We present a model for optimizing the placement of sensors in municipal water networks to detect maliciously-injected contaminants. An optimal sensor configuration minimizes the expected fraction of the population at risk. We formulate this problem as an integer program, which can be solved with generally available IP solvers. We find optimal sensor placements for three real networks with synthetic risk and population data. Our experiments illustrate that this formulation can be solved relatively quickly, and that the predicted sensor configuration is relatively insensitive to uncertainties in the data used for prediction.
We describe COLIN, a Common Optimization Library INterface for C++. COLIN provides C++ template classes that define a generic interface for both optimization problems and optimization solvers. COLIN is specifically designed to facilitate the development of hybrid optimizers, for which one optimizer calls another to solve an optimization subproblem. We illustrate the capabilities of COLIN with an example of a memetic genetic programming solver.
In the LIGA process for manufacturing microcomponents, a polymer film is exposed to an x-ray beam passed through a gold pattern. This is followed by the development stage, in which a selective solvent is used to remove the exposed polymer, reproducing the gold pattern in the polymer film. Development is essentially polymer dissolution, a physical process which is not well understood. We have used coarse-grained molecular dynamics simulation to study the early stage of polymer dissolution. In each simulation a film of non-glassy polymer was brought into contact with a layer of solvent. The mutual penetration of the two phases was tracked as a function of time. Several film thicknesses and two different chain lengths were simulated. In all cases, the penetration process conformed to ideal Fickian diffusion. We did not see the formation of a gel layer or other non-ideal effects. Variations in the Fickian diffusivities appeared to be caused primarily by differences in the bulk polymer film density.
This project is being conducted by Sandia National Laboratories in support of the DARPA Augmented Cognition program. Work commenced in April of 2002. The objective for the DARPA program is to 'extend, by an order of magnitude or more, the information management capacity of the human-computer warfighter.' Initially, emphasis has been placed on detection of an operator's cognitive state so that systems may adapt accordingly (e.g., adjust information throughput to the operator in response to workload). Work conducted by Sandia focuses on development of technologies to infer an operator's ongoing cognitive processes, with specific emphasis on detecting discrepancies between machine state and an operator's ongoing interpretation of events.
Proposed for publication in the Special Issue of
Concurrency and Computation: Practice and Experience - The
High Performance Architectural Challenge: Mass Market Versus
Proprietary Components.
It has recently been shown that local values of the conventional exchange energy per particle cannot be described by an analytic expansion in the density variation. Yet, it is known that the total exchange-correlation (XC) energy per particle does not show any corresponding nonanalyticity. Indeed, the nonanalyticity is here shown to be an effect of the separation into conventional exchange and correlation. We construct an alternative separation in which the exchange part is made well behaved by screening its long-ranged contributions, and the correlation part is adjusted accordingly. This alternative separation is as valid as the conventional one, and introduces no new approximations to the total XC energy. We demonstrate functional development based on this approach by creating and deploying a local-density-approximation-type XC functional. Hence, this work includes both the theory and the practical calculations needed to provide a starting point for an alternative approach towards improved approximations of the total XC energy.
The U.S. Department of Energy recently announced the first five grants for the Genomes to Life (GTL) Program. The goal of this program is to ''achieve the most far-reaching of all biological goals: a fundamental, comprehensive, and systematic understanding of life.'' While more information about the program can be found at the GTL website (www.doegenomestolife.org), this paper provides an overview of one of the five GTL projects funded, ''Carbon Sequestration in Synechococcus Sp.: From Molecular Machines to Hierarchical Modeling.'' This project is a combined experimental and computational effort emphasizing developing, prototyping, and applying new computational tools and methods to elucidate the biochemical mechanisms of the carbon sequestration of Synechococcus Sp., an abundant marine cyanobacteria known to play an important role in the global carbon cycle. Understanding, predicting, and perhaps manipulating carbon fixation in the oceans has long been a major focus of biological oceanography and has more recently been of interest to a broader audience of scientists and policy makers. It is clear that the oceanic sinks and sources of CO(2) are important terms in the global environmental response to anthropogenic atmospheric inputs of CO(2) and that oceanic microorganisms play a key role in this response. However, the relationship between this global phenomenon and the biochemical mechanisms of carbon fixation in these microorganisms is poorly understood. The project includes five subprojects: an experimental investigation, three computational biology efforts, and a fifth which deals with addressing computational infrastructure challenges of relevance to this project and the Genomes to Life program as a whole. Our experimental effort is designed to provide biology and data to drive the computational efforts and includes significant investment in developing new experimental methods for uncovering protein partners, characterizing protein complexes, identifying new binding domains. We will also develop and apply new data measurement and statistical methods for analyzing microarray experiments. Our computational efforts include coupling molecular simulation methods with knowledge discovery from diverse biological data sets for high-throughput discovery and characterization of protein-protein complexes and developing a set of novel capabilities for inference of regulatory pathways in microbial genomes across multiple sources of information through the integration of computational and experimental technologies. These capabilities will be applied to Synechococcus regulatory pathways to characterize their interaction map and identify component proteins in these pathways. We will also investigate methods for combining experimental and computational results with visualization and natural language tools to accelerate discovery of regulatory pathways. Furthermore, given that the ultimate goal of this effort is to develop a systems-level of understanding of how the Synechococcus genome affects carbon fixation at the global scale, we will develop and apply a set of tools for capturing the carbon fixation behavior of complex of Synechococcus at different levels of resolution. Finally, because the explosion of data being produced by high-throughput experiments requires data analysis and models which are more computationally complex, more heterogeneous, and require coupling to ever increasing amounts of experimentally obtained data in varying formats, we have also established a companion computational infrastructure to support this effort as well as the Genomes to Life program as a whole.
Developers of computer codes, analysts who use the codes, and decision makers who rely on the results of the analyses face a critical question: How should confidence in modeling and simulation be critically assessed? Verification and validation (V&V) of computational simulations are the primary methods for building and quantifying this confidence. Briefly, verification is the assessment of the accuracy of the solution to a computational model. Validation is the assessment of the accuracy of a computational simulation by comparison with experimental data. In verification, the relationship of the simulation to the real world is not an issue. In validation, the relationship between computation and the real world, i.e., experimental data, is the issue.
RMPP (reliable message passing protocol) is a lightweight transport protocol designed for clusters that provides end-to-end flow control and fault tolerance. In this article, presentations were made that compares RMPP to TCP, UDP, and "Utopia". The article compared the protocols on four benchmarks: bandwidth, latency, all-to-all, and communication-computation overlap. The results have shown that message-based protocols like RMPP have several advantages over TCP including ease of implementation, support for computation/communication overlap, and low CPU overhead.
Solidification is an important aspect of welding, brazing, soldering, LENS fabrication, and casting. The current trend toward utilizing large-scale process simulations and materials response models for simulation-based engineering is driving the development of new modeling techniques. However, the effective utilization of these models is, in many cases, limited by a lack of fundamental understanding of the physical processes and interactions involved. In addition, experimental validation of model predictions is required. We have developed new and expanded experimental techniques, particularly those needed for in-situ measurement of the morphological and kinetic features of the solidification process. The new high-speed, high-resolution video techniques and data extraction methods developed in this work have been used to identify several unexpected features of the solidification process, including the observation that the solidification front is often far more dynamic than previously thought. In order to demonstrate the utility of the video techniques, correlations have been made between the in-situ observations and the final solidification microstructure. Experimental methods for determination of the solidification velocity in highly dynamic pulsed laser welds have been developed, implemented, and used to validate and refine laser welding models. Using post solidification metallographic techniques, we have discovered a previously unreported orientation relationship between ferrite and austenite in the Fe-Cr-Ni alloy system, and have characterized the conditions under which this new relationship develops. Taken together, the work has expanded both our understanding of, and our ability to characterize, solidification phenomena in complex alloy systems and processes.
We present a technique for determining non-linear resistances, capacitances, and inductances from ring down data in a non-linear RLC circuit. Although the governing differential equations are non-linear, we are able to solve this problem using linear least squares without doing any sort of non-linear iteration.
This paper presents a description of the SIERRA Framework Version 3 parallel transfer operators. The high-level design including object interrelationships, as well as requirements for their use, is discussed. Transfer operators are used for moving field data from one computational mesh to another. The need for this service spans many different applications. The most common application is to enable loose coupling of multiple physics modules, such as for the coupling of a quasi-statics analysis with a thermal analysis. The SIERRA transfer operators support the transfer of nodal and element fields between meshes of different, arbitrary parallel decompositions. Also supplied are ''copy'' transfer operators for efficient transfer of fields between identical meshes. A ''copy'' transfer operator is also implemented for constraint objects. Each of these transfer operators is described. Also, two different parallel algorithms are presented for handling the geometric misalignment between different parallel-distributed meshes.
