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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Nuclear safety Enhanced: A Deep dive into current and future RAVEN applications

As the horizon of nuclear energy expands with the advent of small modular reactors, IV generation reactors, and fusion reactors, there is a growing perspective that the licensing process could benefit from a more comprehensive approach. Moving beyond traditional deterministic and PRA analysis might pave the way for a novel safety analysis paradigm propelled by the increasing computational power at our disposal. This paper explores different methodologies that can improve the outcomes of nuclear safety analysis. These range from uncertainty quantification techniques, aimed at enhancing the precision of safety margins, to deploying dynamic event trees by driving system code simulations, capturing the potential evolutions of severe accidents. These methodologies introduce innovative dimensions to safety analysis, considering the consequences of postulated events and the dynamics of accident sequences. However, they also bring forth challenges, especially in managing the complexity and sheer volume of potential scenarios. The paper touches upon some strategies to counter these challenges, emphasizing the importance of adaptability and continuous evolution in the face of emerging nuclear safety concerns. Additionally, the paper sheds light on the need for advanced tools to apply these methodologies. Among these tools is RAVEN, an open-source software designed for parametric and probabilistic analyses. Its core components, including distribution, sampler, and reduced order model, enable various applications, from risk assessment and mitigation to dynamic learning and plant control logic simulations.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Energy-Resolved Femtosecond Hot Electron Dynamics in Single Plasmonic Nanoparticles

Efficient excitation and harvesting of hot carriers from nanoscale metals is central to many emerging photochemical, photovoltaic, and ultrafast optoelectronic applications. Nevertheless, direct experimental evidence of the energy-dependent femtosecond dynamics in ubiquitous tens-of-nanometer gold structures remains elusive, despite the potentially rich interplay between interfacial and internal plasmonic fields, excitation distributions, and scattering processes. To explore the effects of nanoscale structure on these dynamics, we employ simultaneous time-, angle-, and energy-resolved photoemission spectroscopy of single plasmonic nanoparticles. Photoelectron velocity and electric field distributions reveal bulk-like ballistic hot electron transport in different geometries, lacking any signatures of surface effects. Energy-resolved dynamics are measured in the 1–2 eV range and extrapolated to lower energies via Boltzmann theory, providing a detailed view of hot electron lifetimes within nanoscale gold. Here, we find that particles with relevant dimensions as small as 10 nm serve as exemplary platforms for studying intrinsic metal dynamics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Toward three-dimensional DNA industrial nanorobots

Nanoscale industrial robots have potential as manufacturing platforms and are capable of automatically performing repetitive tasks to handle and produce nanomaterials with consistent precision and accuracy. We demonstrate a DNA industrial nanorobot that fabricates a three-dimensional (3D), optically active chiral structure from optically inactive parts. By making use of externally controlled temperature and ultraviolet (UV) light, our programmable robot, ~100 nanometers in size, grabs different parts, positions and aligns them so that they can be welded, releases the construct, and returns to its original configuration ready for its next operation. Our robot can also self-replicate its 3D structure and functions, surpassing single-step templating (restricted to two dimensions) by using folding to access the third dimension and more degrees of freedom. Our introduction of multiple-axis precise folding and positioning as a tool/technology for nanomanufacturing will open the door to more complex and useful nano- and microdevices.

Robotics↗
DOE OSTI2020

Advanced CMOS Reliability Update: Sub 20nm FinFET Assessment

Advances in FinFET design and fabrication enable manufacturing of denser, more compact integrated circuits (ICs) with substantially reduced leakage while shortening the channel-lengths. The same stress-induced leakage and breakdown degradation mechanisms that affect planar transistors also impact FinFET devices. Reliability concerns such as Bias Temperature Instability (BTI), Time Dependent Dielectric Breakdown (TDDB), and Hot Carrier Injection (HCI) become very important with changes to transistor geometry and fin sidewall crystal orientation. Recent testing has shown that FinFETs respond differently to radiation (radiation effects such as total ionizing dose) when compared to planar transistors. These reliability and radiation effects issues become very important when changing transistor geometry and scaling FinFETs towards smaller feature sizes (22-nm, 16-nm, 14- nm, 10-nm, and smaller critical dimensions). The comparable 2019 state of the art transistor densities in current high-volume manufacturing silicon-based foundries is 7-nm (ISMC, Samsung) and 10-nm (Intel) [www.anandtech.com,fuse.wikichip.org]. Released products include supporting components for the cellphone and commercial microprocessor markets respectively. Extensive development in the foundry industry is driving to a 5-nm technology node in late 2020.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Crack-Free Joining of High-Strength AA7055 Sheets by Friction Based Self-Piercing Riveting with the Aid of Numerical Design

Unique friction-based self-piercing riveting (F-SPR) was employed to join high-strength, low-ductility aluminum alloy 7055 for lightweight vehicle applications. This study aimed to maximize the joint strength of the AA7055 F-SPR joint while avoiding cracking issues due to low ductility at room temperature. A fully coupled Eulerian–Lagrangian (CEL) model was employed to predict the process temperature during F-SPR, and the temperature field was then mapped onto a 2D axisymmetric equivalent model for accelerated numerical analysis. The geometry, dimensions, and material strength of the rivet, as well as the depth of the die cavity and plunging depth, were investigated to enhance joint formation. Also, a static finite-element analysis model was developed to predict and analyze the stress distribution in the rivet under different mechanical testing loading conditions. Overall, the numerical model showed good agreement with the experiment results, such as joint formation and mechanical joint strength. With the aid of virtual fabrication through numerical modeling, the joint design iterations and process development time of F-SPR were greatly reduced regarding the goal of lightweight, high-strength aluminum joining.

36 MATERIALS SCIENCE↗
NASA NTRS1977

A joint fracture toughness evaluation of hot-pressed beryllium

Fracture toughness tests at room temperature were made on three-point bend specimens cut from hot-pressed beryllium obtained from two suppliers. The test specimens had dimensions conforming to ASTM fracture toughness standard E399-72. A total of 42 specimens were machined from each batch of material. Six specimens from each batch were then distributed to seven independent laboratories for testing. The test data from the laboratories were collected and analyzed for differences between the laboratories and the two batches of material. It is concluded that ASTM 399-72 can be used as a valid test procedure for determining the fracture toughness of beryllium, providing that Kf(max) in fatigue cracking could be up to 80 percent of the K(0) value.

Conrad, H.↗
NASA NTRS1986

A comparison of several methods for the calculation of vibration mode shape derivatives

Four methods for the calculation of derivatives of vibration mode shapes (eigenvectors) with respect to design parameters are reviewed and compared. These methods (finite difference method, Nelson's method, modal method and a modified modal method) are implemented in a general-purpose commercial finite element program and applied to a cantilever beam and a stiffened cylinder with a cutout. A beam tip mass, a beam root height and specific dimensions of the cylinder model comprise the design variables. Data are presented showing the amount of central processor time used to compute the first four eigenvector derivatives for each example problem; errors and rapidity of convergence of the approximate derivative to the exact derivative are taken into account. Nelson's method proved to be most reliable and efficient.

Sutter, T. R.↗
NASA NTRS1988

Measurement of the Landsat Thematic Mapper modulation transfer function using an array of point sources

This paper presents a method for measuring the Thematic Mapper (TM) imaging system point spread function (PSF) using TM imagery or a specially constructed target consisting of a two-dimensional array of approximate point sources of known dimensions and radiometric qualities. The target allows 16 separate point sources to be imaged simultaneously by the TM. The point sources were carefully placed on the ground so that their relative positions were known. Owing to sample-scene phasing, each imaged point source exhibits a different amount of blur in the digital image. The target pixels may then be recombined according to their known relative positions to form a single, sampled, nonaliased imaging system PSF. The modulation transfer function is then obtained as the modulus of the discrete Fourier transform of the PSF.

Rauchmiller, Robert F., Jr.↗
NASA NTRS1988

Eigenstructure assignment for a thrust-vectored high angle-of-attack aircraft

Eigenstructure assignment is utilized to design flight control laws for a thrust-vectored aircraft at several different angles of attack. An interesting characteristic of the aircraft model is that the control distribution matrix is rank-deficient. Also, the effectiveness of the control inputs varies with the angle of attack. A pseudocontrol strategy is used to reduce the control space to two dimensions. After the eigenstructure assignment design is complete, the controller is mapped back to the original five-dimensional control space. The designs are shown to exhibit acceptable multivariable stability margins at the aircraft inputs.

Sobel, Kenneth M.↗
NASA NTRS1988

Fractal distributions of stress and strength and variations of b-value

A two-dimensional planar fault zone on which the difference between stress and strength follows a fractal distribution is simulated to study the variation of the frequency-magnitude b-value under different distributions of heterogeneities and ambient stress levels. It is suggested that earthquakes occur in regions where this difference exceeds a specified value and that the size of these regions is a measure of the magnitude of the associated earthquake. A systematic variation in b-value is observed. It is found that the b-value has a positive correlation with the fractal dimension of the distribution and is inversely related to the ambient stress level. Observational data are compared with the simulation, showing that the observed b-value variation before and during earthquake sequences is a result of changes in both the ambient stress level and in the fractal dimension of the stress-strength distribution.

Huang, J.↗
NASA NTRS1990

Structure of three-dimensional turbulent boundary layers

The changes that occur in the Reynolds-stress-producing motion when a cross-stream pressure gradient is applied to an initially two-dimensional turbulent flow are discussed. Two examples are used: (1) a temporal simulation of a channel flow with crossflow applied by a spanwise pressure gradient for t is greater than 0; and (2) a spatial simulation of the boundary layer on an infinite swept wing. Evidence examined to date suggests that the structural changes in the two cases are similar, but the mechanisms may be significantly different, even if effects peculiar to the viscous wall region are ignored. The results from (2) are provisional, based on too short a time series for accurate statistical averages to be obtained. We treat turbulence 'statistics' (solutions of the Navier-Stokes equations in three space dimensions and time) in the same way as experiments: both have limitations of accuracy but both are acceptable representations of real fluid flows.

Bradshaw, P.↗
NASA NTRS1992

Weighted current sheets supported in normal and inverse configurations - A model for prominence observations

A technique which incorporates both photospheric and prominence magnetic field observations is used to analyze the magnetic support of solar prominences in two dimensions. The prominence is modeled by a mass-loaded current sheet which is supported against gravity by magnetic fields from a bipolar source in the photosphere and a massless line current in the corona. It is found that prominence support can be achieved in three different kinds of configurations: an arcade topology with a normal polarity; a helical topology with a normal polarity; and a helical topology with an inverse polarity. In all cases the important parameter is the variation of the horizontal component of the prominence field with height. Adding a line current external to the prominence eliminates the nonsupport problem which plagues virtually all previous prominence models with inverse polarity.

Demoulin, P.↗
NASA NTRS2003

Simulated KWAJEX Convective Systems Using a 2D and 3D Cloud Resolving Model and Their Comparisons with Radar Observations

The 1999 Kwajalein Atoll field experiment (KWAJEX), one of several major TRMM (Tropical Rainfall Measuring Mission) field experiments, has successfully obtained a wealth of information and observation data on tropical convective systems over the western Central Pacific region. In this paper, clouds and convective systems that developed during three active periods (Aug 7-12, Aug 17-21, and Aug 29-Sep 13) around Kwajalein Atoll site are simulated using both 2D and 3D Goddard Cumulus Ensemble (GCE) models. Based on numerical results, the clouds and cloud systems are generally unorganized and short lived. These features are validated by radar observations that support the model results. Both the 2D and 3D simulated rainfall amounts and their stratiform contribution as well as the heat, water vapor, and moist static energy budgets are examined for the three convective episodes. Rainfall amounts are quantitatively similar between the two simulations, but the stratiform contribution is considerably larger in the 2D simulation. Regardless of dimension, fo all three cases, the large-scale forcing and net condensation are the two major physical processes that account for the evolution of the budgets with surface latent heat flux and net radiation solar and long-wave radiation)being secondary processes. Quantitative budget differences between 2D and 3D as well as between various episodes will be detailed.Morover, simulated radar signatures and Q1/Q2 fields from the three simulations are compared to each other and with radar and sounding observations.

Shie, Chung-Lin↗
NASA NTRS2006

Convective Weather Forecast Quality Metrics for Air Traffic Management Decision-Making

Since numerical weather prediction models are unable to accurately forecast the severity and the location of the storm cells several hours into the future when compared with observation data, there has been a growing interest in probabilistic description of convective weather. The classical approach for generating uncertainty bounds consists of integrating the state equations and covariance propagation equations forward in time. This step is readily recognized as the process update step of the Kalman Filter algorithm. The second well known method, known as the Monte Carlo method, consists of generating output samples by driving the forecast algorithm with input samples selected from distributions. The statistical properties of the distributions of the output samples are then used for defining the uncertainty bounds of the output variables. This method is computationally expensive for a complex model compared to the covariance propagation method. The main advantage of the Monte Carlo method is that a complex non-linear model can be easily handled. Recently, a few different methods for probabilistic forecasting have appeared in the literature. A method for computing probability of convection in a region using forecast data is described in Ref. 5. Probability at a grid location is computed as the fraction of grid points, within a box of specified dimensions around the grid location, with forecast convection precipitation exceeding a specified threshold. The main limitation of this method is that the results are dependent on the chosen dimensions of the box. The examples presented Ref. 5 show that this process is equivalent to low-pass filtering of the forecast data with a finite support spatial filter. References 6 and 7 describe the technique for computing percentage coverage within a 92 x 92 square-kilometer box and assigning the value to the center 4 x 4 square-kilometer box. This technique is same as that described in Ref. 5. Characterizing the forecast, following the process described in Refs. 5 through 7, in terms of percentage coverage or confidence level is notionally sound compared to characterizing in terms of probabilities because the probability of the forecast being correct can only be determined using actual observations. References 5 through 7 only use the forecast data and not the observations. The method for computing the probability of detection, false alarm ratio and several forecast quality metrics (Skill Scores) using both the forecast and observation data are given in Ref. 2. This paper extends the statistical verification method in Ref. 2 to determine co-occurrence probabilities. The method consists of computing the probability that a severe weather cell (grid location) is detected in the observation data in the neighborhood of the severe weather cell in the forecast data. Probabilities of occurrence at the grid location and in its neighborhood with higher severity, and with lower severity in the observation data compared to that in the forecast data are examined. The method proposed in Refs. 5 through 7 is used for computing the probability that a certain number of cells in the neighborhood of severe weather cells in the forecast data are seen as severe weather cells in the observation data. Finally, the probability of existence of gaps in the observation data in the neighborhood of severe weather cells in forecast data is computed. Gaps are defined as openings between severe weather cells through which an aircraft can safely fly to its intended destination. The rest of the paper is organized as follows. Section II summarizes the statistical verification method described in Ref. 2. The extension of this method for computing the co-occurrence probabilities in discussed in Section HI. Numerical examples using NCWF forecast data and NCWD observation data are presented in Section III to elucidate the characteristics of the co-occurrence probabilities. This section also discusses the procedure for computing throbabilities that the severity of convection in the observation data will be higher or lower in the neighborhood of grid locations compared to that indicated at the grid locations in the forecast data. The probability of coverage of neighborhood grid cells is also described via examples in this section. Section IV discusses the gap detection algorithm and presents a numerical example to illustrate the method. The locations of the detected gaps in the observation data are used along with the locations of convective weather cells in the forecast data to determine the probability of existence of gaps in the neighborhood of these cells. Finally, the paper is concluded in Section V.

Chatterji, Gano B.↗
NASA NTRS2009

Diagnosis and Reconfiguration using Bayesian Networks: An Electrical Power System Case Study

Automated diagnosis and reconfiguration are important computational techniques that aim to minimize human intervention in autonomous systems. In this paper, we develop novel techniques and models in the context of diagnosis and reconfiguration reasoning using causal Bayesian networks (BNs). We take as starting point a successful diagnostic approach, using a static BN developed for a real-world electrical power system. We discuss in this paper the extension of this diagnostic approach along two dimensions, namely: (i) from a static BN to a dynamic BN; and (ii) from a diagnostic task to a reconfiguration task. More specifically, we discuss the auto-generation of a dynamic Bayesian network from a static Bayesian network. In addition, we discuss subtle, but important, differences between Bayesian networks when used for diagnosis versus reconfiguration. We discuss a novel reconfiguration agent, which models a system causally, including effects of actions through time, using a dynamic Bayesian network. Though the techniques we discuss are general, we demonstrate them in the context of electrical power systems (EPSs) for aircraft and spacecraft. EPSs are vital subsystems on-board aircraft and spacecraft, and many incidents and accidents of these vehicles have been attributed to EPS failures. We discuss a case study that provides initial but promising results for our approach in the setting of electrical power systems.

Knox, W. Bradley↗
NASA NTRS2020

Artificial Thickening of a Transonic Boundary Layer in the Presence of a Pressure Gradient Associated with a Boundary Layer Ingestion Concept

Boundary layer ingestion is an aeropropulsive concept associated with a propulsion airframe integration technique that integrates viscous aerodynamics into a propulsion system to achieve more efficient flight. The effectiveness of this concept is heavily dependent on how much of the boundary layer is being ingested into the propulsor. Scaling this concept for transonic wind tunnel testing is often plagued with blockage issues and requires a modification to the model dimensions such as fuselage length and diameter and wingspan. To simulate the boundary layer for these modified models requires a manipulation of the boundary layer height to achieve the appropriate ratio of boundary layer to propulsor inlet diameter or height. This paper will focus on 15 different transonic boundary layer manipulators to achieve varying turbulent boundary layer heights for a representative single-aisle transport utilizing Boundary Layer Ingestion.

Gregory S Jones↗
DOE OSTI2020

LHC signals for KK graviton from an extended warped extra dimension

We analyze signals at the Large Hadron Collider (LHC) from production and decay of Kaluza-Klein (KK) gravitons in the context of “extended” warped extra-dimensional models, where the standard model (SM) Higgs and fermion fields are restricted to be in-between the usual ultraviolet/Planck brane and a ~ O(10) TeV (new, “intermediate”) brane, whereas the SM gauge fields (and gravity) propagate further down to the ~ O(TeV) infrared brane. Such a framework suppresses flavor violation stemming from KK particle effects, while keeping the KK gauge bosons and gravitons accessible to the LHC. We find that the signals from KK graviton are significantly different than in the standard warped model. This is because the usually dominant decay modes of KK gravitons into top quark, Higgs and longitudinal W/Z particles are suppressed by the above spatial separation between these two sets of particles, thus other decay channels are allowed to shine themselves. In particular, we focus on two novel decay channels of the KK graviton. The first one is the decay into a pair of radions, each of which decays (dominantly) into a pair of SM gluons, resulting in a resonant 4-jet final state consisting of two pairs of dijet resonance. On the other hand, if the radion is heavier and/or KK gluon is lighter, then the KK graviton mostly decays into a KK gluon and a SM gluon. The resulting KK gluon has a significant decay branching fraction into radion and SM gluon, thereby generating (again) a 4-jet signature, but with a different underlying event topology, i.e., featuring now three different resonances. We demonstrate that the High-Luminosity LHC (HL-LHC) has sensitivity to KK graviton of (up to) ~ 4 TeV in both channels, in the specific model with only gluon field (and gravity) propagating in the extended bulk, whereas it is unlikely to have sensitivity in the standard dijet resonance search channel from KK graviton decay into two gluons.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Triangle Method for Dense ReLU Layers [SWR-25-72]

This software is an implementation of the methods for initializing and training neural networks to be more efficient per parameter, described more fully below and in the related publication: In theory, depth should make a ReLU network EXPONENTIALLY more efficient by enabling it to produce an exponential number of piecewise linear sections in its output. This reasoning is largely based on the work of mathematicians that have hand-constructed networks that make good use of depth. In practice however, even very deep ReLU networks that have been randomly initialized will behave identically to their shallow counterparts - missing an entire exponential dimension of efficiency. The triangle method is a first attempt at realizing the exponential potential of deep networks. Instead of randomly setting weights, we force pairs of neurons in each layer learn to build triangles (i.e. functions from [0,1] -> [0,1] that look like triangles). This is a very efficient pattern for generating lots of linear pieces because composing two triangular functions doubles the number of pieces with each composition. The triangle method is more than just a different initialization, it is a new paradigm of training. Instead of making direct updates to the matrix weights, we do an extra step of backpropagation to collect the derivatives of the loss function with respect to the shapes of the triangles, training them to tilt left or right. This process essentially holds the networks hand throughout the loss landscape and forces it to always use depth effectively by producing triangular shapes internally. This can produce several orders of magnitude of improvement on convex one-dimensional regression problems. Much more theoretical work is needed to realize its full potential beyond this context, but the implementation in this repository will still work in arbitrary numbers of dimensions. The file Triangle_Method.py is a generalized form of the method that will build each neuron its own custom 1-d convex activation function (with exponential efficiency). Example usage on one dimensional problems can be found in Example_Usage.ipynb and an example of using this in a real neural network can be found in Example_VGG16_CIFAR10.ipynb.

Milkert, Max [National Renewable Energy Laboratory↗