Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “time 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 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

nnopf

SAND2026-19433O The nnopf tool addresses the optimal power flow (OPF) problem by optimizing electricity delivery from generating plants to consumers. At the same time, it minimizes costs and adheres to power grid constraints. While traditional methods for solving OPF can be computationally intensive, the tool mitigates this challenge by training neural networks on power grids to predict optimal solutions for the OPF problem. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Hart, William [Sandia National Lab. (SNL-CA), Live↗
DOE OSTI2021

Tensor Text-Mining Methods for Malware Identification and Detection, Malware Dynamics Characterization, and Hosts Ranking

Malware is one of the most persistent and costly cyber threats endangering reputation, confidentiality, integrity, and availability for organizations and national security. Consequently, many of the incident detection and prevention systems, and incident responders have begun to utilize machine learning as a helper in the fight against malware and other cyber threats. However, cyber defenders rely on interpretability and generalizability, yet the popular machine learning methods are black-box and often use traditional supervised solutions that do not generalize to novel malware. Therefore, there is a need to improve the existing solutions. At the same time, the majority of the prior research ignored essential evaluation criteria when reporting the results of their methods, which disables the safe reproducibility of the methods in a production environment. Tensor decomposition, on the other hand, enables interpretable unsupervised analysis of the large-scale data for the discovery of hidden patterns. Our findings, performed on real-world and large-scale experiments, show that tensor factorization-based methods yield performance results that surpasses or competes with existing supervised solutions with the added benefit of interpretability and generalizability. With the ability to analyze complex and large-scale data using tensors, we report results that reflect real-world production environments. We propose to develop new game- changing tools for malware identification and characterization that can trace malware evolution, rank the infected or malicious hosts, and streamline the work of incident response teams, malware analysts, and incident detection and prevention systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Deep anomaly detection for industrial systems: a case study

We explore the use of deep neural networks for anomaly detection of industrial systems where the data are multivariate time series measurements. We formulate the problem as a self-supervised learning where data under normal operation are used to train a deep neural network autoregressive model, i.e., use a window of time series data to predict future data values. The aim of such a model is to learn to represent the system dynamic behavior under normal conditions, while expect higher model vs. measurement discrepancies under faulty conditions. In real world applications, many control settings are discrete in nature. In this paper, vector embedding and joint losses are employed to deal with such situations. Both LSTM and CNN based deep neural network backbones are studied on the Secure Water Treatment (SWaT) testbed datasets. Also, Support Vector Data Description (SVDD) method is adapted to such anomaly detection settings with deep neural networks. Evaluation methods and results are discussed based on the SWaT dataset along with potential pitfalls.

anomaly detection, deep neural network↗
DOE OSTI2020

Load altering attack-tolerant defense strategy for load frequency control system

Cyber attacks are emerging threats to every information-oriented energy management system. By violating the cyber systems, the hacker can disrupt the security and stability due to the strong coupling between the cyber and physical facilities. In this paper, one type of cyber attacks designated as the load altering attack is studied for the power system frequency control, and corresponding defense strategies are proposed to improve the frequency control performance. Considering the difficulty of the application of model-based controller into large-scale power systems, a novel model-free defense framework is for the first time presented. Under this framework, both active defense and passive defense strategies are designed. The former assumes that the defender has the initiative to learn different attack scenarios. Adaptive defense strategies are implemented using the online attack identification information and off-line trained strategy pool. The latter assumes that the defender passively tolerates various attack scenarios via the pre-trained off-line strategy. Both approaches prove to be effective through validation based on the IEEE benchmark systems. The proposed defense framework and defense strategies can be extended to other energy control systems to enhance their attack tolerance capability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Neutron calorimeter development at fission and fusion pulsed neutron sources

A neutron calorimeter fielded in pulsed neutron irradiation experiments at the National Ignition Facility (NIF) and White Sands Missile Range Fast Burst Reactor (WSMR FBR) is described, and results are provided and discussed. The calorimeter is modular in design to allow fielding of various neutron absorber materials and thicknesses, as well as use at both fission and fusion sources, all of which has been done. Neutron calorimeters designed for fission sources have been fielded at fusion sources as well, but these instances are not documented in available literature—making this work novel. The functional calorimeter consists of a neutron absorber and two sheathed, grounded thermocouples secured within a subassembly made of thermally insulating materials. This subassembly is placed into a sealed vessel for material and facility safety considerations. The device was fielded at NIF in four polar-direct-drive exploding pusher shots and eleven WSMR FBR pulses. Calorimeter data from NIF experiments show a discernable thermal response accredited to neutron heating within the first 10 s, but the data are dominated by noise from ambient X-ray heating after time = 10 s post-pulse. This response is highly consistent between shots and linearly related to incident neutron fluence and neutron absorber thickness. A temperature rise of 1.1E-2 K/(10 13 neutrons/cm 2 ) per millimeter of absorber thickness was determined for both 0.4 mm and 1 mm thick depleted uranium absorbers with linear best fit R 2 of 0.97 and 0.98 for each thickness and y-axis offsets of 8.8E-3 and 1.3E-2, respectively. WSMR FBR experiment data show a temperature rise of 6.2E-2 K/(10 13 neutrons/cm 2 ) with linear best fit R 2 of 0.14 and y-axis offset of 7.6E-3 for a calorimeter with a 1 mm thick enriched boron carbide ( 10 B 4 C) absorber, though it must be noted that device-to-device variability is significant at both facilities. So these data are also affected by noise on a similar timescale as at NIF, though the noise is significantly lesser in magnitude but oscillatory.

42 ENGINEERING↗
DOE OSTI2023

Transformer Health Monitoring via Synchrophasors

Traditional transformer protection schemes such as differential protection operate once the transformer is in a critical state. Proactive means of transformer health evaluation such as Sweep Frequency Response Analysis, can only be performed periodically with the transformer out-of-service. This work presents a framework where the health and structural integrity of transformers is monitored via synchrophasors in real-time. Synchrophasors and subspace estimation techniques are used to build reduced-order models which are then analyzed across multiple domains. A diagnostics algorithm is developed and tested via Matlab simulations. Test results are promising, opening up new prospects in transformer protection research.

cyber-physical security↗
DOE OSTI2024

ARPA-E Grid Optimization (GO) Competition Challenge 3

Synthetic Input Data and Team Results for the GO Competition Challenge 3 for Events 1 - 4 and the Sandbox, along with problem and format descriptions and code to validate data and solutions, are available here. Data for industry scenarios will not be made public. The Grid Optimization (GO) Competition Challenge 3 focused on the security-constrained optimal power flow (SCOPF) problem. It is part of a continuing effort begun with Challenges 1 and 2, to successfully discover, develop, and test innovative and disruptive software solutions for critical energy challenges and to overcome existing barriers. The broader goal of the of the GO Competition is to accelerate the development of transformational and disruptive methods for solving problems related to the electric power grid and to provide a transparent, fair, and comprehensive evaluation of new solution methods. Challenge 3 used multiperiod dynamic markets, including advisory models for extreme weather events, day-ahead markets, and the real-time markets with an extended look-ahead. In Event 4, whose submission window was August 31-September 4, 2023, 14 teams solved for the objective values of 669 scenarios (39 scenarios required solutions both with and without line switching being allowed). The 591 synthetic scenarios from 9 network models (3.6 GB) are available here. Ten teams were funded to participate and 7 won prizes totaling $2,400,000. The largest prize ($550,000) went to Mississippi State University. An additional $600,000 was awarded in Event 3 (6/15-16/2023). No prizes were awarded in Events 1 (1/25-27/2023) or 2 (4/13-14/2023). For more information on the competition and challenge see the "GO Competition Challenge 3 Information" resource below.

ACOPF↗
DOE OSTI2020

Thermal Energy Storage Using Solid Particles for Long-Duration Energy Storage

The rapid growth of renewable energy increases the importance of economically firming the electricity supply from variable solar photovoltaic- and wind-power generators. Energy storage will be the key to manage variability and to bridge the generation gap over time scales of hours or days for high renewable grid integration. The integration of renewable power and storage of excess electricity has several significant and positive impacts including: 1) expanding the renewable energy portion of total electricity generation, 2) improving the peak-load response, and 3) coordinating the electricity supply and demand over the grid. Long-duration energy storage can potentially complement the reduction of fossil-fuel baseload generation that otherwise would risk grid security when a large portion of grid power comes from variable renewable sources. Several energy storage methods are deployed or under development, including mechanical, chemical or electrochemical, and thermal energy storage (TES). Comparing their economic potential for different scales and applications helps identify suitable technology to support high renewable grid integration. Despite the progress of TES technologies developed and deployed with concentrating solar power (CSP) systems, TES has been undervalued for its potential role in electric energy storage. This paper introduces TES methods applicable to grid energy storage and particularly focuses on solid-particle-based TES to serve the purpose of long-duration energy storage (LDES). The objective of this paper is to present a standalone particle-based TES system for electric storage and to show the potential of TES systems for LDES applications over other energy storage methods such as batteries, compressed-air energy storage, or pumped-storage hydropower.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2023

Hydrologic Impacts of a Strike-Slip Fault Zone: Insights from Joint 3D Body-Wave Tomography of Rock Valley

The Rock Valley fault zone (RVFZ), an intraplate strike-slip fault zone in the southern Nevada National Security Site (NNSS), hosted a series of very shallow (<3 km) earthquakes in 1993. The RVFZ may also have hydrological significance within the NNSS, potentially playing a role in regional groundwater flow, but there is a lack of local hydrological data. In the Spring of 2021, we collected active-source accelerated weight drop seismic data over part of the RVFZ to better characterize the shallow subsurface. Here, we manually picked ~17,000 P-wave travel times and over 14,000 S-wave travel times, which were inverted for P-wave velocity (V P ), S-wave velocity (V S ), and V P /V S ratio in a 3D joint tomographic inversion scheme. Seismic velocities are imaged as deep as ~700 m in areas and generally align with geologic and structural expectations. V P and V S are relatively reduced near mapped and inferred faults, with the most prominent lower V P and V S zone around the densest collection of faults. We image V P /V S ratios ranging from ~1.5 to ~2.4, the extremes of which occur at a depth of ~100 m and are juxtaposed across a fault. One possible interpretation of the imaged seismic velocities is enhanced fault damage near the densest collection of faults with relatively higher porosity and/or crack density at ~100 m depth, with patches of semiperched groundwater present in the sedimentary rock in higher V P /V S areas and drier rock in lower V P /V S areas. A relatively higher V P /V S area beneath the densest faults persists at depth, which suggests percolation of groundwater via the fault damage zone to the regionally connected lower carbonate aquifer. Potentially, the presence and movement of groundwater may have played a role in the 1993 earthquake aftershocks.

58 GEOSCIENCES↗
DOE OSTI2021

Baylor University Campus-Wide Deep Dive

In January 2020, staff members from the Engagement and Performance Operations Center (EPOC) and the Lonestar Education And Research Network (LEARN) met with researchers and staff at Baylor University for the purpose of a Campus-Wide Deep Dive into research drivers. The goal of this meeting was to help characterize the requirements for five campus research use cases and to enable cyberinfrastructure support staff to better understand the needs of the researchers they support. Profiled scientific use cases included: - Experimental High Energy Physics (HEP) - Proton Computed Tomography (pCT) - Nutrition and Relation to Digestive Microbiome - Baylor University Core Research Facilities - Molecular Quantum-dot Cellular Automata (QCA), and Material Science of Quantum Computing - Modeling and Simulation of Low-Dimensional and Nano-Structured Materials - Computational Fluid Dynamics Material for this event included the written documentation from each of the research areas at Baylor University, documentation about the current state of technology support, and a write-up of the discussion that took place in person. The Case Studies highlighted the ongoing challenges that Baylor University has in supporting a cross-section of established and emerging research use cases. Each Case Study mentioned unique challenges which were summarized into common needs. These included: - Tradeoffs for network/software security, and usability of the resulting infrastructure. Better communication to set expectations and understand realities is required. - Computation use on campus is widespread and healthy. While no major problems were uncovered, upgrades to maintain current usage patterns and encourage growth will be required. - Storage is a critical need for enterprise use cases and research. In particular, a campus wide ‘storage architecture’ to support research use cases (e.g. instruments, data sharing) is required in the 2-5 year time window. - Instrumentation on campus is healthy and expanding. Technology must scale with this in the form of computation and storage. - Working with LEARN to upgrade network capacity (in multiples of 10G, or upgrades to 100G) will be required in the 1-3 year time frame. - Network monitoring and visibility will help to establish external science use cases. - Data sharing via portal systems is not currently a critical need, but growing in scope. EPOC can assist Baylor with options.

99 GENERAL AND MISCELLANEOUS↗
NASA NTRS2004

Symbology Development for General Aviation Synthetic Vision Primary Flight Displays for the Approach and Missed-Approach Modes of Flight

Spatial disorientation induced by inadvertent flight into instrument meteorological conditions (IMC) continues to be a leading cause of fatal accidents in general aviation. The Synthetic Vision Systems General Aviation (SVS-GA) research element, an integral part of NASA s Aviation Safety and Security Program (AvSSP), is investigating a revolutionary display technology designed to mitigate low visibility events such as controlled flight into terrain (CFIT) and low-visibility loss of control (LVLoC). The integrated SVS Primary Flight Display (SVS-PFD) utilizes computer generated 3-dimensional imagery of the surrounding terrain augmented with flight path guidance symbology. This unique combination will provide GA pilots with an accurate representation of their environment and projection of their flight path, regardless of time of day or out-the-window (OTW) visibility. The initial Symbology Development for Head-Down Displays (SD-HDD) simulation experiment examined 16 display configurations on a centrally located high-resolution PFD installed in NASA s General Aviation Work Station (GAWS) flight simulator. The results of the experiment indicate that situation awareness (SA) can be enhanced without having a negative impact on flight technical error (FTE), by providing a general aviation pilot with an integrated SVS display to use when OTW visibility is obscured.

Bartolone, Anthony P.↗
DOE OSTI2023

Ultrafast Laser-Excited Optical Emission of Xe under Loose-Focusing Conditions

The optical filament-based radioxenon sensing can potentially overcome the constraints of conventional detection techniques that are relevant for nuclear security applications. This study investigates the spectral signatures of pure xenon (Xe) when excited by ultrafast laser filaments at near-atmosphericpressure and in short and loose-focusing conditions. The two focusing conditions lead to laser intensity differences of several orders of magnitude and different plasma transient behavior. The gaseous sample was excited at atmospheric pressure using ∼7 mJ pulses with a 35 fs pulse duration at 800 nm wavelength. The optical signatures were studied by time-resolved spectrometry and imaging in orthogonal light collection configurations in the ∼400 nm (VIS) and ∼800 nm (NIR) spectral regions. The most prominent spectral lines of atomic Xe are observable in both focusing conditions. An on-axis light collection from an atmospheric air–Xe plasma mixture demonstrates the potential of femtosecond filamentation for the remote sensing of noble gases.

47 OTHER INSTRUMENTATION↗
NASA NTRS1994

Regenerative life support systems - why do we need them?

Human exploration of the solar system will include missions lasting years at a time. Such missions mandate extensive regeneration of life support consumables with efficient utilization of local planetary resources. As missions durations extend beyond one or two years, regenerable human life support systems which supply food and recycle air, water, and wastes become feasible; resupply of large volumes and masses of food, water, and atmospheric gases become unrealistic. Additionally, reduced dependency on resupply or self sufficiency can be an added benefit to human crews in hostile environments far from the security of Earth. Comparisons of resupply and regeneration will be discussed along with possible scenarios for developing and implementing human life support systems on the Moon and Mars.

D J Barta↗
DOE OSTI2021

The role of current and emerging technologies in meeting Japan’s mid- to long-term carbon reduction goals

Using Japan as a proxy for a developed nation, we investigated the role of existing and nascent technologies in curbing carbon emissions. We simulated possible pathways to meeting 2030 and 2050 emission targets within the Japanese electricity supply sector using a single-region model in The Integrated MARKAL-EFOM System (TIMES). Critically, our simulations incorporate novel technologies like hydrogen electrolysers, carbon capture, photochemical water splitting, and emerging photovoltaic cells, assess long-term impacts up to the year 2100, and include life-cycle emissions and learning curves for parameters such as investment cost, efficiency, and emission coefficients. Results indicate that a hybrid approach, using nuclear power and hydrogen from renewable energy-based electrolysis, is cost-effective and provides long-term emission reduction along with energy security. Finally, nuclear, wind, solar, and hydrogen from renewables emerge as key emission reduction technologies, while natural gas with carbon capture plays a minor role in achieving emission reduction targets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Fossil Energy Workshop on Quantum Information Science & Technology (Summary Report)

This report summarizes findings and discussion from the Fossil Energy Workshop on Quantum Information Science & Technology which took place on November 19-21, 2019. Quantum Information Science (QIS) is expected to profoundly change the practice of science and engineering in the coming decades. It is a rapidly progressing field, fueled by large investments from the private sector and governments. Its importance to the U.S. economy and national security is underscored by the National Quantum Initiative Act passed in December 2018. QIS includes quantum sensing, quantum communications, quantum simulation experiments, and quantum computation. QIS technology exploits quantum phenomena for performing tasks that are impossible to do today, such as finding prime factors of large numbers or elucidating reaction mechanisms in complex chemical systems. The opportunities for applying QIS to problems encountered in fossil energy technology development are not known today. This workshop brought together, for the first time, experts in these fields to exchange information and explore potential research opportunities for QIS to advance fossil energy. The goal of the workshop was to develop a set of priority research opportunities that can inform future research efforts in QIS and build a community of next-generation researchers at the intersection of QIS and fossil energy.

20 FOSSIL-FUELED POWER PLANTS↗
NASA NTRS2018

Important Changes to User Access at the NASA CDDIS

The Crustal Dynamics Data Information System (CDDIS) supports data archiving and distribution activities for the space geodesy and geodynamics community. The main objectives of the system are to make space geodesy and geodynamics related data and derived products available in a central archive, to maintain information about the archival of these data, to disseminate these data and information in a timely manner to a global scientific research community, and to provide user based tools for the exploration and use of the archive. Since its inception, the user community has utilized anonymous ftp for accessing and downloading files from the CDDIS archive. Although this protocol allows users to easily automate file downloads, many organizations, data systems, and users have already migrated from ftp or are actively pursuing a move away from the protocol due to problems from a system and security standpoint. Furthermore, U.S. Government agencies have become increasingly concerned about this legacy protocol and ensuring data integrity for the user community have begun recently to disallow the use of the ftp protocol. The CDDIS, operated by NASA GSFC, must therefore address these concerns and provide alternative methods for access to its archive for continued easy and automated download of its contents. This poster will discuss the upcoming changes at CDDIS and provide examples on transitioning from anonymous ftp.

Noll, Carey E.↗
NASA NTRS2022

The Mars 2020 Ground Data System Architecture

The Mars 2020 Mission’s primary objective is to collect 20 geographically unique samples during its prime mission of one and a quarter Martian years, or just over 2 Earth years. Mission planners determined the project needed to develop a system that would enable the operations team to analyze engineering and science data, make science decisions, select viable rover targets at a millimeter resolution and validate an uplink bundle for a car sized rover with more complex science instruments than any previous Mars surface mission. All this had to be done within a five hour time frame. Doing this with a small team would be a challenge, but this had to be accomplished by a large team of engineers and scientists located across North America and Europe. Achieving this level of operational efficiency was unheard of in the prime mission. In addition, the mission had another set of requirements that had nothing to do with surface operations; the Mars 2020 Ground Data System (GDS) was also expected to comply with a new set of security requirements to keep up with the ever changing cybersecurity landscape. The Mars 2020 Ground Data System (GDS) is a re-architected version of the Mars Science Laboratory GDS. The primary goal was to integrate the lessons learned from previous Mars surface missions, accommodate a set of new requirements and capabilities required to ensure mission success, and comply with a new set of cybersecurity controls. The new architecture includes several unique qualities including a data lake, language-agnostic system-wide event-based operations, containerization, automated deployment, network segmentation, infrastructure-as-code, API-driven interfaces, and the first Mars surface GDS to operate primarily in the cloud. The new architecture enabled greater access to the system’s data, tighter integration with the operations team, and a higher level of traceability. The availability of the data also enabled a new set of capabilities previously not possible on surface missions. These new capabilities include an autonomous data to information, pipeline for downlink analysis, horizontal scaling of science data processing capabilities, autonomous round trip data tracking of science and engineering data, integration of flight system state into the tactical planning cycle, high fidelity targeting utilizing kinematic data, and hierarchical image and 3d meshes data representations. This paper will introduce the requirements for the Mars 2020 Mission, the heritage architecture, and the rationale for the changes to achieve the new architecture. The paper will continue to describe the fundamental changes made to the GDS architecture, how these changes enabled a more tightly integrated GDS, and the new capabilities that were enabled by the new architecture. The paper will conclude with the lessons learned from the process of rearchitecting a heritage GDS system and from the first 200 days of operations supporting over 800 users from around the world.

Lopez-Roig, Reynaldo↗