Design and operation of the electric power grid (EPG) relies heavily on computational models. High-fidelity, full-order models are used to study transient phenomena on only a small part of the network. Reduced-order dynamic and power flow models are used when analysis involving thousands of nodes are required due to the computational demands when simulating large numbers of nodes. The level of complexity of the future EPG will dramatically increase due to large-scale deployment of variable renewable generation, active load and distributed generation resources, adaptive protection and control systems, and price-responsive demand. High-fidelity modeling of this future grid will require significant advances in coupled, multi-scale tools and their use on high performance computing (HPC) platforms. This LDRD report demonstrates SNL's capability to apply HPC resources to these 3 tasks: (1) High-fidelity, large-scale modeling of power system dynamics; (2) Statistical assessment of grid security via Monte-Carlo simulations of cyber attacks; and (3) Development of models to predict variability of solar resources at locations where little or no ground-based measurements are available.
Sequence-specific polymers are the basis of the most promising approaches to bottom-up programmed assembly of nanoscale materials. Examples include artificial peptides and nucleic acids. Another class is oligo(N-functional glycine)s, also known as peptoids, which permit greater sidegroup diversity and conformational control, and can be easier to synthesize and purify. We have developed a set of peptoids that can be used to make inorganic nanoparticles more compatible with biological sequence-specific polymers so that they can be incorporated into nucleic acid or other biologically based nanostructures. Peptoids offer degrees of modularity, versatility, and predictability that equal or exceed other sequence-specific polymers, allowing for rational design of oligomers for a specific purpose. This degree of control will be essential to the development of arbitrarily designed nanoscale structures.
In previous work, we developed a Bayesian-based methodology to analyze the reliability of hierarchical systems. The output of the procedure is a statistical distribution of the reliability, thus allowing many questions to be answered. The principal advantage of the approach is that along with an estimate of the reliability, we also can provide statements of confidence in the results. The model is quite general in that it allows general representations of all of the distributions involved, it incorporates prior knowledge into the models, it allows errors in the 'engineered' nodes of a system to be determined by the data, and leads to the ability to determine optimal testing strategies. In this report, we provide the preliminary steps necessary to extend this approach to systems with feedback. Feedback is an essential component of 'complexity' and provides interesting challenges in modeling the time-dependent action of a feedback loop. We provide a mechanism for doing this and analyze a simple case. We then consider some extensions to more interesting examples with local control affecting the entire system. Finally, a discussion of the status of the research is also included.
The annual program report provides detailed information about all aspects of the Sandia National Laboratories, California (SNL/CA) Hazardous Materials Management Program. It functions as supporting documentation to the SNL/CA Environmental Management System Program Manual. This program annual report describes the activities undertaken during the calender past year, and activities planned in future years to implement the Hazardous Materials Management Program, one of six programs that supports environmental management at SNL/CA.
Sandia National Laboratories (SNL), International Border Management Systems (IBMS) Program is working to establish a long-term border security strategy with United States Central Command (CENTCOM). Efforts are being made to synthesize border security capabilities and technologies maintained at the Laboratories, and coordinate with subject matter expertise from both the New Mexico and California offices. The vision for SNL is to provide science and technology support for international projects and engagements on border security.
Renewable energy is an important element in the US strategy for mitigating our dependence on non-domestic oil. Wind energy has emerged as a viable and commercially successful renewable energy source. This is the impetus for the 20% wind energy by 2030 initiative in the US. Furthermore, wind energy is important on to enable a global economy. This is the impetus for such rapid, recent growth. Wind turbine blades are a major structural element of a wind turbine blade. Wind turbine blades have near aerospace quality demands at commodity prices; often two orders of magnitude less cost than a comparable aerospace structure. Blade failures are currently as the second most critical concern for wind turbine reliability. Early blade failures typically occur at manufacturing defects. There is a need to understand how to quantify, disposition, and mitigate manufacturing defects to protect the current wind turbine fleet, and for the future. This report is an overview of the needs, approaches, and strategies for addressing the effect of defects in wind turbine blades. The overall goal is to provide the wind turbine industry with a hierarchical procedure for addressing blade manufacturing defects relative to wind turbine reliability.
The lateral footprint of a cosmic-ray soil moisture probe was determined using diffusion theory and neutron transport simulations. The footprint is radial and can be described by a single parameter, an e-folding length that is closely related to the slowing down length in air. In our work the slowing down length is defined as the crow-flight distance traveled by a neutron from nuclear emission as a fast neutron to detection at a lower energy threshold defined by the detector. Here the footprint is defined as the area encompassed by two e-fold distances, i.e. the area from which 86% of the recorded neutrons originate. The slowing down length is approximately 150 m at sea level for neutrons detected over a wide range of energies - from 10{sup 0} to 10{sup 5} eV. Both theory and simulations indicate that the slowing down length is inversely proportional to air density and linearly proportional to the height of the sensor above the ground for heights up to 100 m. Simulations suggest that the radius of influence for neutrons >1 eV is only slightly influenced by soil moisture content, and depends weakly on the energy sensitivity of the neutron detector. Good agreement between the theoretical slowing down length in air and the simulated slowing down length near the air/ground interface support the conclusion that the footprint is determined mainly by the neutron scattering properties of air.
Production of renewable biofuels to displace fossil fuels currently consumed in the transportation sector is a pressing multiagency national priority (DOE/USDA/EERE). Currently, nearly all fuel ethanol is produced from corn-derived starch. Dedicated 'energy crops' and agricultural waste are preferred long-term solutions for renewable, cheap, and globally available biofuels as they avoid some of the market pressures and secondary greenhouse gas emission challenges currently facing corn ethanol. These sources of lignocellulosic biomass are converted to fermentable sugars using a variety of chemical and thermochemical pretreatments, which disrupt cellulose and lignin cross-links, allowing exogenously added recombinant microbial enzymes to more efficiently hydrolyze the cellulose for 'deconstruction' into glucose. This process is plagued with inefficiencies, primarily due to the recalcitrance of cellulosic biomass, mass transfer issues during deconstruction, and low activity of recombinant deconstruction enzymes. Costs are also high due to the requirement for enzymes and reagents, and energy-intensive cumbersome pretreatment steps. One potential solution to these problems is found in synthetic biology-engineered plants that self-produce a suite of cellulase enzymes. Deconstruction can then be integrated into a one-step process, thereby increasing efficiency (cellulose-cellulase mass-transfer rates) and reducing costs. The unique aspects of our approach are the rationally engineered enzymes which become Trojan horses during pretreatment conditions. During this study we rationally engineered Cazy enzymes and then integrated them into plant cells by multiple transformation techniques. The regenerated plants were assayed for first expression of these messages and then for the resulting proteins. The plants were then subjected to consolidated bioprocessing and characterized in detail. Our results and possible implications of this work on developing dedicated energy crops and their advantage in a consolidated bioprocessing system.