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At least 361 records · Page 20

Optimal Sampling of a Reaction Coordinate in Molecular Dynamics

Estimating how free energy changes with the state of a system is a central goal in applications of statistical mechanics to problems of chemical or biological interest. From these free energy changes it is possible, for example, to establish which states of the system are stable, what are their probabilities and how the equilibria between these states are influenced by external conditions. Free energies are also of great utility in determining kinetics of transitions between different states. A variety of methods have been developed to compute free energies of condensed phase systems. Here, I will focus on one class of methods - those that allow for calculating free energy changes along one or several generalized coordinates in the system, often called reaction coordinates or order parameters . Considering that in almost all cases of practical interest a significant computational effort is required to determine free energy changes along such coordinates it is hardly surprising that efficiencies of different methods are of great concern. In most cases, the main difficulty is associated with its shape along the reaction coordinate. If the free energy changes markedly along this coordinate Boltzmann sampling of its different values becomes highly non-uniform. This, in turn, may have considerable, detrimental effect on the performance of many methods for calculating free energies.

Pohorille, Andrew↗

Prediction of slant path rain attenuation statistics at various locations

The paper describes a method for predicting slant path attenuation statistics at arbitrary locations for variable frequencies and path elevation angles. The method involves the use of median reflectivity factor-height profiles measured with radar as well as the use of long-term point rain rate data and assumed or measured drop size distributions. The attenuation coefficient due to cloud liquid water in the presence of rain is also considered. Absolute probability fade distributions are compared for eight cases: Maryland (15 GHz), Texas (30 GHz), Slough, England (19 and 37 GHz), Fayetteville, North Carolina (13 and 18 GHz), and Cambridge, Massachusetts (13 and 18 GHz).

Goldhirsh, J.↗

Stochastic Modeling in a Multimaterial Continuum Mixture Shock Physics Code

Stochastic modelling approaches are presented to capture random effects at multiple time and length scales. Random processes that occur at the microscale produce nondeterministic effects at the macroscale. Here we present three stochastic modeling approaches that describe random processes at microscopic length scales and map these processes to the macroscopic length scale. The first stochastic modeling approach is based upon a particle based numerical technique to solve a Stochastic Differential Equation (SDE) using an arbitrary diffusion process to capture random processes at the microstructural level. The second approach prescribes a Probability Density Function (PDF) for the drift and diffusion of the random variable derived using the forward and backward Kolmogorov equations. This method requires mean and drift evolution PDF transport equations. The third approach is the coupling of multiple random variables which are dependent on each other. The relationship of the PDFs and a coupling function, known as a copula, produces a Joint Probability Density Function (JPDF). These stochastic modeling approaches are implemented into a Multiple Component (MC) shock physics computational code and used to model statistical fracture and reactive flow applications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

New method for estimating low-earth-orbit collision probabilities

An unconventional but general method is described for estimating the probability of collision between an earth-orbiting spacecraft and orbital debris. This method uses a Monte Caralo simulation of the orbital motion of the target spacecraft and each discrete debris object to generate an empirical set of distances, each distance representing the separation between the spacecraft and the nearest debris object at random times. Using concepts from the asymptotic theory of extreme order statistics, an analytical density function is fitted to this set of minimum distances. From this function, it is possible to generate realistic collision estimates for the spacecraft.

Vedder, John D.↗

Characterization of the Space Shuttle Ascent Debris using CFD Methods

After video analysis of space shuttle flight STS-107's ascent showed that an object shed from the bipod-ramp region impacted the left wing, a transport analysis was initiated to determine a credible flight path and impact velocity for the piece of debris. This debris transport analysis was performed both during orbit, and after the subsequent re-entry accident. The analysis provided an accurate prediction of the velocity a large piece of foam bipod ramp would have as it impacted the wing leading edge. This prediction was corroborated by video analysis and fully-coupled CFD/six degree of freedom (DOF) simulations. While the prediction of impact velocity was accurate enough to predict critical damage in this case, one of the recommendations of the Columbia Accident Investigation Board (CAIB) for return-to-flight (RTF) was to analyze the complete debris environment experienced by the shuttle stack on ascent. This includes categorizing all possible debris sources, their probable geometric and aerodynamic characteristics, and their potential for damage. This paper is chiefly concerned with predicting the aerodynamic characteristics of a variety of potential debris sources (insulating foam and cork, nose-cone ablator, ice, ...) for the shuttle ascent configuration using CFD methods. These aerodynamic characteristics are used in the debris transport analysis to predict flight path, impact velocity and angle, and provide statistical variation to perform risk analyses where appropriate. The debris aerodynamic characteristics are difficult to determine using traditional methods, such as static or dynamic test data, due to the scaling requirements of simulating a typical debris event. The use of CFD methods has been a critical element for building confidence in the accuracy of the debris transport code by bridging the gap between existing aerodynamic data and the dynamics of full-scale, in-flight events.

Murman, Scott M.↗

Uncertainty Quantification Enabled by Automatic Differentiation for Hydrodynamic Simulation of Shock‐to‐Detonation Transition in High Explosives

Quantifying the effects of uncertainty in a reactive burn model on the run-to-detonation time in high explosives (HEs) provides a robust methodology for assessing the probability of an HE failing the IHE qualification standard. Moreover, uncertainty quantification helps evaluate whether the model calibration accurately represents data outside the calibration set. This study uses a specialized hydrodynamic simulation code for modeling detonation to determine the run-to-detonation time of the HE PBX 9502 for various impact velocities. To quickly approximate uncertainties in the model, a surrogate was constructed using a Taylor series expansion centered at the mean of the input parameters. To obtain the sensitivities required for constructing the Taylor series, HYP-percomplex Automatic Differentiation (HYPAD) was implemented. HYPAD is a methodology for infusing existing codes with automatic differentiation capabilities by augmenting variables with one or more imaginary units to compute step-size independent partial derivatives. These derivatives are accurate to machine precision with respect to the implemented numerical algorithm, meaning their accuracy reflects that of the underlying method (e.g., integration or discretization schemes). Using reduced order modeling techniques, the mean and standard deviation of the run-to-detonation time of a shock within PBX 9502 were computed for a number of initial impact velocities. A weighted least squares regression was then performed to obtain a best fit curve and prediction interval for the computed statistics. Historical data points from explosively driven wedge tests were utilized to validate the prediction interval, ensuring its reliability in predicting future outcomes. With this prediction interval and a known safety constraint curve, the most probable point of failure and the probability of failure for the HE PBX 9502 were determined.

97 MATHEMATICS AND COMPUTING↗

Statistics of some atmospheric turbulence records relevant to aircraft response calculations

Methods for characterizing atmospheric turbulence are described. The methods illustrated include maximum likelihood estimation of the integral scale and intensity of records obeying the von Karman transverse power spectral form, constrained least-squares estimation of the parameters of a parametric representation of autocorrelation functions, estimation of the power spectra density of the instantaneous variance of a record with temporally fluctuating variance, and estimation of the probability density functions of various turbulence components. Descriptions of the computer programs used in the computations are given, and a full listing of these programs is included.

Mark, W. D.↗

Improved information criteria for Bayesian model averaging in lattice field theory

Bayesian model averaging is a practical method for dealing with uncertainty due to model specification. Use of this technique requires the estimation of model probability weights. Here, we revisit the derivation of estimators for these model weights. Use of the Kullback-Leibler divergence as a starting point leads naturally to a number of alternative information criteria suitable for Bayesian model weight estimation. We explore three such criteria, known to the statistics literature before, in detail: a Bayesian analog of the Akaike information criterion which we call the BAIC, the Bayesian predictive information criterion, and the posterior predictive information criterion (PPIC). We compare the use of these information criteria in numerical analysis problems common in lattice field theory calculations. We find that the PPIC has the most appealing theoretical properties and can give the best performance in terms of model-averaging uncertainty, particularly in the presence of noisy data, while the BAIC is a simple and reliable alternative.

97 MATHEMATICS AND COMPUTING↗

Model-based quantification of margins and uncertainties in metal additive manufacturing for process design and qualification

Laser powder bed fusion (LPBF) Additive Manufacturing (AM) has the potential to enable the production of components with novel designs and material properties unachievable otherwise. However, process repeatability is a challenge, making qualification ill-defined and greatly reducing the utility of what could be an important manufacturing technology. In this work, a combination of modeling, uncertainty quantification (UQ), and experimentation are used in an effort to predict and bound the range of possible outcomes of the LPBF process. Quantities of interest predicted are melt pool dimensions, microstructure features, and mechanical distortions. A combination of high fidelity thermal-fluid models, microstructure growth models, and reduced fidelity, rapid thermal and mechanical models are used. Uncertainty propagation techniques are used to predict probability distributions of quantities of interest from estimates of process uncertainties. Repeated experiments are done to quantify observed probability distributions and compared to predicted distributions to determine if predictions are precise and accurate. Novel modeling methods are microstrucutre characterization techniques are also discussed. It is found that high fidelity models do a generally good job bounding experimentally observed melt pool morphologies for both bead-on-plate and powder bed cases. Microstructure models are able to bound a number of experimentally observed microstructure statistics, but with low precision due to challenges with calibrating the microstructure growth model parameters. A developed modified inherent strain distortion model does not accurately predict observed distortions. A lumped laser distortion model shows promise in being both accurately and precisely bounding observed outcomes from the deflection comb build, but requires further evaluation on more builds and geometries.

36 MATERIALS SCIENCE↗

Saturated laser fluorescence in turbulent sooting flames at high pressure

The primary objective was to develop a quantitative, single pulse, laser-saturated fluorescence (LSF) technique for measurement of radical species concentrations in practical flames. The species of immediate interest was the hydroxyl radical. Measurements were made in both turbulent premixed diffusion flames at pressures between 1 and 20 atm. Interferences from Mie scattering were assessed by doping with particles or by controlling soot loading through variation of equivalence ratio and fuel type. The efficacy of the LSF method at high pressure was addressed by comparing fluorescence and adsorption measurements in a premixed, laminar flat flame at 1-20 atm. Signal-averaging over many laser shots is sufficient to determine the local concentration of radical species in laminar flames. However, for turbulent flames, single pulse measurements are more appropriate since a statistically significant number of laser pulses is needed to determine the probability function (PDF). PDFs can be analyzed to give true average properties and true local kinetics in turbulent, chemically reactive flows.

King, G. B.↗

Establishing temperature from radiance of dynamically compressed metals

Precise temperature determination is a significant challenge in extreme environments of dynamic compression studies. How can radiance measurements taken in high-pressure shock experiments constrain temperature in a meaningful and physically consistent way? Experiments maintaining sample compression against a transparent window can be tailored to present a uniform measurement area with uncertain spectral emissivity. We compare several methods to analyze radiance collected at multiple wavelengths, applying statistical methods and physical principles to improve temperature inference. With proper radiance collection and analysis, dynamic temperature uncertainties become comparable to thermomechanical ambiguities of the emitting surface.

36 MATERIALS SCIENCE↗

Improving tropical cyclone rapid intensification forecasts with satellite measurements of sea surface salinity and calibrated machine learning

Forecasting rapid intensification (RI) of tropical cyclones (TC) is a mission known for large errors. One under-researched factor that affects TC intensification is salinity, which is important for density stratification in certain ocean regions and can affect the surface enthalpy flux under a strengthening hurricane. To investigate the impact and efficacy of using salinity information in state-of-the-art forecasting, we use a statistical model consisting of a variety of machine learning (ML) methods. For salinity data, we use satellite measurements of pre-storm sea surface salinity (SSS) as a proxy for the salinity stratification. We train and test the model on various ocean basins, including the Atlantic, eastern North Pacific and western North Pacific. A calibrator is trained on top of the ML models to correct and enhance probability forecasts. The calibrator significantly improves probability forecasts relative to recent works. The ML model performance is improved with the addition of SSS in the Eastern North Pacific, western North Pacific, and the Caribbean subregion of the North Atlantic, and the overall model performance is better than previous studies. SSS decreases model skill for a model trained on the full Atlantic basin. In the Indian Ocean, SSS is also notably correlated with RI occurrence, but the TC samples are not sufficient to train ML models.

hurricane↗

Constraints from isoscaling on the source size in energetic heavy ion collisions

In the framework of the statistical multifragmentation model, the nuclear isoscaling analysis is extended to constrain the ratio between the sizes of the decaying sources formed in a collision between two heavy ions. It is found that the ratio between the probabilities of observing n fragments in each event, for each of the sources, follows a scaling law, similar to the traditional nuclear isoscaling. However, the corresponding slope is sensitive to the source sizes. This property is explained analytically using the grand-canonical ensemble. Furthermore, the extent to which our findings are affected by finite size effects and by the deexcitation of the hot primary fragments is investigated. The scaling turns out to be robust and weakly affected by effects implied by these two aspects. We also find that the Poisson distribution is a fairly good approximation to the above mentioned probabilities, associated with both the primordial fragments, produced at the breakup stage, and the final ones, found at the end of the fragment deexcitation process.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Detection of chaotic determinism in time series from randomly forced maps

Time series from biological system often display fluctuations in the measured variables. Much effort has been directed at determining whether this variability reflects deterministic chaos, or whether it is merely "noise". Despite this effort, it has been difficult to establish the presence of chaos in time series from biological sytems. The output from a biological system is probably the result of both its internal dynamics, and the input to the system from the surroundings. This implies that the system should be viewed as a mixed system with both stochastic and deterministic components. We present a method that appears to be useful in deciding whether determinism is present in a time series, and if this determinism has chaotic attributes, i.e., a positive characteristic exponent that leads to sensitivity to initial conditions. The method relies on fitting a nonlinear autoregressive model to the time series followed by an estimation of the characteristic exponents of the model over the observed probability distribution of states for the system. The method is tested by computer simulations, and applied to heart rate variability data.

Non-NASA Center↗

Determining reference standard strength for neutron-irradiated reduced activation ferritic/martensitic steel F82H by Bayesian method

The deterministic approach widely adopted in the design of structural components relies on systematically defined design limits using empirically determined safety factors. However, this approach is not always appropriate because structures are subjected to a variety of loads in the practical environment, which may result in excessively conservative design limits. In recent years, a more rigorous probabilistic approach that incorporates material strength distributions has become an important solution. In the probabilistic approach, the probability density functions of material strength properties underpin the design criteria. Here, the objective of this study is to identify the density distribution functions that best describe tensile properties of irradiated F82H to define a reference strength for DEMO design. Due to the limited number of existing data, this study specifically employs a Bayesian prediction method based on Monte Carlo simulations to determine a material reference value with statistical reliability and to investigate its effectiveness. For example, the dependence of tensile properties of 300 °C irradiated materials on irradiation damage and the range predicted by 95% Bayesian estimation was evaluated. As a statistical model for the dose dependence of statistical parameters, the normal distribution exhibited a better fit for 0.2% proof strength and tensile strength, whereas the distribution of total elongation data gave comparable reference values for both the normal and Weibull distribution models. Both models gave comparable criteria for the distribution of total elongation data. The Weibull model also gave better results for uniform elongation. The function best describing the model was a logarithmic law for both 0.2% proof strength and tensile strength, while a power law for both total and uniform elongation, which allowed for more comprehensive data prediction of irradiation data with statistical accuracy for DEMO reactor design.

36 MATERIALS SCIENCE↗

Viral coefficient and hidden mass in the galaxy groups

The purpose is the verification of the virial mass estimations for small galaxy groups. The dynamical evolution of triple and quintuple galaxies was studied by the numerical simulations. The dependence of the virial coefficient k(t) versus time was derived. Initial k(O) = O. The function k(t) has some strong oscillations from 0.02 to 0.99. Generally, these oscillations are quasiperiodical ones. Such a behavior of k(t) is caused by formation in a system of close isolated temporary double subsystems. A strong correlation between the virial coefficient and the least mutual distance in the system is observed. Such wide oscillations may add into the estimation of virial mass of the galaxy groups an uncertainty of more than one order. An additional uncertainty is introduced by the projection effect. This uncertainty for the individual estimations of the masses approach three orders. Thus any individual estimation of the virial mass is impossible for small galaxy groups. Some possibility of statistical estimation (median or average) of the total mass, including a hidden mass, is shown for the homogeneous samples. The authors propose a method for these estimations based on a comparison of the medians of dynamical parameters (a mean size in projection and a dispersion of relative radial velocities) for the simulated and observed ensembles of the galaxy groups. This method has been applied to a sample of 46 probably physical triplets of galaxies. The probable median of the hidden mass in a volume of the triplet is about 4 M, where M is the total mass of visible matter.

Anosova, Joanna P.↗

Estimated Accuracy of Three Common Trajectory Statistical Methods

Three well-known trajectory statistical methods (TSMs), namely concentration field (CF), concentration weighted trajectory (CWT), and potential source contribution function (PSCF) methods were tested using known sources and artificially generated data sets to determine the ability of TSMs to reproduce spatial distribution of the sources. In the works by other authors, the accuracy of the trajectory statistical methods was estimated for particular species and at specified receptor locations. We have obtained a more general statistical estimation of the accuracy of source reconstruction and have found optimum conditions to reconstruct source distributions of atmospheric trace substances. Only virtual pollutants of the primary type were considered. In real world experiments, TSMs are intended for application to a priori unknown sources. Therefore, the accuracy of TSMs has to be tested with all possible spatial distributions of sources. An ensemble of geographical distributions of virtual sources was generated. Spearman s rank order correlation coefficient between spatial distributions of the known virtual and the reconstructed sources was taken to be a quantitative measure of the accuracy. Statistical estimates of the mean correlation coefficient and a range of the most probable values of correlation coefficients were obtained. All the TSMs that were considered here showed similar close results. The maximum of the ratio of the mean correlation to the width of the correlation interval containing the most probable correlation values determines the optimum conditions for reconstruction. An optimal geographical domain roughly coincides with the area supplying most of the substance to the receptor. The optimal domain s size is dependent on the substance decay time. Under optimum reconstruction conditions, the mean correlation coefficients can reach 0.70 0.75. The boundaries of the interval with the most probable correlation values are 0.6 0.9 for the decay time of 240 h and 0.5 0.95 for the decay time of 12 h. The best results of source reconstruction can be expected for the trace substances with a decay time on the order of several days. Although the methods considered in this paper do not guarantee high accuracy they are computationally simple and fast. Using the TSMs in optimum conditions and taking into account the range of uncertainties, one can obtain a first hint on potential source areas.

Kabashnikov, Vitaliy P.↗

Enabling More than Moore: Accelerated Reliability Testing and Risk Analysis for Advanced Electronics Packaging

For five decades, the semiconductor industry has distinguished itself by the rapid pace of improvement in miniaturization of electronics products-Moore's Law. Now, scaling hits a brick wall, a paradigm shift. The industry roadmaps recognized the scaling limitation and project that packaging technologies will meet further miniaturization needs or ak.a "More than Moore". This paper presents packaging technology trends and accelerated reliability testing methods currently being practiced. Then, it presents industry status on key advanced electronic packages, factors affecting accelerated solder joint reliability of area array packages, and IPC/JEDEC/Mil specifications for characterizations of assemblies under accelerated thermal and mechanical loading. Finally, it presents an examples demonstrating how Accelerated Testing and Analysis have been effectively employed in the development of complex spacecraft thereby reducing risk. Quantitative assessments necessarily involve the mathematics of probability and statistics. In addition, accelerated tests need to be designed which consider the desired risk posture and schedule for particular project. Such assessments relieve risks without imposing additional costs. and constraints that are not value added for a particular mission. Furthermore, in the course of development of complex systems, variances and defects will inevitably present themselves and require a decision concerning their disposition, necessitating quantitative assessments. In summary, this paper presents a comprehensive view point, from technology to systems, including the benefits and impact of accelerated testing in offsetting risk.

Ghaffarian, Reza↗