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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Quantum Computing for Energy-Related Applications

Growing interest in quantum computing and simulations have created opportunities for its deployment to improve processes pertaining to energy production, distribution, and consumption. While quantum computing is considered as a paradigm shift in our basic understanding of physical computation, effective implementation of quantum computing in energy applications also depends on progress and development in the dimensions of both quantum computing hardware and quantum computing algorithms. To fully address the status and future challenges of quantum information science (QIS) applied within the energy sector, in this presentation, we firstly summarize recent advancements on the applications of quantum computing to energy infrastructure and materials, complex energy system processes, advanced manufacturing, and energy system security. Then, we will demonstrate the results of quantum computing both on a simulator and a quantum device accessing from OLCF. Our first example is to use the variational quantum eigensolver (VQE) with a unitary coupled cluster with singles and doubles (UCCSD) ansatz to simulate a series of LixHyq molecules (q=-1, 0, +1). The obtained results showed that the quantum computing VQE-UCCSD is comparable to classical CCSD for small systems like LiH with respect to full configuration interaction (FCI). Targeting on CO2 capture application, our second example is to use VQE to quantify molecular vibrational energies and reaction pathways between CO2 and a simplified amine-based solvent model—NH3 to form H2NCOOH. This research showcases quantum computing applications in the study of CO2 capture reactions.

Duan, Yuhua↗
DOE OSTI2015

Nuclear Security Education Program at the Pennsylvania State University

The availability of trained and qualified nuclear and radiation security experts worldwide has decreased as those with hands-on experience have retired while the demand for these experts and skills have increased. The U.S. Department of Energy's National Nuclear Security Administration's (NNSA) Global Threat Reduction Initiative (GTRI) has responded to the continued loss of technical and policy expertise amongst personnel and students in the security field by initiating the establishment of a Nuclear Security Education Initiative, in partnership with Pennsylvania State University (PSU), Texas A and M (TAMU), and Massachusetts Institute of Technology (MIT). This collaborative, multi-year initiative forms the basis of specific education programs designed to educate the next generation of personnel who plan on careers in the nonproliferation and security fields with both domestic and international focus. The three universities worked collaboratively to develop five core courses consistent with the GTRI mission, policies, and practices. These courses are the following: Global Nuclear Security Policies, Detectors and Source Technologies, Applications of Detectors/Sensors/Sources for Radiation Detection and Measurements Nuclear Security Laboratory, Threat Analysis and Assessment, and Design and Analysis of Security Systems for Nuclear and Radiological Facilities. The Pennsylvania State University (PSU) Nuclear Engineering Program is a leader in undergraduate and graduate-level nuclear engineering education in the USA. The PSU offers undergraduate and graduate programs in nuclear engineering. The PSU undergraduate program in nuclear engineering is the largest nuclear engineering programs in the USA. The PSU Radiation Science and Engineering Center (RSEC) facilities are being used for most of the nuclear security education program activities. Laboratory space and equipment was made available for this purpose. The RSEC facilities include the Penn State Breazeale Reactor (PSBR), gamma irradiation facilities (in-pool irradiator, dry irradiator, and hot cells), neutron beam laboratory, radiochemistry laboratories, and various radiation detection and measurement laboratories. A new nuclear security education laboratory was created with DOE NNSA- GTRI funds at RSEC. The nuclear security graduate level curriculum enables the PSU to educate and train future nuclear security experts, both within the United States as well as worldwide. The nuclear security education program at Penn State will grant a Master's degree in nuclear security starting fall 2015. The PSU developed two courses: Nuclear Security- Detector And Source Technologies and Nuclear Security- Applications of Detectors/Sensors/Sources for Radiation Detection and Measurements (Laboratory). Course descriptions and course topics of these courses are described briefly: - Nuclear Security - Detector and Source Technologies; - Nuclear Security - Applications of Detectors/Sensors/Sources for Radiation Detection and Measurements Laboratory.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2015

High yield neutron generator based on a high-current gasdynamic electron cyclotron resonance ion source

In present paper, an approach for high yield compact D-D neutron generator based on a high current gasdynamic electron cyclotron resonance ion source is suggested. Results on dense pulsed deuteron beam production with current up to 500 mA and current density up to 750 mA/cm{sup 2} are demonstrated. Neutron yield from D{sub 2}O and TiD{sub 2} targets was measured in case of its bombardment by pulsed 300 mA D{sup +} beam with 45 keV energy. Neutron yield density at target surface of 10{sup 9} s{sup −1} cm{sup −2} was detected with a system of two {sup 3}He proportional counters. Estimations based on obtained experimental results show that neutron yield from a high quality TiD{sub 2} target bombarded by D{sup +} beam demonstrated in present work accelerated to 100 keV could reach 6 × 10{sup 10} s{sup −1} cm{sup −2}. It is discussed that compact neutron generator with such characteristics could be perspective for a number of applications like boron neutron capture therapy, security systems based on neutron scanning, and neutronography.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2018

Situ: Identifying and Explaining Suspicious Behavior in Networks

Despite the best efforts of cyber security analysts, networked computing assets are routinely compromised, resulting in the loss of intellectual property, the disclosure of state secrets, and major financial damages. Anomaly detection methods are beneficial for detecting new types of attacks and abnormal network activity, but such algorithms can be difficult to understand and trust. Network operators and cyber analysts need fast and scalable tools to help identify suspicious behavior that bypasses automated security systems, but operators do not want another automated tool with algorithms they do not trust. Experts need tools to augment their own domain expertise and to provide a contextual understanding of suspicious behavior to help them make decisions. In this paper we present Situ, a visual analytics system for discovering suspicious behavior in streaming network data. Situ provides a scalable solution that combines anomaly detection with information visualization. The system's visualizations enable operators to identify and investigate the most anomalous events and IP addresses, and the tool provides context to help operators understand why they are anomalous. Finally, operators need tools that can be integrated into their workflow and with their existing tools. This paper describes the Situ platform and its deployment in an operational network setting. Furthermore, we discuss how operators are currently using the tool in a large organization's security operations center and present the results of expert reviews with professionals.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Engineering Privacy at the Edge: A Practical Guide to Differential Privacy in System Architectures

The rapid expansion of distributed and edge computing platforms—spanning autonomous vehicles, IoT sensors, and healthcare monitors—has heightened concerns about data privacy. Differential Privacy (DP) offers a rigorous mathematical framework to protect sensitive information while retaining analytical utility. This tutorial introduces the foundations of DP for both numerical and categorical datasets and extends the discussion to correlation-aware techniques tailored for structured and high-dimensional data. Hands-on demonstrations will begin with the PETINA (Privacy prEservaTIoN Algorithms) package for numerical data and continue with MIC-DP (Maximum Information Correlated Differential Privacy) for tabular data. Designed for researchers and practitioners in secure systems, embedded architectures, and AI accelerators, the tutorial emphasizes practical and scalable methods for integrating DP into real-world system designs.

Kotevska, Olivera [ORNL] (ORCID:0000000316772243)↗
DOE OSTI2016

Method of securing filter elements

A filter securing system including a filter unit body housing; at least one tubular filter element positioned in the filter unit body housing, the tubular filter element having a closed top and an open bottom; a dimple in either the filter unit body housing or the top of the tubular filter element; and a socket in either the filter unit body housing or the top of the tubular filter element that receives the dimple in either the filter unit body housing or the top of the tubular filter element to secure the tubular filter element to the filter unit body housing.

42 ENGINEERING↗
NASA NTRS2010

Efficient Web Services Policy Combination

Large-scale Web security systems usually involve cooperation between domains with non-identical policies. The network management and Web communication software used by the different organizations presents a stumbling block. Many of the tools used by the various divisions do not have the ability to communicate network management data with each other. At best, this means that manual human intervention into the communication protocols used at various network routers and endpoints is required. Developing practical, sound, and automated ways to compose policies to bridge these differences is a long-standing problem. One of the key subtleties is the need to deal with inconsistencies and defaults where one organization proposes a rule on a particular feature, and another has a different rule or expresses no rule. A general approach is to assign priorities to rules and observe the rules with the highest priorities when there are conflicts. The present methods have inherent inefficiency, which heavily restrict their practical applications. A new, efficient algorithm combines policies utilized for Web services. The method is based on an algorithm that allows an automatic and scalable composition of security policies between multiple organizations. It is based on defeasible policy composition, a promising approach for finding conflicts and resolving priorities between rules. In the general case, policy negotiation is an intractable problem. A promising method, suggested in the literature, is when policies are represented in defeasible logic, and composition is based on rules for non-monotonic inference. In this system, policy writers construct metapolicies describing both the policy that they wish to enforce and annotations describing their composition preferences. These annotations can indicate whether certain policy assertions are required by the policy writer or, if not, under what circumstances the policy writer is willing to compromise and allow other assertions to take precedence. Meta-policies are specified in defeasible logic, a computationally efficient non-monotonic logic developed to model human reasoning. One drawback of this method is that at one point the algorithm starts an exhaustive search of all subsets of the set of conclusions of a defeasible theory. Although the propositional defeasible logic has linear complexity, the set of conclusions here may be large, especially in real-life practical cases. This phenomenon leads to an inefficient exponential explosion of complexity. The current process of getting a Web security policy from combination of two meta-policies consists of two steps. The first is generating a new meta-policy that is a composition of the input meta-policies, and the second is mapping the meta-policy onto a security policy. The new algorithm avoids the exhaustive search in the current algorithm, and provides a security policy that matches all requirements of the involved metapolicies.

Vatan, Farrokh↗
DOE OSTI2019

Innovative Hot Lab Concept for Advanced D and D Application - 19175

Hot Labs are used in the nuclear industry for various purposes: maintenance of nuclear reactor, sampling and testing of fuel, inspection activities and decommissioning. Despite their vast use, their current designs and operations do not meet entirely today's needs and requirements of the operations nor tomorrow's. This paper will give an overview of the research and investigations performed around Hot Cells design and concept in order to integrate new operability modes and functions. The overall idea is to bring modularity, flexibility and adaptability to the Hot Lab nuclear industry. Taking the key principles of Model Based System Engineering, an interoperable data model, the most advanced digital technologies (Building Information Modelling - BIM, Virtual Reality / Augmented Reality, Artificial Intelligence), and looking at all the life-cycle of such a facility, a concept design of a new type of Hot Lab has been developed. Four mains aspects are implemented during this study: Implement the principles of the Industry 4.0; use modular and flexible solutions; explore the concept of in service maintenance and predictive maintenance; optimise the decommissioning and dismantling process by taking into account the entire life-cycle of the facility. The design was developed as a case study taking several assumptions to adapt to any project. The design developed demonstrates that modularity and flexibility can be brought in without compromising the core safety functions of such a facility. This Hot Lab concept brings the current Hot Lab to the next level as the design has been adapted to meet the current operational needs, implement novel ideas and consider its entire life-cycle. This paper will demonstrate how decommissioning and dismantling operations can become more efficient and safer with such a concept. In addition, the Model Based System Engineering approach used from the beginning of the design phase allows to have an optimum architecture during its entire lifetime. It also allowed to flag new topics to be further developed for the benefit of the nuclear industry as a whole. A first example would be the development of the Control System using digital tools and artificial intelligence to run remotely controlled equipment inside the Hot Lab. Assystem is an international engineering group. As a key participant in the nuclear industry for over 50 years, the Group supports its clients in managing their capital expenditure throughout their asset life-cycles. Assystem can offer support in project management, design, digital engineering, industrial control systems, security and safety and industrial digitalisation. Assystem's Imagine program is an internal program intending to serve as an incubator for the development of innovations. The Innovative Hot Lab project integrates one of the four innovation projects Assystem choose to develop and invest in. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Analysis and Mitigation of Cascading Outages Using an Interaction Graph Addressing Transient Stability

Cascading outages of power systems pose great threats to system security and reliability, potentially leading to large-scale blackouts. For analysis and mitigation of cascading outages, this paper proposes a transient stability-incorporated interaction graph. This graph statistically quantifies the interactions among line outages and instabilities of generators, which can model propagation paths and patterns of cascading outages. Compared with an interaction graph that only models line outages, this new interaction graph provides important insights on how transient instability occurs along with cascading outages. It also offers more effective strategies for mitigating outage propagation. The proposed interaction graph can be constructed from datasets of historical or simulated cascading events. It is demonstrated on an NPCC 140-bus system with mitigation strategies.

Guo, Zhenping↗
DOE OSTI2026

Netload Range Cost Curves for Coordinated Transmission-Distribution Planning Under DER Growth Uncertainty

The increasing penetration of distributed energy resources (DERs) requires better coordination between transmission and distribution (T&D) planning to ensure system security and cost efficiency. However, misaligned planning horizons, computational burdens, and privacy concerns hinder effective coordination, leading to either underutilized resources caused by overinvestments or reliability risks due to underinvestment. To address this challenge, we introduce netload range cost curves (NRCCs), a novel approach for managing long-term DER growth uncertainty through T&D coordination, while preserving existing data-sharing and regulatory structures. NRCCs provide pairs of (i) peak substation netload guarantees and (ii) corresponding distribution upgrade options and costs, enabling their seamless integration into transmission planning workflows. To compute NRCCs efficiently, we develop a transmission-aware distribution network planning (TADNP), which is subsequently integrated to an iterative computation procedure. These NRCCs are then embedded into an NRCC-informed transmission planning model to enable resource-efficient coordination. We illustrate our proposed approach with a case study based on realistic distribution and transmission systems in the San Francisco Bay Area, California. Our results indicate the possibility of dramatic savings in transmission investments by incorporating the proposed NRCC-integrated T&D coordination framework.

Li, Yujia↗
DOE OSTI2015

Vulnerability of OFDR-based distributed sensors to radiations

Silica-based optical fibers have recently attracted much interest for their use in harsh environments such as the ones encountered in space, military or high energy physics applications. Small size, fast response, light weight and immunity to electromagnetic fields are favorable advantages that often become decisive for fiber sensing to be chosen over other conventional sensing technologies. As an important and representative example, Fukushima's accident highlighted weaknesses in the safety of nuclear power plants. Since, one of the strategic research axis of the nuclear industry is devoted to the development of novel technologies and sensors to enhance and reinforce the safety in nuclear power plants, especially in the case of accidental conditions associated with a strong increase of the constraints applied to the fiber-based system. The objective of this research field is to develop classes of distributed fiber-based sensors using scattering-based techniques, powerful solutions for various measurands measurement. Optical fiber properties, indeed, depend on several external parameters such as temperature, strain and therefore the fiber itself can be used as the sensitive element. Different classes of fiber-based sensing techniques have been recently investigated such as Fiber Bragg Gratings (FBGs) for discrete measurements and Brillouin, Raman and Rayleigh [8,9] scattering based techniques for distributed measurements of various environmental parameters. Whereas Brillouin and Raman sensor resolutions remain in the range of one meter, the advantage of Rayleigh scattering based technique is that it offers very high spatial resolution from 1 cm down to few μm over several hundred meters of fiber length down to few meters respectively. For nuclear industry, integrating fibers-based sensors has to improve the performances (resolution, operating range,...) of security systems in current nuclear power plants (NPPs) and offers new alternative technologies that may overcome the issues identified for next generation of NPPs. Such integration will only be possible if the OFDR based systems are able to resist to the constraints associated with industrial environments, one of the most constraining being the presence of high level of radiations. In this work, we carry out a systematic study to highlight the OFDR interest and sensitivity to probe the optical samples at high irradiation dose levels. The responses of five optical fibers types, from radiation hardened to radiation sensitive ones, are investigated to explore the influence of both the material compositions and the γ-irradiation on the ODFR sensors. Using these samples, we should highlight the influence of the core dopant concentration on the observed radiation-induced changes as well as the difference observed when the cladding is either radiation resistant or radiation sensitive. Our samples were irradiated using a {sup 60}Co source facility reaching total doses varying from 1 MGy up to a maximum of 10 MGy. All the measurements are performed after diverse months from irradiation to study permanents effects induced from these high γ-rays doses. We'll present at the conference all the experimental results acquired and use them to estimate the potential of OFDR-based systems for operation in radiation environments. (authors)

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2017

A Dimensionally Aligned Signal Projection for Classification of Unintended Radiated Emissions

Characterization of unintended radiated emissions (URE) from electronic devices plays an important role in many research areas from electromagnetic interference to nonintrusive load monitoring to information system security. URE can provide insights for applications ranging from load disaggregation and energy efficiency to condition-based maintenance of equipment-based upon detected fault conditions. URE characterization often requires subject matter expertise to tailor transforms and feature extractors for the specific electrical devices of interest. We present a novel approach, named dimensionally aligned signal projection (DASP), for projecting aligned signal characteristics that are inherent to the physical implementation of many commercial electronic devices. These projections minimize the need for an intimate understanding of the underlying physical circuitry and significantly reduce the number of features required for signal classification. We present three possible DASP algorithms that leverage frequency harmonics, modulation alignments, and frequency peak spacings, along with a two-dimensional image manipulation method for statistical feature extraction. To demonstrate the ability of DASP to generate relevant features from URE, we measured the conducted URE from 14 residential electronic devices using a 2 MS/s collection system. Furthermore, a linear discriminant analysis classifier was trained using DASP generated features and was blind tested resulting in a greater than 90% classification accuracy for each of the DASP algorithms and an accuracy of 99.1% when DASP features are used in combination. Furthermore, we show that a rank reduced feature set of the combined DASP algorithms provides a 98.9% classification accuracy with only three features and outperforms a set of spectral features in terms of general classification as well as applicability across a broad number of devices.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Impact of cyberattacks on safety and stability of connected and automated vehicle platoons under lane changes

Connected and automated vehicles (CAVs) offer a huge potential to improve the operations and safety of transportation systems. However, the use of smart devices and communications in CAVs introduce new risks. CAVs would leverage vehicle to vehicle (V2V) and vehicle to infrastructure (V2I) communication, thus providing additional system access points compared to traditional systems. Automation makes these systems more vulnerable and increases the consequences of cyberattacks. This study utilizes an infrastructure-based communication platform consisting of cooperative adaptive cruise control and lane control advisories developed by the authors to perform cyber risk assessment of CAVs. The study emulates three types of cyberattacks (message falsification, dedicated denial of service, and spoofing attacks) in a representative traffic environment consisting of multiple CAV platoons and lane change events to analyze the safety and stability impacts of the cyberattacks. Simulation experiments using VISSIM reveals that traffic stream and CAV string is unstable under all three types of cyberattacks. The worst case is represented by the message falsification attack. Increases in volatility are observed over a no attack case, with variations increasing by an average of 43%–51% along with an increase of over 3000 crash conflicts. Similarly, lane change crash conflicts are observed to be more severe compared to rear end crash conflicts, showing a higher probability of severe injuries. Further, the case of slight cyberattack on a single CAV also creates significant disruption in the traffic stream. Analysis of variance (ANOVA) reveals the statistical significance of the results. Furthermore, these results pave the way for future design of secure systems from a monitoring perspective.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

A robust dynamic state estimation approach against model errors caused by load changes

Dynamic state estimation (DSE) plays an important role in power system security monitoring and online control. In practice, there are two approaches to implementing DSE. The first approach is distributed DSE, which is based on the assumption that the terminal bus of each generator can be measured by PMUs (phasor measurement units). The assumption cannot be satisfied currently, however, because PMUs usually are installed at important high-voltage buses such as 500-kV buses installed in portions of the grid overseen by the Western Electricity Coordinating Council. Another issue of this approach is that performance of DSE is vulnerable to bad measurement data. The reason for this vulnerability is that DSE is performed separately through measurements at each terminal bus, and measurements at terminal buses are the only measurement upon which DSE can rely. Therefore, important redundant measurements are not included in this approach. The second approach is centralized DSE. This approach does not have the requirement for PMU location, and redundant measurements can be considered fully. However, load changes and grid topology changes impact centralized DSE. In this paper, we propose a new approach for handling the impact of load changes on DSE. We have developed a new algorithm that includes two sequential steps. In the first step, errors caused by load changes are detected by analyzing the difference between prediction results and measured results. In the second step, once model error is detected, a model optimization procedure is run to correct the error so the state estimation error can be mitigated. Simulation results from the IEEE 68 bus system show that the proposed approach can effectively handle model errors caused by load changes.

robust dynamic state estimation, load change, powe↗
DOE OSTI2019

Adjustable and distributionally robust chance-constrained economic dispatch considering wind power uncertainty

This paper proposes an adjustable and distributionally robust chance-constrained (ADRCC) optimal power flow (OPF) model for economic dispatch considering wind power forecasting uncertainty. The proposed ADRCC-OPF model is distributionally robust because the uncertainties of the wind power forecasting are represented only by their first- and second-order moments instead of a specific distribution assumption. The proposed model is adjustable because it is formulated as a second-order cone programming (SOCP) model with an adjustable coefficient. This coefficient can control the robustness of the chance constraints, which may be set up for the Gaussian distribution, symmetrically distributional robustness, or distributionally robust cases considering wind forecasting uncertainty. The conservativeness of the ADRCC-OPF model is analyzed and compared with the actual distribution data of wind forecasting error. The system operators can choose an appropriate adjustable coefficient to tradeoff between the economics and system security.

17 WIND ENERGY↗
DOE OSTI2023

Machine Learning-based Intrusion Detection for Smart Grid Computing: A Survey

Machine learning (ML)-based intrusion detection system (IDS) approaches have been significantly applied and advanced the state-of-the-art system security and defense mechanisms. In smart grid computing environments, security threats have been significantly increased as shared networks are commonly used, along with the associated vulnerabilities. However, compared to other network environments, ML-based IDS research in a smart grid is relatively unexplored, although the smart grid environment is facing serious security threats due to its unique environmental vulnerabilities. In this article, we conducted an extensive survey on ML-based IDS in smart grids based on the following key aspects: (1) The applications of the ML-based IDS in transmission and distribution side power components of a smart power grid by addressing its security vulnerabilities; (2) dataset generation process and its usage in applying ML-based IDSs in the smart grid; (3) a wide range of ML-based IDSs used by the surveyed papers in the smart grid environment; (4) metrics, complexity analysis, and evaluation testbeds of the IDSs applied in the smart grid; and (5) lessons learned, insights, and future research directions.

SCADA↗
DOE OSTI2019

Blockchain Based Remote Data Integrity Checking Tool v1.0

Computer System Security: The software is used to perform remote data integrity checking without relying on a single third party. In order to remove the trusted third party our tool uses distributed ledger (Blockchain) technology. The ledger is used to store evidences (in the form of hash values). These values are used as an input in the integrity checking process.

Wonjiga, Amir↗