Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Computer Security”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Optimization and Control of Electric Power Systems

The analysis and optimization needs for planning and operation of the electric power system are challenging due to the scale and the form of model representations. The connected network spans the continent and the mathematical models are inherently nonlinear. Traditionally, computational limits have necessitated the use of very simplified models for grid analysis, and this has resulted in either less secure operation, or less efficient operation, or both. The research conducted in this project advances techniques for power system optimization problems that will enhance reliable and efficient operation. The results of this work appear in numerous publications and address different application problems include optimal power flow (OPF), unit commitment, demand response, reliability margins, planning, transmission expansion, as well as general tools and algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

A Strategy for NACS investment in Machine Learning

The Nuclear and Chemical Sciences (NACS) Division furnishes the expertise in the scientific areas of chemical, nuclear and isotopic sciences that are foundational in the Laboratory’s national security missions. This expertise is maintained and advanced through identification, development and application of state-of-the-art theoretical, computational and experimental methods and tools. Recent developments in artificial intelligence and machine learning (AI/ML) techniques enabled by advances in computing capabilities and widespread availability of powerful software implementations have made use of these techniques ubiquitous across both science and industry. While the scope of AI/ML applications is incredibly large and evolves very rapidly, the topics most relevant to NACS missions fall into the general category of detecting, categorizing or identifying features in large, complex datasets using either supervised or unsupervised learning. This covers both basic scientific data analysis and the development of efficient surrogate models of real-life technological systems, experimental detectors, or theoretical models. To remain at the forefront of its core scientific disciplines, NACS must both cultivate ML expertise as well as continuously explore applying this expertise to new problems or utilizing new methods. This document identifies the key areas where this support is critical and provides a strategy for investing in them.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2022

A Threat Model of High-Power Electric Vehicle Charging Infrastructure

While electric vehicle powertrains have inherent efficiencies over their conventional counterparts, recharge time remains a significant concern. High power charging (HPC) alleviates the concerns by delivering greater power to speed charging. HPC requires communication among the vehicle, charging infrastructure, and electric supply to facilitate charging. Consequently, the transformation extends the reach and heightens the risks posed by cyberattacks, as an incident may threaten both the power grid and transportation systems. In this paper, a novel consequence-centric methodology is used to formulate an HPC infrastructure threat model. By linking threats to electricity and transportation impacts, a broad understanding of consequences is acquired.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Oak Ridge National Laboratory Annual Sustainability Report 2023

ORNL, managed under contract by UT-Battelle LLC, is DOE’s largest science and energy laboratory and, as such, executes the widest range of mission capabilities. Diverse expertise spans a broad range of scientific and engineering disciplines, enabling research and science achievements to accelerate the delivery of solutions to the marketplace. ORNL supports DOE’s national missions of scientific discovery, clean energy, and security. To execute these activities, ORNL has grown significantly over 80 years of continuous operations, consisting of facilities with commissioning dates ranging from the 1940s to the present—an extraordinary set of distinctive scientific facilities and equipment. The complexities of such a variety of facilities require teamwork among divisions, a wide variety of conservation projects, and creative strategies to achieve the desired energy and water savings. Such a diverse and unique set of major facilities, totaling over 5.5 million square feet, with 6,000 employees, requires an innovative plan to accomplish advancements in operational efficiencies. ORNL is tasked with the management of an extraordinary set of distinctive scientific facilities and equipment for DOE. ORNL is mission-driven, and its mission has grown substantially over the decades. ORNL’s core research capabilities provide broad science and technology support for DOE in the areas of energy, environment, and national security. Currently, ORNL is a world leader in materials, neutron, and nuclear science and engineering, and in high-performance computing and data analytics. ORNL’s vast portfolio of research facilities must be maintained and carefully upgraded to protect the nation’s investment in scientific analysis. The goal of sustainable and resilient operations is to enable more effective execution of ORNL’s science and technology mission. Sustainable operational practices and enhanced resilience strive for excellent results while remaining diligent in energy conservation, environmental stewardship, asset management, and community engagement. The Sustainable ORNL Program (Sustainable ORNL) Continuous improvements in operational and business processes must be integrated into the fabric of the ORNL culture to maximize the return from the investment made in modernizing facilities and equipment. The Sustainable ORNL program promotes the legacy of system-wide best practices, management commitment, and employee engagement that will lead ORNL into a future of efficient, resilient, and sustainable operations. ORNL leadership and Sustainable ORNL champions receive regular status reports on the progress of each project and focus area (i.e., roadmap) and periodic summary reports. More information can be found at the program’s website. The Sustainable ORNL roadmap structure endorses 15 vital roadmaps. The figure below summarizes the current project assignments and demonstrates that each project contributes to the wellbeing of the whole. Continuous employee engagement and regular status reports confirm the ideals of the program. The roadmap structure is not static; as the science mission advances and the needs of the organization evolve, the Sustainable ORNL roadmap structure elements are modified to align with developing priorities. In 2022, Sustainable ORNL made roadmap changes to better align ORNL to support new federal requirements that have been issued.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Modeling Information Multiplexing in the Hippocampus

Modern computers are constantly faced with the challenge of processing ever-growing quantities of data that span a wide range of modalities. Of particular relevance to national security interests is the ability to integrate multimodal data for the purpose of fast decision making. The brain is a biological system that is specialized for high performance at this task, suggesting that understanding the mechanisms by which neural circuits integrate multimodal data may lead to improved man-made detection systems. This research focused on understanding these neural algorithms, and specifically tested the hypothesis that hippocampal neurons multiplex information from two different input streams. Specifically, we compare the spiking behavior of a computational model of hippocampal circuitry with neurophysiological data recorded from rodent hippocampus.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Renewable Energy and Storage Cybersecurity Research (RESCue) Pilot Final Report

The Renewable Energy and Storage Cybersecurity Research (RESCue) project is a collaborative effort aimed at securing the rapidly growing deployment of distributed energy resources (DERs) and transmission-connected hybrid renewable energy systems against escalating cyber threats. This project brings together major original equipment manufacturers (OEMs) of wind, solar, and energy storage, along with major asset owners and DOE National Laboratories, to collectively identify cyber threats, assess risks, and develop robust cybersecurity strategies and solutions. This publication the final report for the first year of the project.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

A Kinetic Monte Carlo Approach for Simulating Cascading Transmission Line Failure

In this work, cascading transmission line failures are studied through a dynamical model of the power system operating under fixed conditions. The power grid is modeled as a stochastic dynamical system where first-principles electromechanical dynamics are excited by small Gaussian disturbances in demand and generation around a specified operating point. In this context, a single line failure is interpreted in a large deviation context as a first escape event across a surface in phase space defined by line security constraints. The resulting system of stochastic differential equations admits a transverse decomposition of the drift, which leads to considerable simplification in evaluating the quasipotential (rate function) and, consequently, computation of exit rates. Tractable expressions for the rate of transmission line failure in a restricted network are derived from large deviation theory arguments and validated against numerical simulations. Extensions to realistic settings are considered, and individual line failure models are aggregated into a Markov model of cascading failure inspired by chemical kinetics. Cascades are generated by traversing a graph composed of weighted edges representing transitions to degraded network topologies. Numerical results indicate that the Markov model can produce cascades with qualitative power-law properties similar to those observed in empirical cascades.

Kinetic Monte Carlo, rare events, Cascading Failur↗
DOE OSTI2021

The Role of the Digital Thread for Security, Resilience, and Adaptability in Manufacturing

The manufacturing sector is dramatically evolving with recent technical and digital advances. Among these, the digital thread is revolutionizing manufacturing operations well beyond the historic downloading of programs to computer numerically controlled (CNC) machine tools and the uploading of edited programs from CNC controllers. The digital thread is “the communication framework that enables a connected data flow and integrated view of the asset’s data throughout its lifecycle across traditionally siloed functional perspectives” (Leiva 2016). It is pervasive around the world and has changed the way society operates; for example, map apps are used to provide time-optimal directions to destinations using real-time traffic feedback. The digital thread makes it possible to digitally verify products, ensure that the latest technologies are deployed across the entire manufacturing ecosystem, and strengthen the workforce by making each individual more efficient and effective. These three foundational advanced manufacturing concepts will ensure a next-generation secure, resilient, and adaptable manufacturing ecosystem and sustainably support current and future needs of society (Lynn et al. 2020).

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

Unraveling the physics of nanofluidic phenomena at the single-molecule level

Despite groundbreaking potential in a broad application space, several nanofluidic phenomena remain poorly understood. Toward advancing the understanding of fluid behavior under nanoscale confinement, we developed a novel, ideal platform for fundamental molecular transport studies, in which the fluidic channel is a single carbon nanotube (CNT). CNTs offer the advantage of simple chemistry and structure, which can be synthetically tuned with nanometer precision and accurately modeled. With combined experimental and computational approaches, we demonstrated that CNT pores with 1-5 nm diameters conduct giant ionic currents that follow an unusual sublinear electrolyte concentration dependence. The large magnitude of the ionic conductance appears to originate from a strong electro-osmotic flow in smooth CNT pores. First-principle simulations suggest that electro-osmotic flow arises from localized negative polarization charges on carbon atoms near a potassium (K + ) ion and from the strong cation-graphitic wall interactions, which drive K + ions much closer to the wall than chlorides (Cl - ). Single-molecule translocation studies reveal that charged molecules may be distinguished from neutral species on the basis of the sign of the transient current change during their passage through the nanopore. Together with shedding light on a few controversial questions in the CNT nanofluidics area, these results may benefit LLNL’s Security Mission by providing the foundation for the development of advanced single-molecule detection system for bio/chem/explosive analytes. In addition, these experimental and computational platforms can be applied to advance fundamental knowledge in other fields, from energy storage and membrane separation to superfluid physics.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Modular Security Apparatus for Managing Distributed Cryptography for Command-and-Control Messages on Operational Technology Networks (Module-OT)

Module-OT is a bump- in- the- wire solution acting as a secure conduit for data between devices or systems across a network. Using the latest in open-source cryptographic libraries, all defined communications undergo authentication, authorization, and encryption. The core system can be easily installed through industry standard processes, and the use of popular open-source packages allows for it to be customizable customized by the developer community or deployed in unique embedded environments.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

XploreNAS : Explore Adversarially Robust and Hardware-efficient Neural Architectures for Non-ideal Xbars

Compute In-Memory platforms such as memristive crossbars are gaining focus as they facilitate acceleration of Deep Neural Networks (DNNs) with high area and compute efficiencies. However, the intrinsic non-idealities associated with the analog nature of computing in crossbars limits the performance of the deployed DNNs. Furthermore, DNNs are shown to be vulnerable to adversarial attacks leading to severe security threats in their large-scale deployment. Thus, finding adversarially robust DNN architectures for non-ideal crossbars is critical to the safe and secure deployment of DNNs on the edge. This work proposes a two-phase algorithm-hardware co-optimization approach called XploreNAS that searches for hardware efficient and adversarially robust neural architectures for non-ideal crossbar platforms. We use the one-shot Neural Architecture Search approach to train a large Supernet with crossbar-awareness and sample adversarially robust Subnets therefrom, maintaining competitive hardware efficiency. Our experiments on crossbars with benchmark datasets (SVHN, CIFAR10, CIFAR100) show up to ~8–16% improvement in the adversarial robustness of the searched Subnets against a baseline ResNet-18 model subjected to crossbar-aware adversarial training. We benchmark our robust Subnets for Energy-Delay-Area-Products (EDAPs) using the Neurosim tool and find that with additional hardware efficiency–driven optimizations, the Subnets attain ~1.5–1.6× lower EDAPs than ResNet-18 baseline.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Opal: A Centralized Memory Manager for Investigating Disaggregated Memory Systems

Many modern applications have memory footprints that are increasingly large, driving system memory capacities higher and higher. Moreover, these systems are often organized where the bulk of the memory is collocated with the compute capability, which necessitates the need for message passing APIs to facilitate information sharing between compute nodes. Due to the diversity of applications that must run on High-Performance Computing (HPC) systems, the memory utilization can fluctuate wildly from one application to another. And, because memory is located in the node, maintenance can become problematic because each node must be taken offline and upgraded individually. To address these issues, vendors are exploring disaggregated, memory-centric, systems. In this type of organization, there are discrete nodes, reserved solely for memory, which are shared across many compute nodes. Due to their capacity, low-power, and non-volatility, Non-Volatile Memories (NVMs) are ideal candidates for these memory nodes. This report discusses a new component for the Structural Simulation Toolkit (SST), Opal, that can be used to study the impact of using NVMs in a disaggregated system in terms of performance, security, and memory management. This page intentionally left blank.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Coordinated Scheduling for Interdependent Electric Power and Natural Gas Infrastructures

The extensive installation of gas-fired power plants in many parts of the world has led electric systems to depend heavily on reliable gas supplies. The use of gas-fired generators for peak load and reserve provision causes high intraday variability in withdrawals from high-pressure gas transmission systems. Such variability can lead to gas price fluctuations and supply disruptions that affect electric generator dispatch, electricity prices, and threaten the security of power systems and gas pipelines. These infrastructures function on vastly different spatio-temporal scales, which prevents current practices for separate operations and market clearing from being coordinated. Here in this article, we apply new techniques for control of dynamic gas flows on pipeline networks to examine day-ahead scheduling of electric generator dispatch and gas compressor operation for different levels of integration, spanning from separate forecasting, and simulation to combined optimal control. We formulate multiple coordination scenarios and develop tractable physically accurate computational implementations. These scenarios are compared using an integrated model of test networks for power and gas systems with 24 nodes and 24 pipes, respectively, which are coupled through gas-fired generators. The analysis quantifies the economic efficiency and security benefits of gas-electric coordination and dynamic gas system operation.

03 NATURAL GAS↗
DOE OSTI2018

Using sensor arrays to decode NO x /NH 3 /C 3 H 8 gas mixtures for automotive exhaust monitoring

In this work, an array of four mixed-potential sensors is employed to identify and quantify gases in complex mixtures of unknown composition which mimic diesel engine exhaust. The sensors use dense metal and metal oxide electrodes with a porous ceramic electrolyte, yttria-stabilized zirconia (YSZ). Since the sensors exhibit cross-specificity toward target gases, we develop a computational model for predicting gas concentrations in the mixtures. Our model is based on fundamental principles of gas-sensor interactions and, furthermore, takes into account the non-linearity of the observed sensor voltage response. Our approach enables accurate predictions of gas concentrations from the voltage output of the sensor array exposed to an extensive set of mixtures involving C 3 H 8 , NH 3 , NO and NO 2 . We find that our predictions remain accurate even if the model is trained using a reduced set of mixtures, or if the number of sensors is decreased to three or two. Finally, our experimental and computational framework can be used to decipher contents of complex gas mixtures of unknown composition in numerous industrial, automotive, and national security settings.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Atrial Model Development and Prototype Simulations CRADA No. TC02224.0

This project was a collaborative effort between Lawrence Livermore National Security, LLC as manager and operator of Lawrence Livermore National Laboratory (LLNL) and Amgen, Inc. ("Amgen"), to develop a capability to computationally evaluate the importance and roles of different ion channels in atrial fibrillation. The first phase of this collaboration was to implement the atrial model, run prototype simulations, and analyze the results.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Public Key-Based Need-to-Know Authorization Engine Final Report CRADA No. TSB-1553-98

The goals of this project were to develop a public key-based authentication service plug-in based on LLNL's requirements, integrate the public key-based authentication with the Intra Verse authorization service adn the LLNL NTK server by developing a full-featured version of the prototyped Intra Verse need-to-know plug in; and to test the authorization and need-to-know plug-in in a secured extranet prototype among selected national Labs.

97 MATHEMATICS AND COMPUTING↗