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At least 181 records · Page 10

Toward a Resilient Cybersecure Hydropower Fleet: Cybersecurity Landscape and Roadmap 2021

With this roadmap, Pacific Northwest National Laboratory (PNNL) hopes to assist the U.S. Department of Energy’s (DOE’s) Water Power Technologies Office (WPTO) in improving the cybersecurity of hydropower plants across the nation. This effort draws upon collected data from the dams sector, from industrial control system cybersecurity threat reports, from similar work focused on neighboring sectors, and from frank discussions with owners, operators, and vendors. While remaining tightly focused on the needs of hydropower projects, during this landscape study and development of the resulting roadmap, the research team sought to remain informed by the larger energy sector’s vision and direction so that the topics and milestones may fit within a larger vision common to the whole.

13 HYDRO ENERGY↗

Pacific Northwest National Laboratory Annual Site Environmental Report for Calendar Year 2022 (Final Report)

Pacific Northwest National Laboratory (PNNL), one of the U.S. Department of Energy (DOE) Office of Science’s 10 national laboratories, provides innovative science and technology development in the areas of energy and the environment, fundamental and computational science, and national security. There are three DOE offices within the Richland area. Two are responsible for the Hanford Site, whereas the Pacific Northwest Site Office (PNSO) oversees PNNL. PNNL prepares this Annual Site Environmental Report to meet the requirements of DOE Order 231.1B, Environmental, Safety and Health Reporting, and DOE Order 458.1, Radiation Protection of the Public and the Environment, assuring that the public is informed of any PNNL-Richland Campus or PNNL-Sequim Campus event that could adversely affect the health and safety of the public, site staff, or the environment. The report provides a synopsis of ongoing environmental management performance and compliance activities for operations that occur on the PNNL-Richland Campus in Richland, Washington, and at the PNNL-Sequim Campus near Sequim, Washington. It describes the location of and background for each facility; addresses compliance with applicable DOE, federal, state, and local regulations, and site-specific permits; documents environmental monitoring efforts and their status; presents potential radiation doses to staff and the public in the surrounding areas; and describes DOE-required data quality assurance methods used for data verification. The ASER summarizes site compliance with federal, state, and local environmental laws, regulations, policies, directives, permits, and Orders, and provides environmental management performance benchmarks and their status to the public, regulatory agencies, community officials, Native American tribes, and public interest groups.

54 ENVIRONMENTAL SCIENCES↗

Cybersecurity Considerations for the Liquified Natural Gas Sector

Due to the highly volatile nature of Liquified Natural Gas (LNG) and the systems required for generation and safe containment, it is likely a targeted cyber-attack on LNG control and safety systems will have a significant economic impact on energy supplies and prices. Moreover, if the interconnected operational technology (OT) devices within LNG systems are exploited to malfunction, the repair and recertification process will almost certainly be longer than for natural gas (NG) systems.

03 NATURAL GAS↗

Pacific Northwest National Laboratory Annual Site Environmental Report for Calendar Year 2023

Pacific Northwest National Laboratory (PNNL), one of the U.S. Department of Energy (DOE) Office of Science’s 10 national laboratories, provides innovative science and technology development in the areas of energy and the environment, fundamental and computational science, and national security. There are three DOE offices within the Richland area. Two are responsible for the Hanford Site, whereas the Pacific Northwest Site Office oversees PNNL. PNNL prepares an Annual Site Environmental Report to meet the requirements of DOE Order 231.1B, Environment, Safety and Health Reporting, and DOE Order 458.1, Radiation Protection of the Public and the Environment, thus assuring that the public is informed of any PNNL-Richland campus or PNNL-Sequim campus event that could adversely affect the health and safety of the public, site staff, or the environment. The report provides a synopsis of ongoing environmental management performance and compliance activities for operations that occur at the PNNL-Richland campus in Richland, Washington, and at the PNNL-Sequim campus near Sequim, Washington. It describes the location of and background for each facility; addresses compliance with applicable DOE, federal, state, and local regulations, and site-specific permits; documents environmental monitoring efforts and their status; presents potential radiation doses to staff and the public in the surrounding areas; and describes DOE-required data quality assurance methods used for data verification. The ASER report describes Compliance with Federal, State, and Local Laws and Regulations in 2023, Environmental Sustainability, Environmental monitoring and dose assessment, Natural and Cultural Resource Management, and Quality Assurance activities that took place during Calendar Year 2023.

40 CFR 61 Subpart H↗

Data Summarization and Inference at Scale

This is the final report for the DOE ASCR grant SC-0022260, Data Summarization and Inference at Scale, PI: Alex Pothen, Purdue University. The goal of the project was to solve data-intensive and compute-intensive problems in the physical sciences, engineering, information science, data science, etc. by designing and implementing new algorithms that could work with a subset of the data. The four subgoals were: (a) The solution of problems where the data is too large to be stored in the memory of a computer. In this streaming model of computation, the data arrives as a stream of elements to the computer, each element is processed as it arrives, and a decision is made to discard the data or to store it; only a small subset of the data proportional to the size of the output solution is stored, and when all the data has been streamed, a solution to the problem is computed from the stored subset. (b) The use of machine learning methods to compute solutions to data-intensive problems. The use of GPUs is critical to obtain high performance on machine learning tasks, but their memory sizes are smaller relative to that of CPUs. For large-scale problems, the data is sampled many times, and small samples are used with repetition, for robustness, to compute solutions to inference tasks. This sampling reduces the memory required to solve the problem, but attention is needed to avoid slow convergence to the solutions, and reduced accuracy of inference. We propose submodular optimization, Large Language Models, and physics-informed neural networks to enable GPU computations here. (c) Modeling and visualization of high-dimensional data using interpretable features. Clinical proteomic data sets from immunology for the detection of cancer and other diseases are temporal and high-dimensional, and algorithms for visualizing these data sets using clinically interpretable features are lacking. We propose methods that compute distances based on the optimal transportation problem and graph edit distances to address this problem. We also propose the use of optimal transport-based distances, spatial statistics, and network structure to classify image data sets, We apply these algorithms to electron micrographs of the peripheral nervous system in the digestive tract. (d) The design of data-intensive algorithms on emerging architectures, specifically, noisy, intermediate-scale quantum (NISQ) devices. Quantum computers offer the possibility of exploring large solution spaces due to the principle of superposition, but current quantum computers are limited by few qubits, short coherence times due to noise, poor interconections among the qubits, etc. We propose the use of the divide and conquer paradigm to solve large-scale problems, wherein collections of small subproblems are solved on the quantum devices, and the solutions to the subproblems are integrated into a solution for the original problem on a classical computer.

97 MATHEMATICS AND COMPUTING↗

Cooperative Education

Los Alamos National Laboratory (LANL) is a multidisciplinary national laboratory that conducts research and development in national security, engineering, materials science, computational modeling, and advanced manufacturing. The laboratory develops innovative technologies to address complex scientific and engineering challenges. This project focuses on the development and evaluation of high-performance absorbing structures through computational design, simulation, and engineering analysis. Absorbing structures are used in applications where damage mitigation, structural protection, and material efficiency are critical performance requirements. The increasing demand for lightweight, high-strength, and highly efficient structural systems has created a need for improved design methodologies capable of maximizing absorption while minimizing weight and material usage. The project utilizes advanced engineering software, including 3D CAD software and FEA, to generate and optimize structural concepts. Computational simulations are performed to evaluate structural behavior under loading conditions, while mathematical analyses are conducted using Python-based tools as well as established analytical equations from material and structural mechanics. The project benefits LANL by supporting the development of advanced design methodologies and improving the understanding of material and structural performance. During the internship term, a significant portion of the design development, simulation, and data analysis activities will be completed. Success of the project depends on collaboration among engineering mentors and technical staff members. Work will be conducted at Los Alamos National Laboratory using laboratory computing resources and engineering software.

42 ENGINEERING↗

Spinoff 2002: Fortieth Anniversary Technology Utilization Program

Since its inception 40 years ago, NASA's Technology Transfer Program has led the way for our nation to benefit from cutting-edge aerospace technologies. In addition to contributing to U.S. economic growth, these technologies are improving the quality of life on Earth while finding new ways to protect and preserve it. NASA's research and development efforts have advanced areas in medicine, communications, manufacturing, computer technology, and homeland security. These breakthroughs, translated into commercial products, are enhancing the lives of Americans everywhere. When a congressional mandate led NASA to develop the Scientific and Technical Information (STI) Program, the Agency began a wide dissemination of its research and development results. In doing so, NASA recognized that many of its technologies were transferable to industry for the development of commercial products. As a result, the Technology Utilization Program was born in 1962. The successful program went through several changes over the years, as its philosophy, mission, and goals adapted into the Technology Transfer Program we know today. The program strives to make the latest technologies available to industry as soon as they are developed. Each year, NASA's Spinoff publication showcases new products and services resulting from commercial partnerships between NASA and private industry. In the 2002 issue, the NASA field centers reflect upon the growth that has made these innovations available to the public. The Research and Development section examines past achievements, current successes, and future goals for each of the ten NASA centers. The Commercial Benefits section proudly highlights 51 new spinoff products, including a heart pump for patients needing a heart transplant, as well as an air purifier that destroys anthrax spores. The Technology Transfer and Outreach section describes the outreach achievements and educational successes made possible through the NASA Commercial Technology Network. Each section of Spinoff 2002 provides compelling evidence of the Technology Transfer Program's success and value. With commercial products and successes spanning from work on the Apollo missions to the International Space Station, the 40th anniversary of the Technology Transfer Program invites us to celebrate our history while planning the future.

Source record↗

Space Development Grid Portal

This viewgraph presentation provides information on the development of a portal to provide secure and distributed grid computing for Payload Operations Integrated Center and Mission Control Center ground services.

Vaziri, Arsi↗

NASA guidelines for assuring the adequacy and appropriateness of security safeguards in sensitive applications

The Office of Management and Budget (OMB) Circular A-71, transmittal Memorandum No. 1, requires that each agency establish a management control process to assure that appropriate administrative, physical and technical safeguards are incorporated into all new computer applications. In addition to security specifications, the management control process should assure that the safeguards are adequate for the application. The security activities that should be integral to the system development process are examined. The software quality assurance process to assure that adequate and appropriate controls are incorporated into sensitive applications is also examined. Security for software packages is also discussed.

Tompkins, F. G.↗

Adaptable Standards for Discovery, Access, and Usability of Oak Ridge National Laboratory’s Data Portals and Catalogs

Oak Ridge National Laboratory (ORNL) is leveraging its established capabilities and subject matter expertise in data curation, governance, management, national security, and risk assessment and mitigation to support the US Department of Energy (DOE) Grid Modernization Initiative. Using standards modeled by the National Institute of Standards and Technology (NIST), the Data Curation Network (DCN), the Oak Ridge Leadership Computing Facility (OLCF), and other leading organizations in the fields of energy research, high-performance computing, and national and homeland security, ORNL seeks to provide a federated approach to research data discovery, use, and interoperability.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

Representation-Independent Iteration of Sparse Data Arrays

An approach is defined that describes a method of iterating over massively large arrays containing sparse data using an approach that is implementation independent of how the contents of the sparse arrays are laid out in memory. What is unique and important here is the decoupling of the iteration over the sparse set of array elements from how they are internally represented in memory. This enables this approach to be backward compatible with existing schemes for representing sparse arrays as well as new approaches. What is novel here is a new approach for efficiently iterating over sparse arrays that is independent of the underlying memory layout representation of the array. A functional interface is defined for implementing sparse arrays in any modern programming language with a particular focus for the Chapel programming language. Examples are provided that show the translation of a loop that computes a matrix vector product into this representation for both the distributed and not-distributed cases. This work is directly applicable to NASA and its High Productivity Computing Systems (HPCS) program that JPL and our current program are engaged in. The goal of this program is to create powerful, scalable, and economically viable high-powered computer systems suitable for use in national security and industry by 2010. This is important to NASA for its computationally intensive requirements for analyzing and understanding the volumes of science data from our returned missions.

James, Mark↗

Experimental Investigation of a Model of a Two-Stage Turboblower

In the present paper an investigation is made of two stages of a multistage turboblower having a vaneless diffuser behind the impeller and guide vanes at the inlet to the nest stage. The method employed was that of investigating the performance of the successive elements of the blower (the impeller, vaneless diffuser, ets.) whereby the kinematics of the flow through the blower could be followed and the pressure at the different points computed. The character of the flow and the physical significance of the loss coefficients could thereby be determined so as to secure the best agreement of the computed with the actual performance of the blower. Since the tests were carried out for various delivery volumes, the dependence of the coefficients on a number of factors (angle of attack, velocities, etc.) could be obtained. The distribution of the losses that occur during the transformation of dynamic pressure at the impeller exit into static pressure could be found and likewise the range within which the friction coefficient varies in the vaneless diffuser. With the aid of factors having a certain physical significance, the centrifugal blower could be computed on the basis of a more or less schematical consideration of the phenomena occuring during the air flow through it, and the use of arbitrary factors and recourse to the geometrical similtude law thus avoided. The present investigation largely summarizes all the previous work af the CHI Blower Section on the different elements of a centrifugal blower. Some considerations on the analysis of model test data for application to full-scale are presented in the appendix.

Dovjik, s.↗

Late Breaking Results: COPPER: Computation Obfuscation by Producing Permutations for Encoding Randomly

Deployed embedded devices face security risks due to increased ease of physical access to the devices by unauthorized users. Capable adversaries can intercept a device to recover the data in memory, including results of performed sensitive computations. Device owners require data confidentiality on their physically insecure devices. To satisfy this goal we implement a novel method, COPPER (Computation Obfuscation by Producing Permutations for Encoding Randomly), to create data which never exists on the device digitally in plaintext format and which is subsequently used for computation. In this paper we utilize COPPER to calculate a moving average computation on encoded data.

embedded systems↗

A review of crosstalk polymorphic circuits and their scalability

Using a control variable, the functionality of Polymorphic circuits can be modified, making them adaptable and useful for reconfiguring circuit behavior — all the way from gate level to system level. State-of-the art polymorphic circuits are based on custom non-linear circuit design or emerging devices such as ambipolar FET, configurable magnetic devices etc. While some of these approaches are inefficient in performance, others involve exotic devices. The Crosstalk computing based polymorphic circuits offer a fresh perspective. In Crosstalk, the interconnect interference between nanoscale metal lines is intentionally engineered to exhibit the programmable Boolean logic behavior. This approach relies on the coupling between metal lines and not on the transistors for computing, resulting in better scalability, security by obscurity, and fault tolerance by reconfiguration. Our novel approach is backed by the mathematical formulation that conveys the rationale to generalize and achieve a wide variety of polymorphic circuits. Our experiments, including design, simulation, and Power Performance Area (PPA) characterization results indicate that crosstalk circuits provide significant improvement in transistor count (about 3x), switching energy (2x), and speed (1.5x) for polymorphic logic circuits. In the best-case scenario, the transistor count reduction is 5x. This paper presents Crosstalk computing’s fundamentals, polymorphism and the scalability aspects to compete/co-exist with CMOS for digital logic implementations below 10 nm. Our scalability study uses Open Source 7 nm PDK, considers all process variation aspects and accommodates worst-case scenarios. The study results for various benchmark circuits show that the Crosstalk technology is a viable alternative to CMOS for digital logic implementations below 10 nm, having 48% density, 57% power, and 10% performance gains over equivalent CMOS counterparts. Finally, we compare Crosstalk Polymorphic Circuit design technique with similar approaches described in related works and discuss its features and constraints.

97 MATHEMATICS AND COMPUTING↗

Cyber Security: Big Data Think II Working Group Meeting

This presentation focuses on approaches that could be used by a data computation center to identify attacks and ensure malicious code and backdoors are identified if planted in system. The goal is to identify actionable security information from the mountain of data that flows into and out of an organization. The approaches are applicable to big data computational center and some must also use big data techniques to extract the actionable security information from the mountain of data that flows into and out of a data computational center. The briefing covers the detection of malicious delivery sites and techniques for reducing the mountain of data so that intrusion detection information can be useful, and not hidden in a plethora of false alerts. It also looks at the identification of possible unauthorized data exfiltration.

computer security↗

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

Historically, scientific computing efforts have demonstrated the clear need for, and effective use of, supercomputing with traditional time-stepped simulations. Nevertheless, there are several areas in the mission spaces of the U.S. Department of Energy and other agencies waiting to tap advanced computing research using a different, discrete event style of modeling, simulation, and analysis. These span a wide spectrum of applications including energy grid resilience, urban planning and policy, transportation science, building technologies, emergency response and planning, environmental impact analysis, computational epidemiology, Internet communications, cyber security, and cyber-physical systems, to name only a few. Even within traditional scientific applications, the role of discrete event modes of execution is increasing in the form of new event-based mathematical solvers such as quantized state integration methods and discrete-continuous hybrid system solvers. Co-design of advanced supercomputing hardware systems is another area that exploits discrete event simulation at its core for effective analyses. Complex systems, entity behaviors and interconnections play a significant role in all these applications, which are mapped to large-scale models with discrete event formulations. To make advancements in all the aforementioned scientific areas, many technical aspects need to be more thoroughly studied and deeply understood in parallel discrete event simulation (PDES). The unique dynamics inherent in a discrete event modeling approach, by their very nature, intersect and influence the entire stack of the computing system, including (a) the unique nature of the instruction sets exercised in PDES workloads without a predominance of high-precision floating point operations, (b) virtual time-constrained multi-threaded execution of many logical processes per processor, (c) extremely variable and difficult to predict network traffic characteristics, (d) interfaces and inter-dependencies with machine learning and artificial intelligence codes at higher software layers, and (e) highly challenging load balancing needs, especially in effectively accounting for accelerated/extremely heterogeneous computing in current and future high-performance computing systems. Efficient and accurate parallel execution of PDES workloads is also dominated by challenges in dealing with their asynchronous concurrency fundamentally present at the model level. Conservative synchronization, optimistic/speculative synchronization, and their hybrid schemes open new questions in fundamental computer science with respect to reversibility of computation and prediction (lookahead) of behaviors inherent within model codes. On the implementation front, there are relatively few scalable, general-purpose parallel discrete event simulators in the world, and even fewer have been studied on emerging hardware platforms. To enable scientific advances using PDES, the research needs in computer science must also be pursued and met in the intersection of the algorithmic and hardware-aware aspects of scalable PDES engines. This report is aimed at capturing a computer science-oriented view of this important area of research in PDES, presenting a sample of important applications with their inherent discrete event technology elements. Needs are outlined in core areas of parallel discrete event research as well as cross-cutting directions in computer science research that positively impact scientific advancements across several important application areas. A selection of priority research opportunities in advanced computing for PDES is identified to serve as reference for key research topics and their order of importance for scientific advancements.

97 MATHEMATICS AND COMPUTING↗

Computer Science Research Needs for Parallel Discrete Event Simulation (PDES)

Historically, scientific computing efforts have demonstrated the clear need for, and effective use of, supercomputing with traditional time-stepped simulations. Nevertheless, there are several areas in the mission spaces of the U.S. Department of Energy and other agencies waiting to tap advanced computing research using a different, discrete event style of modeling, simulation, and analysis. These span a wide spectrum of applications including energy grid resilience, urban planning and policy, transportation science, building technologies, emergency response and planning, environmental impact analysis, computational epidemiology, Internet communications, cyber security, and cyber-physical systems, to name only a few. Even within traditional scientific applications, the role of discrete event modes of execution is increasing in the form of new event-based mathematical solvers such as quantized state integration methods and discrete-continuous hybrid system solvers. Co-design of advanced supercomputing hardware systems is another area that exploits discrete event simulation at its core for effective analyses. Complex systems, entity behaviors and interconnections play a significant role in all these applications, which are mapped to large-scale models with discrete event formulations.

97 MATHEMATICS AND COMPUTING↗