Solution of partial differential equations on vector and parallel computers

The present status of numerical methods for partial differential equations on vector and parallel computers was reviewed. The relevant aspects of these computers are discussed and a brief review of their development is included, with particular attention paid to those characteristics that influence algorithm selection. Both direct and iterative methods are given for elliptic equations as well as explicit and implicit methods for initial boundary value problems. The intent is to point out attractive methods as well as areas where this class of computer architecture cannot be fully utilized because of either hardware restrictions or the lack of adequate algorithms. Application areas utilizing these computers are briefly discussed

Distributed optimization of multi-agent systems: Framework, local optimizer, and applications

Convex optimization problem can be solved in a centralized or distributed manner. Compared with centralized methods based on single-agent system, distributed algorithms rely on multi-agent systems with information exchanging among connected neighbors, which leads to great improvement on the system fault tolerance. Thus, a task within multi-agent system can be completed with presence of partial agent failures. By problem decomposition, a large-scale problem can be divided into a set of small-scale sub-problems that can be solved in sequence/parallel. Hence, the computational complexity is greatly reduced by distributed algorithm in multi-agent system. Moreover, distributed algorithm allows data collected and stored in a distributed fashion, which successfully overcomes the drawbacks of using multicast due to the bandwidth limitation. Distributed algorithm has been applied in solving a variety of real-world problems. Our research focuses on the framework and local optimizer design in practical engineering applications. In the first one, we propose a multi-sensor and multi-agent scheme for spatial motion estimation of a rigid body. Estimation performance is improved in terms of accuracy and convergence speed. Second, we develop a cyber-physical system and implement distributed computation devices to optimize the in-building evacuation path when hazard occurs. The proposed Bellman-Ford Dual-Subgradient path planning method relieves the congestion in corridor and the exit areas. At last, highway traffic flow is managed by adjusting speed limits to minimize the fuel consumption and travel time in the third project. Optimal control strategy is designed through both centralized and distributed algorithm based on convex problem formulation. Moreover, a hybrid control scheme is presented for highway network travel time minimization. Compared with no controlled case or conventional highway traffic control strategy, the proposed hybrid control strategy greatly reduces total travel time on test highway network

Novel inverse methods for crystal self-assembly

Inverse design methods are a promising new strategy to aid the discovery of materials with targeted properties. In this thesis, we employ two novel inverse design methods and apply it to the study of crystal self-assembly in two dimensions. In particular, we introduce a novel zero temperature (ground state -GS) analytical method and find effective interactions that stabilize targeted lattices by means of a constrained non-linear optimization. We demonstrate advantages of this new formulation by designing a square lattice to display increasing energetic differences over relevant lattice competitors and show that such constraints correlate with crystal thermal stability. However, these constraints also reduce density range representation of the target lattice in its phase diagram and suggests an inherent tradeoff in the constrained strategy. Having established a link between crystal property and constraint type, we design the snubsquare lattice by means of energetic constraints over close competitors and show this is in contrast to the design of the kagome lattice which required no such constraints. We then test the limits of the GS method and design the open and challenging truncated square (TS) and truncated hexagonal lattices (TH). Unlike the previous targets, these lattices require the inclusion of a large pool of competitor micro-phases that greatly complicate optimization. Nevertheless, we show the system is still solvable by judicious use of constraints and decision variables. Next, we use a novel relative entropy minimization approach (RE) and the GS method to explore the design space of particles interacting via a potential featuring a single attractive well. Specifically, we design a square, honeycomb and kagome lattice and show that we are able to infer a set of `design rules' from generalities of the resulting interactions in both methods. We validate these rules by designing the challenging TS and TH lattices and show that optimized interactions readily promote target assembly from the fluid state. Finally, we expand the RE method to accommodate multi-component systems and inverse design a variety of crystal binary mixtures featuring triangular, square as well as other intricate and open motifs. We demonstrate how binary systems can help achieve equivalent single component structures but with simpler underlying interactions. Further, we analyze the binary assembly process and find that self interactions act as a `primer' that place particles in the correct local positions while cross interactions, through system coupling, act as the `binder' that lock particles into the correct binary structure.Chemistr

Working Notes from the 1992 AAAI Workshop on Automating Software Design. Theme: Domain Specific Software Design

The goal of this workshop is to identify different architectural approaches to building domain-specific software design systems and to explore issues unique to domain-specific (vs. general-purpose) software design. Some general issues that cut across the particular software design domain include: (1) knowledge representation, acquisition, and maintenance; (2) specialized software design techniques; and (3) user interaction and user interface

The Role of Computers in Research and Development at Langley Research Center

This document is a compilation of presentations given at a workshop on the role cf computers in research and development at the Langley Research Center. The objectives of the workshop were to inform the Langley Research Center community of the current software systems and software practices in use at Langley. The workshop was organized in 10 sessions: Software Engineering; Software Engineering Standards, methods, and CASE tools; Solutions of Equations; Automatic Differentiation; Mosaic and the World Wide Web; Graphics and Image Processing; System Design Integration; CAE Tools; Languages; and Advanced Topics

Interactive Medical Image Registration With Multigrid Methods and Bounded Biharmonic Functions

Interactive image registration is important in some medical applications since automatic image registration is often slow and sometimes error-prone. We consider interactive registration methods that incorporate user-specified local transforms around control handles. The deformation between handles is interpolated by some smooth functions, minimizing some variational energies. Besides smoothness, we expect the impact of a control handle to be local. Therefore we choose bounded biharmonic weight functions to blend local transforms, a cutting-edge technique in computer graphics. However, medical images are usually huge, and this technique takes a lot of time that makes itself impracticable for interactive image registration. To expedite this process, we use a multigrid active set method to solve bounded biharmonic functions (BBF). The multigrid approach is for two scenarios, refining the active set from coarse to fine resolutions, and solving the linear systems constrained by working active sets. We\u27ve implemented both weighted Jacobi method and successive over-relaxation (SOR) in the multigrid solver. Since the problem has box constraints, we cannot directly use regular updates in Jacobi and SOR methods. Instead, we choose a descent step size and clamp the update to satisfy the box constraints. We explore the ways to choose step sizes and discuss their relation to the spectral radii of the iteration matrices. The relaxation factors, which are closely related to step sizes, are estimated by analyzing the eigenvalues of the bilaplacian matrices. We give a proof about the termination of our algorithm and provide some theoretical error bounds. Another minor problem we address is to register big images on GPU with limited memory. We\u27ve implemented an image registration algorithm with virtual image slices on GPU. An image slice is treated similarly to a page in virtual memory. We execute a wavefront of subtasks together to reduce the number of data transfers. Our main contribution is a fast multigrid method for interactive medical image registration that uses bounded biharmonic functions to blend local transforms. We report a novel multigrid approach to refine active set quickly and use clamped updates based on weighted Jacobi and SOR. This multigrid method can be used to efficiently solve other quadratic programs that have active sets distributed over continuous regions

[Activity of Institute for Computer Applications in Science and Engineering]

This report summarizes research conducted at the Institute for Computer Applications in Science and Engineering in applied mathematics, fluid mechanics, and computer science

A Distributed Approach to solve Power Flow problems in new emerging scenarios

Distributed Computing is growing up in interest in many applied fields of scientific research. Power system operation is becoming increasingly complex due to the Distributed Energy Resources (DERs) integration at various voltage levels. In this context, the need to automate grid operation is ever fundamental in order to ensure adequate levels of reliability, flexibility and cost effectiveness of power systems. This report shall be intended as a support for the understanding of methodological aspects and principles for the solution of power flow equations through a distributed approach, in a context where multiple interacting entities share a portion of their grids and want to align their computation in an automated way. The aim is both to give the reader a comprehensive overview of the software used for the implementation, the Portable Scientific Extensible Toolkit for Scientific Computation - PETSc, and the principles followed to build the Distributed Power Flow Solver as well as the specific features that make it different from other distributed solvers available in the literature. Additionally, two frameworks are presented as potential applications for the model. The European transmission networks level, in the context of capacity calculation, and the transmission-distribution networks coupling. In the beginning a short literature review on both frameworks is presented.JRC.C.3-Energy Security, Distribution and Market