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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Computational Framework to design 3D stiffness gradient acoustic metamaterials for impedance matching

Acoustic waves play a crucial role in various applications, including medical imaging, non-destructive testing, and sonar systems. One of the significant challenges in these applications is impedance matching, which is essential for minimizing reflections and maximizing the transfer of acoustic energy between different media. Acoustic metamaterials offer a promising solution to this challenge. In addition to impedance control, gradient stiffness can enhance structural efficiency and enable spatial control of wave propagation, making it a valuable feature in acoustic metamaterial design. In this pa- per, we present our developed computational method to design 3D stiffness gradient acoustic metamaterials for impedance matching. The key steps in our approach include generating initial designs using a periodic covariance function to provide unit cells that are both periodic on the boundaries and randomly formed inside the unit cell. Furthermore, we integrated manufacturing constraints into the design process, ensuring that the structures are interconnected for fabrication. We propose two computational optimization algorithms: GenUnit, based on a non-dominated sorting genetic algorithm (NSGA-II), and MLMatch, which leverages differentiable machine learning. The two approaches are not separate contributions but complementary com- ponents of a unified framework. GenUnit requires no training data and directly interfaces with physics-based simulations, making it highly accurate but slower for large-scale exploration. In contrast, MLMatch is data-hungry during training but, once trained, enables near-instantaneous inference and broad design-space coverage. Together, they form a hybrid strategy: ML- Match rapidly explores the global design space, and GenUnit provides local refinement with high-fidelity accuracy. This balance between training cost, inference time, and precision is the motivation for including both methods in the same study. We applied this dual-algorithm framework to generate two metallic-based metamaterial designs that match the acoustic impedance of water while exhibiting a controlled gradient in stiffness (from stiff to soft). The stiffness gradient is particularly advantageous in applications where one side of the structure must interface with soft or sensitive surfaces, such as human tissue or delicate components. Here, this work paves the way for improved materials in various acoustic applications, particularly in ultrasound devices, by providing better impedance.

Metamaterial↗
DOE OSTI2022

Resolution of 100 photons and quantum generation of unbiased random numbers

Macroscopic quantum phenomena, such as observed in superfluids and superconductors, have led to promising technological advancements and some of the most important tests of fundamental physics. At present, quantum detection of light is mostly relegated to the microscale, where avalanche photodiodes are very sensitive to distinguishing single-photon events from vacuum but cannot differentiate between larger photon-number events. Beyond this, the ability to perform measurements to resolve photon numbers is highly desirable for a variety of quantum information applications including computation, sensing, and cryptography. True photon-number resolving detectors do exist, but they are currently limited to the ability to resolve on the order of 10 photons, which is too small for certain proposals. In this work, we extend photon measurement into the mesoscopic regime by implementing a detection scheme based on multiplexing highly quantum-efficient transition-edge sensors to accurately resolve photon numbers between zero and 100. Further, we then demonstrate the use of our system by implementing a quantum random number generator with no inherent bias. This method is based on sampling a coherent state in the photon-number basis and is robust against environmental noise, phase and amplitude fluctuations in the laser, loss and detector inefficiency as well as eavesdropping. Beyond true random number generation, our detection scheme serves as a means to implement quantum measurement and engineering techniques valuable for photonic quantum information processing.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Deriving Material Properties from Feedback Error Signals in Scanning Tunneling Microscopy

Imperfections in measurements, e.g., deviations and broadening, are not devoid of information; rather, they can reveal valuable physical properties and processes. Scanning tunneling microscopy leverages a negative feedback loop to regulate the tunneling current. Practically, current fluctuates around its set point, and such deviations are considered insignificant and ignored. Here, in this study, we investigate the information embedded in these deviations. In the constant-current mode with an active feedback loop, we observe an unexpected persistent DC current offset from its set point when the tunneling junction is periodically perturbed. We demonstrate both experimentally and theoretically that such error signals encode local tunneling barrier heights and the square of local differential conductance as a consequence of the interplay between rectification and active feedback compensation. We provide evidence on the generalizability of this phenomenology to other negative feedback systems. This new approach has the potential to broadly impact physical sciences by allowing rapid measurements without lock-in amplifiers.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A Feynman-Kac based numerical method for the exit time probability of a class of transport problems

The exit time probability, which gives the likelihood that an initial condition leaves a prescribed region of the phase space of a dynamical system at, or before, a given time, is arguably one of the most natural and important transport problems. In this work, we present an accurate and efficient numerical method for computing this probability for systems described by non-autonomous (time-dependent) stochastic differential equations (SDEs) or their equivalent Fokker-Planck partial differential equations. The method is based on the direct approximation of the Feynman-Kac formula that establishes a link between the adjoint Fokker-Planck equation and the forward SDE. The Feynman-Kac formula is approximated using the Gauss-Hermite quadrature rules and piecewise cubic Hermite interpolating polynomials, and a GPU accelerated matrix representation is used to compute the entire time evolution of the exit time probability using a single pass of the algorithm. The method is unconditionally stable, exhibits second order convergence in space, first order convergence in time, and it is straightforward to parallelize. Applications are presented to the advection diffusion of a passive tracer in a fluid flow exhibiting chaotic advection, and to the runaway acceleration of electrons in a plasma in the presence of an electric field, collisions, and radiation damping. Benchmarks against analytical solutions as well as comparisons with explicit and implicit finite difference standard methods for the adjoint Fokker-Planck equation are presented.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Bayesian analysis of (3 +1)⁢D relativistic nuclear dynamics with the RHIC beam energy scan data

This work presents a Bayesian inference study for relativistic heavy-ion collisions in the beam energy scan program at the BNL Relativistic Heavy-Ion Collider. The theoretical model simulates event-by-event (3+1)-dimensional [(3+1)⁢D] collision dynamics using hydrodynamics and hadronic transport theory. We analyze the model's 20-dimensional posterior distributions obtained using three model emulators with different accuracy and demonstrate the essential role of training an accurate model emulator in the Bayesian analysis. Our analysis provides robust constraints on the quark-gluon plasma's transport properties and various aspects of (3+1)⁢D relativistic nuclear dynamics. By running full model simulations with 100 parameter sets sampled from the posterior distribution, we make predictions for p T -differential observables and estimate their systematic theory uncertainty. Here, a sensitivity analysis is performed to elucidate how individual experimental observables respond to different model parameters, providing useful physics insights into the phenomenological model for heavy-ion collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Analyses of internal structures and defects in materials using physics-informed neural networks

Characterizing internal structures and defects in materials is a challenging task, often requiring solutions to inverse problems with unknown topology, geometry, material properties, and nonlinear deformation. Here, we present a general framework based on physics-informed neural networks for identifying unknown geometric and material parameters. By using a mesh-free method, we parameterize the geometry of the material using a differentiable and trainable method that can identify multiple structural features. We validate this approach for materials with internal voids/inclusions using constitutive models that encompass the spectrum of linear elasticity, hyperelasticity, and plasticity. We predict the size, shape, and location of the internal void/inclusion as well as the elastic modulus of the inclusion. Our general framework can be applied to other inverse problems in different applications that involve unknown material properties and highly deformable geometries, targeting material characterization, quality assurance, and structural design.

36 MATERIALS SCIENCE↗
DOE OSTI2022

2023 Shot Request - MultiPuck + HTTemp [Slides]

As part of LDRD ER project, an OMEGA shot day will be used to demonstrate a successful $T_{ion}(t)$ slope measurement during fusion burn utilizing the new multi-puck system. Shot parameters will be designed to vary the $T_{ion}(t)$ slope during fusion burn to demonstrate the differentiability of the system. Success would mark the first measurement of this type.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Update on 17 O evaluation and fast neutron evaluation for 181 Ta [Slides]

Reliable fast-neutron evaluation can be entirely encapsulated in the reaction model and related input. Ta181 is a particularly relevant case due to extraordinary coverage of various observables by differential experiments that offer much help and relatively little headache. Differences from the similar ENDF/B-VIII evaluation are as follows: more advanced modeling (CC OMP, MSD, MSC, decay schemes), more careful selection of models and parameters, new experimental data, and isomers. Overall, there is improved agreement with differential data and hints of better performance in integral testing.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Kinetics of particles with short-range interactions

Self-assembly is one of the grand challenges of the 21st century – as the devices and materials we would like to build become too complex or small-scale for top-down manufacturing to be efficient, it is increasingly important to find ways to create these through bottom-up, dynamical approaches. Many particles used in self-assembly have very short-ranged attractive interactions, making simulations expensive or impossible. This proposal develops a set of conceptual and computational tools to study the dynamics of self-assembly for particles with short-ranged interactions, harnessing ideas in differential and computational geometry, and stochastic analysis, to accelerate simulations.

74 ATOMIC AND MOLECULAR PHYSICS↗
NASA NTRS1974

Quasi-linear theory via the cumulant expansion approach

The cumulant expansion technique of Kubo was used to derive an intergro-differential equation for f , the average one particle distribution function for particles being accelerated by electric and magnetic fluctuations of a general nature. For a very restricted class of fluctuations, the f equation degenerates exactly to a differential equation of Fokker-Planck type. Quasi-linear theory, including the adiabatic assumption, is an exact theory for this limited class of fluctuations. For more physically realistic fluctuations, however, quasi-linear theory is at best approximate.

Jones, F. C.↗
NASA NTRS1975

Supernova 1972 e in NGC 5253

New absolute energy distributions of the Type 1 supernova 1972e in NGC 5253 extending to about 700 days after maximum light were obtained. A physical model of the expanding envelope, based on the identification of the feature at 6550 A with H-alpha, is proposed. It is described as a differentially expanding atmosphere, with electron density ranging from 10 to the 10th power near maximum light to about 10 to the 7th power, 340 days later, illuminated by a photosphere with temperature in the range 10,000 K to 7,000 K. More than 200 days after maximum, the spectrum was dominated by four features between 4200 A and 5500 A. Three of these four features matched the blended emissions from over 100 lines of Fe II. Possible identifications of the fourth feature with Mg I lambda 4571 or permitted lines of Fe II are also discussed.

Kirshner, R. P.↗
NASA NTRS1982

Polarization studies of the Venus UV contrasts - Cloud height and haze variability

The present investigation is concerned with the measurement of differences in the polarization of bright and dark areas on Venus. The differential polarization is matched by simple models in which the cloud height, amount of submicron haze above the clouds, and absorber amount in the clouds are varied. Physical and chemical models consistent with the findings are proposed. The differences in polarization between bright and dark ultraviolet features on Venus are found to have a straightforward interpretation in terms of known constituents of the atmosphere near the cloud tops. The observations of the polarization in four colors over 2 1/2 Venus years imply that the submicron haze and UV absorbers are anticorrelated, and that the clouds lie slightly (approximately 1 km) lower in the dark regions. These findings pose strong constraints on any model for the brightness variations in the UV.

Esposito, L. W.↗
NASA NTRS1987

Theories of multiple equilibria and weather regimes : A critical reexamination. II - Baroclinic two-layer models

Previous results based on low- and intermediate-order truncations of the two-layer model suggest the existence of multiple equilibria and/or multiple weather regimes for the extratropical large-scale flow. The importance of the transient waves in the synoptic scales in organizing the large-scale flow and in the maintenance of weather regimes was emphasized. The result shows that multiple equilibria/weather regimes that are present in lower-order models examined disappear when a sufficient number of modes are kept in the spectral expansion of the solution to the governing partial differential equations. Much of the chaotic behavior of the large-scale flow that is present in intermediate-order models is now found to be spurious. Physical reasons for the drastic modification are offered. A peculiarity in the formulation of most existing two-layer models is noted that also tends to exaggerate the importance of baroclinic processes and increase the degree of unpredictability of the large-scale flow.

Cehelsky, Priscilla↗
NASA NTRS2004

Complexity of life via collective mind

e mind is introduced as a set of simple intelligent units (say, neurons, or interacting agents), which can communicate by exchange of information without explicit global control. Incomplete information is compensated by a sequence of random guesses symmetrically distributed around expectations with prescribed variances. Both the expectations and variances are the invariants characterizing the whole class of agents. These invariants are stored as parameters of the collective mind, while they contribute into dynamical formalism of the agents' evolution, and in particular, into the reflective chains of their nested abstract images of the selves and non-selves. The proposed model consists of the system of stochastic differential equations in the Langevin form representing the motor dynamics, and the corresponding Fokker-Planck equation representing the mental dynamics (Motor dynamics describes the motion in physical space, while mental dynamics simulates the evolution of initial errors in terms of the probability density). The main departure of this model from Newtonian and statistical physics is due to a feedback from the mental to the motor dynamics which makes the Fokker-Planck equation nonlinear. Interpretation of this model from mathematical and physical viewpoints, as well as possible interpretation from biological, psychological, and social viewpoints are discussed. The model is illustrated by the dynamics of a dialog.

collective intelligence↗
NASA NTRSDate not supplied

Flow field Reconstruction for Inhomogeneous Turbulence using Data and Physics Driven Models

A methodology combining Large Eddy Simulation (LES) trained data and a physics driven wave packet model to obtain a reduced order reconstruction for broadband, three-dimensional, temporally stationary but spatially inhomogeneous, incompressible turbulence. Wake turbulence generated by an axisymmetric dragging disk with a turbulent co-flow serves as the benchmark test case. We begin by studying the proper-orthogonal decomposition of the turbulent fluctuations taken from a high-resolution LES to first identify whether the fields demonstrate a low-rank character. It is argued that the presence of the turbulent co-flow results in a largely broadband character lacking any tonal properties. This is especially true for Strouhal numbers greater than 1 and only a small fraction of energy is contained in the leading order Kelvin-Helmholtz modes. As such reconstructions and reduced order modeling purely relying on data from LES does not appear to be a lucrative solution - contrary to problems with strongly tonal character. To supplement the missing energy from a low order truncated mode expansion, we utilize a physics based super-resolution (enrichment) algorithm that relies on spatio-temporally localized Gabor wave packets whose time evolution is described using a set of ordinary differential equations. The reconstructed flow has single- and two-point correlations that are consistent with the reference high resolution simulation data.

SLS↗
DOE OSTI2021

Combined selection of the dynamic model and modeling error in nonlinear aeroelastic systems using Bayesian Inference

Here, we report a Bayesian framework for concurrent selection of physics-based models and (modeling) error models. We investigate the use of colored noise to capture the mismatch between the predictions of calibrated models and observational data that cannot be explained by measurement error alone within the context of Bayesian estimation for stochastic ordinary differential equations. Proposed models are characterized by the average data-fit, a measure of how well a model fits the measurements, and the model complexity measured using the Kullback–Leibler divergence. The use of a more complex error models increases the average data-fit but also increases the complexity of the combined model, possibly over-fitting the data. Bayesian model selection is used to find the optimal physical model as well as the optimal error model. The optimal model is defined using the evidence, where the average data-fit is balanced by the complexity of the model. The effect of colored noise process is illustrated using a nonlinear aeroelastic oscillator representing a rigid NACA0012 airfoil undergoing limit cycle oscillations due to complex fluid–structure interactions. Several quasi-steady and unsteady aerodynamic models are proposed with colored noise or white noise for the model error. The use of colored noise improves the predictive capabilities of simpler models.

42 ENGINEERING↗
NASA NTRS1993

Inversion of gravity and bathymetry in oceanic regions for long-wavelength variations in upper mantle temperature and composition

Long-wavelength variations in geoid height, bathymetry, and SS-S travel times are all relatable to lateral variations in the characteristic temperature and bulk composition of the upper mantle. The temperature and composition are in turn relatable to mantle convection and the degree of melt extraction from the upper mantle residuum. Thus the combined inversion of the geoid or gravity field, residual bathymetry, and seismic velocity information offers the promise of resolving fundamental aspects of the pattern of mantle dynamics. The use of differential body wave travel times as a measure of seismic velocity information, in particular, permits resolution of lateral variations at scales not resolvable by conventional global or regional-scale seismic tomography with long-period surface waves. These intermediate scale lengths, well resolved in global gravity field models, are crucial for understanding the details of any chemical or physical layering in the mantle and of the characteristics of so-called 'small-scale' convection beneath oceanic lithosphere. In 1991 a three-year project to the NASA Geophysics Program was proposed to carry out a systematic inversion of long-wavelength geoid anomalies, residual bathymetric anomalies, and differential SS-S travel time delays for the lateral variation in characteristic temperature and bulk composition of the oceanic upper mantle. The project was funded as a three-year award, beginning on 1 Jan. 1992.

Solomon, Sean C.↗
NASA NTRS1993

A formational model for the polygonal terrains of Mars: Taking a crack at the genesis of the Martian polygons

The mechanism for the genesis of the polygonal terrains in Acidalia and Utopia Planitia has long been sought: however, no completely satisfying model was put forth that characterizes the evolution of these complexly patterned terrains. The polygons are roughly hexagonal but some are not entirely enclosed by fractures. These polygonal features range in widths from approximately 5 to 20 km. Several origins were proposed that describe the polygon borders as desiccation cracks, columnar jointing in a cooled lava, or frost-wedge features. These tension-induced cracking hypotheses were addressed by Pechmann, who convincingly disputes these mechanisms of formation based on scale magnitude difficulties and morphology. Pechmann suggests instead that the cracks delineating the 5-20-km-wide polygons on the northern plains of Mars are graben resulting from deep-seated, uniform, horizontal tension. The difficulty with this hypothesis is that no analogous polygonal forms are known to have originated by tectonism on Earth. McGill and Hills propose that the polygonal terrains on Mars resulted from either rapid desiccation of sediments or cooling of volcanics coupled with differential compaction of the material over a buried irregular topographic surface. They suggest that fracturing was enhanced over the areas of positive relief and was suppressed above the topographic lows. McGill and Hills suggest that the spacing of the topographic highs primarily controls the size of the Martian polygons and the physics of the shrinkage process is a secondary concern. Ray et. al. conducted a terrestrial study of patterned ground in periglacial areas of the U.S. to determine the process responsible for polygonal ground formation. They developed a model for polygon formation in which convection of seasonal melt water above a permafrost layer, driven by an unstable density stratification, differentially melts the permafrost interface, causing it to become undulatory.

Wenrich, M. L.↗