Publications

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Advanced computing hardware and software written to exploit massively parallel architectures greatly facilitate the computation of extremely large problems. On the other hand, these tools, though enabling higher fidelity models, have often resulted in much longer run-times and turn-around-times in providing answers to engineering problems. The impediments include smaller elements and consequently smaller time steps, much larger systems of equations to solve, and the inclusion of nonlinearities that had been ignored in days when lower fidelity models were the norm. The research effort reported focuses on the accelerating the analysis process for structural dynamics though combinations of model reduction and mitigation of some factors that lead to over-meshing.

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The advent of high quality factor (Q) microphotonic-resonators has led to the demonstration of high-fidelity optical sensors of many physical phenomena (e.g. mechanical, chemical, and biological sensing) often with far better sensitivity than traditional techniques. Microphotonic-resonators also offer potential advantages as uncooled thermal detectors including significantly better noise performance, smaller pixel size, and faster response times than current thermal detectors. In particular, microphotonic thermal detectors do not suffer from Johnson noise in the sensor, offer far greater responsivity, and greater thermal isolation as they do not require metallic leads to the sensing element. Such advantages make the prospect of a microphotonic thermal imager highly attractive. Here, we introduce the microphotonic thermal detection technique, present the theoretical basis for the approach, discuss our progress on the development of this technology and consider future directions for thermal microphotonic imaging. Already we have demonstrated viability of device fabrication with the successful demonstration of a 20{micro}m pixel, and a scalable readout technique. Further, to date, we have achieved internal noise performance (NEP{sub Internal} < 1pW/{radical}Hz) in a 20{micro}m pixel thereby exceeding the noise performance of the best microbolometers while simultaneously demonstrating a thermal time constant ({tau} = 2ms) that is five times faster. In all, this results in an internal detectivity of D*{sub internal} = 2 x 10{sup 9}cm {center_dot} {radical}Hz/W, while roughly a factor of four better than the best uncooled commercial microbolometers, future demonstrations should enable another order of magnitude in sensitivity. While much work remains to achieve the level of maturity required for a deployable technology, already, microphotonic thermal detection has demonstrated considerable potential.

Decisions for climate policy will need to take place in advance of climate science resolving all relevant uncertainties. Further, if the concern of policy is to reduce risk, then the best-estimate of climate change impacts may not be so important as the currently understood uncertainty associated with realizable conditions having high consequence. This study focuses on one of the most uncertain aspects of future climate change - precipitation - to understand the implications of uncertainty on risk and the near-term justification for interventions to mitigate the course of climate change. We show that the mean risk of damage to the economy from climate change, at the national level, is on the order of one trillion dollars over the next 40 years, with employment impacts of nearly 7 million labor-years. At a 1% exceedance-probability, the impact is over twice the mean-risk value. Impacts at the level of individual U.S. states are then typically in the multiple tens of billions dollar range with employment losses exceeding hundreds of thousands of labor-years. We used results of the Intergovernmental Panel on Climate Change's (IPCC) Fourth Assessment Report 4 (AR4) climate-model ensemble as the referent for climate uncertainty over the next 40 years, mapped the simulated weather hydrologically to the county level for determining the physical consequence to economic activity at the state level, and then performed a detailed, seventy-industry, analysis of economic impact among the interacting lower-48 states. We determined industry GDP and employment impacts at the state level, as well as interstate population migration, effect on personal income, and the consequences for the U.S. trade balance.

This report documents the architecture and implementation of a Parallel Digital Forensics infrastructure. This infrastructure is necessary for supporting the design, implementation, and testing of new classes of parallel digital forensics tools. Digital Forensics has become extremely difficult with data sets of one terabyte and larger. The only way to overcome the processing time of these large sets is to identify and develop new parallel algorithms for performing the analysis. To support algorithm research, a flexible base infrastructure is required. A candidate architecture for this base infrastructure was designed, instantiated, and tested by this project, in collaboration with New Mexico Tech. Previous infrastructures were not designed and built specifically for the development and testing of parallel algorithms. With the size of forensics data sets only expected to increase significantly, this type of infrastructure support is necessary for continued research in parallel digital forensics. This report documents the implementation of the parallel digital forensics (PDF) infrastructure architecture and implementation.

This document outlines ways to more effectively communicate with U.S. Federal decision makers by outlining the structure, authority, and motivations of various Federal groups, how to find the trusted advisors, and how to structure communication. All three branches of Federal governments have decision makers engaged in resolving major policy issues. The Legislative Branch (Congress) negotiates the authority and the resources that can be used by the Executive Branch. The Executive Branch has some latitude in implementation and prioritizing resources. The Judicial Branch resolves disputes. The goal of all decision makers is to choose and implement the option that best fits the needs and wants of the community. However, understanding the risk of technical, political and/or financial infeasibility and possible unintended consequences is extremely difficult. Primarily, decision makers are supported in their deliberations by trusted advisors who engage in the analysis of options as well as the day-to-day tasks associated with multi-party negotiations. In the best case, the trusted advisors use many sources of information to inform the process including the opinion of experts and if possible predictive analysis from which they can evaluate the projected consequences of their decisions. The paper covers the following: (1) Understanding Executive and Legislative decision makers - What can these decision makers do? (2) Finding the target audience - Who are the internal and external trusted advisors? (3) Packaging the message - How do we parse and integrate information, and how do we use computer simulation or models in policy communication?