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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.

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At least 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A Flexible and Secure Evaluation Platform for Overvoltage Protection in Power Electronics Systems

This paper summarizes the fault mechanisms specifically for the overvoltage protection schemes in power electronic converters and the resulted power electronics enabled systems. A flexible and secure evaluation platform for overvoltage protection, has also been presented based on this conceptual mechanism. The proposed platform aims at testing the protection performance of distinctive overvoltage protection schemes. It would be applied to verify the effectiveness, identify potential strengths and weaknesses, and obtain the most critical protection response time to provide sufficient engineering insights for the designer. The operation principle and detailed design guideline have been presented first. The comprehensive component stress has been analyzed. An intensive set of LTSpice simulations have been conducted to show the validity of the proposed assessment approach.

Zheng, Sheng↗
DOE OSTI2017

Uncertainty analysis of wavelet-based feature extraction for isotope identification on NaI gamma-ray spectra

Low-resolution isotope identifiers are widely deployed for nuclear security purposes, but these detectors currently demonstrate problems in making correct identifications in many typical usage scenarios. While there are many hardware alternatives and improvements that can be made, performance on existing low resolution isotope identifiers should be able to be improved by developing new identification algorithms. We have developed a wavelet-based peak extraction algorithm and an implementation of a Bayesian classifier for automated peak-based identification. The peak extraction algorithm has been extended to compute uncertainties in the peak area calculations. To build empirical joint probability distributions of the peak areas and uncertainties, a large set of spectra were simulated in MCNP6 and processed with the wavelet-based feature extraction algorithm. Kernel density estimation was then used to create a new component of the likelihood function in the Bayesian classifier. Furthermore, identification performance is demonstrated on a variety of real low-resolution spectra, including Category I quantities of special nuclear material.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Rainier Mesa/Shoshone Mountain Hydrostratigraphic Framework Model-Prime Model Model Development Process and Model Description, Revision 0

This document presents the results of revisions to the Rainier Mesa/Shoshone Mountain (RM/SM) hydrostratigraphic framework model (HFM) that was constructed for Corrective Action Unit (CAU) 99: Rainier Mesa/Shoshone Mountain. The revised HFM is described as the “RM/SM HFM-Prime” and serves as the base HFM. The modeling efforts and the revisions described in this report have been performed as part of the Underground Test Area (UGTA) Activity that was initiated by the U.S. Department of Energy (DOE), National Nuclear Security Administration Nevada Field Office (NNSA/NFO) to assess and evaluate the effects of the underground nuclear tests on groundwater at the Nevada National Security Site (NNSS) and vicinity. This document builds on the content of the internal Hydrostratigraphic Framework Model of the Rainier Mesa Area Phase I' - Base Model: Model Development Process & Data Package Description (N-I, 2014a) and specific document review comments from the UGTA RM/SM CAU Preemptive Review members (Zavarin, 2015). This document provides, where necessary, the justifications and rationale for interpretations and revisions to the hydrostratigraphic framework of the RM/SM CAU. The fundamental objective of the effort described in this report was to revise the RM/SM HFM, particularly in the areas and vicinity of the sub-CAU models, in order to incorporate some of the higher-resolution hydrogeologic interpretations used to construct several of the sub-CAU scale flow and transport models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Security Evaluation of Smart Cards and Secure Tokens: Benefits and Drawbacks for Reducing Supply Chain Risks of Nuclear Power Plants

The supply chain attack pathway is being increasingly used by adversaries to bypass security controls and gain unauthorized access to sensitive networks and equipment (e.g., Critical Digital Assets). Cyber-attacks targeting supply chain generally aim to compromise the environments, products, or services of vendors and suppliers to inject, add, or substitute authentic software and hardware with malicious elements. These malicious elements are deemed to be authentic as they arise from the vendor or supplier (i.e., the supply chain). This research aims to leverage findings and assumptions made from the previous report to determine the security benefits and drawbacks of a smart card- based hardware root of trust. Smart cards can provide devices inside Nuclear Power Plants (NPP) with a secure environment to store keys in and perform sensitive operations such as digital signature generation. These abilities can be leveraged to increase supply chain cybersecurity by autonomously providing NPP Licensees with reports on device integrity, authenticity and measurements of executable and non-executable data.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2022

A Cybersecurity Threat Profile for a Connected Lighting System

In this paper we analyze a threat profile performed on a fault-detection use case for streetlights. A threat profile establishes security requirements, justifies security measures, yields actionable controls, and effectively communicates risk to stakeholders. This effort provides critical information for making threat-based decisions to increase security at a reasonable cost, and can effectively be used by development teams, software architects, and managers to make cybersecurity a part of their ongoing culture of awareness, training, and prevention. This leads to more secure systems and better-understood security. On-premise, cloud, and hybrid architectures with different authentication mechanisms were modeled and later categorized using the Microsoft STRIDE framework. An analysis of the recommended controls for each threat was performed to determine which controls could and should be put in place by manufacturers or third-party suppliers, and which controls need to be left up the end-user to implement.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Mo 99 Draft Report.

The Nuclear Science Advisory Committee (NSAC) 99 Molybdenum ( 99 Mo) Subcommittee met December 14-15, 2017 to address the charge to NSAC requesting that a fourth annual review of the National Nuclear Security Administration (NNSA) 99 Mo program be performed. The Subcommittee found that the NNSA has continued to make progress over the course of the year based on the specific American Medical Isotopes Production Act of 2012 (AMIPA) requirements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Trinity Supercomputer Now Fully Operational

Now one of the fastest supercomputers in the United States, the Trinity Supercomputer Phase II project was completed during the summer of 2017, and the computer became fully operational during an unclassified “open science” run. The computer has now transitioned to classified mode. The Trinity supercomputer is designed to provide increased computational capability for the NNSA Nuclear Security Enterprise in support of increasing geometric and physics fidelities in nuclear weapons simulation codes, while maintaining expectations for total time to solution. The capabilities of Trinity are required for supporting the NNSA Stockpile Stewardship program’s certification and assessments to ensure that the nation’s nuclear stockpile is safe, secure and effective. With an expected operational lifetime through 2020, Trinity is an approximately 41.5 petaflop (41.5 million billion calculations per second, peak performance) supercomputer based on the Cray XC40 architecture. It consists of 19,420 compute nodes utilizing two processor architectures, Intel Xeon Haswell and Intel Xeon Phi Knights Landing. It is a water-cooled system with a power requirement of about 10 megawatts. The Trinity project is managed and operated by Los Alamos National Laboratory and Sandia National Laboratories under the Alliance for Computing at Extreme Scale (ACES) partnership. The system is located at the Nicholas Metropolis Center for Modeling and Simulation at Los Alamos and covers approximately 5,200 square feet of floor space.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Nuclear Materials Process Modeling at the Y-12 National Security Complex

The Y-12 National Security Complex (Y-12) has implemented process modeling for various accountable nuclear materials operations that are performed throughout the plant. Using a discrete, event-based dynamic simulation program, key nuclear material streams are modeled, allowing Y-12 to effectively manage numerous points of interest within the plant’s production operations. Integration of the various material processes into a single, interdependent supply and demand model is one of the ongoing focuses within Y-12’s process modeling effort. The primary purpose of using dynamic simulation modeling is to allow for analysis of the nuclear materials inventories and forecasted supplies based on future demands. Analysis of these inventories includes capacity evaluation, bottleneck mitigation, and assessments of individual pieces of equipment to inform future facility investment decisions and associated project schedules. Modeling of the nuclear materials processes throughout the complex also allows for incorporation of changes relevant to production capabilities such as the upcoming transition of specific operations to the new Uranium Processing Facility. Prior to implementation of process modeling, Y-12 forecasted supply and demand of accountable nuclear materials streams using Microsoft Excel. With deterministic models such as Microsoft Excel, the annual forecasts, generated within data input condition parameters, can only provide a fixed point of data. Fixed data cannot simulate integrated material streams and account for the possibility of occurrences and other changes that dynamic simulations take into consideration. Y-12’s dynamic process modeling allows integrated simulations of multiple accountable nuclear materials processes, including supply and demand forecasting and analysis, and is a coordinated effort involving many steps of verification and validation (V&V), site briefings, testing, reporting, data mining, planning, and documentation that spans various programs throughout the Y-12 complex.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

An Automated, Disruption-Tolerant Device Authentication and Key Management Framework for Critical Systems

Key management is critical to secure operation. Distributed control systems, such as Supervisory Control and Data Acquisition (SCADA) systems, have unique operational requirements that make conventional key management solutions less effective and burdensome. In this paper a novel Kerberos based framework for automated, disruption-tolerant key management for control system environments is presented. Experimental tests and their results are presented to quantify expected performance overhead of this approach. In addition, Zeek sensor analytics are presented to monitor the health and security of the key management framework operation.

Edgar, Thomas W.↗
DOE OSTI2019

Identity-based quantum signature scheme with strong security

Recently, Chen et al. proposed an identity-based quantum signature scheme (IDQSS). Their scheme has the advantages of the classical identity-based signature (IDS) scheme. However, Chen et al.’s scheme cannot resist against the private key generator (PKG)’s forgery attack. On the other hand, in their scheme, many rounds of quantum swap tests have to be performed by the verifier during the signature verification phase. To improve the security and efficiency of the IDQSS, a new IDQSS is proposed. In our scheme, the private key of the signer is generated by PKG according to the signer’s identity, which is used as the corresponding public key. The signer generates a quantum signature with her private key and the secret parameters shared with the verifier. Anyone can verify the quantum signature with the identity of the signer. Our scheme overcomes the security drawback of Chen et al.’s scheme and inherits the merits of the classical IDS system. It has the security properties such as information-theoretical security, non-repudiation and unforgeability. At the same time, in our scheme, the verifier need not perform any quantum swap test. Therefore, our IDQSS is more secure and efficient.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

An Automated Disruption-Tolerant Key Management Framework for Critical Systems

Key management is critical to secure operation. Distributed control systems, such as Supervisory Control and Data Acquisition (SCADA) systems, have unique operational requirements that make conventional key management solutions less effective and burdensome. This paper presents a novel Kerberos-based framework for automated, disruption-tolerant key management for control system environments. Here, experimental tests and their results are presented to quantify the expected performance overhead of this approach. Additionally, Zeek sensor analytics are presented to aid in monitoring the health and security of the key management framework operation.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

Blockchain-Enabled Cyber-Secure Microgrid Control Using Consensus Algorithm: Preprint

This paper proposes a distributed control method based on a consensus algorithm for distributed energy resources (DERs) using blockchain as a secure communication medium for cyber resilience. Each DER communicates with a local blockchain server that is maintained by the distributed ledger technology to allow for securely sharing local measurements among neighboring assets to achieve the global control objectives, i.e., voltage and frequency regulation as well as accurate power sharing among the DERs, including collective grid-forming capability. To prove that the distributed control can retain system stability under a blockchain-induced variable communication delay, Lyapunov function-based stability analysis is carried out. This paper demonstrates the concept on an 11-bus test case developed in MATLAB Simulink, which has been modified from the IEEE 9-bus test case, to study dynamic operations of the five inverter-based DERs working with a blockchain-induced variable delay. The results validate the superior performance of the proposed control method, compared to heavily compromised operations of the other test cases without the security measure, affected by heavy communication delays and communication interruptions.

blockchain↗
DOE OSTI2025

Model-based Hierarchical Reinforcement Learning for Improved Physical Security Design: A Prototype

Prior work in FY24 developed an adversarial AI agent aid in path analysis of physical protection systems. This agent, trained using a model-based reinforcement learning algorithm, was able to successfully learn the most vulnerable path in facilities. It was able to extend the current state of practice for physical protection design by exhibiting dynamic behavior based on current environmental conditions. Whereas PathTrace largely performs a static, graph-based analysis, the AI agent was able to make decisions based on relative position in the facility, current conditions (was the adversarial agnet discovered?), and proximity to secondary targets. The agent demonstrated some novel capabilities, but had limitations that need to be resolved before it can be used for production purposes. For example, the adversarial agent generalizes poorly and takes a relatively long time to train. Nonetheless, there is still considerable promise for developing the adversarial agent further in order to explore even richer, more dynamic behaviors (e.g., adversary motivations, environmental debris, and more). This work considers a complementary idea; development of a planning agent. The planning agent is envisioned as an auto-complete-like tool that can help accelerate security system design by human experts. The agent would respect existing barriers and sensors placed by a human expert while offering cost-effective suggestions (i.e., implicitly balancing effectiveness with cost) to improve the design. The goal is for this agent to be part of an expert’s toolbox, not to totally upend the current state-of-practice, or to displace human experts. The ultimate goal would be concurrent training of both the adversarial and planning agent together, to learn entirely through self-play. This would represent an entirely new way of performing system deign. We selected a hierarchical, model-based reinforcement learning algorithm to serve as the planning agent. This is an extension of concepts used in the prior FY24 adversarial agent work. There, we had a single agent acting an environment. Here, we have two different sub-agents (policies), working together, to form a complete agent. There is a manager policy, which can select abstract goals on slower time scales, and a worker, which performs primitive actions to reach goals selected by the manager. It is worth noting that this class of algorithm is challenging to work with. From our understanding, our work is one of the first successful uses of model-based reinforcement learning (MBRL) in nuclear energy1 , and likely the first hierarchical model-based reinforcement learning application in nuclear energy. Further, this work is one of the first known attempts to apply AI to perform a design tasks in nuclear energy. Consequently, there were significant implementation challenges and the bulk of the work was focused on successful implementation and algorithm design. The results presented here are very low technology readiness level as a consequence of the lack of related literature, but still represent a significant step forward in the pursuit of applied AI for design.

42 ENGINEERING↗
DOE OSTI2020

BigData Express: Toward Predictable, Schedulable, and High-Performance Data Transfer [Slides]

BigData Express: a schedulable, predictable, and high-performance data transfer service. A peer-to-peer, scalable, and extensible data transfer model; A visually appealing, easy-to-use web portal; A high-performance data transfer engine; On-demand provisioning of end-to-end network paths with guaranteed QoS; Robust and flexible error handling; CILogon-based security (certificate version); A rich set of REST APIs to support scientific workflows

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

Impact of Blockchain Delay on Grid-Tied Solar Inverter Performance: Preprint

This paper investigates the impact of the delay resulting from a blockchain, a promising security measure, for a hierarchical control system of inverters connected to the grid. The blockchain communication network is designed at the secondary control layer for resilience against cyberattacks. To represent the latency in the communication channel, a model is developed based on the complexity of the blockchain framework. Taking this model into account, this work evaluates the plant’s performance subject to communication delays, introduced by the blockchain, among the hierarchical control agents. In addition, this article considers an optimal model-based control strategy that performs the system’s internal control loop. The work shows that the blockchain’s delay size influences the convergence of the power supplied by the inverter to the reference at the point of common coupling. In the results section, real-time simulations on OPAL-RT are performed to test the resilience of two parallel inverters with increasing blockchain complexity.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2020

An Assessment of the Usability of Machine Learning Based Tools for the Security Operations Center

Gartner, a large research and advisory company, anticipates that by 2024 80% of security operation centers (SOCs) will use machine learning (ML) based solutions to enhance their operations. 1 1 https://www.ciodive.com/news/how-data-science-tools-can-lighten-the-load-for-cybersecurity-teams/572209/ In light of such widespread adoption, it is vital for the research community to identify and address usability concerns. This work presents the results of the first in situ usability assessment of ML-based tools. With the support of the US Navy, we leveraged the national cyber range-a large, air-gapped cyber testbed equipped with state-of-the-art network and user emulation capabilities-to study six US Naval SOC analysts' usage of two tools. Our analysis identified several serious usability issues, including multiple violations of established usability heuristics for user interface design. We also discovered that analysts lacked a clear mental model of how these tools generate scores, resulting in mistrust a and/or misuse of the tools themselves. Surprisingly, we found no correlation between analysts' level of education or years of experience and their performance with either tool, suggesting that other factors such as prior background knowledge or personality play a significant role in ML-based tool usage. Our findings demonstrate that ML-based security tool vendors must put a renewed focus on working with analysts, both experienced and inexperienced, to ensure that their systems are usable and useful in real-world security operations settings.

Oesch, T↗
DOE OSTI2017

Nevada National Security Site Environmental Report 2016

This Nevada National Security Site Environmental Report (NNSSER) was prepared to satisfy DOE Order DOE O 231.1B, “Environment, Safety and Health Reporting.” Its purpose is to (1) report compliance status with environmental standards and requirements, (2) present results of environmental monitoring of radiological and nonradiological effluents, (3) report estimated radiological doses to the public from releases of radioactive material, (4) summarize environmental incidents of noncompliance and actions taken in response to them, (5) describe the National Nuclear Security Administration Nevada Field Office (NNSA/NFO) Environmental Management System and characterize its performance, and (6) highlight significant environmental programs and efforts. This NNSSER summarizes data and compliance status for calendar year 2016 at the Nevada National Security Site (NNSS) and its two Nevada-based support facilities, the North Las Vegas Facility (NLVF) and the Remote Sensing Laboratory–Nellis (RSL-Nellis). It also addresses environmental restoration (ER) projects conducted at the Tonopah Test Range (TTR) and the Nevada Test and Training Range (NTTR). NNSA/NFO directs the management and operation of the NNSS and six sites across the nation. In addition to the NNSA itself, the six sites include two in Nevada (NLVF and RSL-Nellis) and four in other states (RSL-Andrews in Maryland, Livermore Operations in California, Los Alamos Operations in New Mexico, and Special Technologies Laboratory in California). Los Alamos, Lawrence Livermore, and Sandia National Laboratories are the principal organizations that sponsor and implement the nuclear weapons programs at the NNSS. National Security Technologies, LLC (NSTec), is the current Management and Operating contractor accountable for the successful execution of work and ensuring that work is performed in compliance with environmental regulations. The six sites all provide support to enhance the NNSS as a location for its multiple missions. The three major NNSS missions include National Security/Defense, Environmental Management, and Nondefense. The major programs that support these missions are Stockpile Stewardship and Management, Nonproliferation and Counterterrorism, Nuclear Emergency Response, Strategic Partnership Projects, Environmental Restoration, Waste Management, Conservation and Renewable Energy, Other Research and Development, and Infrastructure. The major facilities that support the programs include the U1a Facility, Big Explosives Experimental Facility (BEEF), Device Assembly Facility, Dense Plasma Focus Facility, Joint Actinide Shock Physics Experimental Research Facility, Radiological/Nuclear Countermeasures Test and Evaluation Complex, Nonproliferation Test and Evaluation Complex (NPTEC), Radiological/Nuclear Weapons of Mass Destruction Incident Exercise Site, the Area 5 Radioactive Waste Management Complex (RWMC), and the Area 3 Radioactive Waste Management Site (RWMS).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2018

Characterization of Flexible Operation Performance of N-R HES Components in support of a Model-Based Pre-conditioner

The concept of Nuclear-Renewable Hybrid Energy Systems (N-R HES) is meant to combine different energy technologies in synergistic ways to achieve a more secure and economical energy supply. The N-R HES unit is constituted by a small-sized pressurized water reactor coupled with a Rankine energy conversion cycle, a gas-fired turbine, an energy storage component, and a hydrogen production plant.

08 HYDROGEN↗