Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “System 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 1,783 records · Page 99

Development of a Solar Heat and Power Co-Generation System, CRADA No. TC02152.0

This was a collaborative effort between Lawrence Livermore National Security, LLC as manager and operator of Lawrence Livermore National Laboratory (LLNL) and Tassajara Technologies, Inc. (TTI), to develop, fabricate and demonstrate a Solar Heat and Power Co-generation System. The technical objectives of this CRADA were to engineer, design and build a prototype Solar Thermal Process Heat and Power Demonstration System that would be suitable for use at the Arc of Hilo food processing facility. This would be accomplished in two phases. The first phase would entail the building of a prototype at Tassajara facilities. Base design parameters, including the subsystem interactions that would produce reliable performance at the lowest cost per watt of energy generated with the desired balance of power and heat to meet the requirements of the designated food processing applications from Arc of Hilo, would be provided by LLNL. The data and design development would be integrated into the second phase engine prototype and solar thermal system that would be built and delivered, with interface requirements to the Miko Building.

14 SOLAR ENERGY↗

Digital Twin Technology for Safety, Security, and Training in Spent Nuclear Fuel Handling

The increasing complexity of spent nuclear fuel handling requires significant resources to ensure safety, security, and personnel training. As nuclear facilities have continued to advance in scale and technology, the integration of digital tools has become indispensable. Among these tools, digital twins, which are virtual models of physical systems, are emerging as invaluable tools for enhancing safety protocols, security measures, and training in the nuclear sector. These models were conceptualized in the Industry 4.0 revolution. Digital twins can process data from physical systems in real time (by using sensors), include multiple code packages to enable simulations of different physics applications, and even implement artificial intelligence or machine learning techniques for advanced data processing. Despite the advantages that digital twins provide, challenges still exist regarding their widespread implementation. For instance, data used by a digital twin must be accurate to ensure that the digital twin is accurately tuned. Furthermore, if insecure digital twins are targeted by hackers, then they can pose serious risks to the security and safety of nuclear facilities.

Digital twins↗

A review of artificial intelligence applications in manufacturing operations

Abstract Artificial intelligence (AI) and machine learning (ML) can improve manufacturing efficiency, productivity, and sustainability. However, using AI in manufacturing also presents several challenges, including issues with data acquisition and management, human resources, infrastructure, as well as security risks, trust, and implementation challenges. For example, getting the data needed to train AI models can be difficult for rare events or costly for large datasets that need labeling. AI models can also pose security risks when integrated into industrial control systems. In addition, some industry players may be hesitant to use AI due to a lack of trust or understanding of how it works. Despite these challenges, AI has the potential to be extremely helpful in manufacturing, particularly in applications such as predictive maintenance, quality assurance, and process optimization. It is important to consider the specific needs and capabilities of each manufacturing scenario when deciding whether and how to use AI in manufacturing. This review identifies current developments, challenges, and future directions in AI/ML relevant to manufacturing, with the goal of improving understanding of AI/ML technologies available for solving manufacturing problems, providing decision‐support for prioritizing and selecting appropriate AI/ML technologies, and identifying areas where further research can yield transformational returns for the industry. Early experience suggests that AI/ML can have significant cost and efficiency benefits in manufacturing, especially when combined with the ability to capture enormous amounts of data from manufacturing systems.

Plathottam, Siby Jose↗

The Chemical Management System (CMS): A Useful Tool for Inventory Management

Comprehensive inventory management is central to the efficient operation of any facility that uses and stores chemicals. There are numerous software packages available that perform this function satisfactorily. Most commercially available inventory management software is regulatory or procurement focused and usually comes with upfront or monthly fees. Finally, this report describes freely downloadable software developed at Sandia National Laboratories that delivers an effective inventory management system with an additional focus on chemical security.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Zinc-Adeninate Metal–Organic Framework: A Versatile Photoluminescent Sensor for Rare Earth Elements in Aqueous Systems

Rare earth elements (REEs) are critically important for national security and advanced technologies. Consequently, significant effort has been devoted towards increasing REE domestic production, including the extraction of REEs from coal, coal combustion byproducts, and their associated waste streams such as acid mine drainage. Analytical methods for rapid quantification of REE content in aqueous phases can facilitate REE recovery through rapid identification of high-value waste streams. Here, we show that BioMOF-100 can be used as a fluorescent-based sensitizer for emissive REE ion detection in water, providing rapid (<10 min) analysis times and sensitive detection (parts-per-billion detection limits) for terbium, dysprosium, samarium, europium, ytterbium, and neodymium, even in the presence of acids or secondary metals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

TRIM: AI Guided Random Number Generation for Resource-Constrained IoT Systems

Random numbers often serve as the backbone for many security solutions in diverse domains such as cryptography, side channel leakage prevention, and moving target defense. However, generating true random numbers requires a physical source of entropy (e.g. hardware, quantum, environmental phenomenon) making it difficult to realize at a large scale and at a low cost. On the flip side, pseudorandom number generators (easy to implement) following a specific distribution (e.g. Gaussian) can be easily compromised given a sufficient amount of traces. In this work, we have developed a machine learning-guided generative approach that can be used to create portable, resource-efficient, and cost-effective random number generators with high throughput and true randomness characteristics. We implement the proposed approach as a highly parameterized framework and perform extensive evaluation for different settings. The framework was able to learn from true random sources such as irrational numbers and environmental audio noise and imitate those sources towards generating new good quality random numbers on demand. We have generated more than 1 billion bits and observed robust performance in terms of true randomness metrics obtained from NIST SP 800-22 and FIPS 140-1 randomness test suites achieving a throughput of up to 142.85 Mbps. Compared to the state-of-the-art (SOTA) technique, the iso-cost setup of our framework can achieve more than 500 Mbps in a distributed setting. We have evaluated the efficacy of running the true randomness imitation AI models on target edge devices such as Raspberry Pi 4 (Model B), Nvidia Jetson Nano, Nvidia Jetson Orin Nano and Nvidia Jetson Xavier. We have also looked at the security of the TRIM framework itself against different adversarial threat models.

Cybersecurity↗

Smart Grid Status and Metrics Report Appendices

A smart grid uses digital power control and communication technology to improve the reliability, security, flexibility, and efficiency of the electric system, from large generation through the delivery systems to electricity consumers and a growing number of distributed generation and storage resources. To convey progress made in achieving the vision of a smart grid, this report uses a set of six characteristics derived from the National Energy Technology Laboratory Modern Grid Strategy. The Smart Grid Status and Metrics Report defines and examines 21 metrics that collectively provide insight into the grid’s capacity to embody these characteristics. This appendix presents papers covering each of the 21 metrics identified in Section 2.1 of the Smart Grid Status and Metrics Report. These metric papers were prepared in advance of the main body of the report and collectively form its informational backbone.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Path Scan Operational Data-Based Test Report

The TTP program is managed by DHS S&T Cyber Division and facilitates the transition of technology from the research lab to the Homeland Security Enterprise. It serves as a connection point for cyber security researchers, the Federal Government, and the private sector. Technologies targeted are those that are likely to transition successfully to the commercial market and expected to have notable impact on the cyber security of our Nation’s networks or systems. The test element of the TTP program aids in the technology transfer process and is not intended to be adversarial. Additional information on the TTP program and the iterative process used can be found in Appendix A - TTP Program Overview.

97 MATHEMATICS AND COMPUTING↗

Random Laser Physical Unclonable Function

We report on the fabrication and characterization of nanocrystalline ZnO films for use as a random laser physical unclonable function (PUF). Correlation between processing conditions and film microstructure will be made to optimize the lasing properties and random response. We will specifically examine the repeatability and security of PUFs demonstrated in this novel system. This demonstration has promise to impact many of Sandia's core missions including counterfeit detection.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Pit Realization Process Manufacturing Readiness Assessments

This document defines a manufacturing readiness assessment process within a Product Realization Process (PRP) for pit manufacturing at Los Alamos National Laboratory (LANL) having the following objectives. Meet National Nuclear Security Administration (NNSA) Defense Programs Business Process System (DPBPS) PRP requirements. Use language established within LANL’s pit manufacturing program. Enable a disciplined approach to evaluate pit manufacturing readiness. Provide effective tools and metrics to assess manufacturing system maturity.

42 ENGINEERING↗

Cybersecurity for Distance Relay Protection

This project is a DOE follow-up effort on the CREDC workshop held on September 13, 2018 in Cambridge, MA to discuss cybersecurity of distance relays, which considered the benefits, vulnerabilities and risk mitigations for the use of communication systems in power system protection. The objectives of this project are to define the taxonomy of relay protection and associated communications; define use cases describing approaches to reduce the cyber-attack surface on those protective relays; and evaluate the loss of operational functional capability from changes to communication coverage. Mitigating controls will also be evaluated to understand if there are other approaches to reduce attack surfaces while maintaining communications or partial communications. Distance relays are used to protect transmission lines of approximately 10 to 300 miles in length, by detecting short circuits (i.e., faults) on the lines and then tripping circuit breakers in the substation. Such protection systems are a subset of the power system and they incorporate sensing, logic and communication functions. Protection system exposure to cyberattack could be drastically limited by disconnecting relays from all vulnerable communication systems, but this may adversely impact overall power system performance in the absence of cyberattack. This project began with a use case analysis of protection systems with communications, as summarized in this report. It continued with modeling, testing and evaluation in a miniature power system (MPS), located in the Western Area Power Administration (WAPA) Electric Power Training Center (EPTC). The project also incorporated feedback from two industry meetings held in February and September 2019. The suggested next steps account for and complement the work already underway with DOE/CESER funding: 1. Study the performance of LCD and PC vs. PUTT, which is less reliant on communication system performance and GPS timing references. The PUTT scheme could prove to be more resilient to cyberattack or communications-related disruption. It could also be more tolerant of message re-routing with SDN/SDR communication systems. On the other hand, it will be more vulnerable to false tripping during dynamic events or to loss of the voltage signal. The optimum choice of scheme may depend on the specific power system and risk assessment. This study could provide a new template for evaluation based on business functions. 2. Research and develop new methods to detect and monitor distributed physical attacks, possibly using drones, video sensors, thermal sensors, machine learning and other advanced techniques. This will help mitigate the impact of cyberattack on the protection system, and will also help mitigate the impact of wild fires. 3. Implement a scalable PKI for use in electric utility protection systems. This will encourage widespread adoption of secure authentication methods that are already available, but not widely used at present. This will help secure engineering access to the relays. 4. Investigate the use of SDN in combination with SDR to achieve better cybersecurity and electromagnetic security of the network, incorporating path variability. This would help secure both engineering access and peer-to-peer GOOSE messaging. 5. Perform additional testing, with operator evaluation of “red button” scenarios, PUTT vs. LCD, relay mis-operations, and other cyberattacks in the EPTC. This is an important advantage of testing in the EPTC rather than by computer simulation or even hardware-in-the-loop simulation; the EPTC is already dedicated to managing the situational awareness, operator response times and other human impacts. One of the project objectives was to settle on a common nomenclature for this problem space. We have concluded that the OSI layer model, supplemented by ANSI device numbers and other IEEE standards, is already well-accepted by the industry. The IEEE PSRC knowledge base provides a great deal of public information

24 POWER TRANSMISSION AND DISTRIBUTION↗

Bridge Seismic Screening Tool (BSST), Version 2.0

The Regional Resiliency Assessment Program (RRAP) is a cooperative assessment of specific critical infrastructure within a designated geographic area and a regional analysis of the surrounding infrastructure that addresses a range of infrastructure resilience issues that could have regionally and nationally significant consequences. In 2018, DHS’s Cybersecurity and Infrastructure Security Agency (CISA) sponsored the Oregon Transportation Systems RRAP project in coordination with the Office of the Governor (under the oversight of the state resilience officer), the Oregon Office of Emergency Management (OEM), the Oregon Department of Transportation (ODOT), and other regional stakeholders (CISA 2021). This project focuses on assessing the impacts of a Cascadia Subduction Zone (CSZ) earthquake on state transportation systems and, in particular, how those impacts may affect the ability of emergency response efforts to move supplies into the region. The intended outcome of this analysis is the prioritization of transportation routes and modes for additional planning, investment, hardening, or other activities to enhance their resilience—and therefore, to enhance their ability to support response and recovery efforts following a CSZ earthquake. An important part of this transportation system-level assessment has been to assess the seismic vulnerability of the state highway system. In doing so, the RRAP project team used the Bridge Seismic Screening Tool (BSST) to assess, at a system-level, the potential impacts that a CSZ earthquake could have on state highway bridges (Bergerson et al. 2019).1 Argonne National Laboratory (Argonne), in collaboration with the Washington State Department of Transportation (WSDOT), originally developed the BSST as part of the 2017 Washington State Transportation Systems RRAP project, a sister project to the 2018 Oregon Transportation Systems RRAP project. Argonne updated the BSST during this more recent project in Oregon based on feedback from stakeholders and subject matter experts (SMEs) on the original version of the tool. The first step in the BSST is to assess the seismic vulnerability of roadway bridges following a CSZ earthquake to determine a projected or potential damage state. Damage states then help determine approximate reopening times for bridge crossings.2 This document provides details on the BSST methodology, the implementation of that tool to analyze the projected damage incurred in a CSZ earthquake scenario, and the determination of corresponding reopening times of interstate, state highway, and local bridges following such an event.

58 GEOSCIENCES↗

2021 GeoAI Workshop Report: The Trillion Pixel Challenge

The convergence of geospatial big data with advancements from artificial intelligence, cloud infrastructure, and high-performance computing continues to revolutionize mapping and analysis of Earth's surface in unprecedented detail. Rapid innovations in sensing technologies will soon collect geospatial data in even higher resolution and throughput. These developments offer the potential for breakthroughs in science, policy, and national security via end-to-end GeoAI systems that can provide fresh insights into how humans occupy and alter their environment over time. At the 2021 GeoAI Trillion Pixel workshop, international subject matter experts from government, academia, industry, and nonprofit organizations gathered virtually to discuss the Trillion Pixel GeoAI Challenge. The event focused on six major themes currently influencing scientific innovation and breakthroughs. Particular focus was paid to societal impacts. As an additional takeaway message, the gathering identified remaining application gaps and challenges that are in need of stronger community partnerships and collaborations.

58 GEOSCIENCES↗

Workshop on Establishing and Operating a National Nuclear Security Support Centre Hypothetical Scenario: “Centralia Nuclear Security Support Centre Technical Support Plan”

This plan outlines the systemic and coordinated management of the CNSSC technical support programme. In accordance with the CNSSC Strategy Implementation Plan and Memoranda of Understanding among stakeholders, Centralia Border Guards (CBG) and Centralia Nuclear Energy Agency (CNEA) will lead the effort to develop standardized approach to technical support and will provide technical support to the following CNSSC stakeholders: CBG, CNEA, Centralia National Police (CNP), Centralia Coast Guard (CCG), and CentrAtom/Centralia Nuclear Power Plant (CNPP).

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗

Spatial Microsimulation and Activity Allocation in Python: An Update on the Likeness Toolkit

Understanding human security and social equity issues within human systems requires large-scale models of population dynamics that simulate high-fidelity representations of individuals and access to essential activities (work/school, social, errands, health). Likeness is a Python toolkit that provides these capabilities for Oak Ridge National Laboratory's (ORNL) UrbanPop spatial microsimulation project. In step with the initial development phase for Likeness (2021 - 2022), we built out several foundational examples of work/school and health service access. In this paper, we describe expansion and scaling of Likeness capabilities to metropolitan areas in the United States. We then provide an integrated demonstration of our methods based on a case study of Leon County, FL and perform validation exercises on 1) neighborhood demographic composition and 2) visits by demographic cohorts (gender/age) obtained from point of interest (POI) footfall data for essential services (grocery stores). Taking into account lessons learned from our case study, we scope improvements to our model as well as provide a roadmap of the anticipated Likeness development cycle into 2023 - 2024.

Tuccillo, Joe↗

Predictive Analytics for Hydropower Fleet Intelligence

A primary challenge in hydropower industry is the ability to maintain cost-competitiveness, reliability, and security of hydropower assets through evolving power system contexts and aging of the fleet. Maintaining cost-effective and reliable operations under these conditions is expected to require new modernization and maintenance paradigms for changing contexts. Changes in existing practices for O&M will require an understanding of the current state and health of hydropower assets, and the impact of changing paradigms on asset health and reliability. The Hydropower Fleet Intelligence project is developing and evaluating standardized methodologies and analysis tools for data-driven asset reliability and management technologies for hydropower, leading to eventual predictive maintenance planning, repair/replacement decision making, and asset-reliability and cost-optimized operations. A key question is the feasibility of using existing data sets at hydropower facilities to perform assessments of asset reliability. This document uses data from hydropower facilities to assess the potential for using available analytics methods for asset reliability estimates. In addition to reliability assessments, the feasibility of using existing analytics techniques for several other potential applications is discussed. Finally, a case study that a data-driven model is trained to learn nominal operations via vibration data from an asset of a certain plant, and then utilized to identify anomalies on a similar asset from a different plant, highlighting the generic use of proposed Prognostics and Health Management (PHM) approaches.

Yucesan, Yigit↗

National Aeronautics and Space Administration. 2003 Strategic Plan

As the 21st century begins to unfold, NASA will focus, with renewed vigor, on the challenges and opportunities before us and on developing the unique capabilities that strengthen America and address our national needs. Our Mission is driven by science, exploration, and discovery, and it will be carried out with a firm commitment to fiscal responsibility. We will study climate change and the natural and human-induced hazards to Earth's ecosystem. We will help to counter the threat of international terrorism by developing technologies that can improve the security and safety of our air transportation system. We will lead the world into a new understanding of our planet, our solar system, and the universe around us, and in so doing, we will begin to understand whether life may have developed elsewhere in the cosmos. This strategic plan lays out our hopes for the future and the important things we seek to accomplish for America. We are privileged to be entrusted with these pursuits and thrilled to be able to carry them out. We invite you to join us on this great adventure. Releasing this strategic plan with our 2004 budget request represents our new commitment to the integration of budget and performance reporting. In this way, we will ensure that strategic priorities are aligned with and influence budget priorities. Our new Integrated Budget and Performance Document, a companion volume to this strategic plan, expands on the goals and objectives presented here and identifies the specific long-term and annual performance measures for which we will be held accountable.

STRATEGIC PLANNING↗

Vertical Drop Testing and Analysis of the Wasp Helicopter Skid Gear

This report describes an experimental program to assess the impact performance of a skid gear for use on the Wasp kit-built helicopter, which is marketed by HeloWerks, Inc. of Hampton, Virginia. In total, five vertical drop tests were performed. The test article consisted of a skid gear mounted beneath a steel plate. A seating platform was attached to the upper surface of the steel plate, and two 95th percentile Hybrid III male Anthropomorphic Test Devices (ATDs) were seated on the platform and secured using a four-point restraint system. The test article also included ballast weights to ensure the correct position of the Center-of-Gravity (CG). Twenty-six channels of acceleration data were collected per test at 50,000 samples per second. The five drop tests were conducted on two different gear configurations. The details of these test programs are presented, as well as an occupant injury assessment. Finally, a finite element model of the skid gear test article was developed for execution in LS-DYNA, an explicit nonlinear transient dynamic code, for predicting the skid gear and occupant dynamic responses due to impact.

Jackson, Karen E.↗