and also of Bessel operator-valued functions of an imaginary argument are presented.

97 MATHEMATICS AND COMPUTING↗

Integrating biocatalysis with chemocatalysis for selective transformations

The integration of biocatalysis with chemocatalysis combines the excellent selectivity of the former with the robust reactivity of the latter and offers many advantages, such as lower cost, higher yield, enhanced selectivity, as well as less waste generation. Despite the challenge of incompatibilities between different classes of catalysts, recent advances in synthetic chemistry and biology provide ample opportunities for multistep cascade transformations that combine biocatalysis and chemocatalysis. In this research, we review recent progress in merging biocatalysis with chemocatalysis, highlighting selected examples of photo-/electricity-driven biotransformations and recently developed strategies for addressing the catalyst incompatibility issue.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

PANNA: Properties from Artificial Neural Network Architectures

We report prediction of material properties from first principles is often a computationally expensive task. Recently, artificial neural networks and other machine learning approaches have been successfully employed to obtain accurate models at a low computational cost by leveraging existing example data. Here, we present a software package “Properties from Artificial Neural Network Architectures” (PANNA) that provides a comprehensive toolkit for creating neural network models for atomistic systems following the Behler–Parrinello topology. Besides the core routines for neural network training, it includes data parser, descriptor builder for Behler–Parrinello class of symmetry functions and force-field generator suitable for integration within molecular dynamics packages. PANNA offers a variety of activation and cost functions, regularization methods, as well as the possibility of using fully-connected networks with custom size for each atomic species. PANNA benefits from the optimization and hardware-flexibility of the underlying TensorFlow engine which allows it to be used on multiple CPU/GPU/TPU systems, making it possible to develop and optimize neural network models based on large datasets.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Small system studies: A theory overview

There is now a substantial body of evidence that a deconfined quark-gluon plasma is created in ultrarelativistic collisions of heavy nuclei. Some key observables which are used to gauge the production of the quark-gluon plasma are the hadronic spectra and multiplicities across many species, azimuthal anisotropies in the production of various hadrons, jet quenching, photon/dilepton production, and heavy quarkonium suppression. A key question in the study of the quark-gluon plasma is what happens to these observables as one changes the system size. In particular, it is very interesting to study collisions of “small systems” such as pp, dA, pA, and e + e - since naively one does not expect to produce a QGP in these cases. One of the surprises from such studies was the existence of sizable azimuthal anisotropies in the hadron spectra in the highest multiplicity classes, which led to speculations that one can generate a QGP in such relatively rare events. This interpretation, however, is complicated by the fact that there can be multiple sources of azimuthal anisotropy. I will discuss our current understanding of the different sources of azimuthal anisotropies and the multiplicity windows in which each mechanism is expected to dominate. I will also provide a critical discussion of the reliability of hydrodynamic models applied to small systems. Finally, I will briefly discuss jet quenching and heavy quarkonium suppression in small systems and discuss whether or not these observables show any indication of the production of a small QGP droplet.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗