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At least 271 records · Page 15

Computational analysis of deployable wind turbine systems in defense operational energy applications.

The U.S. military has been exploring pathways to reduce the logistical burden of fuel on virtually all their missions globally. Energy harvesting of local resources such as wind and solar can help increase the resilience and operational effectiveness of military units, especially at the most forward operating bases where the fuel logistics are most challenging. This report considers the potential benefits of wind energy provided by deployable wind turbines as measured by a reduction in fuel consumption and supply convoys to a hypothetical network of Army Infantry Brigade Combat Team bases. Two modeling and simulation tools are used to represent the bases and their operations and quantify the impacts of system design variables that include wind turbine technologies, battery storage, number of turbines, and wind resource quality. The System of Systems Analysis Toolkit Joint Operational Energy Model serves as a baseline scenario for comparison. The Hybrid Optimization of Multiple Energy Resources simulation tool is used to optimize a single base within the larger Joint Operational Energy Model. The results of both tools show that wind turbines can provide significant benefits to contingency bases in terms of reduced fuel use and number of convoy trips to resupply the base. The match between the turbine design and wind resource, which is statistically low across most of the global land area, is a critical design consideration. The addition of battery storage can enhance the benefits of wind turbines, especially in systems with more wind turbines and higher wind resources. Wind turbines may also provide additional benefits to other metrics such as resilience that may be important but not fully considered in the current analysis. ACKNOWLEDGEMENTS The authors would like to thank the following individuals for their helpful support, feedback and review to improve this report: U.S. Department of Energy Wind Energy Technologies Office, Patrick Gilman and Bret Barker; Idaho National Laboratory, Jake Gentle and Bradley Whipple; The National Renewable Energy Laboratory, Robert Preus and Tony Jimenez; Sandia National Laboratories, Alan Nanco, Dennis Anderson, and Hai Le. In addition, numerous discussions with military and industry stakeholders over the year were invaluable in focusing the efforts represented in this report.

17 WIND ENERGY↗

HEMP Transformer Defense Through Power Electronics

High altitude electromagnetic pulses and geo-magnetic disturbances have the potential to severely impact the electric power grid by damaging large power transformers and causing severe power quality issues. This impact comes as a result of a quasi-static bias induced on transmission lines by geomagnetically induced currents which saturate magnetic components in the electric power system. This paper introduces the concept of utilizing a h-bridge inverter on the neutral of a LPT to inject a DC bias equivalent voltage onto the neutral side of the transformer windings. This biasing floats the transformer windings, eliminating the effect of the DC current and keeping the transformer from saturating. Schematic diagrams will be presented, along with simulation model data using Typhoon and PLECS, and finally test results from a benchtop hardware test.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Shape Optimization for Control and Isolation of Structural Vibrations in Aerospace and Defense Applications

Among the main challenges in shape optimization is the coupling of Finite Element Method (FEM) codes in a way that facilitates efficient computation of shape derivatives. This is particularly difficult with multi-physics problems involving legacy codes, where the costs of implementing and maintaining shape derivative capabilities are prohibitive. There are two mathematically equivalent approaches to computing the shape derivative: the volume method, and the boundary method. Each has a major drawback: the boundary method is less accurate, while the volume method is more invasive to the FEM code. Prior implementations of shape derivatives at Sandia have been based on the volume method. We introduce the strip method, which computes shape derivatives on a strip adjacent to the boundary. The strip method makes code coupling simple. Like the boundary method, it queries the state and adjoint solutions at quadrature nodes, but requires no knowledge of the FEM code implementations. At the same time, it exhibits the higher accuracy of the volume method. The development of the strip method also offers us the opportunity to share some lessons learned about implementing the volume method and boundary method, to show shape optimization results on problems of interest, and to begin addressing the other main challenges at hand: constraints on optimized shapes, and their interplay with optimization algorithms.

97 MATHEMATICS AND COMPUTING↗

Human Performance Improvement Task Group Task 21-1 Best Practice: Using virtual capabilities or options for HPI application (to reduce errors, strengthening defenses, strengthening the organization, and/or increasing capacity)

In 2020 the world was impacted by COVID-19. How work is done was dramatically changed for a large portion of the workforce. Many have made the abrupt shift to working from their home while others have adapted to COVID protocols (such as social distancing and wearing facemasks). Fundamentally, Human and Organizational Performance Improvement concepts and science did not change – only the delivery method changed (in some cases). The primary effect has been to accelerate dynamics already present in society – from e-commerce to online education to remote healthcare. Change is never easy for humans. However, remote work should be viewed as an opportunity; not a fix to a problem. In this Best Practice paper, you’ll get practical suggestions to help you reduce errors and improve Human Performance in remote, socially-distanced “work-from-home” environments.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Antifoam Development for Eliminating Flammability Hazards and Decreasing Cycle Time in the Defense Waste Processing Facility

Foam, due to the high gas generation rates of boiling and chemical reaction offgasing, requires control measures to prevent the foam from contaminating the condensate and to facilitate efficient plant operation. Antifoam was utilized to minimize foam production during chemical processing in the DWPF and during High-Level Waste (HLW) evaporation at SRS and Hanford. However, the current antifoam used in the SRS DWPF increases flammability risk during chemical processing (generates three flammable degradation products) and while feeding the melter (can decompose to CO/hydrogen). It is also the likely source of methyl functional groups for the organo-mercury present in the tank farm and excessive mercury in Saltstone. Additionally, the planned startup of Salt Waste Processing Facility (SWPF), with much higher throughput, will challenge DWPF to process at higher gas generation rates. DWPF employs Antifoam 747, a superspreader produced by Momentive Performance Materials, as an antifoaming agent during waste processing. During DWPF chemical processing, antifoam must be effective up to boiling (i.e., up to 103°C) and between a pH of 3-13. Antifoam 747 is most effective at a pH range of 6-8 and degrades as pH deviates. In addition, SRNL identified three flammable antifoam degradation products using mass spectrometer (MS) and fourier transform infrared (FTIR) offgas analyzers during simulations. A new antifoam or a new method to control foam is needed to minimize DWPF processing time and reduce the risk of contamination. In addition, testing should be completed to ensure that other antifoams used in HLW processing do not have similar flammability hazards or cause unintended impacts in downstream processing.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

FLC Award: QED: Quantum Ensured Defense of the Smart Electric Grid

A reliable electric power supply is crucial for modern day life as well as national security, economic productivity, and life-and-death essentials. During the COVID pandemic, internet and cell communications became a “must-have” for government and business operations, education, and communicating COVID testing for vaccine information. Loss of electric power quickly leads to human health and national security emergencies. When a major winter storm hit Texas in mid-February 2021, the system was overwhelmed and over 4M people lost power. Although this crisis arose from an unprecedented weather event - not a cyberattack - it serves as a vivid illustration of the impact power disruption can have on our American way of life. The recent cyberattack on the Colonial Oil Pipeline also provides a stark reminder that infrastructure supporting our daily lives has vulnerabilities.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Deployable Wind-Hybrid Power Systems for Defense and Disaster Response Applications

This report presents an analysis of the performance of deployable energy systems comprised of wind energy systems integrated with diesel generators, photovoltaic systems, and battery storage to meet the load requirements of a representative U.S. Army forward operating base. The analysis is conducted using HOMER, a microgrid analysis software that can search through a wide range of parameters to design and optimize microgrid power systems. The search parameters include the system architecture, the wind and solar resources, and the availability of diesel fuel. The results of the analysis measure the relative performance of the different systems and environments in terms of the overall transportation cost to deploy the system and the ability to provide resilience in terms of meeting mission critical loads.

02 PETROLEUM↗

Model Driven Deception for Defense of Operational Technology Environments

Due to the strong integration of real-world physics, OT deception platforms must operate differently than traditional IT deceptions. For instance, turning off a valve will be detected downstream by other sensors because the flow will reduce and stop. Additionally, controllers and applications leverage data from sensors to send control commands to each other. A believable deception must be integrated with the system to project the effects of events. An attack will likely attempt to control the physical process in a negative manner. To make the attacker believe they are achieving their objective, it must predict the effects of these actions, to a reasonable degree. Our approach to simulating a model to generate realistic decoy behavior is explored including description of two approaches: a physics model-based approach and a data driven approach. The performance of two machine learning techniques are investigated in their ability to learn a good enough model of the physics of the system.

97 MATHEMATICS AND COMPUTING↗