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At least 1,009 records · Page 56

Computation of Variability in the Average Thermal and Mechanical Properties of a Melt-infiltrated Sic/sic Composite

Thermal conductivity and tensile properties (elastic modulus, proportional limit strength, inplane tensile strength, and strain to failure) of a SiC/SiC composite were experimentally determined at 816 and 1204 C. Tests were performed at room temperature on the same material to obtain interlaminar shear and tensile strength. For each thermal and mechanical property 24 tests were conducted to capture the variation. A random sampling method was used to quantify the variability exhibited by the mean values of the thermal and mechanical properties. The minimum number of tests required to characterize the mean value of each thermal or mechanical property for the composite was determined by varying the group size of the random sample.

Kalluri, Sreeramesh↗

Asymptotic Energies and QED Shifts for Rydberg States of Helium

This paper reviews progress that has been made in obtaining essentially exact solutions to the nonrelativistic three-body problem for helium by a combination of variational and asymptotic expansion methods. The calculation of relativistic and quantum electrodynamic corrections by perturbation theory is discussed, and in particular, methods for the accurate calculation of the Bethe logarithm part of the electron self energy are presented. As an example, the results are applied to the calculation of isotope shifts for the short-lived 'halo' nucleus He-6 relative to He-4 in order to determine the nuclear charge radius of He-6 from high precision spectroscopic measurements carried out at the Argonne National Laboratory. The results demonstrate that the high precision that is now available from atomic theory is creating new opportunities to create novel measurement tools, and helium, along with hydrogen, can be regarded as a fundamental atomic system whose spectrum is well understood for all practical purposes.

Drake, G.W.F.↗

EMU Suit Performance Simulation

Introduction: Designing a planetary suit is very complex and often requires difficult trade‐offs between performance, cost, mass, and system complexity. To verify that new suit designs meet requirements, full prototypes must be built and tested with human subjects. However, numerous design iterations will occur before the hardware meets those requirements. Traditional draw‐prototype‐test paradigms for research and development are prohibitively expensive with today's shrinking Government budgets. Personnel at NASA are developing modern simulation techniques that focus on a human‐centric design paradigm. These new techniques make use of virtual prototype simulations and fully adjustable physical prototypes of suit hardware. This is extremely advantageous and enables comprehensive design down‐selections to be made early in the design process. Objectives: The primary objective was to test modern simulation techniques for evaluating the human performance component of two EMU suit concepts, pivoted and planar style hard upper torso (HUT). Methods: This project simulated variations in EVA suit shoulder joint design and subject anthropometry and then measured the differences in shoulder mobility caused by the modifications. These estimations were compared to human‐in‐the‐loop test data gathered during past suited testing using four subjects (two large males, two small females). Results: Results demonstrated that EVA suit modeling and simulation are feasible design tools for evaluating and optimizing suit design based on simulated performance. The suit simulation model was found to be advantageous in its ability to visually represent complex motions and volumetric reach zones in three dimensions, giving designers a faster and deeper comprehension of suit component performance vs. human performance. Suit models were able to discern differing movement capabilities between EMU HUT configurations, generic suit fit concerns, and specific suit fit concerns for crewmembers based on individual anthropometry

Cowley, Matthew S.↗

Automated Behavior Analysis of Malware: A Case Study of WannaCry Ransomware

Ransomware, a class of self-propagating malware that uses encryption to hold the victims’ data ransom, has emerged in recent years as one of the most dangerous cyber threats, with widespread damage; e.g., zero-day ransomware WannaCry has caused world-wide catastrophe, from knocking U.K. National Health Service hospitals offline to shutting down a Honda Motor Company in Japan [1]. Our close collaboration with security operations of large enterprises reveals that defense against ransomware relies on tedious analysis from high-volume systems logs of the first few infections. Sandbox analysis of freshly captured malware is also commonplace in operation. We introduce a method to identify and rank the most discriminating ransomware features from a set of ambient (non-attack) system logs and at least one log stream containing both ambient and ransomware behavior. These ranked features reveal a set of malware actions that are produced automatically from system logs, and can help automate tedious manual analysis. We test our approach using WannaCry and two polymorphic samples by producing logs with Cuckoo Sandbox during both ambient, and ambient plus ransomware executions. Our goal is to extract the features of the malware from the logs with only knowledge that malware was present. We compare outputs with a detailed analysis of WannaCry allowing validation of the algorithm’s feature extraction and provide analysis of the method’s robustness to variations of input data—changing quality/quantity of ambient data and testing polymorphic ransomware. Most notably, our patterns are accurate and unwavering when generated from polymorphic WannaCry copies, on which 63 (of 63 tested) antivirus (AV) products fail.

Chen, Qian↗

Recent Hydrodynamic Modeling Enhancements in OpenFAST: Preprint

To improve the hydrodynamic modeling capabilities of the offshore wind design and modeling tool OpenFAST, a restructuring of the HydroDyn hydrodynamics module was undertaken with several new features implemented. The generation of the wave field is now separated from HydroDyn into a new module called SeaState. Unlike previous versions of HydroDyn, which precomputed the wave kinematics at the undisplaced positions of the hydrodynamic nodes, the new SeaState module computes the complete time history of the wave field at the vertices of a user-defined wave grid. During the simulation, the wave kinematics at any point within the grid can be efficiently interpolated, allowing the strip-theory wave loads to be evaluated based on the wave kinematics at the displaced structure position. A phase correction was also implemented for the potential-flow wave-exciting loads to account for large structure displacements. Several wave-stretching methods were implemented for the strip-theory solution along with a wave-load redistribution method that ensures smooth variation of the nodal loads as the nodes of a discrete hydrodynamic mesh enter and exit the water. The load smoothing is included to avoid the excitation of unphysical high-frequency structural vibration during hydroelastic simulations. The MacCamy-Fuchs diffraction correction for the strip-theory solution and the capability to insert a constrained NewWave into extreme stochastic sea states with directional spreading were also added. The present article documents the formulations of the new improvements to HydroDyn with example applications and numerical results.

constrained wave↗

Crossing The Gap Using Variational Quantum Eigensolver: A Comparative Study

Within the evolving domain of quantum computational chemistry, the Variational Quantum Eigensolver (VQE) has been developed to explore not only the ground state but also the excited states of molecules. In this study, we compare the performance of Variational Quantum Deflation (VQD) and Subspace-Search Variational Quantum Eigensolver (SSVQE) methods in determining the low-lying excited states of $LiH$. Our investigation reveals that while VQD exhibits a slight advantage in accuracy, SSVQE stands out for its efficiency, allowing the determination of all low-lying excited states through a single parameter optimization procedure. We further evaluate the effectiveness of optimizers, including Gradient Descent (GD), Quantum Natural Gradient (QNG), and Adam optimizer, in obtaining $LiH$'s first excited state, with the Adam optimizer demonstrating superior efficiency in requiring the fewest iterations. Moreover, we propose a novel approach combining Folded Spectrum VQE (FS-VQE) with either VQD or SSVQE, enabling the exploration of highly excited states. We test the new approaches for finding all three $H_4$'s excited states. Folded Spectrum SSVQE (FS-SSVQE) can find all three highly excited states near $-1.0$ Ha with only one optimizing procedure, but the procedure converges slowly. In contrast, although Folded spectrum VQD (FS-VQD) gets highly excited states with individual optimizing procedures, the optimizing procedure converges faster.

Chen, I-Chi↗

The cosmic ray differential diurnal variation dependences on the zenith angle and the geomagnetic disturbance

Simultaneous and continuous muon measurements in two opposite azimuthal directions under equal zenith angles demonstrated the importance of this method for cosmic ray diurnal variation investigations. Lately these measurements were extended by means of improved telescopes. The obtained cosmic ray diurnal variations were presented as intensity differential curves. Theoretical investigations connected the properties of these curves with some interplanetary spece parameters. The harmonics of these curves were interpreted physically. Some order difference curves were introduced. In earlier works some dependences between the parameters characterizing the first and the second harmonics of the differential intensity curves and the geomagnetic activity were found. Then all measurements were carried out under only one zenith angle. The results of investigations of similar dependences using data of simultaneous measurements under three different zenith angles are presented.

Kavlakov, S.↗

Evaluation of a strained-coordinate perturbation procedure - Nonlinear subsonic and transonic flows

An evaluation is made of a perturbation method devised to obtain highly accurate approximations to families of strongly nonlinear solutions which are either continuous or discontinuous, and which represent variations in some arbitrary parameter. The method first defines a unit perturbation by using two nonlinear solutions which differ from one another by a nominal change in some geometric or flow parameter, then employs this unit perturbation to predict a family of related nonlinear solutions over a range of parameter variation. Coordinate straining is incorporated into this perturbation method for determining the unit perturbation to account for the movement of discontinuities and maxima of high-gradient regions due to the perturbation. Attention is given to transonic and subsonic flows. Comparisons of the perturbation results with the corresponding 'exact' nonlinear solutions show a remarkable accuracy and range of validity of the perturbation method across the spectrum of examples considered.

Stahara, S. S.↗

A novel approach for estimating densities of secretive species from road-survey and spatial-movement data

Accurate estimates of population density are a critical component of effective wildlife conservation and management. However, many snake species are so secretive that their density cannot be determined using traditional methods such as capture–mark–recapture. Thus, the status of most terrestrial snake populations remains completely unknown. We developed a novel simulation-based technique for estimating density of secretive snakes that combined behavioural observations of snake road-crossing behaviour (crossing speed), effort-corrected road-survey data, and simulations of spatial movement patterns derived from radio-telemetry, without relying on mark–recapture. Here, we used radio-telemetry data to parameterise individual-based movement models that estimate the frequency with which individual snakes cross roads and used information on survey vehicle speed and snake crossing speed to determine the probability of detecting a snake, given that it crosses the road transect during a survey. Snake encounter frequencies during systematic road surveys were then interpreted in light of detection probabilities and simulation model results to estimate snake densities and to assess various factors likely to affect abundance estimates. We demonstrated the broad applicability of this approach through a case study of the imperiled southern hognose snake (Heterodon simus) in the North Carolina (USA) Sandhills. We estimated that H. simus occurs at average densities of 0.17 ha –1 in the North Carolina Sandhills and explored the sensitivity of this estimate to assumptions and variation in model parameters. Our novel method allowed us to generate the first abundance estimates for H. simus. We found that H. simus exists at low densities relative to congeners and other mid-sized snake species, raising concern that this species may not only have declined in geographic range, but may also occur at low densities or be declining in their strongholds, such as the North Carolina Sandhills. We present a framework for estimating density of species that have traditionally been considered too secretive to study at the population level. This method will greatly enhance our ability to study and manage a wide variety of snake species and could be applied to other secretive wildlife species that are most frequently encountered during road surveys.

59 BASIC BIOLOGICAL SCIENCES↗

Spatial decomposition of magnetic anisotropy in magnets: Application to doped Fe 16 N 2

We propose a scheme of decomposition of the total relativistic energy in solids to intra- and interatomic contributions. The method is based on a site variation of such fundamental constant as the speed of light. As a practical illustration of the method, we tested such decomposition in the case of a spin-orbit interaction variation for the decomposition of the magnetic anisotropy energy (MAE) in CoPt. We further studied the α" - Fe 16 N 2 magnet doped by Bi, Sb, Co, and Pt atoms. It was found that the addition of Pt atoms can enhance the MAE by as much as five times while Bi and Sb substitutions double the total MAE. Using the proposed technique, we demonstrate the spatial distribution of these enhancements. Our studies also suggest that Sb, Pt, and Co substitutions could be synthesized by experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Riley County Water Resources Project Summary - Comparing Runoff Curve Calculation Methods to Inform Local Resiliency Initiatives in Riley County, Kansas

Riley County, Kansas, has observed increased levels of flooding, potentially due to changes in land use/land cover (LULC) and seasonal vegetation variation. This study contrasts two methods of generating runoff curve numbers (CN) from 2006-2020. (1) The traditional Soil Conservation Service CN calculation method uses a look-up table and tracked LULC to determine runoff changes. These tables allow for land cover-specific CN and account for various farming techniques but lack flexibility in calculations for various seasons or plant health. (2) A dynamic method employs normalized difference vegetation index (NDVI) compiled over the rainy season each year to calculate CN using seasonal vegetation. This method allows for a more precise analysis of runoff variability within and between rainy seasons because it can be updated with greater temporal detail and captures higher spatial resolutions by using NDVI as a proxy for LULC. This study further uses inputs from the United States Geological Survey (USGS) National Land Cover Database (NLCD), the United States Department of Agriculture (USDA) Cropland Data Layer, and Landsat imagery to create more precise LULC raster datasets including both urban cover and crop-specific land use and curve number maps of the area. Results can guide decision makers in the City of Manhattan, Riley County Department of Planning and Development, Riley County Conservation District, the Kansas Forest Service, and the Kansas Department of Health and Environment toward informed decisions on resiliency strategies to address future flooding.

DEVELOP Project Summary↗

Diurnal variations of cosmic ray geomagnetic cut-off threshold rigidities

The spectrographic global survey method was used to investigate the rigidity variations Rc of geomagnetic cut-off as a function of local time and the level of geomagnetic disturbance for a number of stations of the world wide network. It is shown that geomagnetic cut-off threshold rigidities undergo diurnal variations. The diurnal wave amplitude decreases with increasing threshold rigidity Rc, and the wave maximum occurs at 2 to 4 hr LT. The amplitude of diurnal variations increases with increasing geomagnetic activity. The results agree with those from trajectory calculations made for an asymmetric model of the magnetosphere during different geomagnetic disturbance conditions.

Dvornikov, V. M.↗

Improved heavy-ion PID using scintillation light detector with neural network analysis: a Monte Carlo simulation study

The photon collection efficiency of gaseous scintillator detectors varies according to the position of the impinging charged particles in the medium that generates scintillation light. Thus, when impinging particles are distributed over a large area, the intrinsic photon-number resolution of the system is affected by a large variation. This work presents and discusses a method for adjusting the total number of detected photons to account for variation in the photon collection efficiency as a function of the position of the light source within the scintillating medium. The method was developed and validated by processing data from systematic simulation studies based on GEANT4 that model the response of the Energy Loss Optical Scintillation System (ELOSS) detector. The position of the charged particle is calculated using a deep neural network algorithm. This is accomplished by analyzing the distribution of scintillation light recorded by the array of photosensors. The estimated particle position is then used to calculate the correction factor and adjust the amount of captured light to account for variations in the photon collection efficiency. The neural network algorithm provides excellent tracking capabilities, achieving sub-millimeter position resolution and an angular resolution of 12 mrad, approaching the performance of traditional tracking detectors (e.g., drift chambers). The present method can be generalized to any optical scintillation system where the photon collection efficiency depends on the position of the impinging particle.

Heavy-ion detectors↗

Estimation of surface moisture availability from remote temperature measurements

Analysis of moisture availability, determined from GOES IR surface temperature measurements and a boundary layer model, and antecedent precipitation are presented for data taken over Texas and Argentina. Correlations between antecedent precipitation and moisture availability are high where the spatial variation in moisture availability is much larger than an inherent uncertainty in the method, which is judged to be about + or - 0.2 for the moisture availability parameter. In regions where there are large gradients of precipitation, the IR method can provide useful information on variations in soil moisture availability and, by implication, in precipitation.

Flores, Alberto L.↗

On instruction sets and their formats

Central to instruction set design is the issue of the instruction format. Some common format encoding techniques are discussed, and a method of representing high-level language parse trees by means of formats that cover successively larger portions of a tree is introduced. Variations are introduced on the method that represent directed acyclic graphs as well as simple parse trees, and that encode constants in a special fashion. For a particular representation, the number of times each format is executed to run a sample program to completion is measured.

Flynn, M. J.↗

Support Vector Machines for Classification of Direct Energy Deposition Standoff Distance for Improved Process Control

A critical factor in the implementation of direct energy deposition is the ability to maintain the standoff distance between the nozzle and the build surface, as this influences powder capture efficiency and overall part quality. Due to process-related variations, layer height may vary, causing unintended variation in standoff distance and poor build quality. While prior work has utilized contact probing to qualify standoff distance during processing, in situ methods for qualification of standoff distance are of major interest. The present work seeks to understand efficacy of image-based methods for classifying standoff distance variation in real-time using support vector machines (SVMs). It was hypothesized that the size of the melt pool and the amount of spatter will have significant correlations with deviations in the standoff distance; thus, SVMs were used on a dataset that is comprised of morphological features of melt pool size and image entropy. The SVM model was used to classify melt pool images into categories according to standoff distance variation from nominal. K-folds cross validation was used to find the optimal hyperparameters for the SVM model. To understand the impact of the selected features on the classification performance and inference speed, multiple models were trained with differing numbers of included features. Results for classification score, inference time, and image preprocessing/feature extraction from these data are reported. The present results show that the SVM model was able to predict the standoff distance classification with an accuracy of 97 percent and a speed of 0.122 s per image, making it a viable solution for real-time control of standoff distance.

Klesmith, Zoe↗

Hybrid analytical technique for the nonlinear analysis of curved beams

The application of a two-step hybrid technique to the geometrically nonlinear analysis of curved beams is used to demonstrate the potential of hybrid analytical techniques in nonlinear structural mechanics. The hybrid technique is based on successive use of the perturbation method and a classical direct variational procedure. The functions associated with the various-order terms in the perturbation expansion of the fundamental unknowns, and their sensitivity derivatives with respect to material and geometric parameters of the beam, are first obtained by using the perturbation method. These functions are selected as coordinate functions (or modes) and the classical direct variational technique is then used to compute their amplitudes. The potential of the proposed hybrid technique for nonlinear analysis of structures is discussed. The effectiveness of the hybrid technique is demonstrated by means of numerical examples. The symbolic computation system Mathematica is used in the present study. The tasks performed on Mathematica include: (1) generation of algebraic expressions for the perturbation functions of the different response quantities and their sensitivity derivatives: and (2) determination of the radius of convergence of the perturbation series.

Noor, A. K.↗

An iterative reconstruction algorithm for pole figure inversion using total variation regularization

This paper describes a new discrete method for inverting X-ray pole figures to estimate the orientation distribution function (ODF). The method employs the equal-volume `cubochoric' representation for uniform discretization of orientation space, SO(3). The forward-projection model is combined with an anisotropic total variation term to iteratively determine the ODF. Here, the efficacy of the new method is evaluated with both model and experimental data and compared with existing discrete and series expansion methods.

97 MATHEMATICS AND COMPUTING↗