An Artificial Immune System Strategy for Robust Chemical Spectra Classification via Distributed Heterogeneous Sensors

The timely detection and classification of chemical and biological agents in a wartime environment is a critical component of force protection in hostile areas. Moreover, the possibility of toxic agent use in heavily populated civilian areas has risen dramatically in recent months. This thesis effort proposes a strategy for identifying such agents vis distributed sensors in an Artificial Immune System (AIS) network. The system may be used to complement electronic nose ( E-nose ) research being conducted in part by the Air Force Research Laboratory Sensors Directorate. In addition, the proposed strategy may facilitate fulfillment of a recent mandate by the President of the United States to the Office of Homeland Defense for the provision of a system that protects civilian populations from chemical and biological agents. The proposed system is composed of networked sensors and nodes, communicating via wireless or wired connections. Measurements are continually taken via dispersed, redundant, and heterogeneous sensors strategically placed in high threat areas. These sensors continually measure and classify air or liquid samples, alerting personnel when toxic agents are detected. Detection is based upon the Biological Immune System (BIS) model of antigens and antibodies, and alerts are generated when a measured sample is determined to be a valid toxic agent (antigen). Agent signatures (antibodies) are continually distributed throughout the system to adapt to changes in the environment or to new antigens. Antibody features are determined via data mining techniques in order to improve system performance and classification capabilities. Genetic algorithms (GAs) are critical part of the process, namely in antibody generation and feature subset selection calculations. Demonstrated results validate the utility of the proposed distributed AIS model for robust chemical spectra recognition

Relaxing Synchronization in Distributed Simulated Annealing

Simulated annealing is an attractive, but expensive, heuristic for approximating the solution to combinatorial optimization problems. Since simulated annealing is a general purpose method, it can be applied to the broad range of NP-complete problems such as the traveling salesman problem, graph theory, and cell placement with a careful control of the cooling schedule. Attempts to parallelize simulated annealing, particularly on distributed memory multicomputers, are hampered by the algorithm’s requirement of a globally consistent system state. In a multicomputer, maintaining the global state S involves explicit message traffic and is a critical performance bottleneck. One way to mitigate this bottleneck is to amortize the overhead of these state updates over as many parallel state changes as possible. By using this technique, errors in the actual cost C(S) of a particular state S will be introduced into the annealing process. This dissertation places analytically derived bounds on the cost error in order to assure convergence to the correct result. The resulting parallel Simulated Annealing algorithm dynamically changes the frequency of global updates as a function of the annealing control parameter, i.e. temperature. Implementation results on an Intel iPSC/2 are reported

Generalized Differential-Integral Quadrature and Application to the Simulation of Incompressible Viscous Flows Including Parallel Computation

This research covers three topics: the development of numerical techniques for the solution of partial differential and integral equations; simulations of incompressible viscous flows using these techniques; and their extension to parallel computation of the incompressible N-S equations

Parallel and Distributed Multi-Algorithm Circuit Simulation

With the proliferation of parallel computing, parallel computer-aided design (CAD) has received significant research interests. Transient transistor-level circuit simulation plays an important role in digital/analog circuit design and verification. Increased VLSI design complexity has made circuit simulation an ever growing bottleneck, making parallel processing an appealing solution for addressing this challenge. In this thesis, we propose and develop a parallel and distributed multi-algorithm approach to leverage the power of multi-core computer clusters for speeding up transistor-level circuit simulation. The targeted multi-algorithm approach provides a natural paradigm for exploiting parallelism for circuit simulation. Parallel circuit simulation is facilitated through the exploration of algorithm diversity where multiple simulation algorithms collaboratively work on a single simulation task. To utilize computer clusters comprising of multi-core processors, each algorithm is executed on a separate node with sufficient system resource such as processing power, memory and I/O bandwidth. We propose two communication schemes, namely master-slave and peer-to-peer schemes, to allow for inter-algorithm communication. Compared with the shared-memory based multi-algorithm implementation, the proposed simulation approach alleviates cache/memory contention as a result of multi-algorithm execution and provides further runtime speedups

Techniques of High Performance Reservoir Simulation for Unconventional Challenges

The quest to improve the performance of reservoir simulators has been evolving with the newly encountered challenges of modeling more complex recovery mechanisms and related phenomena. Reservoir subsidence, fracturing and fault reactivation etc. require coupled flow and poroelastic simulation. These features, in turn, bring a heavy burden on linear solvers. The booming unconventional plays such as shale/tight oil in North America demand reservoir simulation techniques to handle more physics (or more hypotheses). This dissertation deals with three aspects in improving the performance of reservoir simulation toward these unconventional challenges. Compositional simulation is often required for many reservoir studies with complex recovery mechanisms such as gas inject. But, it is time consuming and its parallelization often suffers sever load imbalance problems. In the first section, a novel approach based on domain over-decomposition is investigated and implemented to improve the parallel performance of compositional simulation. For a realistic reservoir case, it is shown the speedup is improved from 29.27 to 62.38 on 64 processors using this technique. Another critical part that determines the performance of a reservoir simulator is the linear solver. In the second section, a new type of linear solver based the combinatorial multilevel method (CML) is introduced and investigated for several reservoir simulation applications. The results show CML has better scalability and performance empirically and is well-suited for coupled poroelastic problems. These results also suggest that CML might be a promising way of precondition for flow simulation with and without coupled poroelastic calculations. In order to handle unconventional petroleum fluid properties for tight oil, the third section incorporates a simulator with extended vapor-liquid equilibrium calculations to consider the capillarity effect caused by the dynamic nanopore properties. The enhanced simulator can correctly capture the pressure dependent impact of the nanopore on rock and fluid properties. It is shown inclusion of these enhanced physics in simulation will lead to significant improvements in field operation decision-making and greatly enhance the reliability of recovery predictions

Numerical simulations of ion thruster-induced plasma dynamics

Electric space propulsion is superior to conventional chemical systems because of its greatly enhanced fuel efficiency. However, electric thrusters induce a plasma environment that has raised various concerns in terms of its potential impact on the spacecraft and on scientific instruments aboard. Our work addresses two aspects of this plasma environment: the neutralization regime of an ion thruster, i.e. the mixing between electrons and ions ejected by the thruster, and the interaction of the neutralized thruster beam with the solar wind. The objectives of our work are the following: (i) the development of a numerical simulation tool for investigating the process of ion thruster beam neutralization as well as the solar wind interaction of the neutralized beam, and (ii) the application of this tool for a detailed study of the plasma physics pertinent to the neutralization process. The first objective is met by setting up the parallel three-dimensional electromagnetic particle-in-cell simulation code ISOLDE - the Ion engine SOLver. We then employ our simulation code to carry out a systematic investigation of the plasma physical processes accompanying ion thruster beam neutralization. Starting off with a quasi-1D injection geometry, we continuously refine the simulation conditions by applying an external magnetic field, introducing a spatial separation between electron and ion source and considering a practically point-like electron emitter to finally arrive at a simulation scenario comparable to the actual ion thruster aboard NASA's Deep Space 1 spacecraft.Elektrische Raumfahrt-Antriebe sind aufgrund ihrer weitaus besseren Treibstoff- Ausnutzung konventionellen chemischen Triebwerken überlegen. Allerdings induzieren sie eine Plasma-Umgebung, deren Einfluss auf das Raumfahrzeug und auf wissenschaftliche Instrumente an Bord noch zu klären ist. Die vorliegende Arbeit behandelt zwei Aspekte dieser Plasma-Umgebung: das Neutralisations-Regime eines Ionentriebwerks, d.h. den Mischvorgang zwischen den vom Triebwerk ausgestoßenen Elektronen und Ionen, sowie die Wechselwirkung des neutralisierten Triebwerksstrahls mit dem Sonnenwind. Zielsetzung der Arbeit ist (i) die Entwicklung einer numerischen Simulation sowohl für den Neutralisationsvorgang als auch für die Sonnenwind-Wechselwirkung des neutralisierten Triebwerksstrahls, und (ii) die Anwendung dieser Simulation für eine eingehende Untersuchung der den Neutralisationsvorgang begleitenden plasmaphysikalischen Prozesse. Die in dieser Arbeit entwickelte numerische Simulation ist ein paralleler, dreidimensionaler, elektromagnetischer Particle-in-Cell Code: ISOLDE - der Ion engine SOLver. Bei der Anwendung von ISOLDE auf den Neutralisationsvorgang eines Ionentriebwerks wird zunächst eine quasi-eindimensionale Injektionsgeometrie untersucht, bevor die Simulationsbedingungen sukzessive verfeinert werden: durch Anlegen eines externen Magnetfeldes, Einführung einer räumlichen Trennung zwischen Elektronen- und Ionenquelle sowie Verwendung eines praktisch punktförmigen Elektronen-Emitters, um schließlich bei einem Simulations-Szenario anzukommen, das dem realen Ionentriebwerk an Bord der Deep Space 1 Raumsonde entspricht

a feasibility study for the spatial reconstruction of conductivity distributions by means of sensitivities

To enhance interpretation capabilities of transient electromagnetic (TEM) methods, a multidimensional inverse solution is introduced, which allows for a explicit sensitivity calculation with reduced computational effort. The main conservation of computational load is obtained by solving Maxwell's equations directly in time domain. This is achieved by means of a high efficient Krylov-subspace technique that is particularly developed for the fast computation of EM fields in the diffusive regime. Traditional modeling procedures for Maxwell's equations yields solutions independently for every frequency or, in the time domain, at a given time through explicit time stepping. Because of this, frequency domain methods are rendered extremely time consuming for multi-frequency simulations. Likewise the stability conditions required by explicit time stepping techniques often result in highly inefficient calculations for large diffusion times and conductivity contrasts. The computation of sensitivities is carried out using the adjoint Green functions approach. For time domain applications, it is realized by convolution of the background electrical field information, originating from the primary signal, with the impulse response of the receiver acting as secondary source. In principle, the adjoint formulation may be extended allowing for a fast gradient calculation without calculating and storing the whole sensitivity matrix but just the gradient of the data residual. This technique, which is also known as migration, is widely used for seismic and, to some extend, for EM methods as well. However, the sensitivity matrix, which is not easily given by migration techniques, plays a central role in resolution analysis and would therefore be discarded ...thesi