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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Science & Technology Review December 2025 - Optimizing Future Design

At Lawrence Livermore National Laboratory, we focus on science and technology research to ensure our nation’s security. We also apply that expertise to solve other important national problems in energy, bioscience, and the environment. Science & Technology Review is published eight times a year to communicate, to a broad audience, the Laboratory’s scientific and technological accomplishments in fulfilling its primary missions. The publication’s goal is to help readers understand these accomplishments and appreciate their value to the individual citizen, the nation, and the world.

36 MATERIALS SCIENCE↗
NASA NTRS2001

Simulation of Physical Experiments in Immersive Virtual Environments

An object-oriented event-driven immersive Virtual environment is described for the creation of virtual labs (VLs) for simulating physical experiments. Discussion focuses on a number of aspects of the VLs, including interface devices, software objects, and various applications. The VLs interface with output devices, including immersive stereoscopic screed(s) and stereo speakers; and a variety of input devices, including body tracking (head and hands), haptic gloves, wand, joystick, mouse, microphone, and keyboard. The VL incorporates the following types of primitive software objects: interface objects, support objects, geometric entities, and finite elements. Each object encapsulates a set of properties, methods, and events that define its behavior, appearance, and functions. A container object allows grouping of several objects. Applications of the VLs include viewing the results of the physical experiment, viewing a computer simulation of the physical experiment, simulation of the experiments procedure, computational steering, and remote control of the physical experiment. In addition, the VL can be used as a risk-free (safe) environment for training. The implementation of virtual structures testing machines, virtual wind tunnels, and a virtual acoustic testing facility is described.

Noor, Ahmed K.↗
DOE OSTI2025

Flexible Pilot Jobs Framework for Distributed High Throughput Computing

Experimental particle physics has been at the forefront of analyzing the world’s largest datasets for decades. The high-energy physics (HEP) community was among the first to develop suitable software and computing tools for this purpose. GlideinWMS is a Glidein-based workload management system whose purpose is to provide experiments like CMS at CERN, DUNE at Fermilab, and others, a way to access and efficiently use vast amounts of computing resources. This system wants to provide a simple way to submit jobs to a set of computing resources, that will be provided to users behind the scenes. Glideins are the pilot jobs executed on the worker nodes at the grid sites, performing operations such as hardware detection, environment setup, and error handling. After all these operations, they will launch the actual user job. Many grid sites are supported, such as shared clusters, Google CE, and AWS. My internship aimed to design and code a flexible pilot jobs framework that will replace the one used by GlideinWMS, developing a modular and flexible skeleton of the Glidein and adding further functionalities. My project also focused on the application of machine learning techniques as support to this management system.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Multi-hadron systems via Lattice QCD

This project supported a broad set of research in theoretical nuclear physics which has been designed to support current and future experimental DOE facilities. The broad summary of physical observables of interest in this project were the bread-and-butter observables obtained in experimental nuclear and particle physics experiments, namely scattering amplitude including multi-hadronic states. The primary goal of this project was to design a systematically improvable paradigm for accessing such amplitudes directly from the Standard Model of Particle Physics. The main tools that were used and explored in this project were scattering theory, lattice QCD, and future quantum computers. The physics outputs included various novel formalisms, exploratory lattice QCD calculations, and a new proposal for studying any scattering observable using future quantum computers.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Wormholes without averaging

After averaging over fermion couplings, SYK has a collective field description that sometimes has “wormhole” solutions. We study the fate of these wormholes when the couplings are fixed. Working mainly in a simple model, we find that the wormhole saddles persist, but that new saddles also appear elsewhere in the integration space — “half-wormholes.” The wormhole contributions depend only weakly on the specific choice of couplings, while the half-wormhole contributions are strongly sensitive. The half-wormholes are crucial for factorization of decoupled systems with fixed couplings, but they vanish after averaging, leaving the non-factorizing wormhole behind.

1/N Expansion↗
NASA NTRS2002

Empirical mode decomposition apparatus, method and article of manufacture for analyzing biological signals and performing curve fitting

A computer implemented physical signal analysis method includes four basic steps and the associated presentation techniques of the results. The first step is a computer implemented Empirical Mode Decomposition that extracts a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform which produces a Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum. The third step filters the physical signal by combining a subset of the IMFs. In the fourth step, a curve may be fitted to the filtered signal which may not have been possible with the original, unfiltered signal.

Huang, Norden E.↗
NASA NTRS2004

Empirical mode decomposition apparatus, method and article of manufacture for analyzing biological signals and performing curve fitting

A computer implemented physical signal analysis method includes four basic steps and the associated presentation techniques of the results. The first step is a computer implemented Empirical Mode Decomposition that extracts a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform which produces a Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum. The third step filters the physical signal by combining a subset of the IMFs. In the fourth step, a curve may be fitted to the filtered signal which may not have been possible with the original, unfiltered signal.

Huang, Norden E.↗
DOE OSTI2026

Data-driven particle dynamics: Structure-preserving coarse-graining for emergent behavior in non-equilibrium systems

Multiscale systems are ubiquitous in science and technology, but are notoriously challenging to simulate as short spatiotemporal scales must be appropriately linked to emergent bulk physics. When expensive high-dimensional dynamical systems are coarse-grained into low-dimensional models, the entropic loss of information leads to emergent physics which are dissipative, history-dependent, and stochastic. To machine learn coarse-grained dynamics from time-series observations of particle trajectories, we propose a framework using the metriplectic bracket formalism that preserves these properties by construction; most notably, the framework guarantees discrete notions of the first and second laws of thermodynamics, conservation of momentum, and a discrete fluctuation-dissipation balance crucial for capturing non-equilibrium statistics. We introduce the mathematical framework abstractly before specializing to a particle discretization. As labels are generally unavailable for entropic state variables, we introduce a novel self-supervised learning strategy to identify emergent structural variables. We validate the method on benchmark systems and demonstrate its utility on two challenging examples: (1) coarse-graining star polymers at challenging levels of coarse-graining while preserving non-equilibrium statistics, and (2) learning models from high-speed video of colloidal suspensions that capture coupling between local rearrangement events and emergent stochastic dynamics. We provide open-source implementations in both PyTorch and LAMMPS, enabling large-scale inference and extensibility to diverse particle-based systems.

Computational Engineering, Finance, and Science (c↗
NASA NTRS2006

Composite Erosion by Computational Simulation

Composite degradation is evaluated by computational simulation when the erosion degradation occurs on a ply-by-ply basis and the degrading medium (device) is normal to the ply. The computational simulation is performed by a multi factor interaction model and by a multi scale and multi physics available computer code. The erosion process degrades both the fiber and the matrix simultaneously in the same slice (ply). Both the fiber volume ratio and the matrix volume ratio approach zero while the void volume ratio increases as the ply degrades. The multi factor interaction model simulates the erosion degradation, provided that the exponents and factor ratios are selected judiciously. Results obtained by the computational composite mechanics show that most composite characterization properties degrade monotonically and approach "zero" as the ply degrades completely.

Chamis, Christos C.↗
DOE OSTI2024

Multi-level Monte Carlo methods in chemical applications with Lennard-Jones potentials and other landscapes with isolated singularities

We describe and compare outcomes of various Multi-Level Monte Carlo (MLMC) method variants, motivated by the potential of improved computational efficiency over rejection based Monte Carlo, which scales poorly with problem dimension. With an eye toward its application to computational chemical physics, we test MLMC's ability to sample trajectories on two problems — a familiar double-well potential, with known stationary distributions, and a Lennard-Jones solid potential (a Galton Board). By sampling Brownian motion trajectories, we are able to compute expectations of observable averages. These multi-basin potential energy problems capture the essence of the challenges with using MLMC, namely, maintaining correspondence of sample paths as time-resolution is varied. Addressing this challenge properly can lead to MLMC significantly outperforming standard Monte Carlo path sampling. We describe the essence of this problem and suggest strategies that circumvent diverging multilevel sample paths for an important class of problems. In the tests we also compare the computational cost of several, “adaptive,” variants of MLMC. Our results demonstrate that MLMC overcomes the collision, time scale limitation of the more familiar Brownian path MC samplers, and our implementation provides tunable error thresholds, making MLMC a promising candidate for application to larger and more complex molecular systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2017

Computational and Experimental Fluid-Structure Interaction Analysis of a High-Lift Wing with a Slat-Cove Filler for Noise Reduction

Airframe noise is a significant component of overall noise produced by transport aircraft during landing and approach (low speed maneuvers). A significant source for this noise is the cove of the leading-edge slat. The slat-cove filler (SCF) has been shown to be effective at mitigating slat noise. The objective of this work is to understand the fluid-structure interaction (FSI) behavior of a superelastic shape memory alloy (SMA) SCF in flow using both computational and physical models of a high-lift wing. Initial understanding of flow around the SCF and wing is obtained using computational fluid dynamics (CFD) analysis at various angles of attack. A framework compatible with an SMA constitutive model (implemented as a user material subroutine) is used to perform FSI analysis for multiple flow and configuration cases. A scaled physical model of the high-lift wing is constructed and tested in the Texas A&M 3 ft-by-4-foot wind tunnel. Initial validation of both CFD and FSI analysis is conducted by comparing lift, drag and pressure distributions with experimental results.

Scholten, William D.↗
NASA NTRS2003

Computer implemented empirical mode decomposition method apparatus, and article of manufacture utilizing curvature extrema

A computer implemented physical signal analysis method is includes two essential steps and the associated presentation techniques of the results. All the steps exist only in a computer: there are no analytic expressions resulting from the method. The first step is a computer implemented Empirical Mode Decomposition to extract a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals based on local extrema and curvature extrema. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform. The final result is the Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum.

Huang, Norden Eh↗
DOE OSTI2025

EPICS2025: Informal Status Report

This will be my (D.E.Cullen) final EPICS report. I am now 85 years old, and it is time for me to pass these data files on to the next generation to maintain. Here I will concentrate on documenting the history of the EPICS data files (how we got here) and where I think/suggest we should be headed into the future (where we are going). Where we actually go is of course entirely in the hands of and based on the decisions of whoever inherits these data files.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1975

Supercritical wing sections II: A handbook

The numerical aspect of theoretical work on transonics and supercritical wing sections are compiled. A model of the trailing edge is introduced which eliminates the loss of 15 to 20 percent experienced with heavily aft-loaded models, and it is indicated how drag creep can be reduced at off-design conditions. A rotated finite difference scheme is presented which can handle supersonic as well as subsonic free stream Mach numbers and leads to an effective three-dimensional program for the computation of transonic flow past an oblique wing. In the case of two-dimensional flow, the method is extended to take into account the displacement thickness computed by a semiempirical turbulent boundary layer correction. A series of supercritical wing sections is discussed together with comparisons between experimental and theoretical data. Computer programs and a brief manual for their operation are listed. It is shown that the programs furnish a physically adequate computer simulation of the compressible flows that arise in problems of transonic aerodynamics.

Bauer, F.↗
NASA NTRS1999

Computer implemented empirical mode decomposition method, apparatus and article of manufacture

A computer implemented physical signal analysis method is invented. This method includes two essential steps and the associated presentation techniques of the results. All the steps exist only in a computer: there are no analytic expressions resulting from the method. The first step is a computer implemented Empirical Mode Decomposition to extract a collection of Intrinsic Mode Functions (IMF) from nonlinear, nonstationary physical signals. The decomposition is based on the direct extraction of the energy associated with various intrinsic time scales in the physical signal. Expressed in the IMF's, they have well-behaved Hilbert Transforms from which instantaneous frequencies can be calculated. The second step is the Hilbert Transform. The final result is the Hilbert Spectrum. Thus, the invention can localize any event on the time as well as the frequency axis. The decomposition can also be viewed as an expansion of the data in terms of the IMF's. Then, these IMF's, based on and derived from the data, can serve as the basis of that expansion. The local energy and the instantaneous frequency derived from the IMF's through the Hilbert transform give a full energy-frequency-time distribution of the data which is designated as the Hilbert Spectrum.

Huang, Norden E.↗