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At least 811 records · Page 45

SUMMIT v2.1 Summary Report

Standard Unified Modeling Mapping and Integration Toolkit (SUMMIT) is a software capability developed by Sandia National Laboratories (SNL) under the direction and funding of the Department of Homeland Security (DHS), Science and Technology Directorate (S&T). SUMMIT is a scalable platform technology for linking together “best-in-class” models, data, and simulation tools to enable analysts, emergency planners and incident managers to more effectively, economically, and rapidly prepare, analyze, train, and respond to real or potential incidents. The SUMMIT software architecture was created under the Integrated Modeling, Mapping, and Simulation (IMMS) Project and was motivated by the issuance of Homeland Security Presidential Directive 8 (HSPD-8) which called for continuous improvement of our Nation’s preparedness to respond to catastrophic events. Furthermore, a state-of-the-art training and exercise facility called the National Exercise Simulation Center (NESC) was established within the Federal Emergency Management Agency (FEMA) headquarters.

97 MATHEMATICS AND COMPUTING↗

Benchmarking Anticipated Wind Project Lifetimes: Results from a Survey of U.S. Wind Industry Professionals

This paper draws on a survey of wind industry professionals to clarify trends in the expected useful life of land-based wind power plants in the United States. The expected useful life of a project affects expectations about its profitability, the timing of possible decommissioning or repowering, and its levelized costs. We find that most wind project developers, sponsors and long-term owners have increased project-life assumptions over time, from a typical term of ~20 years in the early 2000s to ~25 years by the mid-2010s and ~30 years more recently. Current assumptions range from 25 to 40 years, with an average of 29.6 years. The estimated average levelized cost of energy (LCOE) for new wind projects built in 2018 is $\$ $40.4/MWh (real 2018$\$ $), assuming a 20-year project life. With a 25-year useful life and no change in assumed operations and maintenance (O&M) expenditures or wind plant performance over time, LCOE declines by 10%, to $\$ $36.2/MWh, because capital costs are recovered over five additional years of production. At the now-common 30-year assumed life, levelized costs decrease another 7%, to $\$ $33.5/MWh (under the same unaltered assumptions about O&M and performance). Even longer assumed lifetimes lead to further (but diminishing) LCOE reductions—e.g., to $\$ $31.7/MWh and $\$ $30.3/MWh for 35- and 40-year lives, respectively. The data and trends presented here may inform assumptions used by electric system planners, modelers and analysts. The results may also provide useful benchmarks to the wind industry, helping developers and assets owners to compare their expectations with those of their peers.

17 WIND ENERGY↗

2019 Annual Technology Baseline [Slides]

Consistent cost and performance data for various electricity generation technologies can be difficult to find and may change frequently for certain technologies. With the Annual Technology Baseline (ATB), the National Renewable Energy Laboratory annually provides an organized and centralized set of such cost and performance data. The ATB uses the best information from the Department of Energy national laboratories' renewable energy analysts as well as information from the Energy Information Administration for fuel-based technologies. The ATB has been reviewed by experts and it includes the following electricity generation technologies: land-based wind, offshore wind, utility-scale solar photovoltaics (PV), commercial-scale solar PV, residential-scale solar PV, concentrating solar power, geothermal power, hydropower, utility-scale battery storage, coal, natural gas, nuclear, and conventional biopower. This webinar presentation introduces the 2019 ATB.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Quantum Computing and Cryptography: Analysis, Risks, and Recommendations for Decisionmakers

Some influential American policymakers, scholars, and analysts are extremely concerned with the effects that quantum computing will have on national security. Similar to the way space technology was viewed in the context of the US-Soviet rivalry in the Cold War, they view scientific advancement in quantum computing as a race with significant national security consequences and a part of the emerging US-China rivalry. It is claimed that the winner of this race will be able to thwart all the cryptographic efforts of the loser and gain unfettered access to any state secret of the losing government. Additionally, it is suggested that the winner will be able to protect their secrets with a higher level of security than contemporary cryptography guarantees at the moment. This paper argues that these three claims are considerably overstated, and that policymakers and scholars should shift focus to a different national security problem that quantum computing will create. Maintaining the long-term security of secret information secured by contemporary cryptographic protections, which will fail against an attack by a future quantum computer, is the predominant challenge needing attention. This paper takes a technically-informed approach to this issue. It first lays out the national security problems that are envisioned in much of the current discourse surrounding quantum computing. Then, it will assess the technical advantages that quantum computers will have over classical computers in the field of cryptography. Next, it will provide an explanation of the specific ways that the technical realities of quantum computing are inconsistent with the predominant areas of concern. Following, it will highlight the more pressing national security problem posed by quantum computing that the public discussion has, for the most part, missed. The piece will conclude with recommendations for how to mitigate this issue.

97 MATHEMATICS AND COMPUTING↗

Sensitivity and Uncertainty Workflow of Full System SIERRA Models Supporting High Consequence Applications

Credibility of end-to-end CompSim (Computational Simulation) models and their agile execution requires an expressive framework to describe, communicate and execute complex computational tool chains representing the model. All stakeholders from system engineering and customers through model developers and V&V partners need views and functionalities of the workflow representing the model in a manner that is natural to their discipline. In the milestone and in this report we define workflow as a network of computation simulation activities executed autonomously on a distributed set of computational platforms. The FY19 ASC L2 Milestone (6802) for the Integrated Workflow (IWF) project was designed to integrate and improve existing capabilities or develop new functionalities to provide a wide range of stakeholders a coherent and intuitive platform capable of defining and executing CompSim modeling from analysis workflow definition to complex ensemble calculations. The main goal of the milestone was to advance the integrated workflow capabilities to support the weapon system analysts with a production deployment in FY20. Ensemble calculations supporting program decisions include sensitivity analysis, optimization and uncertainty quantification. The goal of the L2 milestone aligned with the ultimate goal of the IWF project is to foster cultural and technical shift toward and integrated CompSim capability based on automated workflows. Specific deliverables were defined in five broad categories: 1) Infrastructure, including development of distributed-computing workflow capability, 2) integration of Dakota (Sandia's sensitivity, optimization and UQ engine) with SAW (Sandia Analysis Workbench), 3) ARG (Automatic Report Generator introspecting analysis artifacts and generating human-readable extensible and archivable reports), 4) Libraries and Repositories aiding capability reuse, and 5) Exemplars to support training, capturing best practices and stress testing of the platform. A set of exemplars was defined to represent typical weapon system qualification CompSim projects. Analyzing the required capabilities and using the findings to plan implementation of required capabilities ensured optimal allocation of development resources focused on production deployment after the L2 is completed. It was recognized early that the end-to-end modeling applications pose a considerable number of diverse risks, and a formal risk tracking process was implemented. The project leveraged products, capabilities and development tasks of IWF partners. SAW, Dakota, Cubit, Sierra, Slycat, and NGA (NexGen Analytics, a small business) contributed to the integrated platform developed during this milestone effort. New products delivered include: a) NGW (Next Generation Workflow) for robust workflow definition and execution, b) Dakota wizards, editor and results visualization, and c) the automatic report generator ARG. User engagement was initiated early in the development process eliciting concrete requirements and actionable feedback to assure that the integrated CompSim capability will have high user acceptance and impact. The current integrated capabilities have been demonstrated and are continually being tested by a set of exemplars ranging from training scenarios to computationally demanding uncertainty analyses. The integrated workflow platform has been deployed on both SRN (Sandia Restricted Network) and SCN (Sandia Classified Network). Computational platforms where the system has been demonstrated span from Windows (Creo the CAD platform chosen by Sandia) to Trinity HPC (Sierra and CTH solvers). Follow up work will focus on deployment at SNL and other sites in the nuclear enterprise (LLNL, KCNSC), training and consulting support to democratize the analysis agility, process health and knowledge management benefits the NGW platform provides.

97 MATHEMATICS AND COMPUTING↗

Artificial Intelligence, the Final Piece to the Counterforce Puzzle?

It is widely expected that artificial intelligence (AI) will disrupt and fundamentally transform many aspects of social, economic, and political life over the coming decades. As we are in the early stages of AI adoption in most fields, many discussions of its potential necessarily impact remain vague and superficial, including where national security is concerned. Nevertheless, some scholars have productively explored AI’s impact on the character of warfare, the balance of power among states, and human society itself. This article contributes to this growing body of literature by examining how this new technology might interact with one of the most prominent features of the post-World War II strategic environment: nuclear weapons. Specifically, it asks whether AI-driven improvements to intelligence, surveillance, and reconnaissance (ISR) capabilities, i.e., automated image recognition/computer vision, could enable an effective counterforce capability and thereby imperil nuclear deterrence and weaken first-strike stability. Since the advent of the nuclear age, analysts have been divided over the meaning of nuclear weapons for international politics. Proponents of the “nuclear revolution” argue that nuclear weapons, particularly a secure second-strike capability, which would allow a state to retaliate with nuclear force after suffering a first strike, satisfy a state’s security needs because they present a potential for unacceptable damage that would deter any potential challenger from even considering aggression. In their view, international politics in the shadow of nuclear weapons would be largely peaceful, competition would be relegated to the margins, and nuclear superiority would be meaningless. However, recent research suggests that this may not be the case. In fact, nuclear weapon states have sought to hold at risk the nuclear arsenals of their adversaries throughout the nuclear age. Still, no country has attacked another’s operational nuclear arsenal. That is because the requirements for a disarming strike are considerably higher than for damage limitation or retaliation against nuclear attack. A state trying to disarm its opponent would have to be certain to destroy, or at least disable, all of its adversary’s nuclear weapons. Even one operational nuclear warhead could inflict unacceptable damage in a retaliatory blow. The inability to be certain that a first strike could find and eliminate all enemy nuclear weapons has been the main roadblock for effective counterforce. As the number of battlefield sensors grows and ISR capabilities improve, however, this roadblock is crumbling. Some expect it to be fully overcome with the help of AI.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Sensitivity and Uncertainty Workflow of Full System SIERRA Models Supporting High Consequence Applications (Executive Summary)

The overall goal of this work was to advance the integrated workflow capabilities to provide the weapon system analysts the tools to construct, communicate and robustly execute end-to-end computational simulation models and analysis. Specifically, this includes developing and running automated, CompSim workflows that map model inputs to responses from large-scale studies executed on a distributed, heterogenous computing environment (e.g., CAD applications on Windows laptop to Sierra FEM codes on Trinity within a single workflow). The workflows developed enable ensemble calculations in support of ND program decisions, including sensitivity analysis, optimization and uncertainty quantification.

97 MATHEMATICS AND COMPUTING↗

Data Architecture for Security Monitoring (Project Summary)

The research has 2 thrusts: 1. new data architectures and tech-transfer-ready prototype tools that use write optimized data structures (WODS) to track real-world events, provide value to analysts, and support our cyber missions; and 2. algorithm research to address infinite streams of data, including expiration and sustainability.

97 MATHEMATICS AND COMPUTING↗

NREL's Balance-of-System Cost Model for Land-Based Wind

NREL's Land-based Balance of System Systems Engineering (LandBOSSE) model is a tool for modeling the balance of system (BOS) costs of land-based wind plants. BOS costs currently account for approximately 30% of the capital expenditures needed to install a land-based wind plant and include all costs associated with installing a wind plant, such as permitting, labor, material, and equipment costs associated with site preparation, foundation construction, electrical infrastructure, and tower installation. NREL developed LandBOSSE after identifying a need for a hybrid of process-based and empirically derived model that can provide flexibility for assessing wind plant BOS costs at a system level. NREL's prior BOS models have relied on empirical fits of legacy industry data, which limit their predictive ability. LandBOSSE, however, was designed to help users explore tradeoffs between innovative design scenarios while balancing the level of detail and speed required for model execution. The model was developed using a hybrid of process-based and empirically derived methods to create a modular model design that will allow for updates as wind energy technology evolves. The goal of LandBOSSE is to allow researchers, analysts, wind power developers, government agencies, and the public to explore how BOS may vary for different wind plant designs.

17 WIND ENERGY↗

Arms Control Opportunities for Inherently Safe and Secure Nuclear Command, Control, and Communications

The Department of Defense Science Board has stated that the United States is "not prepared to defend againsr cyber-attacks and that the military could lose "trust in the information and ability to control U.S. systems and forces [including nuclear forces]." One potential weak spot in cyber-security is storing encryption keys in computer memory. This paper explores the use of hardware devices (so-called Physical Unclonable Functions, or PUFs) to generate, in the nuclear weapon itself, unique encryption keys each time they are needed. Not only do we find that this has the potential to mitigate a number of cyberthreats, but such hardware has the potential to greatly diminish the total uncertainty associated with radiation-based warhead authentication procedures; a procedure many analysts feel will be key to future arms control regimes. After outline the use of PUFs in nuclear command, control, and communications--and indicating some of the areas that still require further research--we discuss their application to arms control and warhead authentication

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

SIERRA Code Coupling Module: Arpeggio User Manual (V.4.54)

The SNL Sierra Mechanics code suite is designed to enable simulation of complex multiphysics scenarios. The code suite is composed of several specialized applications which can operate either in standalone mode or coupled with each other. Arpeggio is a supported utility that enables loose coupling of the various Sierra Mechanics applications by providing access to Framework services that facilitate the coupling. More importantly Arpeggio orchestrates the execution of applications that participate in the coupling. This document describes the various components of Arpeggio and their operability. The intent of the document is to provide a fast path for analysts interested in coupled applications via simple examples of its usage.

42 ENGINEERING↗

Addendum to the REBUS Users Guide: REBUS-PC (V.1.5)

The Department of Energy (DOE) National Nuclear Security Administration (NNSA) Material Management and Minimization (M3) Reactor Conversion Program uses the REBUS-PC computer code to provide reactor physics and core design information such as neutron flux distributions in space, energy, and time, and to track isotopic changes in fuel and neutron absorbers with burnup. REBUS-PC has evolved from the original REBUS code, which was created starting in the 1960’s to study large liquid metal cooled fast reactors. In particular, additional outputs were added to improve user convenience and some inputs were modified to improve the functionality of the software. REBUS and REBUS-PC both model the external cycle, and are very general codes with 1D, 2D, and 3D neutronics capabilities, and with complete fuel shuffling capabilities. REBUS remains an extremely efficient reactor analysis tool for use in fast reactor systems, and so development has continued at Argonne National Laboratory (ANL) to this day for non-thermal reactor applications. While retaining the efficient computational engine of REBUS, REBUS-PC has evolved to its present status with continuous development since 1999. REBUS-PC has numerous changes and enhancements directed toward the needs of the thermal reactor analyst using Windows or Linux-based computational platforms.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Facility Informatics with GeoVisipedia (Final Report)

Characterization and understanding of nuclear fuel cycle facilities is of considerable interest to DNN R&D and the nonproliferation community due to their importance in nuclear weapons manufacture. Satellite imagery is a key source of information about these facilities, particularly in denied areas. Such imagery can be useful in its own right but annotations applied to the imagery vastly expand the value of the imagery and its usefulness by providing object descriptions, context and potentially linkages to other relevant information. GeoVisipedia (Geospatial Visual Wikipedia) is a new and novel approach to collecting, organizing, sharing and preserving knowledge about nuclear facilities to support nonproliferation efforts. Our approach is unique in that it emphasizes geospatial visual information about nuclear facilities rather than focusing exclusively on textual information. GeoVisipedia users, such as all-source analysts and decision makers, have access to richly annotated nuclear facility imagery with hyperlinks to visual and textual information that provides users with details and context about the facility. A major accomplishment of this project was to develop technology that allows annotations from one satellite image of a facility to be propagated to other satellite imagery of the facility. New satellite imagery of the facility is automatically populated with all previous annotations of the facility. This technology breakthrough provides users with the annotations, and hence knowledge and insight, from all the Subject Matter Experts (SMEs) who have previously annotated imagery of the facility. This capability was demonstrated in a GeoVisipedia prototype, awarded a patent and is described in several publications. In the latter part of the project an informal collaboration was established with the DNN R&D Multi Informatics for Nuclear Operations Scenarios (MINOS) venture. A second prototype of GeoVisipedia was developed that directly supports the MINOS venture. This prototype is called the Nuclear Facility Information Explorer (NFIX) and is tailored to the High Flux Isotope Reactor (HFIR) facility, a testbed for the MINOS venture. NFIX downloads sensor metadata and operator logs, parses and displays this information. NFIX has been licensed and deployed to several laboratories participating in the MINOS venture.

97 MATHEMATICS AND COMPUTING↗

Enabling coordinated, distributed development of scientific software: A research agenda for adapting a team of teams approach

The “team of teams” concept is a strategy for coordinating activities within and across organizations, developed by General Stanley McChrystal and his colleagues based on their experiences leading the Joint Special Operations Task Force in Iraq from 2003-2008. These experiences, and the lessons learned from them, are recounted in the books Team of Teams (McChrystal 2015) and One Mission (Fussell 2017) (the authors and contributors to these books will hereafter be jointly referred to as McChrystal et al.). Essentially, their story is one of rapidly adapting a rigid, siloed organization to defeat the flexible, resilient, and fast-moving network of Al Qaeda in Iraq. As described in the books, when McChrystal took over the Task Force, he found a collection of highly competent, efficient teams of analysts and warfighters which nonetheless had difficulty operating in a unified manner due to close internal ties, distrust of outsiders, bureaucratic stove pipes, and cultural differences stemming from the diverse organizations Task Force teams were affiliated with, including Army Special Forces, CIA, and NSA.

97 MATHEMATICS AND COMPUTING↗

RETRO RX

RETRO Rx is an R&D 100 Gold Award-winning suite of tools that provides a new class of analytics in the space between traditional epidemiological models and unanalyzed spreadsheets of data. Unlike traditional models, these tools provide analysts, scientists, practitioners, and decision makers a way to easily and effectively do sophisticated analyses using a simple user interface. AIDO guides users at the early stages of a disease outbreak by comparing the current parameters to historic outbreaks. RED Alert constructs a broad historical picture of disease incidence (recent outbreak included) to detect disease reemergence at its earliest stages, locally and globally. RETRO Rx compiles data and presents analysis in a clear, concise visual format to support disease mitigation and prevention planning. Both are available currently as web-based apps. A prototype of the RED Alert mobile app with enhanced functionality is available for beta testing and AIDO mobile app development is planned.

59 BASIC BIOLOGICAL SCIENCES↗

Efficient Binary Static Code Data Flow Analysis Using Unsupervised Learning

The ever increasing need to ensure that code is reliably, efficiently and safely constructed has fueled the evolution of popular static binary code analysis tools. In identifying potential coding flaws in binaries, tools such as IDA Pro are used to disassemble the binaries into an opcode/assembly language format in support of manual static code analysis. Because of the highly manual and resource intensive nature involved with analyzing large binaries, the probability of overlooking potential coding irregularities and inefficiencies is quite high. In this paper, a light-weight data, unsupervised data flow methodology is described which uses highly-correlated data flow graph (CDFGs) to identify coding irregularities such that analysis time and required computing resources are minimized. Such analysis accuracy and efficiency gains are achieved by using a combination of graph analysis and unsupervised machine learning techniques which allows an analyst to focus on the most statistically significant flow patterns while performing binary static code analysis.

97 MATHEMATICS AND COMPUTING↗

Demand Driven Cycamore Archetypes

Future nuclear fuel cycle options may present advantages over today’s once-through fuel cycle. Nuclear fuel cycle simulation tools assess the performance of those fuel cycles as well as the dynamics of long-term technology transitions. In many nuclear fuel cycle simulation tools, it has historically been the responsibility of the user to manually define facility deployment schemes and all facility parameters. While this is straightforward in simple fuel cycles, transitions from one fuel cycle to another can be more complex. In particular, deployment schemes for supportive fuel cycle facilities beyond the reactor become complex if the analyst desires to avoid gaps in the nuclear fuel and power supply chain during those transition scenarios. As nuclear fuel cycle analysis approaches questions regarding the feasibility and performance of the deployment schemes and technology choices during technology transition, automation of this historically manual process is necessary. The main objective of this work was to develop and demonstrate Cyclus automation capabilities toward key nuclear fuel cycle transition scenarios. While deploying reactors to meet power demand is trivial, and existed in the earliest versions of CYCLUS, automated, predictive deployment and decommissioning of other facilities is more complex. These include mining, milling, enrichment, fuel fabrication, reprocessing, and others. For example, a balanced closed fuel cycle may require ensuring that there is enough fast reactor fuel for their operation and may drive deployment of a fleet of light water reactors. This concern comprises the main challenge that drove the project effort. The Demand-Driven Cycamore Archetype project (NEUP-FY16-10512) aimed to develop CYCAMORE demand-driven deployment capabilities and thereby automate transition scenario definition. The developed software package, d3ploy, in the form of a CYCLUS Institution agent, deploys Facilities to meet the front-end and back-end demands of the fuel cycle. The University of South Carolina and the University of Illinois applied multiple algorithmic approaches to this challenge. This project developed an in situ demand-driven development schedule calculation through non-optimizing, deterministic-optimizing, and stochastic-optimizing algorithms as CYCLUS archetypes and demonstrated these new archetypes in program-supporting fuel cycle transition scenarios. Both objectives were achieved. This report documents the results and deliverables obtained toward these achievements in detail.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Adaptive Self-Tuning of Signal Detection Parameters

The quality of automatic detections from sensor networks depends on a large number of data processing parameters that interact in complex ways. The largely manual process of identifying effective parameters is painstaking and does not guarantee that the resulting controls are the optimal configuration settings, yet achieving superior automatic detection of events is closely related to these parameters. We present an automated sensor tuning (AST) system that tunes effective parameter settings for each sensor detector to the current state of the environment by leveraging cooperation within a neighborhood of sensors. After a stabilization period, the AST algorithm can adapt in near real-time to changing conditions and automatically self-tune a signal detector to identify (detect) only signals from events of interest. The overall goal is to reduce the number of missed legitimate event detections and the number of false event detections. Our current work focuses on reducing false signal detections early in the seismic signal processing pipeline, which leads to fewer false events and has a significant impact on reducing analyst time and effort. Applicable both for existing sensor performance boosting and new sensor deployment, this system provides an important new method to automatically tune complex remote sensing systems. Systems tuned in this way will achieve better performance than is currently possible by manual tuning, and with much less time and effort devoted to the tuning process. With ground truth on detections from a seismic sensor network monitoring the Mount Erebus Volcano in Antarctica, we show that AST increases the probability of detection while decreasing false alarms.

58 GEOSCIENCES↗