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作者： Earle, Denise National University of Ireland Maynooth (Ireland)

学位级别：Ph.D.

Seriation is a data analytic tool for obtaining a permutation of a set of objects with the goal of revealing structural information within the set of objects. The purpose of this thesis is to investigate and develop tools for seriation with the goal of using these tools to enhance data visualisation. The particular focus of this thesis is on dendrogram seriation algorithms. A dendrogram is a tree-like structure used for visualising the results of a hierarchical clustering and the order of the leaves in a dendrogram provides a permutation of a set of objects. Dendrogram seriation algorithms rearrange the leaves of a dendrogram in order to find a permutation that optimises a given criterion. Dendrogram seriation algorithms are widely used, however, the research in this area is often confusing because of inconsistent or inadequate terminology. This thesis proposes new notation and terminology with the goal of better understanding and comparing dendrogram seriation algorithms. Seriation criteria measure the goodness of a permutation of a set of objects. Popular seriation criteria include the path length of a permutation and measuring anti-Robinson form in a symmetric matrix. This thesis proposes two new seriation criteria, lazy path length and banded anti-Robinson form, and demonstrates their effectiveness in improving a variety of visualisations. The main contribution of this thesis is a new dendrogram seriation algorithm. This algorithm improves on other dendrogram seriation algorithms and is also flexible because it allows the user to either choose from a variety of seriation criteria, including the new criteria mentioned above, or to input their own criteria. Finally, this thesis performs a comparison of several seriation algorithms, the results of which show that the proposed algorithm performs competitively against other algorithms. This leads to a set of general guidelines for choosing the most appropriate seriation algorithm for different seriation interests and

关键词： Dendrogram seriation data visualisation algorithms and applications

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Telemetry Fault-Detection algorithms: applications for Spacecraft Monitoring and Space Environment Sensing

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JOURNAL OF AEROSPACE INFORMATION SYSTEMS 2018年第5期15卷 239-252页

作者： Carlton, Ashley Morgan, Rachel Lohmeyer, Whitney Cahoy, Kerri MIT Dept Aeronaut & Astronaut 77 Massachusetts Ave Cambridge MA 02139 USA MIT Dept Aeronaut & Astronaut Aeronaut & Astronaut Earth Atmospher Planetary & Sci Dept 77 Massachusetts Ave Cambridge MA 02139 USA

algorithms have been developed that identify unusual behavior in satellite health telemetry. Telemetry from solid-state power amplifiers and amplifier thermistors from 32 geostationary Earth orbit communications satellites from 1991 to 2015 are examined. Transient event detection and change-point event detection techniques that use a sliding window-based median are used, statistically evaluating the telemetry stream compared to the local norm. This approach allows application of the algorithms to any spacecraft platform because there is no reliance in the algorithms on satellite- or component-specific parameters, and it does not require a priori knowledge about the data distribution. Individual telemetry data streams are analyzed with the event detection algorithms, resulting in a compiled list of unusual events for each satellite. This approach identifies up to six events of up to six events that affect 51 of 53 telemetry streams at once, indicative of a spacecraft system-level event. In two satellites, the same top event date (4 December 2008) occurs over more than 10 years of telemetry from both satellites. Of the five spacecraft with known maneuvers, the algorithms identify the maneuvers in all cases. Event dates are compared to known operational activities, space weather events, and available anomaly lists to assess the use of event detection algorithms for spacecraft monitoring and sensing of the space environment.

关键词： Space Environment Spacecrafts Telemetry System algorithms and applications Fault Detection Techniques Geostationary Operational Environmental Satellite Thermistors Earth Communications Satellite Spacecraft System

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Automatic Runtime Scheduling Via Directed Acyclic Graphs for CFD applications

Automatic Runtime Scheduling Via Directed Acyclic Graphs for...

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AIAA Aviation Forum

作者： Torres, Hilario C. Murman, Scott NASA Ames Res Ctr NASA Adv Supercomp Div Moffett Field CA 94035 USA

ISBN: (数字)9781624107047

ISBN: (纸本)9781624107047

The order of execution of computational kernels for Single-Program, Multiple-Data (SPMD) programs is usually determined at compile time. These static predetermined schedules can lead to performance issues at runtime, and are difficult to implement for inhomogeneous situations, such as variable-order or multi-physics applications. It is especially challenging to generate performant schedules when it is unknown whether specific kernels require execution, as a function of user inputs, or the kernel execution time changes dependent on the hardware. This paper presents a solution to this problem by dynamically scheduling computational kernels at runtime using directed acyclic graphs to track the data dependencies between kernels. This system is specifically designed to leverage existing computational infrastructure as much as possible, facilitating the extension to legacy applications. This scheduling system is demonstrated using the eddy high-order multi-physics solver developed at NASA. The details regarding the implementation, our experiences using this system, and performance are discussed.

关键词： NASA High Performance Computing algorithms and applications Application Programming Interface Sandia National Laboratories Molecular Dynamics Hydrodynamics NASA ames

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Multi-Objective Cooperated Path Planning of Multiple Unmanned Aerial Vehicles Based on Revisit Time

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JOURNAL OF AEROSPACE INFORMATION SYSTEMS 2021年第12期18卷 919-932页

作者： Haghighi, Hassan Asadi, Davood Delahaye, Daniel Univ Toulouse Natl Sch Civil Aviat F-31400 Toulouse France Adana Alparslan Turkes Sci & Technol Univ Dept Aerosp Engn TR-01250 Adana Turkey

This paper investigates multi-objective optimization of coordinated patrolling flight of multiple unmanned aerial vehicles in the vicinity of terrain, while respecting their performance parameters. A new efficient modified A-star (A*) algorithm with a novel defined criterion known as individual revisit time cell value is introduced and extended to the whole area of the three-dimensional mountainous environment. As a contribution to solving tradeoffs in the optimization problem, revisit time is conjugated with other contrary costs effective in flight planning through Pareto analysis. By introducing the revisit time and applying a specific setup to mitigate computational complexity, the proposed algorithm efficiently revisits the desired zones, which are more important to be revisited during the patrolling mission. The results of the introduced modified A* algorithm are compared in various scenarios with two different algorithms: a complete and optimal algorithm known as Dijkstra, and an evolutionary algorithm known as the genetic algorithm. Simulation results demonstrate that the proposed algorithm generates faster and more efficient trajectories in complex multi-agent scenarios due to the introduced cell selection method and dynamic-based simplifications applied in this research.

关键词： UAV Path Planning Multi Objective Evolutionary algorithms Multi Objective Genetic Algorithm Flight Planning Optimization Algorithm algorithms and applications Flight Altitude Ailerons Markov Decision Process

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OPERATIONS-RESEARCH AND CAPACITY EXPANSION PROBLEMS - A SURVEY

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OPERATIONS RESEARCH 1982年第5期30卷 907-947页

作者： LUSS, H Bell Laboratories Holmdel New Jersey

Planning for the expansion of production capacity is of vital importance in many applications within the private and public sectors. Examples can be found in heavy process industries, communication networks, electrical power services, and water resource systems. In all of these applications, the expansion of production capacity requires the commitment of substantial capital resources over long periods of time. Capacity expansion planning consists primarily of determining future expansion times, sizes, and locations, as well as the types of production facilities. Since the late 1950s, operations research methodology has been used to develop various models and solution approaches suitable for different applications. In this paper, we attempt to unify the existing literature on capacity expansion problems, emphasizing modeling approaches, algorithmic solutions, and relevant applications. The paper includes an extensive list of references covering a broad spectrum of capacity expansion problems.

关键词： 182 survey of models algorithms and applications 366 survey of capacity expansion problems

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GENERALIZED COMPOUND SCALING ALGORITHM AND APPLICATION TO MINIMUM WEIGHT DESIGN OF PLATE STRUCTURES

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AIAA JOURNAL 1992年第10期30卷 2532-2539页

作者： GRANDHI, RV VENUGOPAL, NS VENKAYYA, VB WRIGHT LAB WRIGHT PATTERSON AFB OH 45433 USA

This paper presents the generalized compound scaling algorithm and its application to optimum weight design of plate structures. The optimum designs are reached by simply scaling the design variables to an optimum intersection of multiple constraints. A four-noded isoparametric plate element is used for modeling the structure. Sensitivity computations and the optimization algorithm are discussed. The optimization cost involved (excluding the finite element analyses) is very small using this algorithm. The procedure is demonstrated on three example problems using stress and displacement constraints with side bounds on the design variables.

关键词： algorithms and applications Optimization Algorithm Finite Element Modeling Transverse Shear Sensitivity Analysis Structural Optimization Material Properties Cantilever Beam Nastran Structural Weight

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Automated generation of high-order partial derivative models

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AIAA JOURNAL 2003年第8期41卷 1590-1598页

作者： Turner, JD Amdyn Syst Res & Dev White GA 30184 USA

A standard problem in science and engineering consists of developing mathematics and sensitivity models for complex applications for optimizing a candidate design. A chain rule-based evaluation technique is presented for analytically evaluating partial derivatives of nonlinear functions and differential equations defined by a high-level language. A coordinate embedding strategy is introduced that replaces all scalar variables with higher-dimensional objects. The higher-dimensional objects are defined by a concatenation of the original scalar and its Jacobian, Hessian, and higher-order partials. Exact sensitivity models are recovered for arbitrarily complex mathematical models. An operator-overloading technique is used to define generalized operators for basic and standard library functions. The generalized operators encode the chain rule of calculus and store the results of partial derivative calculations in the artificial dimensions used to redefine the scalar operations. Hidden operations automatically generate and evaluate exact first-through fourth-order partial derivative models, which are accurate to the working precision of the machine. The new algorithm replaces a normally complex, error-prone, time-consuming, and laborintensive process for producing the partials with an automatic procedure. Module functions encapsulate new data types, and extended mathematic and library functions for handling vector, matrix, and tensor operations. Matrix operations are shown to generalize easily. The algorithm has broad potential for impacting the design and use of mathematical programming tools for applications in science and engineering. Several applications are presented that demonstrate the effectiveness of the methods.

关键词： Mathematical Models FORTRAN Computing Kinetic Energy Taylor Series Gaussian Elimination Software Architecture algorithms and applications Molecular Dynamics Robotics

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APPROXIMATION IN NONHIERARCHIC SYSTEM OPTIMIZATION

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AIAA JOURNAL 1994年第1期32卷 198-205页

作者： RENAUD, JE GABRIELE, GA RENSSELAER POLYTECH INST DEPT MECH ENGN AERONAUT ENGN & MECHTROYNY 12180

This paper reports on the effectiveness of a nonhierarchic system optimization algorithm in application to complex coupled systems problems. A second-order nonhierarchic system optimization algorithm developed in earlier studies is modified in this study to provide for individual constraint/state modeling. A cumulative constraint formulation was used in previous implementation studies. The test problems in this study are each complex coupled systems. Complex coupled systems require an iterative solution strategy to evaluate system states. Nonhierarchic algorithm development is driven by these types of problems, and their study is imperative. The algorithm successfully optimizes each of the complex coupled systems. A significant reduction in the number of system analyses required for optimization is observed as compared with conventional optimization using the generalized reduced-gradient method.

关键词： Iterative Solution algorithms and applications Optimization Algorithm Gradient Method Heat Sinks Multidisciplinary Design Optimization Electronic Component Thermal Analysis Artificial Neural Network Nonlinear Programming

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algorithms and application of sparse matrix assembly and equation solvers for aeroacoustics

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AIAA JOURNAL 2002年第4期40卷 661-670页

作者： Watson, WR Nguyen, DT Reddy, CJ Vatsa, VN Tang, WH NASA Langley Res Ctr Computat Modeling & Simulat Branch Hampton VA 23681 USA Old Dominion Univ Multidisciplinary Parallel Vector Computat Ctr Norfolk VA 23529 USA EM Inc Hampton VA 23666 USA NASA Langley Res Ctr Computat Modeling & Simulat Branch Hampton VA 23681 USA Hong Kong Univ Sci & Technol Dept Civil & Struct Engn Kowloon Hong Kong Peoples R China

An algorithm for symmetric sparse equation solutions on an unstructured grid is described. Efficient, sequential sparse algorithms for degree-of-freedom reordering, supernodes, symbolic/numerical factorization, and forward/backward solution phases are reviewed. Three sparse algorithms for the generation and assembly of symmetric systems of matrix equations are presented. The accuracy and numerical performance of the sequential version of the sparse algorithms are evaluated over the frequency range of interest in a three-dimensional aeroacoustics application. Results show that the solver solutions are accurate using a discretization of 12 points per wavelength. Results also show that the first assembly algorithm is impractical for high-frequency noise calculations. The second and third assembly algorithms have nearly equal performance at low values,of source frequencies, but at higher values of source frequencies the third algorithm saves CPU time and RAM., The, CPU time and the RAM required by the second and third assembly algorithms are two orders of magnitude smaller than that required by the sparse equation solver. A sequential version of these sparse algorithms can, therefore, be conveniently incorporated into a substructuring (or domain decomposition) formulation to achieve parallel, computation, where different substructures are handled by different parallel processors.

关键词： Aeroacoustics Unstructured Grid algorithms and applications Three Dimensional Elements Trusses Dirichlet Boundary Condition Boundary Value Problems Nacelles Aircraft Noise Atmospheric Conditions

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Application of Chance-Constrained and Sample-Based Path Search for High Level Behavioural Planning: A Case Study of Autonomous Highway Lane Change Scenario

Application of Chance-Constrained and Sample-Based Path Sear...

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AIAA Science and Technology Forum and Exposition (AIAA SciTech)

作者： Selvakumar, Jhanani Turkoglu, Kamran NIO USA Inc Adv Technol Div Autonomous Driving Grp 3200 N 1st St San Jose CA 95134 USA

ISBN: (数字)9781624105951

ISBN: (纸本)9781624105951

In this paper, we address the problem of high-level path-planning, for the application of an autonomous vehicle on a highway, using a chance-constraint based rapidly exploring random tree (CC-RRT*) methodology. Random exploration tree search quickly explores the free space available to the vehicle to generate feasible and/or optimal paths from one point to another. The inclusion of chance constraints allows us to effectively handle the uncertainty that arises from the behavior of other agents on the highway, as well as the noise in the measurements and process noise associated with our vehicle model. The novel contribution of this work is the adaptation of the constraints of high way driving (such as kinodynamic model, collision avoidance, and routing) to the framework of chance constraints and point-mass sample-based tree search. A succinct description of our problem formulation and solution method are presented along with some numerical simulations to illustrate the efficacy and performance of the proposed algorithm for the application of highway driving.

关键词： Real Time Path Planning Numerical Simulation Robots algorithms and applications Boundary Value Problems Admissible Heuristic Velocity Profiles Search Algorithm Heading Angle Computing

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