Reducing the duration and frequency of blackouts in remote communities poses an engineering challenge for grid operators. Outage effects can also be mitigated locally through microgrids. This paper develops a systematic procedure to account for these challenges by creating microgrids prioritizing high value assets within vulnerable communities. Nighttime satellite imagery is used to identify vulnerable communities. Using an asset classification and rating system, multi-Asset clusters within these communities are prioritized. Infrastructure data, geographic information systems, satellite imagery, and spectral clustering are used to form and rank microgrid candidates. A microgrid sizing algorithm is included to guide through the microgrid design process. An application of the methodology is presented using real event, location, and asset data.
This report begins with an evaluation of cladding degradation mechanisms deemed important to assessing barrier capability. Unlike similar efforts done in the past, this evaluation accounts for the hypothetical conditions associated with direct dual-purpose canister (DPC) disposal, including conditions resulting from a postulated, in-package, steady-state criticality event. A total of 16 cladding degradation mechanisms are examined assuming direct disposal of DPCs in two different hypothetical repositories: a saturated repository in shale and an unsaturated repository in alluvium.
Consider a scalar field f : M → R, where M is a triangulated simplicial mesh in Rd. A level set, or contour, at value v is a connected component of f–1 (v). As v is changed, these contours change topology, merge into each other, or split. Contour trees are concise representations of f that track this contour behavior. The vertices of these trees are the critical points of f, where the gradient is zero. The edges represent changes in the topology of contours. It is a fundamental data structure in data analysis and visualization, and there is significant previous work (both theoretical and practical) on algorithms for constructing contour trees. Suppose M has n vertices, N facets, and t critical points. A classic result of Carr, Snoeyink, and Axen (2000) gives an algorithm that takes O(n log n+Nα(N)) time (where α(·) is the inverse Ackermann function). A further improvement to O(t log t + N) time was given by Chiang et al. All these algorithms involve a global sort of the critical points, a significant computational bottleneck. Unfortunately, lower bounds of Ω(t log t) also exist. We present the first algorithm that can avoid the global sort and has a refined time complexity that depends on the contour tree structure. Intuitively, if the tree is short and fat, we get significant improvements in running time. For a partition of the contour tree into a set of descending paths, P, our algorithm runs in O($\Sigma$pϵP |p| log |p| + tα(t) + N). This is at most O(t log D + N), where D is the diameter of the contour tree. Moreover, it is O(tα(t) + N) for balanced trees, a significant improvement over the previous complexity. Our algorithm requires numerous ideas: partitioning the contour tree into join and split trees, a local growing procedure to iteratively build contour trees, and the use of heavy path decompositions for the time complexity analysis. There is a crucial use of a family of binomial heaps to maintain priorities, ensuring that any comparison made is between comparable nodes of the contour tree. We also prove lower bounds showing that the $\Sigma$pϵP |p| log |p| complexity is inherent to computing contour trees.
An existing shared risk framework designed for assessing and comparing threat-based risks to water utilities is being extended to incorporate electric power. An important differentiating characteristic of this framework is the use of a system-centric rather than an asset-centric approach. This approach allows anonymous sharing of results and enables comparison of assessments across different utilities within an infrastructure sector. By allowing utility owners to compare their assessments with others, they can improve their self-assessments and identification of "unknown unknowns". This document provides an approach for extension of the framework to electric power, including treatment of dependencies and interdependencies. The systems, threats, and mathematical description of associated risks used in a prototype framework are provided. The method is extensible so that additional infrastructure sectors can be incorporated. Preliminary results for a proof of concept calculation are provided.
This report contains a summary of our efforts to correlate head injury simulations predicting intracranial fluid cavitation with clinical assessments of brain injury from blunt impact to the head. Magnetic resonance imaging (MRI) data, collected on traumatic brain injury (TBI) subjects by researchers at the MIND Institute of New Mexico, was acquired for the current work. Specific blunt impact TBI case histories were selected from the TBI data for further study and possible correlation with simulation. Both group and single-subject case histories were examined. We found one single-subject case that was particularly suited for correlation with simulation. Diffusion tensor image (DTI) analysis of the TBI subject identified white matter regions within the brain displaying reductions in fractional anisotropy (FA), an indicator of local damage to the white matter axonal structures. Analysis of functional magnetic resonance image (fMRI) data collected on this individual identified localized regions of the brain displaying hypoactivity, another indicator of brain injury. We conducted high fidelity simulations of head impact experienced by the TBI subject using the Sandia head-neck-torso model and the shock physics computer code CTH. Intracranial fluid cavitation predictions were compared with maps of DTI fractional anisotropy and fMRI hypoactivity to assess whether a possible correlation exists. The ultimate goal of this work is to assess whether one can correlate simulation predictions of intracranial fluid cavitation with the brain injured sites identified by the fMRI and DTI analyses. The outcome of this effort is described in this report.
QOOH radicals are key intermediates in the chain of reactions leading to the autoignition of hydrocarbons and oxygenated organic compounds. They are thought to undergo two main reactions: OH elimination to form a cyclic ether and HO2 elimination to form an alkene. However, theoretical analysis of various substituted hydroperoxyalkyl radicals has found two new pathways: OH transfer and internal H abstraction assisted OH elimination. To determine the importance of these new pathways, their barrier heights for several substituted alkanes were calculated using various quantum chemical theories and compared to those of the well-known pathways. Several cases revealed possible competition with the well-known pathways. Rate coefficients were calculated for propyl systems but further studies will need to complete rate coefficients and branching fractions for all systems analyzed to understand these new reactions’ role in autoignition.
Aeroseismometery is a novel, cutting edge capability that involves balloon based systems for detecting and geolocating sources of infrasound. The incident infrasound from a range of sources such as volcanos, earthquakes, explosions, supersonic aircraft impinges upon the balloon system causing it to respond dynamically. The dynamic response is post-processed to locate the infrasound source. This report documents the derivation of an analytical model that predicts the balloon dynamics. Governing equations for the system are derived as well as a transfer function relating the infrasound signal to the net force on the balloon components. Experimental measurements of the infrasound signals are convolved with the transfer function and the governing equations numerically time integrated to obtain predictions of the displacement, velocity and acceleration of the balloon system. The predictions are compared to the experimental measurements with good agreement observed. The derivation focuses only on the vertical dynamics of the balloon system. Future work will develop governing equations for the swinging response of the balloon to the incident infrasound.