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Idaho National Laboratory, in collaboration with Invensys, performed a laboratory assessment on Invensys Foxboro Control Software. During this assessment, vulnerabilities were discovered, evaluated, and mitigation strategies developed.
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This software improves upon the Clifford gate+T gate magic state strong simulation algorithm by Brayvi and Gosset. It provides a better stabilizer state decomposition that scales as 2^{0.463t}, an improvement over 2^{0.468t}, for t T gate magic states. This code enables simulations of universal quantum computing with that asymptotic scaling cost. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525 SAND2020-14293 O
LLNL's Computational Nuclear Data and Theory Group have created a 2009.3 revised release of the Evaluated Nuclear Data Library (ENDL2009.3). This library is designed to support LLNL's current and future nuclear data needs and will be employed in nuclear reactor, nuclear security and stockpile stewardship simulations with ASC codes. The ENDL2009 database was the most complete nuclear database for Monte Carlo and deterministic transport of neutrons and charged particles. It was assembled with strong support from the ASC PEM and Attribution programs, leveraged with support from Campaign 4 and the DOE/Office of Science's US Nuclear Data Program. This document lists the revisions and fixes made in a new release called ENDL2009.3, by com- paring with the existing data in the previous release ENDL2009.2. These changes are made in conjunction with the revisions for ENDL2011.3, so that both the .3 releases are as free as possible of known defects.
Advanced manufacturing and engineering are fundamental to the economic strength and national security of the United States. With the introduction of advanced modeling and simulation practices in manufacturing and engineering over the last several decades, we are producing better products, more quickly, and at decreased cost. Through the adoption of high-performance computing (HPC) enabled workflows, in small- to medium-sized manufacturers and engineering firms, which employ fewer than 500 people, is renewing United States manufacturing and engineering. Despite successes, there are significant barriers to widespread adoption of these tools. Our Phase I SBIR project, Next-Generation Analysis and Visualization Platform for Manufacturing and Engineering Workflows, aims to address several of these barriers. Our project helped us evaluate the feasibility and benefits and mitigate risks of asynchronous processing for analysis and visualization workflows. We evaluated the impact of asynchronous, non-blocking communication can have on the user experience in a complex visualization application. Besides the impact on users, we wanted to understand the impacts on developers (development application programming interfaces (APIs))and generated applications (robustness and stability). Any asynchronous platform implementation is bound to rely on multiple threads which can make the programming model extraordinarily complex and prone to bugs. If not managed carefully, the complexity and resulting instability would be an unacceptable evolution for widely used production tools like ParaView and putting the success of the Phase II project at risk.
There are a number of current needs in the development of the Pu and Am separations that underpin larger interest areas including nuclear waste issues, nuclear weapons, nuclear forensics, nuclear fuels and similarly related fields. In the large areas of interest, there are a number of sub-fields that include corrosion chemistry, pyrochemistry, solution-phase chemistry, rapid separations, environmental speciation, and other similar efforts. However, in all of the these fields it is important to realize that the underlying chemistry that underpins these efforts is similar in that Pu and Am are bound to ligands that can be in the solid, aqueous, or gas phase and separations occurs due to the preferential binding of the ligand to Pu or Am based on a number of factors that include pH, concentration, oxidation state, etc. In the past, most of the Pu and Am chemistry has occurred in limited scope within universities where micro-scale and bench-top scale chemistry are the dominate investigative theme. At US national laboratory and their international counterparts, larger scale reactions have been attempted such that industrial scale chemistry has been completed. Some of this technology has been harnessed in radiopharmaceuticals and nuclear fuel reprocessing. However, such bench-top research is expensive to due to the safety and security that is concerned when dealing with Pu, and scale-up of reactions is even more resource intensive. In an effort to offset this expensive, it would be of interest to explore the ability to predict selectivity based on the computational modeling of actinide chemistry. This has historically been limited by the abilities of large supercomputers, but with the emphasis on developing exascale computers within the US and similar efforts by other countries this predictive modeling has potential to produce significant results that would yield improved understanding of actinide chemistry.
There is growing interest in the United States and abroad to increase the use of biomass as an energy source due to environmental and energy security benefits. In the United States, the biofuel and biopower industries are regulated by different policies and different agencies and have different drivers, which impact the maximum price the industries are willing to pay for biomass. This article describes a dynamic computer simulation model that analyzes future behavior of bioenergy feedstock markets based on varying policy and technical options. The model simulates the long-term dynamics of these markets by treating advanced biomass feedstocks as a commodity and projecting the total demand of each industry, as well as the market price over time. The model is used for an analysis of the United States bioenergy feedstock market that projects supply, demand, and market price given three independent buyers: domestic biopower, domestic biofuels, and foreign exports. With base-case assumptions, the biofuels industry is able to dominate the market and meet the federal Renewable Fuel Standard (RFS) targets for advanced biofuels. Further analyses suggest that United States bioenergy studies should include estimates of export demand for biomass in their projections, and that GHG-limiting policy would partially shield both industries from export dominance.
Modern Building Automation Systems (BASs), as the brain that enable the smartness of a smart building, often require increased connectivity both among system components as well as with outside entities, such as the cloud, to enable low-cost remote management, optimized automation via outsourced cloud analytics, and increased building-grid integrations. As smart buildings move towards open communication technologies, providing access to BASs through the building's intranet, or even remotely through the Internet, has become a common practice. However, increased connectivity and accessibility come with increased cyber security threats. BASs were historically developed as closed environments with limited cyber-security considerations. As a result, BASs in many buildings are vulnerable to cyber-attacks that may cause adverse consequences, such as occupant discomfort, excessive energy usage, and unexpected equipment downtime. Therefore, there is a strong need to advance the state-of-the-art in cyber-physical security for BASs and provide practical solutions for attack mitigation in buildings. However, an inclusive and systematic review of BAS vulnerabilities, potential cyber-attacks with impact assessment, detection & defense approaches, and cyber resilient control strategies is currently lacking in the literature. This review paper fills the gap by providing a comprehensive up-to-date review of cyber-physical security for BASs at three levels in commercial buildings: management level, automation level, and field level. The general BASs vulnerabilities and protocol-specific vulnerabilities for the four dominant BAS protocols (i.e., BACnet, KNX, LonWorks, and Modbus) are reviewed, followed by a discussion on four attack targets and seven potential attack scenarios. Furthermore, the impact of cyber-attacks on BASs is summarized as signal corruption, signal delaying, and signal blocking. The typical cyber-attack detection and defense approaches are identified at the three levels. Cyber resilient control strategies for BASs under attack are categorized into passive and active resilient control schemes. Open challenges and future opportunities are finally discussed.
Cyber-security challenges have the potential for becoming one of the defining issues of our time. Cyber-attacks have become an ever-increasing threat and the United States (US) Federal Bureau of Investigation (FBI) now ranks cyber-crime as one of its most important law enforcement activities. In addition to the general problems associated with cyber-crime, critical infrastructure (CI) related to energy production, manufacturing, water supply and other systems have come under attack. For example, drinking water utilities are increasingly incorporating computer technology into their routine operations and are therefore increasingly vulnerable to cyber- threats. Systems control and data acquisition (SCADA) systems used to manage automated physical processes essential to water treatment and distribution systems have become standard in medium to large drinking water utilities and in many small water systems. However, even with the application of standard information technology cybersecurity best practices these types of systems have proven to be vulnerable to cyber-attacks. In 2015, the US Department of Homeland Security (DHS) responded to 25 cybersecurity incidents in the Water Sector and to 46 incidents in the Energy Sector. Comparatively, between 2014 and 2015, the reported number of Water Sector incidents actually increased by 78.6% (from 14 to 25). The DHS is in a collaborative partnership with the US Environmental Protection Agency to ensure cybersecurity in the Water Sector. As a result of this partnership a number of guidance documents and techniques have been developed to counter cyber-attacks and minimize cyber vulnerability. These approaches are documented along with a summary of common vulnerabilities. However, a new approach which has great promise in protecting drinking water systems against hacking and cyber-attacks, based on the concept of unidirectional gateways, is presented and discussed.
Graph partitioning has emerged as an area of interest due to its use in various applications in computational research. One way to partition a graph is to solve for the eigenvectors of the corresponding graph Laplacian matrix. This project focuses on the eigensolver LOBPCG and the evaluation of a new preconditioner: Randomized Cholesky Factorization (rchol). This proconditioner was tested for its speed and accuracy against other well-known preconditioners for the method. After experiments were run on several known test matrices, rchol appears to be a better preconditioner for structured matrices. This research was sponsored by National Nuclear Security Administration Minority Serving Institutions Internship Program (NNSA-MSIIP) and completed at host facility Sandia National Laboratories. As such, after discussion of the research project itself, this report contains a brief reflection on experience gained as a result of participating in the NNSA-MSIIP.
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TestSNAP is a stand-alone prototype of the SNAP force kernel used in the LAMMPS molecular dynamics code. It contains synthetic input data (neighbor atom positions) and reference output data (forces on atoms) for several different SNAP models. The prototype performs the force calculation repeatedly, checking the results against the reference data. At the end it reports the grind time [msec/atomstep] and RMS force error [eV/A]. This allows performance experts to quickly test new hardware and software strategies, obtain a realistic performance estimate and verify that the computation was performed correctly. SAND2019-12243 M Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.
The project that developed this is unclassified, with the mandate to produce open source code. This code computes the hitting time moments of a graph using a linear algebra configuration. The goal of this work is to explore the performance capabilities of the Chapel programming language. Toward that end, we generate random adjacency matrices which represent a random graph. The code can also read in an adjacency matrix from a file. The main computation is the Conjugate Gradient method.SAND2020-12651 M. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.
The reports included in this report are for project activities that occurred from October 2011 through September 2012. These reports describe in detail the discoveries, achievements, and challenges encountered by our talented and enthusiastic principal investigators (PIs). Many of the reports describe R&D efforts that were “successful” in their pursuits and resulted in a positive outcome or technology realization. As we’ve stated before, and continue to stress, in some cases the result is a “negative” finding, for instance a technology is currently impractical or out of reach. This can often be viewed erroneously as a “failure,” but is actually a valid outcome in the pursuit of high-risk research, which often leads to unforeseen new paths of discovery. Either result advances our knowledge and increases our ability to identify solutions and/or likewise avoid costly paths not appropriate for the challenges presented. The SDRD program continues to provide an unfettered mechanism for innovation and development that returns multifold to the NNSS mission. Overall the program is a strong R&D innovation engine, benefited by an enhanced mission, committed resources, and sound competitiveness to yield maximum benefit. The 23 projects described exemplify the creativity and ability of a diverse scientific and engineering talent base. The efforts also showcase an impressive capability and resource that can be brought to find solutions to a broad array of technology needs and applications relevant to the NNSS mission and national security.
This fact sheet describes the Transportation Secure Data Center (TSDC) - an NREL-operated resource that provides secure access to detailed GPS travel data for valuable research purposes in a way that protects original participant privacy.
Nuclear power today accounts for approximately 20% of the electrical supply for the US. It provides reliable energy that helps to stabilize the national grid. In contrast to current nuclear power facilities, future concepts operate at higher temperatures, are operationally more efficient, more fully utilize the energy stored within the fuel, and reduce the amount of waste produced. Recent advances in chemistry and materials sciences provide an unprecedented opportunity to develop the critical systems—the fuel, coolant, and structural materials—needed for deployment of advanced nuclear reactor designs. To address the challenge of stringent demands on material systems as their properties and performance continuously evolve over the operational lifetime, the frameworks to uncover the underlying processes that cause reduced performance have been developed over the last decade. There is now the prospect of designing materials that report upon their own damage, are self-healing, and leverage what would be considered deleterious chemical processes to increase their performance within advanced reactor designs. Success will provide an energy source needed to secure a stable and safe energy supply for the nation. To identify the key research directions required to discover the chemical processes and material degradation mechanisms that result in loss of performance of the fuel, coolant, and structural materials, nearly 150 theoreticians, computational experts, and experimentalists from industry, national laboratories, academia, and federal agencies participated in a workshop held in August 2017. Based on the discussions held at the workshop, five Priority Research Directions (PRDs) were identified. These PRDs defined the key scientific challenges that must be met as well as the opportunities that can be exploited to achieve a multi-scale spatial and temporal understanding of fundamental processes that govern the properties and performance of the different material systems required for advanced reactors.
This document supports the application of Cyber-Informed Engineering (CIE) within the context of Enterprise Risk Management (ERM) to enhance cyber-resilience. It highlights that many critical infrastructure organizations use ERM to manage business risks and emphasizes the importance of evaluating critical systems and assets. The proposed approach can be adopted independently of formal ERM processes and offers a starting point for integrating CIE alongside existing or new ERM practices. Both CIE and ERM are iterative, and their alignment fosters continuous improvement and supports the engineering and operations cultures of an organization.