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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 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Timescales of Quantum Equilibration, Dissipation and Fluctuation in Nuclear Collisions

Understanding the dynamics of equilibration processes in quantum systems as well as their interplay with dissipation and fluctuation is a major challenge in quantum many-body theory. The timescales of such processes are investigated in collisions of atomic nuclei using fully microscopic approaches. Findings from time-dependent Hartree-Fock and time-dependent random-phase approximation calculations are compared for 13 systems over a broad range of energies. The timescale for full mass equilibration ( ~ 2 × 10 - 20 s ) is found to be much larger than timescales for neutron-to-proton equilibration, kinetic energy, and angular momentum dissipations which are on the order of 10 - 21 s . Fluctuations of mass numbers in the fragments and correlations between their neutron and proton numbers build up within only a few 10 - 21 s . This suggests that dissipation is basically not impacted by mass equilibration, but is mostly driven by the exchange of nucleons between the fragments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1993

Microgravity vibration isolation technology: Development to demonstration

The low gravity environment provided by space flight has afforded the science community a unique area for the study of fundamental and technological sciences. However, the dynamic environment observed on space shuttle flights and predicted for Space Station Freedom has complicated the analysis of prior 'microgravity' experiments and prompted concern for the viability of proposed space experiments requiring long term, low gravity environments. Thus, isolation systems capable of providing significant improvements to this random environment have been developed. This dissertation deals with the design constraints imposed by acceleration sensitive, microgravity experiment payloads in the unique environment of space. A theoretical background for the inertial feedback and feedforward isolation of a payload was developed giving the basis for two experimental active inertial isolation systems developed for the demonstration of these advanced active isolation techniques. A prototype six degree of freedom digital active isolation system was designed and developed for the ground based testing of an actively isolated payload in three horizontal degrees of freedom. A second functionally equivalent system was built for the multi-dimensional testing of an active inertial isolation system in a reduced gravity environment during low gravity aircraft trajectories. These multi-input multi-output control systems are discussed in detail with estimates on acceleration noise floor performance as well as the actual performance acceleration data. The attenuation performance is also given for both systems demonstrating the advantages between inertial and non-inertial control of a payload for both the ground base environment and the low gravity aircraft acceleration environment. A future goal for this area of research is to validate the technical approaches developed to the 0.01 Hz regime by demonstrating a functional active inertial feedforward/feedback isolation system during orbital flight. A NASA IN-STEP flight experiment has been proposed to accomplish this goal, and the expected selection for the IN-STEP program has been set for Jul. of 1993.

Grodsinsky, Carlos M.↗
DOE OSTI2021

Design Space Exploration of Emerging Memory Technologies for Machine Learning Applications

Memory design space exploration methods study memory systems’ performances and limitations before implementation. The computer memory design space has grown exponentially because of the enormous growth of memory types, memory controllers, and application software. Computer simulators are commonly used for memory design space exploration. However, complex memory simulations take an enormous amount of time. Hence, in this paper, we proposed a machine learning-based design space exploration method for dynamic random-access memory and non-volatile memory systems. We applied our method to the CosmoGAN and LeNet applications to predict the following six memory response parameters: (i) bandwidth, (ii) power, (iii) average latency, (iv) average total latency, (v) memory reads, and (vi) memory writes. Our experimental results show that machine learning models can predict memory response parameter values faster than simulations. We used support vector machine, random forest, and gradient boosting machine learning models. We observed that the support vector machine provides better performance for bandwidth, average latency, and average total latency. The random forest model works better for memory reads and writes. The gradient boosting model provides superior prediction performance for power. We provide a detailed discussion on learning curve characteristics, error analysis, and memory type recommendation.

Hasan, S M Shamimul↗
NASA NTRS1967

On optimal stochastic midcourse guidance.

Feedback from observations introduced into midcourse guidance correction program, showing optimal random feedback solution obtained for deterministic optimal feedback control problems

FEEDBACK CONTROL SYSTEM↗
NASA NTRS1988

Capacity and cutoff rate calculations for a concatenated coding system

A model is developed for a concatenated coding system, and from it the overall channel cutoff rate and capacity is found using random coding arguments. The effects of interleaving between the inner and outer codes and of the availability of side information to the outer decoder are considered. The performance of several specific concatenated coding systems is calculated and used for comparison with the random coding results. From the analysis, a number of general conclusions regarding the design of concatenated coding systems are presented. All the results are derived assuming a block inner code.

Herro, Mark A.↗
NASA NTRS1975

Effects of automobile steering characteristics on driver vehicle system dynamics in regulation tasks

A regulation task which subjected the automobile to a random gust disturbance which is countered by driver control action is used to study the effects of various automobile steering characteristics on the driver/vehicle system. The experiments used a variable stability automobile specially configured to permit insertion of the simulated gust disturbance and the measurement of the driver/vehicle system characteristics. Driver/vehicle system dynamics were measured and interpreted as an effective open loop system describing function. Objective measures of system bandwidth, stability, and time delays were deduced and compared. These objective measures were supplemented by driver ratings. A tentative optimum range of vehicle dynamics for the directional regulation task was established.

Mcruer, D. T.↗
NASA NTRS1995

A Novel Photonic Clock and Carrier Recovery Device

In high-speed fiber-optic communications systems, the ability to recover the clock from the incoming random data is essential. The recovered clock must be in precise synchronism with the incoming data and is used in further signal processing systems, such as regenerative repeaters, time division switching systems, and demultiplexers. A high-speed photonic clock regenerator is described.

photonic↗
NASA NTRS1981

The Space Telescope

The Space Telescope, still under construction, is discussed in light of the constraints imposed on ground-based telescopes. The history of the Space Telescope is traced from its conceptual origin to its actual construction, and design considerations used to determine the Space Telescope construction are described. The optical system of the telescope will have an aperture of 2.4 m, a focal ratio of 24, and a front of primary to focus of 1.5 m. The fine guidance system will use astigmatic images at the edge of the field of view to provide the guidance signal for maintaining stability to 0.007 arcseconds. The guidestars are required for 85% of random fields located at the galactic poles, and the system sensitivity must meet performance specifications for stars brighter than 13.5 magnitude. The scientific instruments - the wide field camera, the faint object camera, the faint object spectrograph, the high resolution spectrograph, the high speed photometer, and the fine guidance sensors - are discussed in detail. Finally, the operations system, including schedule contraints and the Science Institute, is presented.

Odell, C. R.↗
DOE OSTI2021

Chiral Spin Textures in Amorphous Iron–Germanium Thick Films

Topological solitary fields, such as magnetic and polar skyrmions, are envisioned to revolutionize microelectronics. These configurations have been stabilized in solid-state materials with a global inversion symmetry breaking, which translates in magnetic materials into a vector spin exchange known as the Dzyaloshinskii-Moriya interaction (DMI), as well as spin chirality selection and isotropic solitons. This work reports experimental evidence of 3D chiral spin textures, such as helical spins and skyrmions with different chirality and topological charge, stabilized in amorphous Fe-Ge thick films. Overall, these results demonstrate that structurally and chemically disordered materials with a random DMI can resemble inversion symmetry broken systems with similar magnetic properties, moments, and states. Disordered systems are distinguished from systems with global inversion symmetry breaking by their degenerate spin chirality that allows for forming isotropic and anisotropic topological spin textures at remanence, while offering greater flexibility in materials synthesis, voltage, and strain manipulation.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Magnetic Materials: Chiral Spin Textures in Amorphous Iron–Germanium Thick Films (Adv. Mater. 8/2021)

Topological solitary fields, such as magnetic and polar skyrmions, are envisioned to revolutionize microelectronics. These configurations have been stabilized in solid-state materials with a global inversion symmetry breaking, which translates in magnetic materials into a vector spin exchange known as the Dzyaloshinskii–Moriya interaction (DMI), as well as spin chirality selection and isotropic solitons. This work reports experimental evidence of 3D chiral spin textures, such as helical spins and skyrmions with different chirality and topological charge, stabilized in amorphous Fe–Ge thick films. These results demonstrate that structurally and chemically disordered materials with a random DMI can resemble inversion symmetry broken systems with similar magnetic properties, moments, and states. In conclusion, disordered systems are distinguished from systems with global inversion symmetry breaking by their degenerate spin chirality that allows for forming isotropic and anisotropic topological spin textures at remanence, while offering greater flexibility in materials synthesis, voltage, and strain manipulation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Machine learning-enabled discovery of ionic liquid–solvent electrolytes exhibiting high ionic conductivity

Ionic liquids (ILs), which are a class of materials with versatile nature and growing popularity, are facing impediments toward widespread usage as electrolytes due to various factors such as low ionic conductivity, high viscosity, high market price etc. One of the ways these limitations can be addressed is by mixing ILs with a molecular solvent. In a combinatorial sense, there exists an immense number of specific IL–solvent combinations. An exhaustive experimental or even simulation-based investigation of the chemical space spanned by such combinations can be extremely time-consuming, expensive, and nearly impossible. An alternative approach is to employ machine learning-based models developed from available databases. Although there exists prior literature that integrates machine learning to investigate mixtures of specific solvents with ILs, these models lack generalization necessitating development of a large number of ML models to handle various solvents. To remedy this shortcoming, as a part of designing green electrolytes with high ionic conductivity that can have potential applications in next-generation batteries and solar cells, this work aims to develop a unified machine learning model to predict ionic conductivity of any IL–solvent mixture system. In this regard, three models, namely, Random Forest, extreme gradient boosting (XGBoost), and artificial neural network (ANN) were formulated using the NIST ILThermo database. The dataset contained 549 unique ionic liquids from 16 cation families and 81 unique solvents, representing a total of 23 712 datapoints. SHAPLEY additive explanation (SHAP) method was used to assess the impact of various features on model prediction and their significance was compared with literature to gain physical insight about the model behavior. Finally, using the developed models, approximately 2.5 million IL–solvent mixtures at five different compositions were screened at room temperature. The high-throughput screening yielded nearly 19 000 IL–solvent mixtures for which ionic conductivity was found to exceed the ionic conductivity of conventional Li-ion battery electrolyte.

25 ENERGY STORAGE↗
DOE OSTI2023

Contact-Less Integrity Verification of Microelectronics Using Near-Field EM Analysis

Modern microelectronics life-cycle and supply chain ecosystem bring multiple untrusted entities, which can compromise their integrity. A major integrity issue of microelectronics stems from piracy of intellectual properties (IP) and counterfeiting, which causes significant revenue loss to the semiconductor manufacturers. Further, these components often lead to compromised functionality, reliability, security, and safety of an electronic system. This paper presents secure information transmission and probing methods for verifying the integrity of digital integrated circuit (ICs) based on their electromagnetic (EM) near-field emissions and thereby protecting systems against counterfeit components. The proposed method has been tested on both high-level instructions executed by microprocessors or Systems-on-Chip (serving as examples of software), and also logic circuits within FPGA fabrics and ASICs (serving as examples of hardware). The authentication information required by each digital system is generated using a pseudo-random number generator circuit and securely transmitted via near-field magnetic emissions. The authorized party can probe these emissions using a near-field probe, process the acquired signals to improve the signal-to-noise ratio (SNR), and then recover the secure information through matched filtering. Experimental results from commercial SoCs are used to demonstrate the proposed technique. Methods for reducing EM interference during integrity verification of both FPGAs and ASICs are also described.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Multifidelity Monte Carlo estimation for efficient uncertainty quantification in climate-related modeling

Abstract. Uncertainties in an output of interest that depends on the solution of a complex system (e.g., of partial differential equations with random inputs) are often, if not nearly ubiquitously, determined in practice using Monte Carlo (MC) estimation. While simple to implement, MC estimation fails to provide reliable information about statistical quantities (such as the expected value of the output of interest) in application settings such as climate modeling, for which obtaining a single realization of the output of interest is a costly endeavor. Specifically, the dilemma encountered is that many samples of the output of interest have to be collected in order to obtain an MC estimator that has sufficient accuracy – so many, in fact, that the available computational budget is not large enough to effect the number of samples needed. To circumvent this dilemma, we consider using multifidelity Monte Carlo (MFMC) estimation which leverages the use of less costly and less accurate surrogate models (such as coarser grids, reduced-order models, simplified physics, and/or interpolants) to achieve, for the same computational budget, higher accuracy compared to that obtained by an MC estimator – or, looking at it another way, an MFMC estimator obtains the same accuracy as the MC estimator at lower computational cost. The key to the efficacy of MFMC estimation is the fact that most of the required computational budget is loaded onto the less costly surrogate models so that very few samples are taken of the more expensive model of interest. We first provide a more detailed discussion about the need to consider an alternative to MC estimation for uncertainty quantification. Subsequently, we present a review, in an abstract setting, of the MFMC approach along with its application to three climate-related benchmark problems as a proof-of-concept exercise.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1973

Theory of disordered Heisenberg ferromagnets

A Green's function technique is used to calculate the magnetic properties of Heisenberg ferromagnets in which the exchange interactions deviate randomly in strength from the mean interaction. Systems of sc, bcc, and fcc topologies and of general spin values are treated. Disorder produces marked effects in the density of spin wave states, in the form of enhancement of the low-energy density and extension of the energy band to higher values. The spontaneous magnetization and the Curie temperature decrease with increasing disorder. The effects of disorder are shown to be more pronounced in the ferromagnetic than in the paramagnetic phase.

Stubbs, R. M.↗
NASA NTRS1972

Data smoothing and error detection based on linear interpolation

A method is presented, based on linear interpolation, for detecting and correcting bad data points in a set of data without contaminating the good data points. The method used is not concerned with the small random errors usually attributed to a noisy system. It assumes that the data points which are in error are relatively isolated from each other and that the number of such points is small compared to the total number of data points.

Guerra, V. M.↗
NASA NTRS1977

Wind models for flight simulator certification of landing and approach guidance and control systems

The definition of a model suitable for certification was the main objective of this report. The model was designed to simplify and reduce the wind model parameters to enable evaluation of a large number of aircraft and control system design parameters. Analytical descriptions of wind phenomena were presented. For those parameters defying analytic description, probabilistic descriptions were sought. A brief analysis of the effects of wind on aircraft motion was conducted. The axes transformations required between wind and turbulence components in their inherent axis system and in the airplane's axis system were shown. Techniques of providing a random process on computers for the representation of turbulence were presented. A simulation model was presented that combines all the foregoing components.

Schaeffer, D. R.↗