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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 OSTI2022

Improving Effective Mass Estimations in Pu-Metal Annuli

Determining the effective mass of 240 Pu in a plutonium metal item can be achieved through a number of destructive and non-destructive assay techniques. However, these techniques have one or more shortcomings. These include the need for large quantities of plutonium, long measurement time, or lack of sufficient accuracy. While efforts have been made to mitigate these issues by estimating 240 Pu quantities through neutron coincidence counting techniques, these estimates are subject to systematic bias, and their estimates are not well characterized when other factors of the annulus’ physical form and composition are accounted for. In this work, we expand upon these non-destructive assay techniques via the implementation of random forest machine learning models, which produce correction functions that augment and improve the effective mass estimates derived from classical leakage multiplication, singles, doubles, and triples multiplicity counting equations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1995

Weight distributions for turbo codes using random and nonrandom permutations

This article takes a preliminary look at the weight distributions achievable for turbo codes using random, nonrandom, and semirandom permutations. Due to the recursiveness of the encoders, it is important to distinguish between self-terminating and non-self-terminating input sequences. The non-self-terminating sequences have little effect on decoder performance, because they accumulate high encoded weight until they are artificially terminated at the end of the block. From probabilistic arguments based on selecting the permutations randomly, it is concluded that the self-terminating weight-2 data sequences are the most important consideration in the design of constituent codes; higher-weight self-terminating sequences have successively decreasing importance. Also, increasing the number of codes and, correspondingly, the number of permutations makes it more and more likely that the bad input sequences will be broken up by one or more of the permuters. It is possible to design nonrandom permutations that ensure that the minimum distance due to weight-2 input sequences grows roughly as the square root of (2N), where N is the block length. However, these nonrandom permutations amplify the bad effects of higher-weight inputs, and as a result they are inferior in performance to randomly selected permutations. But there are 'semirandom' permutations that perform nearly as well as the designed nonrandom permutations with respect to weight-2 input sequences and are not as susceptible to being foiled by higher-weight inputs.

Dolinar, S.↗
DOE OSTI2020

Modeling the role of local crystallographic correlations in microstructures of Ti-6Al-4V using a correlated structure visco-plastic self-consistent polycrystal plasticity formulation

This paper presents a multi-level crystal plasticity-based simulation framework for modeling mechanical response and microstructure evolution of Ti-6Al-4V with α-lath/lamellar microstructures. Here, the model is a correlated structure visco-plastic self-consistent (CS-VPSC) formulation linking three scales: a single crystals micro-scale, a lath/lamellar colony meso-scale, and a lath/lamellar aggregate macro-scale. A selected hardening law for the evolution of critical resolved shear stress per slip system used in CS-VPSC is phenomenological. However, it adjusts the resistances of basal and prismatic slip systems based on the geometry of slip transfer between adjacent lamellae. Consistent with experimental evidences, the resolved shear stress on the pyramidal slip planes is dependent not only on the stress in the direction of slip but also on the two orthogonal shear stress components and the three normal stress components (non-Schmid effects). Electron backscatter diffraction (EBSD) data in conjunction with a procedure relying on α→β phase transformation is used to construct paired variants of α-laths/lamellae satisfying their local crystallographic correlations. The procedure fits volume fractions of individual laths/lamellae with the experimental EBSD data and selects a distribution of habit planes between adjacent variants with respect to the loading direction. The simulation framework is applied to interpret the deformation behavior in tension and compression along two sample directions of Ti-6Al-4V fabricated via laser powder bed fusion. Moreover, the model is used to simulate texture evolution during rolling of the material to large strains. It is demonstrated that the model is capable of predicting plastic anisotropy/asymmetry and the concomitant texture evolution. While the model reveals a significant effect of habit plane inclination with respect to the loading direction on yield stress, the comparison of the data and model predictions shows that a random distribution of habit planes fits the flow response. It is further inferred that the tension-compression asymmetry arises from the non-Schmid effects.

36 MATERIALS SCIENCE↗
DOE OSTI2021

A predictive discrete-continuum multiscale model of plasticity with quantified uncertainty

Multiscale models of materials, consisting of upscaling discrete simulations to continuum models, are unique in their capability to simulate complex materials behavior. The fundamental limitation in multiscale models is the presence of uncertainty in the computational predictions delivered by them. In this work, a sequential multiscale model has been developed, incorporating discrete dislocation dynamics (DDD) simulations and a strain gradient plasticity (SGP) model to predict the size effect in plastic deformations of metallic micro-pillars. The DDD simulations include uniaxial compression of micro-pillars with different sizes and over a wide range of initial dislocation densities and spatial distributions of dislocations. An SGP model is employed at the continuum level that accounts for the size-dependency of flow stress and hardening rate. Sequences of uncertainty analyses have been performed to assess the predictive capability of the multiscale model. The variance-based global sensitivity analysis determines the effect of parameter uncertainty on the SGP model prediction. The multiscale model is then constructed by calibrating the continuum model using the data furnished by the DDD simulations. A Bayesian calibration method is implemented to quantify the uncertainty due to microstructural randomness in discrete dislocation simulations (density and spatial distribution of dislocations) on the macroscopic continuum model prediction (size effect in plastic deformation). Here, the outcomes of this study indicate that the discrete-continuum multiscale model can accurately simulate the plastic deformation of micro-pillars, despite the significant uncertainty in the DDD results. Additionally, depending on the macroscopic features represented by the DDD simulations, the SGP model can reliably predict the size effect in plasticity responses of the micropillars with below 10% of error.

36 MATERIALS SCIENCE↗
NASA NTRS1983

Surface roughness effects with solid lubricants dispersed in mineral oils

The lubricating effectiveness of solid-lubricant dispersions are investigated in both point and line contacts using surfaces with both random and directional roughness characteristics. Friction and wear data obtained at relatively low speeds and at room temperature, indicate that the existence of solid lubricants such as graphite, MoS2, and PTFE in a plain mineral oil generally will not improve the effectiveness of the oil as a lubricant for such surfaces. Under boundary lubrication conditions, the friction force, as a function of time, initially depends upon the directional roughness properties of the contacting surfaces irrespective of whether the base oil or dispersions are used as lubricants.

Cusano, C.↗
NASA NTRS1985

Statistical methods for efficient design of community surveys of response to noise: Random coefficients regression models

Research studies of residents' responses to noise consist of interviews with samples of individuals who are drawn from a number of different compact study areas. The statistical techniques developed provide a basis for those sample design decisions. These techniques are suitable for a wide range of sample survey applications. A sample may consist of a random sample of residents selected from a sample of compact study areas, or in a more complex design, of a sample of residents selected from a sample of larger areas (e.g., cities). The techniques may be applied to estimates of the effects on annoyance of noise level, numbers of noise events, the time-of-day of the events, ambient noise levels, or other factors. Methods are provided for determining, in advance, how accurately these effects can be estimated for different sample sizes and study designs. Using a simple cost function, they also provide for optimum allocation of the sample across the stages of the design for estimating these effects. These techniques are developed via a regression model in which the regression coefficients are assumed to be random, with components of variance associated with the various stages of a multi-stage sample design.

Tomberlin, T. J.↗
NASA NTRS1992

Computational simulation of coupled material degradation processes for probabilistic lifetime strength of aerospace materials

The research included ongoing development of methodology that provides probabilistic lifetime strength of aerospace materials via computational simulation. A probabilistic material strength degradation model, in the form of a randomized multifactor interaction equation, is postulated for strength degradation of structural components of aerospace propulsion systems subjected to a number of effects or primative variables. These primative variable may include high temperature, fatigue or creep. In most cases, strength is reduced as a result of the action of a variable. This multifactor interaction strength degradation equation has been randomized and is included in the computer program, PROMISS. Also included in the research is the development of methodology to calibrate the above described constitutive equation using actual experimental materials data together with linear regression of that data, thereby predicting values for the empirical material constraints for each effect or primative variable. This regression methodology is included in the computer program, PROMISC. Actual experimental materials data were obtained from the open literature for materials typically of interest to those studying aerospace propulsion system components. Material data for Inconel 718 was analyzed using the developed methodology.

Boyce, Lola↗
NASA NTRS1992

Computational simulation of probabilistic lifetime strength for aerospace materials subjected to high temperature, mechanical fatigue, creep and thermal fatigue

This report presents the results of a fourth year effort of a research program, conducted for NASA-LeRC by the University of Texas at San Antonio (UTSA). The research included on-going development of methodology that provides probabilistic lifetime strength of aerospace materials via computational simulation. A probabilistic material strength degradation model, in the form of a randomized multifactor interaction equation, is postulated for strength degradation of structural components of aerospace propulsion systems subject to a number of effects or primitive variables. These primitive variables may include high temperature, fatigue or creep. In most cases, strength is reduced as a result of the action of a variable. This multifactor interaction strength degradation equation has been randomized and is included in the computer program, PROMISS. Also included in the research is the development of methodology to calibrate the above-described constitutive equation using actual experimental materials data together with regression analysis of that data, thereby predicting values for the empirical material constants for each effect or primitive variable. This regression methodology is included in the computer program, PROMISC. Actual experimental materials data were obtained from industry and the open literature for materials typically for applications in aerospace propulsion system components. Material data for Inconel 718 has been analyzed using the developed methodology.

Boyce, Lola↗
NASA NTRS1991

Rossby waves in a fluctuating zonal mean flow

The effects of the zonal mean wind variability on the energy propagation of a stationary Rossby wave in a barotropic nondivergent atmosphere are studied. It is shown that the random nature of the zonal wind fluctuations do not allow Rossby wave energy to propagate from its energy source. The mechanism for this effect is strongly dependent on the spatial resolution at which the zonal mean flow is assumed to be known. Some speculations are offered on the relation between this mechanism and the systematic error of some low-resolution climate models.

Pandolfo, Lionel↗
DOE OSTI2023

Machine Learning Based Resilience Testing of an Address Randomization Cyber Defense

Moving target defenses (MTDs) are widely used as an active defense strategy for thwarting cyberattacks on cyber-physical systems by increasing diversity of software and network paths. Recently, machine Learning (ML) and deep Learning (DL) models have been demonstrated to defeat some of the cyber defenses by learning attack detection patterns and defense strategies. It raises concerns about the susceptibility of MTD to ML and DL methods. Here, in this article, we analyze the effectiveness of ML and DL models when it comes to deciphering MTD methods and ultimately evade MTD-based protections in real-time systems. Specifically, we consider a MTD algorithm that periodically randomizes address assignments within the MIL-STD-1553 protocol—a military standard serial data bus. Two ML and DL-based tasks are performed on MIL-STD-1553 protocol to measure the effectiveness of the learning models in deciphering the MTD algorithm: 1) determining whether there is an address assignments change i.e., whether the given system employs a MTD protocol and if it does 2) predicting the future address assignments. The supervised learning models (random forest and k-nearest neighbors) effectively detected the address assignment changes and classified whether the given system is equipped with a specified MTD protocol. On the other hand, the unsupervised learning model (K-means) was significantly less effective. The DL model (long short-term memory) was able to predict the future addresses with varied effectiveness based on MTD algorithm's settings.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2025

Aided Active Learning (AAL) for Enhanced Critical Heat Flux Prediction

Accurate prediction of critical heat flux (CHF) is crucial for the safe and efficient operation of nuclear reactors. Traditional CHF modeling methods often require extensive experimental data, which are hard to obtain. This study introduces the Aided Active Learning (AAL) framework, which strategically minimizes data requirements without sacrificing model accuracy. Unlike conventional Active Learning (AL), AAL introduces an additional step of randomly selecting a subset from the sample pool before applying the query strategy. To evaluate the performance of AAL, two query strategies—uncertainty-based sampling and error-reduction sampling—were evaluated across the following models: random forest (RF), feedforward neural network (FNN), and variational feedforward neural network (vFNN). The proposed framework demonstrated that AAL effectively reduces the number of training samples needed to achieve comparable predictive accuracy. For the RF model, AL required only 710 samples to achieve an R2 score of 0.98, as compared to the 4,785 samples needed by random sampling. Similarly, the FNN model achieved the same R2 score with just 355 samples when using AL, a significant improvement over the 825 samples required by random sampling. In case of uncertainty-based sampling strategy, vFNN attained an R2 of 0.98 with 3,420 samples, reducing the sample requirement by 47% relative to the 6,440 samples needed for random sampling. Its performance suggests that larger training data are required to fully leverage its uncertainty quantification capabilities.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1996

Dynamics of Disorder-Order Transitions in Hard Sphere Colloidal Dispersions in micro-g

We performed a series of experiments on 0.518 millimeter PMMA spheres suspended in an index matching mixture of decalin and tetralin the microgravity environment provided by the Shuttle Columbia on mission STS-73. The samples ranged in concentration from 0.49 to 0.62. volume fraction (phi) of spheres, which covers the range in which liquid, coexistence, solid and glass phases are expected from Earth bound experiments. Light scattering was used to probe the static structure, and the particle dynamics. Digital and 35 mm photos provided information on the morphology of the crystals. In general, the crystallites grew considerably larger (roughly an order of magnitude larger) than the same samples with identical treatment in 1 g. The dynamic light scattering shows the typical short time diffusion and long time caging effects found in 1 g. The surprises that were encountered in microgravity include the preponderance of random hexagonal close packed (RHCP) structures and the complete absence of the expected face centered cubic (FCC) structure, existence of large dendritic crystals floating in the coexistence samples (where liquid and solid phases coexist) and the rapid crystallization of samples which exist only in glass phase under the influence of one g. These results suggest that colloidal crystal growth is profoundly effected by gravity in yet unrecognized ways. We suspect that the RCHP structure is related to the nonequilibrium growth that is evident from the presence of dendrites. An analysis of the dendritic growth instabilities is presented within the framework of the Ackerson-Schatzel equation.

Zhu, J. X.↗
DOE OSTI2024

Formation of Disordered Cocontinuous Phases by Randomly Linked Star Copolymers

Cocontinuous polymeric nanostructures have garnered significant interest due to their ability to combine different properties of two separate polymer domains. Randomly linked copolymer networks have proven to be especially robust for formation of disordered cocontinuous phases across wide composition ranges (≈30 wt % or more). While theoretical treatments of microphase-separated networks have focused primarily on the role of random elastic forces imposed on the self-assembled nanostructures by virtue of the network architecture, experimental studies seeking to disentangle these contributions from other potential effects, such as dispersity in preferred interfacial curvatures, have been scarce. To provide insight into this matter, we here study the self-assembly of randomly linked star copolymers (RSCs), constructed by linking premade polymer arms of polystyrene (PS) and poly(d,l-lactide) (PLA) using 3, 4, and 6-functional connectors. This architecture yields similar distributions of preferred curvature as networks made using corresponding difunctional strands, but lacks the elastic forces imposed by a network architecture. Gravimetry and small-angle X-ray scattering, coupled with scanning electron microscopy, were performed to identify the percolation of PS/PLA RSCs. Remarkably, the 4-arm RSC system exhibited a disordered cocontinuous window of ≈25 wt %, indicating that dispersity in preferred curvature can in some cases be sufficient to robustly drive formation of this morphology. However, the other RSC architectures showed smaller cocontinuous ranges, which we interpret in terms of the influence of homopolymer stars in the 3-arm case and the narrower distribution of preferred interfacial curvatures in the 6-arm case. Finally, thin layers of interconnected porous PS were achieved by solution-processing, suggesting that RSCs have the potential to serve as a robust and easily processable cocontinuous polymeric nanomaterials in both bulk and membrane geometries.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A Vibrational Energy Harvesting Sensor Based on Linear and Rotational Electromechanical Effects

In this investigation, a magnetically coupled double-spring design is presented for harvesting low-level non-stationary random vibrational energy. The sensor relies on multimodal coupling between the translation and rotation of a two-spring magnet and coil system to widen the harvesting bandwidth. Energy methods are used to develop a model to characterize the electromechanical response of the system, the solution of which is obtained using stochastic techniques based on a particle swarm algorithm. This approach provides an efficient method to estimate system parameters that otherwise are difficult or impossible to determine with independent measurements. The experimental results demonstrate agreement with the theoretical predictions over a limited bandwidth. The sensor can effectively harvest non-stationary vibration energy down to 10 -4 g within a limited bandwidth of 130–150 Hz. The sensor prototype has an operational volume of 2.6 cm 3 with a calculated power density of 0.2 W/cm 3 . The sensor’s small size results in a coupling efficiency of approximately 6% across the tested bandwidth.

42 ENGINEERING↗
DOE OSTI2021

Cost-Effectiveness Analysis of Stereotactic Ablative Radiation Therapy in Patients With Oligometastatic Cancer

The Stereotactic Ablative Radiation therapy for Comprehensive Treatment of Oligometastatic Tumors phase 2 randomized clinical trial found that stereotactic ablative radiation therapy (SABR) improved outcomes among cancer patients with oligometastatic disease. Yet, the cost of SABR along with the large number of patients with oligometastatic disease raises the important question of value. This study sought to evaluate the cost-effectiveness of the addition of SABR compared with standard therapy alone among cancer patients with oligometastatic disease.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS1980

Neutral cometary atmospheres. I - An average random walk model for photodissociation in comets

A method for constructing physically realistic photochemical models, taking into account the isotropic ejection of dissociated molecular fragments as well as radiation pressure acceleration, has been developed using Monte Carlo techniques. The effect of the isotropic ejection, as opposed to the radial motion arbitrarily assumed in Haser's model, is adequately described by a simple average random walk model. It is shown that measured radial (Haser) scale lengths are in fact only lower limits to a range of possible true scale lengths for a given brightness profile, which explains the current discrepancies between observed scale lengths and those predicted by photochemistry.

Combi, M. R.↗