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A particle simulation code was developed that is suited to Multiple Instruction Multiple Data multiprocessor computers. The resulting code is designed to be portable between a large class of multiprocessor computer architectures, including hypercubes (e.g., Intel iPSC/860), shared memory machines (e.g., Cray, SGI, DASH), and simple uniprocessors (e.g., SUN, VAX, IBM PC). This code provides a powerful general framework that can be adapted to specific applications, such as thermomechanical modeling, general 3-D geometry support, or visualization support via a codeveloped CPlot data reduction and visualization system. Chemistry models were implemented and validated with comparison to continuum solutions of thermochemically relaxing gas mixtures and with experimental results from the high speed flow about a circular cylinder. Furthermore, the exchange of energy between translational and internal modes was modeled. New models were developed, combining greater efficiency than earlier phenomenological models. They offer greater physical detail by addressing vibrational energy as a discretely distributed quantity.

Spatio-temporal modelling is an increasingly popular topic in Statistics. Our paper contributes to this line of research by developing the theory, simulation and inference for a spatio-temporal Ornstein-Uhlenbeck process. We conduct detailed simulation studies and demonstrate the practical relevance of these processes in an empirical study of radiation anomaly data. Finally, we describe how predictions can be carried out in the Gaussian setting.

Spatio-temporal modelling is an increasingly popular topic in Statistics. Our paper contributes to this line of research by developing the theory, simulation and inference for a spatio-temporal Ornstein-Uhlenbeck process. We conduct detailed simulation studies and demonstrate the practical relevance of these processes in an empirical study of radiation anomaly data. Finally, we describe how predictions can be carried out in the Gaussian setting.

The rules that specify how the information contained in DNA codes amino acids, is called "the genetic code". Using a simplified version of the Penna nodel, we are using computer simulations to investigate the importance of the genetic code and the number of amino acids in Nature on population dynamics. We find that the genetic code is not a random pairing of codons to amino acids and the number of amino acids in Nature is an optimum under mutations.

In this work, several (5) statistical estimators for solving the typical remote sensing 'inverse' problem are explained, illustrated and evaluated using both real data sets connecting surface windspeed and whitecap coverage and simulated data. The results suggests the superiority of some of these estimators.

The performances of the distance nearest neighbor rule, one-stage rank nearest neighbor rule and two-stage rank nearest neighbor rule for the two-population statistical classification problem are studied through simulation processes. Normal distributions with different mean, normal distributions with different variances, exponential distributions and Cauchy distributions are considered. (Author)

The performances of the distance nearest neighbor rule, one-stage rank nearest neighbor rule and two-stage rank nearest neighbor rule for the two-population statistical classification problem are studied through simulation processes. Normal distributions with different mean, normal distributions with different variances, exponential distributions and Cauchy distributions are considered. (Author)

Tests were conducted to provide flight conditions for qualifying the Viking Decelerator System in a simulated Mars environment. A balloon launched decelerator test (BLDT) vehicle which has an external shape similar to the actual Mars Viking Lander Capsule was used so that the decelerator would be deployed in the wake of a blunt body. An effort was made to simulate the BLDT vehicle flights from the time they were dropped from the balloon, through decelerator deployment, until stable decelerator conditions were reached. The procedure used to simulate these flights using the Statistical Trajectory Estimation Program (STEP) is discussed. Using primarily ground-based position radar and vehicle onboard rate gyro and accelerometer data, the STEP produces a minimum variance solution of the vehicle trajectory and calculates vehicle attitude histories. Using film from cameras in the vehicle along with a computer program, attitude histories for portions of the flight before and after decelerator deployment were calculated independent of the STEP simulation. With the assumption that the vehicle motions derived from camera data are accurate, a comparison reveals that STEP was able to simulate vehicle motions for all flights both before and after decelerator deployment.

A recent modification of the methodology of profile analysis, which allows the testing for differences between two functions as a whole with a single test, rather than point by point with multiple tests is discussed. The modification is applied to the examination of the issue of motion/no motion conditions as shown by the lateral deviation curve as a function of engine cut speed of a piloted 737-100 simulator. The results of this application are presented along with those of more conventional statistical test procedures on the same simulator data.

A recent modification of the methodology of profile analysis, which allows the testing for differences between two functions as a whole with a single test, rather than point by point with multiple tests is discussed. The modification is applied to the examination of the issue of motion/no motion conditions as shown by the lateral deviation curve as a function of engine cut speed of a piloted 737-100 simulator. The results of this application are presented along with those of more conventional statistical test procedures on the same simulator data.

Kalman filter theory and sextant measurements for lunar midcourse guidance and navigation simulation

In support of Task 07/040 (support to AIR 7000), the generation of correlated sea clutter returns using the Memoryless Nonlinear Transform is investigated. The generation of such clutter is critical to the performance analysis of radar detection schemes under realistic clutter scenarios. This feature must be incorporated into clutter models being built at DSTO to test radar detector performance. Examples of the transform's application is given for a number of target distributions of interest.

Statistical Methods in Discrete Event Simulation, and related course 1981 - George Washington University

A statistical analysis of the breaking behavior of Ni nanowires is presented. Using molecular dynamic simulations, we have determined the time evolution of both the nanowire atomic structure and its minimum cross section (Sm(t)). Accumulating thousands of independent breaking events, Sm histograms are built and used to study the influence of the temperature, the crystalline stretching direction and the initial nanowire size. The proportion of monomers, dimers and more complex structures at the latest stages of the breaking process are calculated, finding important differences among results obtained for different nanowire orientations and sizes. Three main cases have been observed. (A) [111] stretching direction and large nanowire sizes: the wire evolves from more complex structures to monomers and dimers prior its rupture; well ordered structures is presented during the breaking process. (B) Large nanowires stretched along the [100] and [110] directions: the system mainly breaks from complex structures (low probability of finding monomers and dimers), having disordered regions during their breakage; at room temperature, a huge histogram peak around Sm=5 appears, showing the presence of long staggered pentagonal Ni wires with ...-5-1-5-... structure. (C) Initial wire size is small: strong size effects independently on the temperature and stretching direction. Finally, the local structure around monomers and dimmers do not depend on the stretching direction. These configurations differ from those usually chosen in static studies of conductance.

A statistical analysis of the breaking behavior of Ni nanowires is presented. Using molecular dynamic simulations, we have determined the time evolution of both the nanowire atomic structure and its minimum cross section (Sm(t)). Accumulating thousands of independent breaking events, Sm histograms are built and used to study the influence of the temperature, the crystalline stretching direction and the initial nanowire size. The proportion of monomers, dimers and more complex structures at the latest stages of the breaking process are calculated, finding important differences among results obtained for different nanowire orientations and sizes. Three main cases have been observed. (A) [111] stretching direction and large nanowire sizes: the wire evolves from more complex structures to monomers and dimers prior its rupture; well ordered structures is presented during the breaking process. (B) Large nanowires stretched along the [100] and [110] directions: the system mainly breaks from complex structures (low probability of finding monomers and dimers), having disordered regions during their breakage; at room temperature, a huge histogram peak around Sm=5 appears, showing the presence of long staggered pentagonal Ni wires with ...-5-1-5-... structure. (C) Initial wire size is small: strong size effects independently on the temperature and stretching direction. Finally, the local structure around monomers and dimmers do not depend on the stretching direction. These configurations differ from those usually chosen in static studies of conductance.

The use of mmWave frequencies is one of the key strategies to achieve the fascinating 1000x increase in the capacity of future 5G wireless systems. While for traditional sub-6 GHz cellular frequencies several well-developed statistical channel models are available for system simulation, similar tools are not available for mmWave frequencies, thus preventing a fair comparison of independently developed transmission and reception schemes. In this paper we provide a simple albeit accurate statistical procedure for the generation of a clustered MIMO channel model operating at mmWaves, for both the cases of slowly and rapidly time-varying channels. Matlab scripts for channel generation are also provided, along with an example of their use.

ADA769387

This paper introduces a dual active load path fail-safe fatigue design concept analyzed by Monte Carlo simulation. The concept utilizes the inherent fatigue life differences between selected pairs of components for an active dual path system, enhanced by a stress level bias in one component. The design is applied to a baseline design; a safe life fatigue problem studied in an American Helicopter Society (AHS) round robin. The dual active path design is compared with a two-element standby fail-safe system and the baseline design for life at specified reliability levels and weight. The sensitivity of life estimates for both the baseline and fail-safe designs was examined by considering normal and Weibull distribution laws and coefficient of variation levels. Results showed that the biased dual path system lifetimes, for both the first element failure and residual life, were much greater than for standby systems. The sensitivity of the residual life-weight relationship was not excessive at reliability levels up to R = 0.9999 and the weight penalty was small. The sensitivity of life estimates increases dramatically at higher reliability levels.

Voltage-gated ion channels are key molecules for the generation and propagation of electrical signals in excitable cell membranes. The voltage-dependent switching of these channels between conducting and nonconducting states is a major factor in controlling the transmembrane voltage. In this study, a statistical mechanics model of these molecules has been discussed on the basis of a two-dimensional spin model. A new Hamiltonian and a new Monte Carlo simulation algorithm are introduced to simulate such a model. It was shown that the results well match the experimental data obtained from batrachotoxin-modified sodium channels in the squid giant axon using the cut-open axon technique.

Voltage-gated ion channels are key molecules for the generation and propagation of electrical signals in excitable cell membranes. The voltage-dependent switching of these channels between conducting and nonconducting states is a major factor in controlling the transmembrane voltage. In this study, a statistical mechanics model of these molecules has been discussed on the basis of a two-dimensional spin model. A new Hamiltonian and a new Monte Carlo simulation algorithm are introduced to simulate such a model. It was shown that the results well match the experimental data obtained from batrachotoxin-modified sodium channels in the squid giant axon using the cut-open axon technique.

Voltage-gated ion channels are key molecules for the generation and propagation of electrical signals in excitable cell membranes. The voltage-dependent switching of these channels between conducting and nonconducting states is a major factor in controlling the transmembrane voltage. In this study, a statistical mechanics model of these molecules has been discussed on the basis of a two-dimensional spin model. A new Hamiltonian and a new Monte Carlo simulation algorithm are introduced to simulate such a model. It was shown that the results well match the experimental data obtained from batrachotoxin-modified sodium channels in the squid giant axon using the cut-open axon technique.

Discrete-event simulation is one of the most important techniques available for studying complex stochastic systems. In this paper we review the principal methods available for analyzing both the transient and steady-state simulation problems in sequential and parallel computing environments. Next we discuss several of the variance reduction methods designed to make simulations run more efficiently. Finally, a short discussion is given of the methods available to study optimization using simulation.

Tests are conducted on a quad-redundant fault tolerant flight control computer to establish upset characteristics of an avionics system in an electromagnetic field. A numerical simulation and statistical model are described in this work to analyze the open loop experiment data collected in the reverberation chamber at NASA LaRC as a part of an effort to examine the effects of electromagnetic interference on fly-by-wire aircraft control systems. By comparing thousands of simulation and model outputs, the models that best describe the data are first identified and then a systematic statistical analysis is performed on the data. All of these efforts are combined which culminate in an extrapolation of values that are in turn used to support previous efforts used in evaluating the data.

Reproduction is part of the regulations of daily speech. Everyday experience shows there are different ways to convey the same information: starting sentences that are quickly rephrased using other words, manuscripts passing through draft states before the writer decides upon the final version. In more ways than one, any text is always but the sample of another one and the words read are but the visible part of an iceberg. James Joyce's "Ulysses" was content analyzed using the Regressive Imagery Dictionary. Among other things, this dictionary allows a person to assess the degree of presence, in texts, of primordial thought content. A negative linear profile is observed, i.e., primordial content decreases as the one-day journey goes by. Pondering this negative linear profile generates wonder about the enterprise of statistical analysis, how little it says, how brittle is a quantitative analysis of a literary work in the face of the uncertainty that surrounds such data. New ways to look at literary data consist of resampling thousands of time data that by nature exist in only one exemplar, bringing empirical study of literature down to what literature is made of--inking out, excisions, alterations, disappearances. The rates of primordial thought content were repeated 2000 times, using a bootstrap algorithm. The best contribution a researcher can make to empirical studies of literature is to "hammer" scholars to see how well resampling allows researchers to assess the degree of uncertainty associated with any measurement. (Contains 3 figures, 5 notes, and 16 references.) (Author/NKA)

This study uses simulation techniques to examine the statistical power of the group- randomized design and the matched-pair (MP) randomized block design under various parameter combinations. Both nearest neighbor matching and random matching are used for the MP design. The power of each design for any parameter combination was calculated from 1,000 simulated datasets. The random pair effect HLM model "with" and "without" covariance adjustment, and the fixed pair effect HLM model "with" and "without" covariance adjustment were used to analyze the data from the matched-pair design, and the HLM with covariance adjustment was used to analyze the data from the completely randomized cluster design. Models Used to Generate Data at Stage 1 is appended. (Contains 4 tables and 1 figure.)

Current challenges and problems pertaining to the development and application of the DSMC method for high-altitude aerodynamics are discussed. Attention is paid to issues related to the efficiency and accuracy of the method in the near-continuum regime, as well as its use for modeling of rarefied flows with real gas effects. Accurate prediction of force and heat aerodynamic characteristics of reentry vehicles and spacecraft requires comprehensive investigation of hypersonic flows in the near-continuum regime. A powerful software system SMILE, which uses the direct simulation Monte Carlo method as a numerical approach and is built basing on the contemporary knowledge in this field, is developed to solve advanced problems of high-altitude aerothermodynamics. Effective numerical algorithms and physically grounded models of real gas effects are implemented in SMILE. Aerodynamics of promising reentry capsule in the near-continuum regime is considered as an example.

Current challenges and problems pertaining to the development and application of the DSMC method for high-altitude aerodynamics are discussed. Attention is paid to issues related to the efficiency and accuracy of the method in the near-continuum regime, as well as its use for modeling of rarefied flows with real gas effects. Accurate prediction of force and heat aerodynamic characteristics of reentry vehicles and spacecraft requires comprehensive investigation of hypersonic flows in the near-continuum regime. A powerful software system SMILE, which uses the direct simulation Monte Carlo method as a numerical approach and is built basing on the contemporary knowledge in this field, is developed to solve advanced problems of high-altitude aerothermodynamics. Effective numerical algorithms and physically grounded models of real gas effects are implemented in SMILE. Aerodynamics of promising reentry capsule in the near-continuum regime is considered as an example.

This report describes the research completed by Florida International University on military collaboration. The research first reviewed and generated a literature review on collaboration. The research created an agent-based simulation model named the Team Coordination Model to study collaboration between a group of people on a defined job or mission. The agent-based model was used to study military operations in an urban terrain scenario. Additionally, we developed statistical tools to analyze social networks to uncover collaboration patterns.

This report describes the research completed by Florida International University on military collaboration. The research first reviewed and generated a literature review on collaboration. The research created an agent-based simulation model named the Team Coordination Model to study collaboration between a group of people on a defined job or mission. The agent-based model was used to study military operations in an urban terrain scenario. Additionally, we developed statistical tools to analyze social networks to uncover collaboration patterns.

A graphical test bed in which the results of simulation experiment can be reported and analyzed is described. The test bed is based o the regression adjusted graphics and estimation methodology developed by Heidelberger and Lewis (Ref. 1) for regenerative simulation. From the graphics and associated numeric, the experimenter can summarize and see simultaneously relative properties, such as bias, normality and standard deviation, of several estimators of a characteristic of a population for up to 8 sample sizes. The evolution of these properties with sample size is also displayed. The graphics is supported on a lien printer to make it and the program portable. The technique is illustrated by examples concerning the effects of changes in data distribution on the behavior of the lag one serial correlation coefficient, the estimation of the shape parameter of Gamma random variables and a comparison of different methods (jackknife, bootstrap) for estimating the standard error of an estimator.

A graphical test bed in which the results of simulation experiment can be reported and analyzed is described. The test bed is based o the regression adjusted graphics and estimation methodology developed by Heidelberger and Lewis (Ref. 1) for regenerative simulation. From the graphics and associated numeric, the experimenter can summarize and see simultaneously relative properties, such as bias, normality and standard deviation, of several estimators of a characteristic of a population for up to 8 sample sizes. The evolution of these properties with sample size is also displayed. The graphics is supported on a lien printer to make it and the program portable. The technique is illustrated by examples concerning the effects of changes in data distribution on the behavior of the lag one serial correlation coefficient, the estimation of the shape parameter of Gamma random variables and a comparison of different methods (jackknife, bootstrap) for estimating the standard error of an estimator.

A primary advantage to using modeling and simulation (M&S) in a test program is it can often answer test measures that, if answered using real-world data, would require unrealistically expensive, time-consuming, or complex test events. Simulation outputs, though, are only as good as the underlying assumptions and models built into the simulation. For even moderately complex simulations, it is not easy to predict the quality of simulation results based purely on the logic that if component models, theoretical component interactions, and simulation inputs are valid, then the simulation results will be as valid as the results of a real-world test event under the same conditions. Direct comparison of simulation results to real-world test data is often conducted as part of a simulation validation effort. The analyst is faced with a difficult question: has enough data been collected under these conditions to be considered a statistically significant sample for comparison with the simulation?

Some methods of analyzing experimental data for complex targets and reverberation are outlined, including a heuristic discussion of what constitutes an ensemble and how to obtain one experimentally. The problem of then determining whether or not the actual data form a valid ensemble is considered. Tests for the stability, or stationarity, of the underlying random mechanism are briefly described (test of independence and homogeneity); tests of whether or not a particular data set belongs to some postulated probability distribution are provided (goodness-of-fit), including a powerful test for establishing the normality or non-normality of the sample. Among the tests considered are the X squared, the Kolmogorov-Smirnov, the runs test, and the W-test for normality. These tests are carried out for some hypothetical reverberation data to illustrate the individual tests, at particular ranges, which can include the domain of a target reverberation. Some second-order properties of various classes of second moments of these data are also discussed, and an approach to relating simulated data to those from a real environment is briefly sketched. This memorandum is intended as a preliminary guide to the statistical treatment of data that are obtained in target and background measurements.

This report encompasses some methods applied when validating the MOVES model for experimentation under various U.S. Marine AV-8A Harrier squadron operating scenarios. The Statistical methods represented in the report are those that were applied for the U.S. Marine Users of MOVES. These statistical methods are the t-test, F-test, Confidence Intervals, Normal Distribution Plot, and the Wilcoxon-Mann-Whitney test. These methods will be used by the U.S. and U.S. when validating for the AV-8B and Sea Harrier MOVES.

This research investigated the combined influence of simulation work and metamodel specification on the statistical quality of the estimates obtained from the resulting metamodels of the simulation data. A 9 x 2 x 2 experiment consisting of 9 cases of simulation work, 2 levels of metamodel specification, and 2 levels of design fractionation were designed for 8 different configurations of M/M/k queues. The only observed statistic for this experiment was the average queue length. Simulation estimates for each configuration's average queue length were calculated directly from the simulation data. In addition, the metamodels were fit to the simulation data and were used to estimate the average queue length for each configuration. Residuals were calculated for each estimate as the difference between the analytic solution for average queue length and the given estimate. The residuals were analyzed graphically and via Single-Factor ANOVA to determine if the amount of simulation work or metamodel specification affected the statistical quality of the estimates. This research showed conclusively that the amount of simulation work had no significant effect and that the metamodel specification had a significant effect on the statistical quality of the estimates obtained from metamodels. Response surface methodology, Computer simulation, Least squares regression, Experimental design, Metamodel, M/M/k Queues.

In this paper, we present statistical simulators for cascaded Rayleigh fading channels with and without line-of-sight (LOS). These simulators contain two individual summations and are therefore easy to implement with lower complexity. Detailed statistical properties, including auto- and cross-correlations of the in-phase, quadrature components of the channels, envelopes, and squared envelopes, are derived. The time-average statistical properties and the corresponding variance are also investigated to justify that the proposed simulators achieve good convergence performance. Extensive Monte Carlo simulations are performed for various statistical properties to validate the proposed simulators. Results show that the simulators provide fast convergence to all desired statistical properties, including the probability density function (PDF), various auto- and cross-correlations, level crossing rate (LCR), and average fading duration (AFD). While various tests and measurements in dense scattering urban and forest environments indicate that mobile-to-mobile channels may experience cascaded Rayleigh fading, the proposed statistical models can be applied to simulate the underlying channels.

The Bootstrap method application in simulation supposes that value of random variables are not generated during the simulation process but extracted from available sample populations. In the case of Hierarchical Bootstrap the function of interest is calculated recurrently using the calculation tree. In the present paper we consider the optimization of sample sizes in each vertex of the calculation tree. The dynamic programming method is used for this aim. Proposed method allows to decrease a variance of system characteristic estimators.

The Bootstrap method application in simulation supposes that value of random variables are not generated during the simulation process but extracted from available sample populations. In the case of Hierarchical Bootstrap the function of interest is calculated recurrently using the calculation tree. In the present paper we consider the optimization of sample sizes in each vertex of the calculation tree. The dynamic programming method is used for this aim. Proposed method allows to decrease a variance of system characteristic estimators.

The Canadian Department of National Defence uses military workforce modelling and simulation to inform the decision-making process with regard to the management of military personnel. Defence Research and Development Canada (DRDC) has a suite of workforce models that have been used in a variety of studies over many years to answer questions, generate forecasts and analyse various scenarios under consideration. Over time, these simulation models have been refined, errors corrected, and results validated against historical data. Consequently, the level of confidence in these models is very high. As computer technology advances, the need arises periodically to update these models to take advantage of newer technology and to provide more advanced capabilities. DRDC is updating its workforce modelling and simulation technology through the development of a Python-based discrete event simulation environment that is intended to replace various commercial simulation software products in which existing DRDC workforce models have been built. DRDC has begun the process of rebuilding select workforce models in this new environment. Rebuilding a simulation model using new technology usually results in some loss of confidence in the model even if the features of the new technology are impressive. This is due to the possibility of reintroducing errors, inexperience with the new technology, and a lack of validation against hard data. To establish confidence in the new model implementation, it is necessary to validate its equivalence to the older trusted version. This can be done by subjecting both implementations to identical input scenarios and comparing simulation output. However, because workforce models frequently make use of random effects modelled using probability distributions (e.g. age at recruitment, release events, and course failures), variability in simulation output from the same input is expected.

We show that a simple modification of Formulation 1 of Farassat results in a new analytic expression that is highly suitable for broadband noise prediction when extensive turbulence simulation is available. This result satisfies all the stringent requirements, such as permitting the use of the exact geometry and kinematics of the moving body, that we have set as our goal in the derivation of useful acoustic formulas for the prediction of rotating blade and airframe noise. We also derive a simple analytic expression for the autocorrelation of the acoustic pressure that is valid in the near and far fields. Our analysis is based on the time integral of the acoustic pressure that can easily be obtained at any resolution for any observer time interval and digitally analyzed for broadband noise prediction. We have named this result as Formulation 2B of Farassat. One significant consequence of Formulation 2B is the derivation of the acoustic velocity potential for the thickness and loading terms of the Ffowcs Williams-Hawkings (FW-H) equation. This will greatly enhance the usefulness of the Fast Scattering Code (FSC) by providing a high fidelity boundary condition input for scattering predictions.

When MOSFETs are scaled to deep submicron dimensions the discreteness and randomness of the dopant charges in the channel region introduces significant fluctuations in the device characteristics. This effect, predicted 20 year ago, has been confirmed experimentally and in simulation studies. The impact of the fluctuations on the functionality, yield, and reliability of the corresponding systems shifts the paradigm of the numerical device simulation. It becomes insufficient to simulate only one device representing one macroscopical design in a continuous charge approximation. An ensemble of macroscopically identical but microscopically different devices has to be characterized by simulation of statistically significant samples. The aims of the numerical simulations shift from predicting the characteristics of a single device with continuous doping towards estimating the mean values and the standard deviations of basic design parameters such as threshold voltage, subthreshold slope, transconductance, drive current, etc. for the whole ensemble of 'atomistically' different devices in the system. It has to be pointed out that even the mean values obtained from 'atomistic' simulations are not identical to the values obtained from continuous doping simulations. In this paper we present a hierarchical approach to the 'atomistic' simulation of aggressively scaled decanano MOSFETs. A full scale 3D drift-diffusion'atomostic' simulation approach is first described and used for verification of the more economical, but also more restricted, options. To reduce the processor time and memory requirements at high drain voltage we have developed a self-consistent option based on a thin slab solution of the current continuity equation only in the channel region. This is coupled to the Poisson's equation solution in the whole simulation domain in the Gummel iteration cycles. The accuracy of this approach is investigated in comparison with the full self-consistent solution. At low drain voltage only single solution of the nonlinear Poisson equation is sufficient to extract the current with satisfactory accuracy. A pilot version of a hydrodynamic 'atomistic' simulator has been developed in order to study the effect of the nonequilibrium, non local transport in decanano MOSFETs on the random dopant induced current fluctuations. For the first time we have also applied the density gradient approach in 3D to investigate the effect of the quantum confinement on the threshold voltage fluctuations. The developed 'atomistic' simulation techniques have been applied to study various fluctuation resistant MOSFET architectures including epitaxial and delta doped devices.

The feasibility of conducting a statistical analysis of simulation experiments to study airport capacity is investigated. First, the form of the distribution of airport capacity is studied. Since the distribution is non-Gaussian, it is important to determine the effect of this distribution on standard analysis of variance techniques and power calculations. Next, power computations are made in order to determine how economic simulation experiments would be if they are designed to detect capacity changes from condition to condition. Many of the conclusions drawn are results of Monte-Carlo techniques.

Traditional validation of flight control systems is based primarily upon empirical testing. Empirical testing is sufficient for simple systems in which a.) the behavior is approximately linear and b.) humans are in-the-loop and responsible for off-nominal flight regimes. A different possible concept of operation is to use adaptive flight control systems with online learning neural networks (OLNNs) in combination with a human pilot for off-nominal flight behavior (such as when a plane has been damaged). Validating these systems is difficult because the controller is changing during the flight in a nonlinear way, and because the pilot and the control system have the potential to co-adapt in adverse ways traditional empirical methods are unlikely to provide any guarantees in this case. Additionally, the time it takes to find unsafe regions within the flight envelope using empirical testing means that the time between adaptive controller design iterations is large. This paper describes a new concept for validating adaptive control systems using methods based on Bayesian statistics. This validation framework allows the analyst to build nonlinear models with modal behavior, and to have an uncertainty estimate for the difference between the behaviors of the model and system under test.

The basic problem in equilibrium statistical mechanics is to compute phase space average, in which Monte Carlo method plays a very important role. We begin with a review of nonlocal algorithms for Markov chain Monte Carlo simulation in statistical physics. We discuss their advantages, applications, and some challenge problems which are still awaiting for better solutions. We discuss some of the recent development in simulation where reweighting is used, such as histogram methods and multicanonical method. We then discuss the transition matrix Monte Carlo method and associated algorithms. The transition matrix method offers an efficient way to compute the density of states. Thus entropy and free energy, as well as the usual thermodynamic averages, are obtained as functions of model parameter (e.g. temperature) in a single run. New sampling algorithms, such as the flat histogram algorithm and equal-hit algorithm, offer sampling techniques which generate uniform probability distribution for some chosen macroscopic variable.

The basic problem in equilibrium statistical mechanics is to compute phase space average, in which Monte Carlo method plays a very important role. We begin with a review of nonlocal algorithms for Markov chain Monte Carlo simulation in statistical physics. We discuss their advantages, applications, and some challenge problems which are still awaiting for better solutions. We discuss some of the recent development in simulation where reweighting is used, such as histogram methods and multicanonical method. We then discuss the transition matrix Monte Carlo method and associated algorithms. The transition matrix method offers an efficient way to compute the density of states. Thus entropy and free energy, as well as the usual thermodynamic averages, are obtained as functions of model parameter (e.g. temperature) in a single run. New sampling algorithms, such as the flat histogram algorithm and equal-hit algorithm, offer sampling techniques which generate uniform probability distribution for some chosen macroscopic variable.

Initially the authors completed a literature search in order to identify existing methods of computer simulation validation. Nonparametric statistical techniques were subsequently adapted to both deterministic and stochastic simulations, and these procedures were applied to a computer model currently in use at the Ballistic Research Laboratory. Monte-Carlo methods provided an indication of the power of these tests, and a mention of future work concerning attempts to increase this power has been included in this report. Keywords: VAST(Vulnerability Analysis for Surface Targets).

We review progress that has been made in utilizing one form of Direct Statistical Simulation (DSS) to describe geophysical and astrophysical flows that are anisotropic and inhomogeneous. We first explain the approach, which is based upon a systematic and conservative expansion of the equations of motion for low-order equal-time cumulants. We place the method into context with other statistical procedures. Truncation at second order in the hierarchy of cumulants is equivalent to retaining the interaction between zonal mean flows and eddies. Eddy-eddy interactions appear at higher orders, but care must be taken to keep the higher-order expansions realizable with non-negative probability distribution functions. The strengths and weaknesses of different levels of approximation are assessed with numerical experiments on the fiducial problem of a stochastically forced jet on a spherical surface. The results give an insight into the mechanisms that may control jet spacing and strength, and indicate interesting avenues for future research.

The high number of planet discoveries made in the last years provides a good sample for statistical analysis, leading to some clues on the distributions of planet parameters, like masses and periods, at least in close proximity to the host star. We likely need to wait for the extremely large telescopes (ELTs) to have an overall view of the extrasolar planetary systems. In this context it would be useful to have a tool that can be used for the interpretation of the present results,and also to predict what the outcomes would be of the future instruments. For this reason we built MESS: a Monte Carlo simulation code which uses either the results of the statistical analysis of the properties of discovered planets, or the results of the planet formation theories, to build synthetic planet populations fully described in terms of frequency, orbital elements and physical properties. They can then be used to either test the consistency of their properties with the observed population of planets given different detection techniques or to actually predict the expected number of planets for future surveys. In addition to the code description, we present here some of its applications to actually probe the physical and orbital properties of a putative companion within the circumstellar disk of a given star and to test constrain the orbital distribution properties of a potential planet population around the members of the TW Hydrae association. Finally, using in its predictive mode, the synergy of future space and ground-based telescopes instrumentation has been investigated to identify the mass-period parameter space that will be probed in future surveys for giant and rocky planets

Turbulence and dynamo induced by the magnetorotational instability (MRI) are analyzed using quasi-linear statistical simulation methods. It is found that homogenous turbulence is unstable to a large scale dynamo instability, which saturates to an inhomogenous equilibrium with a strong dependence on the magnetic Prandtl number (Pm). Despite its enormously reduced nonlinearity, the dependence of the angular momentum transport on Pm in the quasi-linear model is qualitatively similar to that of nonlinear MRI turbulence. This indicates that recent convergence problems may be related to large scale dynamo and suggests how dramatically simplified models may be used to gain insight into the astrophysically relevant regimes of very low or high Pm.