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 1,243 records · Page 69
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Generative Representations for Evolving Families of Designs

Since typical evolutionary design systems encode only a single artifact with each individual, each time the objective changes a new set of individuals must be evolved. When this objective varies in a way that can be parameterized, a more general method is to use a representation in which a single individual encodes an entire class of artifacts. In addition to saving time by preventing the need for multiple evolutionary runs, the evolution of parameter-controlled designs can create families of artifacts with the same style and a reuse of parts between members of the family. In this paper an evolutionary design system is described which uses a generative representation to encode families of designs. Because a generative representation is an algorithmic encoding of a design, its input parameters are a way to control aspects of the design it generates. By evaluating individuals multiple times with different input parameters the evolutionary design system creates individuals in which the input parameter controls specific aspects of a design. This system is demonstrated on two design substrates: neural-networks which solve the 3/5/7-parity problem and three-dimensional tables of varying heights.

Hornby, Gregory S.↗
DOE OSTI2024

Non-resonant anomaly detection with background extrapolation

Complete anomaly detection strategies that are both signal sensitive and compatible with background estimation have largely focused on resonant signals. Non-resonant new physics scenarios are relatively under-explored and may arise from off-shell effects or final states with significant missing energy. In this paper, we extend a class of weakly supervised anomaly detection strategies developed for resonant physics to the non-resonant case. Machine learning models are trained to reweight, generate, or morph the background, extrapolated from a control region. A classifier is then trained in a signal region to distinguish the estimated background from the data. The new methods are demonstrated using a semi-visible jet signature as a benchmark signal model, and are shown to automatically identify the anomalous events without specifying the signal ahead of time.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2018

Low dimensional metal halide perovskites and hybrids

Organic-inorganic metal halide hybrids are an important class of crystalline materials with exceptional structural and property tunability. Recently metal halide perovskites with ABX 3 structure have been extensively investigated as new generation semiconductors for various optoelectronic devices, including photovoltaic cells, light emitting diodes, photodetectors, and lasers, for their exceptional optical and electronic properties. By controlling the morphological dimensionality, low dimensional metal halide perovskites, including 2D perovskite nanoplatelets, 1D perovskite nanowires, and 0D perovskite quantum dots, have been developed to exhibit distinct properties from their bulk counterparts, due to quantum size effects. Besides ABX 3 perovskites, organic-inorganic metal halide hybrids, containing the same fundamental building block of metal halide octahedra (BX 6 ), can also be assembled to possess other types of crystallographic structures. Using appropriate organic and inorganic components, low dimensional organic-inorganic metal halide hybrids with 2D, quasi-2D, corrugated-2D, 1D, and 0D structures at the molecular level have been developed and studied. Due to the strong quantum confinement and site isolation, these low dimensional metal halide hybrids at the molecular level exhibit remarkable and unique properties that are significantly different from those of ABX 3 perovskites. In light of the rapid development of low dimensional metal halide perovskites and hybrids, it is indeed timely to review the recent progress in these areas. Also, there is a need to clarify the difference between morphological low dimensional metal halide perovskites and molecular level low dimensional metal halide hybrids, as currently the terminologies of low dimensional perovskites are not appropriately used in many cases. Finally, in this review article, we discuss the synthesis, characterization, application, and computational studies of low dimensional metal halide perovskites and hybrids.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Chemical Modification Mechanisms in Hybrid Hafnium Oxo-methacrylate Nanocluster Photoresists for Extreme Ultraviolet Patterning

The potential implementation of extreme ultraviolet (EUV) lithography into next generation device processing is bringing urgency to identify resist materials that optimize EUV lithographic performance. Inorganic/organic hybrid nanoparticles or clusters constitute a promising new class of materials, with high EUV sensitivity from the core and tunable chemistry through the coordinating ligands. Development of a thorough mechanistic understanding of the solubility switching reactions in these materials is an essential first step toward their implementation in patterning applications but remains challenging due to the complexity of their structures, limitations in EUV sources, and lack of rigorous in situ characterization. Here, we report a mechanistic investigation of the solubility switching reactions in hybrid clusters comprising a small HfOx core capped with a methacrylic acid ligand shell (HfMAA). We show that EUV-induced reactions can be studied by performing in situ infrared (IR) spectroscopy of electron-irradiated films using a variable energy electron gun. Combining additional ex situ metrology, we track the chemical evolution of the material at each stage of a typical resist processing sequence. For instance, we find that a cross-linking reaction initiated by decarboxylation of the methacrylate ligands under electron irradiation constitutes the main solubility switching mechanism, although there are also chemical changes imparted by a typical post application bake (PAB) step alone. Lastly, synchrotron-based IR microspectroscopy measurements of EUV-irradiated HfMAA films enable a comparison of reactions induced by EUV vs electron beam irradiation of the same resist material, yielding important insight into the use of electron beam irradiation as an experimental model for EUV exposure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Structural basis of omalizumab therapy and omalizumab-mediated IgE exchange

Omalizumab is a widely used therapeutic anti-IgE antibody. Here we report the crystal structure of the omalizumab–Fab in complex with an IgE-Fc fragment. This structure reveals the mechanism of omalizumab-mediated inhibition of IgE interactions with both high- and low-affinity IgE receptors, and explains why omalizumab selectively binds free IgE. The structure of the complex also provides mechanistic insight into a class of disruptive IgE inhibitors that accelerate the dissociation of the high-affinity IgE receptor from IgE. We use this structural data to generate a mutant IgE-Fc fragment that is resistant to omalizumab binding. Treatment with this omalizumab-resistant IgE-Fc fragment, in combination with omalizumab, promotes the exchange of cell-bound full-length IgE with omalizumab-resistant IgE-Fc fragments on human basophils. Furthermore, this combination treatment also blocks basophil activation more efficiently than either agent alone, providing a novel approach to probe regulatory mechanisms underlying IgE hypersensitivity with implications for therapeutic interventions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Topological chiral crystals with helicoid-arc quantum states

The quantum behaviour of electrons in materials is the foundation of modern electronics and information technology, and quantum materials with topological electronic and optical properties are essential for realizing quantized electronic responses that can be used for next generation technology. Here we report the first observation of topological quantum properties of chiral crystals in the RhSi family. We find that this material class hosts a quantum phase of matter that exhibits nearly ideal topological surface properties originating from the crystals’ structural chirality. Electrons on the surface of these crystals show a highly unusual helicoid fermionic structure that spirals around two high-symmetry momenta, indicating electronic topological chirality. The existence of bulk multiply degenerate band fermions is guaranteed by the crystal symmetries; however, to determine the topological invariant or charge in these chiral crystals, it is essential to identify and study the helicoid topology of the arc states. The helicoid arcs that we observe on the surface characterize the topological charges of ±2, which arise from bulk higher-spin chiral fermions. These topological conductors exhibit giant Fermi arcs of maximum length (π), which are orders of magnitude larger than those found in known chiral Weyl fermion semimetals. Here, our results demonstrate an electronic topological state of matter on structurally chiral crystals featuring helicoid-arc quantum states. Such exotic multifold chiral fermion semimetal states could be used to detect a quantized photogalvanic optical response, the chiral magnetic effect and other optoelectronic phenomena predicted for this class of materials.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Understanding shape entropy through local dense packing

Entropy drives the phase behavior of colloids ranging from dense suspensions of hard spheres or rods to dilute suspensions of hard spheres and depletants. Entropic ordering of anisotropic shapes into complex crystals, liquid crystals, and even quasicrystals was demonstrated recently in computer simulations and experiments. The ordering of shapes appears to arise from the emergence of directional entropic forces (DEFs) that align neighboring particles, but these forces have been neither rigorously defined nor quantified in generic systems. In this paper, we show quantitatively that shape drives the phase behavior of systems of anisotropic particles upon crowding through DEFs. We define DEFs in generic systems and compute them for several hard particle systems. We show they are on the order of a few times the thermal energy (k B T) at the onset of ordering, placing DEFs on par with traditional depletion, van der Waals, and other intrinsic interactions. In experimental systems with these other interactions, we provide direct quantitative evidence that entropic effects of shape also contribute to self-assembly. We use DEFs to draw a distinction between self-assembly and packing behavior. We show that the mechanism that generates directional entropic forces is the maximization of entropy by optimizing local particle packing. Finally, we show that this mechanism occurs in a wide class of systems and we treat, in a unified way, the entropy-driven phase behavior of arbitrary shapes, incorporating the well-known works of Kirkwood, Onsager, and Asakura and Oosawa.

36 MATERIALS SCIENCE↗
DOE OSTI2017

CMB spectral distortions as solutions to the Boltzmann equations

We propose to re-interpret the cosmic microwave background spectral distortions as solutions to the Boltzmann equation. This approach makes it possible to solve the second order Boltzmann equation explicitly, with the spectral y distortion and the momentum independent second order temperature perturbation, while generation of μ distortion cannot be explained even at second order in this framework. We also extend our method to higher order Boltzmann equations systematically and find new type spectral distortions, assuming that the collision term is linear in the photon distribution functions, namely, in the Thomson scattering limit. As an example, we concretely construct solutions to the cubic order Boltzmann equation and show that the equations are closed with additional three parameters composed of a cubic order temperature perturbation and two cubic order spectral distortions. The linear Sunyaev-Zel'dovich effect whose momentum dependence is different from the usual y distortion is also discussed in the presence of the next leading order Kompaneets terms, and we show that higher order spectral distortions are also generated as a result of the diffusion process in a framework of higher order Boltzmann equations. The method may be applicable to a wider class of problems and has potential to give a general prescription to non-equilibrium physics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Diffusive dynamics of critical fluctuations near the QCD critical point

A quantitatively reliable theoretical description of the dynamics of fluctuations in nonequilibrium is indispensable in the experimental search for the QCD critical point by means of ultrarelativistic heavy-ion collisions. Herein we consider the fluctuations of the net-baryon density which becomes the slow, critical mode near the critical point. Due to net-baryon number conservation the dynamics is described by the fluid dynamical diffusion equation, which we extend to contain a white noise stochastic current. Including nonlinear couplings from the 3d Ising model universality class in the free energy functional, we solve the fully interacting theory in a finite size system. We observe that purely Gaussian white noise generates non-Gaussian fluctuations, but finite size effects and exact net-baryon number conservation lead to significant deviations from the expected behavior in equilibrated systems. In particular the skewness shows a qualitative deviation from infinite volume expectations.With this benchmark established we study the real-time dynamics of the fluctuations. We recover the expected dynamical scaling behavior and observe retardation effects and the impact of critical slowing down near the pseudocritical temperature.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Epitaxy on polycrystalline substrates

Motivated by combinatorial and high-throughput approaches to the discovery of antibodies and drugs in pharmaceutical research, efforts such as the Materials Genome Initiative (1) have been envisioned to develop similar algorithms for the discovery, design, and realization of next-generation materials, such as superconducting (2), magnetoresistive (3), dielectric (4), and luminescent (5) materials. However, such experimental approaches have not become pervasive across all classes of materials. For example, in the study of thin-film, functional complex oxides, systematic, small-scale exploration has remained the standard. However, studies like that of Wittkamper et al. (6), which explore many different substrates by using a polycrystalline substrate, stand poised to open the door for high-throughput studies of complex materials.

Pandya, Shishir↗
DOE OSTI2023

Modeling hadronization using machine learning

We present the first steps in the development of a new class of hadronization models utilizing machine learning techniques. We successfully implement, validate, and train a conditional sliced-Wasserstein autoencoder to replicate the Pythia generated kinematic distributions of first-hadron emissions, when the Lund string model of hadronization implemented in Pythia is restricted to the emissions of pions only. The trained models are then used to generate the full hadronization chains, with an IR cutoff energy imposed externally. The hadron multiplicities and cumulative kinematic distributions are shown to match the Pythia generated ones. We also discuss possible future generalizations of our results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Regime Characterization of Offshore Wind Resource Using Unsupervised Learning

Predictability of wind resource conditions is critical for offshore wind design and operations. While many studies of extreme wind conditions focus on specific events such as low-level jets or ramps, these rely on threshold definitions that limit generality. Here we present a data-driven framework that combines principal component analysis (PCA), self-organizing maps (SOM), and k-means clustering to classify wind resource conditions as typical and anomalous from climatological data. Anomalies are defined not by fixed thresholds but by flagging samples located far from SOM node centers inside the baseline SOM structure. This reframes extremes as rare ebents and hence, likely difficult to anticipate by numerical weather prediction models. We applied this approach to 23 years (2000–2022) of hourly profiles from the NOW-23 hindcast model at the Humboldt Wind Energy Area. Classification is conducted on a feature space consisting of 10 m wind speed and direction, bulk shear and veer across 30–270 m, and a low-level jet index. Dimensionality reduction is achieved through PC. A 2 × 3 OM lattice trained on the PCA vectors identified six baseline regimes spanning weak to strong flow states. High quantization-error profiles are identified and re-clustered into four anomalous regimes. The baseline regimes exhibited clear seasonal and diurnal cycles. Meanwhile, the anomalous regimes represented <10 % of all hours but showed distinct combinations of speed, shear, and veer, when compared to the baseline regimes. Anomalous regimes are typically short-lived (~few hours), yet their transitions can lead to hub-height wind changes of −18 to +9 m s -1 . For a representative 15 MW turbine, these shifts imply rapid swings in capacity factor from near-full output to negligible generation. Validation with lidar buoy data showed 51% agreement in SOM labels across ~6,000 overlapping hours, with most mismatches confined to adjacent speed classes. HRRR comparisons further revealed that anomalous regimes were disproportionately associated with forecast biases exceeding 5 m s -1 . Together, these results reframe extremes in offshore wind from absolute maxima or minima to weather states that are difficult to anticipate from models.

17 WIND ENERGY↗
NASA NTRS1972

An adaptive replacement algorithm for paged-memory computer systems.

A general class of adaptive replacement schemes for use in paged memories is developed. One such algorithm, called SIM, is simulated using a probability model that generates memory traces, and the results of the simulation of this adaptive scheme are compared with those obtained using the best nonlookahead algorithms. A technique for implementing this type of adaptive replacement algorithm with state of the art digital hardware is also presented.

Thorington, J. M., Jr.↗
NASA NTRS1985

On symmetric and upwind TVD schemes

A class of explicit and implicit total variation diminishing (TVD) schemes for the compressible Euler and Navier-Stokes equations was developed. They do not generate spurious oscillations across shocks and contact discontinuities. In general, shocks can be captured within 1 to 2 grid points. For the inviscid case, these schemes are divided into upwind TVD schemes and symmetric (nonupwind) TVD schemes. The upwind TVD scheme is based on the second-order TVD scheme. The symmetric TVD scheme is a generalization of Roe's and Davis' TVD Lax-Wendroff scheme. The performance of these schemes on some viscous and inviscid airfoil steady-state calculations is investigated. The symmetric and upwind TVD schemes are compared.

Yee, H. C.↗
NASA NTRS1987

Generation of a dynamo magnetic field in a protoplanetary accretion disk

A new computational technique is developed that allows realistic calculations of dynamo magnetic field generation in disk geometries corresponding to protoplanetary and protostellar accretion disks. The approach is of sufficient generality to allow, in the future, a wide class of accretion disk problems to be solved. Here, basic modes of a disk dynamo are calculated. Spatially localized oscillatory states are found to occur in Keplerain disks. A physical interpretation is given that argues that spatially localized fields of the type found in these calculations constitute the basic modes of a Keplerian disk dynamo.

Stepinski, T.↗
NASA NTRS1992

H Ly-alpha transmittance of thin foils of C, Si/C, and Al/C for keV particle detectors

A class of instruments designed for remote sensing of space plasmas by measuring energetic neutral atoms (ENA) uses a thin foil as both a signal generator and a light shield. An ENA imager must look directly at the ENA source region, which is also usually an intense source of H Ly-alpha (1216 A) photons. It is desirable to minimize the energy threshold for ENA detectors, at the same time maximizing the blocking of H Ly-alpha. Optimizing filter design to meet these two contrary requirements has led us to measure the transmittance of thin C, Si/C, and Al/C foils at H Ly-alpha. Our results indicate that (1) transmittance of less than 0.0007 can be achieved with 7 micro-g/sq cm Si on 1.7 micro-g/sq cm C; (2) an Si/C composite foil with a thin carbon layer is more effective in blocking UV radiation while having the lowest energy threshold of all the foils measured; and (3) transmittance of Si/C foils of known Si and C thicknesses cannot be accurately predicted, but must be measured.

Drake, V. A.↗
NASA NTRS2012

Automated Design of Noise-Minimal, Safe Rotorcraft Trajectories

NASA and the international community are investing in the development of a commercial transportation infrastructure that includes the increased use of rotorcraft, specifically helicopters and aircraft such as a 40-passenger civil tilt rotors. Rotorcraft have a number of advantages over fixed wing aircraft, primarily in not requiring direct access to the primary fixed wing runways. As such they can operate at an airport without directly interfering with major air carrier and commuter aircraft operations. However, there is significant concern over the impact of noise on the communities surrounding the transportation facilities. In this paper we propose to address the rotorcraft noise problem by exploiting powerful search techniques coming from artificial intelligence, coupled with simulation and field tests, to design trajectories that are expected to improve on the amount of ground noise generated. This paper investigates the use of simulation based on predictive physical models to facilitate the search for low-noise trajectories using a class of automated search algorithms called local search. A novel feature of this approach is the ability to incorporate constraints into the problem formulation that addresses passenger safety and comfort.

Morris, Robert A.↗
NASA NTRS2014

Optimization of a Lunar Pallet Lander Reinforcement Structure Using a Genetic Algorithm

This paper presents a design automation process using optimization via a genetic algorithm to design the conceptual structure of a Lunar Pallet Lander. The goal is to determine a design that will have the primary natural frequencies at or above a target value as well as minimize the total mass. Several iterations of the process are presented. First, a concept optimization is performed to determine what class of structure would produce suitable candidate designs. From this a stiffened sheet metal approach was selected leading to optimization of beam placement through generating a two-dimensional mesh and varying the physical location of reinforcing beams. Finally, the design space is reformulated as a binary problem using 1-dimensional beam elements to truncate the design space to allow faster convergence and additional mechanical failure criteria to be included in the optimization responses. Results are presented for each design space configuration. The final flight design was derived from these results.

Burt, Adam O.↗