Publications

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This research explores four experiments of adaptive host-based intrusion detection (ID) techniques in an attempt to develop systems that can detect novel exploits. The technique considered to have the most potential is adaptive critic designs (ACDs) because of their utilization of reinforcement learning, which allows learning exploits that are difficult to pinpoint in sensor data. Preliminary results of ID using an ACD, an Elman recurrent neural network, and a statistical anomaly detection technique demonstrate an ability to learn to distinguish between clean and exploit data. We used the Solaris Basic Security Module (BSM) as a data source and performed considerable preprocessing on the raw data. A detection approach called generalized signature-based ID is recommended as a middle ground between signature-based ID, which has an inability to detect novel exploits, and anomaly detection, which detects too many events including events that are not exploits. The primary results of the ID experiments demonstrate the use of custom data for generalized signature-based intrusion detection and the ability of neural network-based systems to learn in this application environment.

This report describes the underlying principles and goals of the Sandia ASCI Verification and Validation Program Validation Metrics Project. It also gives a technical description of two case studies, one in structural dynamics and the other in thermomechanics, that serve to focus the technical work of the project in Fiscal Year 2001.

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We present the results of Molecular Dynamics and Monte Carlo simulations of n-butane and isobutane in silicalite. We begin with a comparison of the bulk adsorption and diffusion properties for two different parameterizations of the interaction potential between the hydrocarbon species, both of which have been shown to reproduce experimental gas-liquid coexistence curves. We examine diffusion as a function of the loading of the zeolite, as well as the temperature dependence of the diffusion constant at loading and for infinite dilution. Both force fields give accurate descriptions of bulk properties. We continue with simulations in which interfaces are formed between single component gases and the zeolite. After reaching equilibrium, we examine the dynamics of exchange between the bulk gas and the zeolite. In particular, we examine the average time spent in the adsorption layer by molecules as they enter the zeolite from the gas in an attempt to probe the microscopic origins of the surface barrier. The microscopic barrier is found to be insignificant for experimental systems. Finally, we calculate the permeability of the zeolite for n-butane and isobutane as a function of pressure. Our results underestimate the experimental results by an order of magnitude, indicating a strong effect from the surface barrier in these simulations. Our simulations are performed for a number of different gas temperatures and pressures, covering a wide range of state points.

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As a participating national lab in the inter-institutional effort to resolve performance issues of the non-elutable ion exchange technology for Cs extraction, they have carried out a series of characterization studies of UOP IONSIV{reg_sign} IE-911 and its component parts. IE-911 is a bound form (zirconium hydroxide-binder) of crystalline silicotitanate (CST) ion exchanger. The crystalline silicotitanate removes Cs from solutions by selective ion exchange. The performance issues of primary concern are: (1) excessive Nb leaching and subsequent precipitation of column-plugging Nb-oxide material, and (2) precipitation of aluminosilicate on IE-911 pellet surfaces, which may be initiated by dissolution of Si from the IE-911, thus creating a supersaturated solution with respect to silica. In this work, they have identified and characterized Si- and Nb-oxide based impurity phases in IE-911, which are the most likely sources of leachable Si and Nb, respectively. Furthermore, they have determined the criteria and mechanism for removal from IE-911 of the Nb-based impurity phase that is responsible for the Nb-oxide column plugging incidents.

The construction of inverse states in a finite field F{sub P{sub P{alpha}}} enables the organization of the mass scale by associating particle states with residue class designations. With the assumption of perfect flatness ({Omega}total = 1.0), this approach leads to the derivation of a cosmic seesaw congruence which unifies the concepts of space and mass. The law of quadratic reciprocity profoundly constrains the subgroup structure of the multiplicative group of units F{sub P{sub {alpha}}}* defined by the field. Four specific outcomes of this organization are (1) a reduction in the computational complexity of the mass state distribution by a factor of {approximately}10{sup 30}, (2) the extension of the genetic divisor concept to the classification of subgroup orders, (3) the derivation of a simple numerical test for any prospective mass number based on the order of the integer, and (4) the identification of direct biological analogies to taxonomy and regulatory networks characteristic of cellular metabolism, tumor suppression, immunology, and evolution. It is generally concluded that the organizing principle legislated by the alliance of quadratic reciprocity with the cosmic seesaw creates a universal optimized structure that functions in the regulation of a broad range of complex phenomena.

Arithmetic conditions relating particle masses can be defined on the basis of (1) the supersymmetric conservation of congruence and (2) the observed characteristics of particle reactions and stabilities. Stated in the form of common divisors, these relations can be interpreted as expressions of genetic elements that represent specific particle characteristics. In order to illustrate this concept, it is shown that the pion triplet ({pi}{sup {+-}}, {pi}{sup 0}) can be associated with the existence of a greatest common divisor d{sub 0{+-}} in a way that can account for both the highly similar physical properties of these particles and the observed {pi}{sup {+-}}/{pi}{sup 0} mass splitting. These results support the conclusion that a corresponding statement holds generally for all particle multiplets. Classification of the respective physical states is achieved by assignment of the common divisors to residue classes in a finite field F{sub P{sub {alpha}}} and the existence of the multiplicative group of units F{sub P{sub {alpha}}} enables the corresponding mass parameters to be associated with a rich subgroup structure. The existence of inverse states in F{sub P{sub {alpha}}} allows relationships connecting particle mass values to be conveniently expressed in a form in which the genetic divisor structure is prominent. An example is given in which the masses of two neutral mesons (K{degree} {r_arrow} {pi}{degree}) are related to the properties of the electron (e), a charged lepton. Physically, since this relationship reflects the cascade decay K{degree} {r_arrow} {pi}{degree} + {pi}{degree}/{pi}{degree} {r_arrow} e{sup +} + e{sup {minus}}, in which a neutral kaon is converted into four charged leptons, it enables the genetic divisor concept, through the intrinsic algebraic structure of the field, to provide a theoretical basis for the conservation of both electric charge and lepton number. It is further shown that the fundamental source of supersymmetry can be expressed in terms of hierarchical relationships between odd and even order subgroups of F{sub P{sub {alpha}}}, an outcome that automatically reflects itself in the phenomenon of fermion/boson pairing of individual particle systems. Accordingly, supersymmetry is best represented as a group rather than a particle property. The status of the Higgs subgroup of order 4 is singular; it is isolated from the hierarchical pattern and communicates globally to the mass scale through the seesaw congruence by (1) fusing the concepts of mass and space and (2) specifying the generators of the physical masses.

This technical report presents the initial proposal and renewable proposals for an LDRD project whose intended goal was to enable applications to take full advantage of the hardware available on Sandia's current and future massively parallel supercomputers by analyzing various ways of combining distributed-memory and shared-memory programming models. Despite Sandia's enormous success with distributed-memory parallel machines and the message-passing programming model, clusters of shared-memory processors appeared to be the massively parallel architecture of the future at the time this project was proposed. They had hoped to analyze various hybrid programming models for their effectiveness and characterize the types of application to which each model was well-suited. The report presents the initial research proposal and subsequent continuation proposals that highlight the proposed work and summarize the accomplishments.

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Superresolution concepts offer the potential of resolution beyond the classical limit. This great promise has not generally been realized. In this study we investigate the potential application of superresolution concepts to synthetic aperture radar. The analytical basis for superresolution theory is discussed. The application of the concept to synthetic aperture radar is investigated as an operator inversion problem. Generally, the operator inversion problem is ill posed. A criterion for judging superresolution processing of an image is presented.

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The DAKOTA (Design Analysis Kit for Optimization and Terascale Applications) toolkit provides a flexible and extensible interface between simulation codes and iterative analysis methods. DAKOTA contains algorithms for optimization with gradient and nongradient-based methods; uncertainty quantification with sampling, analytic reliability, and stochastic finite element methods; parameter estimation with nonlinear least squares methods; and sensitivity analysis with design of experiments and parameter study methods. These capabilities may be used on their own or as components within advanced strategies such as surrogate-based optimization, mixed integer nonlinear programming, or optimization under uncertainty. By employing object-oriented design to implement abstractions of the key components required for iterative systems analyses, the DAKOTA toolkit provides a flexible and extensible problem-solving environment for design and performance analysis of computational models on high performance computers. This report serves as a reference manual for the commands specification for the DAKOTA software, providing input overviews, option descriptions, and example specifications.

An effort is underway at Sandia National Laboratories to develop a library of algorithms to search for potential interactions between surfaces represented by analytic and discretized topological entities. This effort is also developing algorithms to determine forces due to these interactions for transient dynamics applications. This document describes the Application Programming Interface (API) for the ACME (Algorithms for Contact in a Multiphysics Environment) library.

We report first-principles total energy calculations of interaction of nitrogen in silicon with silicon self-interstitials. Substitutional nitrogen captures a silicon interstitial with 3.5 eV binding energy forming a (100) split interstitial ground-state geometry, with the nitrogen forming three bonds. The low-energy migration path is through a bond bridge state having two bonds. Fast diffusion of nitrogen occurs through a pure interstitialcy mechanism: the nitrogen never has less than two bonds. Near-zero formation energy of the nitrogen interstitialcy with respect to the substitutional rationalizes the low solubility of substitutional nitrogen in silicon. © 2001 American Institute of Physics.

In this paper the development of a gridless method to solve compressible flow problems is discussed. The governing evolution equations for velocity divergence {delta}, vorticity {omega}, density {rho}, and temperature T are obtained from the primitive variable Navier-Stokes equations. Simplifications to the equations resulting from assumptions of ideal gas behavior, adiabatic flow, and/or constant viscosity coefficients are given. A general solution technique is outlined with some discussion regarding alternative approaches. Two radial flow model problems are considered which are solved using both a finite difference method and a compressible particle method. The first of these is an isentropic inviscid 1D spherical flow which initially has a Gaussian temperature distribution with zero velocity everywhere. The second problem is an isentropic inviscid 2D radial flow which has an initial vorticity distribution with constant temperature everywhere. Results from the finite difference and compressible particle calculations are compared in each case. A summary of the results obtained herein is given along with recommendations for continuing the work.

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In manufacturing, the conceptual design and detailed design stages are typically regarded as sequential and distinct. Decisions made in conceptual design are often made with little information as to how they would affect detailed design or manufacturing process specification. Many possibilities and unknowns exist in conceptual design where ideas about product shape and functionality are changing rapidly. Few if any tools exist to aid in this difficult, amorphous stage in contrast to the many CAD and analysis tools for detailed design where much more is known about the final product. The Materials Process Design Environment (MPDE) is a collaborative problem solving environment (CPSE) that was developed so geographically dispersed designers in both the conceptual and detailed stage can work together and understand the impacts of their design decisions on functionality, cost and manufacturability.

This paper investigates the questions of what statistical information about a memory request sequence is useful to have in making page replacement decisions. Our starting point is the Markov Request Model for page request sequences. Although the utility of modeling page request sequences by the Markov model has been recently put into doubt ([13]), we find that two previously suggested algorithms (Maximum Hitting Time [11] and Dominating Distribution [14]) which are based on the Markov model work well on the trace data used in this study. Interestingly, both of these algorithms perform equally well despite the fact that the theoretical results for these two algorithms differ dramatically. We then develop succinct characteristics of memory access patterns in an attempt to approximate the simpler of the two algorithms. Finally, we investigate how to collect these characteristics in an online manner in order to have a purely online algorithm.