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NASA NTRS2001

A Latency-Tolerant Partitioner for Distributed Computing on the Information Power Grid

NASA's Information Power Grid (IPG) is an infrastructure designed to harness the power of graphically distributed computers, databases, and human expertise, in order to solve large-scale realistic computational problems. This type of a meta-computing environment is necessary to present a unified virtual machine to application developers that hides the intricacies of a highly heterogeneous environment and yet maintains adequate security. In this paper, we present a novel partitioning scheme. called MinEX, that dynamically balances processor workloads while minimizing data movement and runtime communication, for applications that are executed in a parallel distributed fashion on the IPG. We also analyze the conditions that are required for the IPG to be an effective tool for such distributed computations. Our results show that MinEX is a viable load balancer provided the nodes of the IPG are connected by a high-speed asynchronous interconnection network.

Das, Sajal K.↗

NASA NTRS2001

Physical Processes Governing Atmospheric Trace Constituents Measured from an Aircraft on PEM-Tropics

Before the mission, the PI (principal investigator) was instrumental in securing real-time use of the new 51-level ECMWF (European Centre for Medium Range Weather Forecasts) meteorological data. During the mission, he provided flight planning and execution guidance as meteorologist for the P-3B. Mr. Yong Zhu computed and plotted meteorological forecast maps using the ECMWF data and transmitted them to the field from MIT (Massachusetts Institute of Technology). Dr. John Cho was in the field for the Christmas Island portion to extract data from the on-site NOAA (National Oceanic and Atmospheric Administration) radars for local wind profiles that were used at the flight planning meetings. When the power supply for the VHF radar failed, he assisted the NOAA engineer in its repair. After the mission, Mr. Zhu produced meteorological data memos, which were made available to the PEM (Pacific Exploratory Mission)-Tropics B science team on request. An undergraduate student, Ms. Danielle Morse, wrote memos annotating the cloud conditions seen on the aircraft external monitor video tapes. Dr. Cho and the PI circulated a memo regarding the status (and associated problems) of the meteorological measurement systems on the DC-8 and P-3B to the relevant people on the science team. Several papers by members of our project were completed and accepted by JGR (Journal of Geophysical Research) for the first special section on PEM-Tropics B. These papers included coverage of the following topics: 1) examination of boundary layer data; 2) water vapor transport; 3) tropospheric trace constituent layers; 4) summarizations of the meteorological background and events during PEM-Tropics B; 5) concomitant lidar measurements of ozone, water vapor, and aerosol.

Newell, Reginald E.↗

NASA NTRS2016

The Earth Observing System (EOS) Ground System: Leveraging an Existing Operational Ground System Infrastructure to Support New Missions

The Earth Observer System (EOS) was officially established in 1990 and went operational in December 1999 with the launch of its flagship spacecraft Terra. Aqua followed in 2002 and Aura in 2004. All three spacecraft are still operational and producing valuable scientific data. While all are beyond their original design lifetime, they are expected to remain viable well into the 2020s. The EOS Ground System is a multi-mission system based at NASA Goddard Space Flight Center that supports science and spacecraft operations for these three missions. Over its operational lifetime to date, the EOS Ground System has evolved as needed to accommodate mission requirements. With an eye towards the future, several updates are currently being deployed. Subsystem interconnects are being upgraded to reduce data latency and improve system performance. End-of-life hardware and operating systems are being replaced to mitigate security concerns and eliminate vendor support gaps. Subsystem hardware is being consolidated through the migration to Virtual Machine based platforms. While mission operations autonomy was not a design goal of the original system concept, there is an active effort to apply state-of-the-art products from the Goddard Mission Services Evolution Center (GMSEC) to facilitate automation where possible within the existing heritage architecture. This presentation will provide background information on the EOS ground system architecture and evolution, discuss latest improvements, and conclude with the results of a recent effort that investigated how the current system could accommodate a proposed new earth science mission.

Earth Science Mission Operations (ESMO)↗

DOE OSTI2015

Report to the National Park Service for Permit LAKE-2014-SCI-002

The overall purpose of the study is to determine how to use existing geologic data to predict gamma-ray background levels as measured during aerial radiological surveys. Aerial radiological surveys have typically been for resource exploration purposes but are now also used for homeland security purposes and nuclear disaster assessment as well as determining the depth of snowpack. Foreknowledge of the background measured during aerial radiological survey will be valuable for all the above applications. The gamma-ray background comes from the rocks and soil within the first 30 cm of the earth’s surface in the area where the survey is being made. The background should therefore be predictable based on an understanding of the distribution and geochemistry of the rocks on the surface. We are using a combination of geologic maps, remote sensing imagery and geochemical data from existing databases and the scientific literature to develop a method for predicting gamma-ray backgrounds. As part of this project we have an opportunity to ground truth our technique along a survey calibration line near Lake Mojave that is used by the Remote Sensing Lab (RSL) of National Security Technologies, LLC (NSTec). RSL makes aerial measurements along this line on a regular basis, so the aerial background in the area is well known. By making ground-based measurements of the gamma-ray background and detailed observations of the geology of the ground surface as well as local topography we will have the data we need to make corrections to the models we build based on the remote sensing and geologic data. Our project involves collaborators from the Airborne Geophysics Section of the Geological Survey of Canada as well as from NSTec’s RSL. Findings

Burnley, Pamela C.↗

DOE OSTI2021

Investigating Vegetation Responses to Underground Nuclear Explosions Through Integrated Analyses

Vegetation has the potential to respond to underground nuclear explosions, yet these links have not been fully explored. Given the lack of previously described signatures, the changes in vegetation are possibly subtle. The integration of multiple different data streams is potentially a useful approach to improve signal detection. Here, we investigate whether semi-arid vegetation growth patterns responded to eight legacy underground nuclear tests at the Nevada National Security Site in southern Nevada, USA. We tested for spatial and temporal changes in vegetation cover, tree growth patterns, and tree leaf spectral properties using ground-based measurements, including those from tree-rings and hyperspectral surface vegetation reflectance, as well as space-based measurements of Normalized Difference Vegetation Index (NDVI) from Landsat. Multiple data streams suggest a localized (<1.2 km) spatial pattern whereby tree growth is enhanced closer to the source of the underground test relative to sites further away. We also observed a more regional (>1.2–9 km) pattern whereby tree growth is suppressed coincident with a drought beginning 1 year before the 1989 tests, but continuing in the 5 years following the tests, which is anomalous relative to what is expected based on the response of tree growth to previous droughts. furthermore, quantification of the relative effects of the tests on vegetation remains a challenge due to the coincident drought and the potential for other disturbances to have impacted tree growth at this time, but the integration of these data reveals a more nuanced growth response than any other one data set indicates alone.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

DOE OSTI2015

An Integrated Signaling-Encryption Mechanism to Reduce Error Propagation in Wireless Communications: Performance Analyses

Traditional encryption techniques require packet overhead, produce processing time delay, and suffer from severe quality of service deterioration due to fades and interference in wireless channels. These issues reduce the effective transmission data rate (throughput) considerably in wireless communications, where data rate with limited bandwidth is the main constraint. In this paper, performance evaluation analyses are conducted for an integrated signaling-encryption mechanism that is secure and enables improved throughput and probability of bit-error in wireless channels. This mechanism eliminates the drawbacks stated herein by encrypting only a small portion of an entire transmitted frame, while the rest is not subject to traditional encryption but goes through a signaling process (designed transformation) with the plaintext of the portion selected for encryption. We also propose to incorporate error correction coding solely on the small encrypted portion of the data to drastically improve the overall bit-error rate performance while not noticeably increasing the required bit-rate. We focus on validating the signaling-encryption mechanism utilizing Hamming and convolutional error correction coding by conducting an end-to-end system-level simulation-based study. The average probability of bit-error and throughput of the encryption mechanism are evaluated over standard Gaussian and Rayleigh fading-type channels and compared to the ones of the conventional advanced encryption standard (AES).

advanced encryption standard (AES)↗

DOE OSTI2023

The Design and Implementation of a Secure Datastore Based on Ethereum Smart Contract

In this paper, we present a secure datastore based on an Ethereum smart contract. Our research is guided by three research questions. First, we will explore to what extend a smart-contract-based datastore should resemble a traditional database system. Second, we will investigate how to store the data in a smart-contract-based datastore for maximum flexibility while minimizing the gas consumption. Third, we seek answers regarding whether or not a smart-contract-based datastore should incorporate complex processing such as data encryption and data analytic algorithms. The proposed smart-contract-based datastore aims to strike a good balance between several constraints: (1) smart contracts are publicly visible, which may create a confidentiality concern for the data stored in the datastore; (2) unlike traditional database systems, the Ethereum smart contract programming language (i.e., Solidity) offers very limited data structures for data management; (3) all operations that mutate the blockchain state would incur financial costs and the developers for smart contracts must make sure sufficient gas is provisioned for every smart contract call, and ideally, the gas consumption should be minimized. Our investigation shows that although it is essential for a smart-contract-based datastore to offer some basic data query functionality, it is impractical to offer query flexibility that resembles that of a traditional database system. Furthermore, we propose that data should be structured as tag-value pairs, where the tag serves as a non-unique key that describes the nature of the value. We also conclude that complex processing should not be allowed in the smart contract due to the financial burden and security concerns. The tag-based secure datastore designed this way also defines its applicative perimeter, i.e., only applications that align with our strategy would find the proposed datastore a good fit. Those that would rather incur higher financial cost for more data query flexibility and/or less user burden on data pre- and post-processing would find the proposed database too restrictive.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Leveraging artificial intelligence and advanced food processing techniques for enhanced food safety, quality, and security: a comprehensive review

Artificial intelligence is emerging as a transformative force in addressing the multifaceted challenges of food safety, food quality, and food security. This review synthesizes advancements in AI-driven technologies, such as machine learning, deep learning, natural language processing, and computer vision, and their applications across the food supply chain, based on a comprehensive analysis of literature published from 1990 to 2024. AI enhances food safety through real-time contamination detection, predictive risk modeling, and compliance monitoring, reducing public health risks. It improves food quality by automating defect detection, optimizing shelf-life predictions, and ensuring consistency in taste, texture, and appearance. Furthermore, AI addresses food security by enabling resource-efficient agriculture, yield forecasting, and supply chain optimization to ensure the availability and accessibility of nutritious food resources. This review also highlights the integration of AI with advanced food processing techniques such as high-pressure processing, ultraviolet treatment, pulsed electric fields, cold plasma, and irradiation, which ensure microbial safety, extend shelf life, and enhance product quality. Additionally, the integration of AI with emerging technologies such as the Internet of Things, blockchain, and AI-powered sensors enables proactive risk management, predictive analytics, and automated quality control. By examining these innovations' potential to enhance transparency, efficiency, and decision-making within food systems, this review identifies current research gaps and proposes strategies to address barriers such as data limitations, model generalizability, and ethical concerns. These insights underscore the critical role of AI in advancing safer, higher-quality, and more secure food systems, guiding future research and fostering sustainable food systems that benefit public health and consumer trust.

AI↗

DOE OSTI2021

Resilient Information Architecture Platform for Smart Grid (RIAPS)

A number of emerging trends will substantially alter the operation and control of the electric grid over the next several decades. These trends include ensuring resiliency under severe weather events, increasing integration of renewable electricity generation, supporting changing electricity demand patterns, and the improving cost effectiveness of distributed energy resources. To address these challenges, the future “Smart Grid” management will need to transition from centralized to coordinated distributed control paradigm. Reliable operation of the Smart Grid depends on distributed intelligence realized through software applications that run on distributed computing devices attached to the power system to collect data and collaboratively manage resources. However, much of the existing software for Smart Grid-enabled devices is either proprietary or developed with custom solutions, which limits interoperability among the heterogeneous devices and hinders the ability to manage system-level reliability, security, and resiliency requirements. Additionally, this approach makes Smart Grid applications hard to maintain, evolve, verify, and replace; resulting in high development and deployment costs. Further development of the Smart Grid requires a reusable software base-layer to move from hard-coded functionality to a plug-and-play architecture capable of managing system-level objectives and constraints in addition to providing consistent common services across heterogeneous devices and applications. Vanderbilt University, in collaboration with North Carolina State University and Washington State University has developed a foundation ‘software platform’ for developing and deploying robust, reliable, effective and secure software applications for the Smart Grid. The Resilient Information Architecture Platform for the Smart Grid (RIAPS) provides core services for building effective and powerful smart grid applications. It offers unique services for real-time data dissemination, fault tolerance, and coordination across apps distributed over the network.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

FY25 Electric Grid Security Annual Report

Sandia’s Electric Grid Security program advances a national vision of energy dominance and accessibility, while applying our national security -emphasis on ensuring of a secure, resilient, and affordable electric system for all users. Our achievements reflect a strategic approach combining technology development; modeling, simulation, and data analytics; and partnered demonstrations and outreach to further the adoption of advanced grid and storage technologies. Our FY25 efforts leverage the strengths of our partnerships—spanning Sandia’s core science and technology competencies as well as external technology leaders—to develop the solutions today which enable the grid of tomorrow. Key accomplishments in this report that support our strategy span our technical program areas and include: • New open-source analytical tools for systems -level planning and optimization, including significant advances to the QuESt analytical environment; • Further advancement of artificial intelligence and machine learning to enhanced grid operations and planning as we rise to the challenge of new large loads; • Development of solid-state power conversion technologies and a new medium-voltage research lab; • New technologies to assess wildfire vulnerabilities and mitigate potential impacts; • Advanced applications of new cybersecurity technologies with industry partners; • Contributions to understanding the impacts of electromagnetic pulses and geomagnetic disturbances on grid components; and • Digital twin development for hybrid microgrids with multiple generators, storage, and loads. This report indicates key areas of research and engagement and summarizes the impact of Sandia’s contributions through notable accomplishments, journal publications, patents, and technical conferences and presentations. It is provided with the hope that readers discover ways we can further team to create our modern grid and apply the outcomes of our efforts. The bulk of work described herein is funded by several offices within the U.S. Department of Energy (USDOE), including the Office of Electricity (OE); Cybersecurity, Energy Security, and Emergency Response (CESER); former offices such as the Office of Energy Efficiency and Renewable Energy (EERE), the Grid Deployment Office (GDO), the Office of Clean Energy Demonstrations (OCED), and other key programs at USDOE. As we continue to state in these annual reports, the contributors to our successes are too numerous to name here, though our team wishes to express our deep gratitude to the numerous program and project sponsors at the US Department of Energy, who often function equally as technical collaborators; our many partners in industry, academia, utilities, and other national labs; and fellow researchers and business partners at Sandia whose leadership and creativity have enabled the accomplishments described herein.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

An Introduction to Los Alamos National Laboratory [Slides]

The Weapon Systems Engineering Division (W) provides the system engineering and program management necessary to sustain the safety, reliability, and security of the Los Alamos National Laboratory’s assets in the active United States nuclear stockpile - the B61, W76, W78 and W88. The Division generates key certification data for Annual Assessment supporting the Laboratory Director's letter to the President on the health of those warheads. This role demands ongoing surveillance of the active stockpile and evaluation of the potential impact of any issues through design, engineering, fabrication, testing using state-of-the-art computational simulation tools and engineering test facilities. The Division works in close liaison with the several production facilities across the nuclear security complex as well as with the customers in the US Navy and Air Force.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2016

Nevada National Security Site Underground Radionuclide Inventory, 1951-1992: Accounting for Radionuclide Decay through September 30, 2012

This report is an update of report LA-13859-MS (Bowen et al., 2001). In that original report, the underground radionuclide inventory at the Nevada National Security Site (NNSS) was decay corrected to September 23, 1992, the date of the last underground nuclear test at the NNSS. In this report, the inventory is updated to account for the decay of radionuclides over two additional decades (1992-2012) and revised tritium, fission product and actinide inventory figures and tables are presented. The maximum contaminant levels for radionuclides were also updated to Safe Drinking Water Act Maximum Contaminant Levels (MCLs) (CFR, 2013). Also, a number of minor errata found in the original publication were corrected. An inventory of radionuclides produced by 828 underground nuclear tests conducted at the NNSS by the Lawrence Livermore National Laboratory, the Los Alamos National Laboratory, and the Department of the Defense from 1951 to 1992 includes tritium, fission products, actinides, and activation products. The inventory presented in this report provides an estimate of radioactivity remaining underground at the NNSS after nuclear testing. The original test inventory is decayed to September 30, 2012, and predictions of inventory decay over the subsequent 1000 years are presented. For the purposes of summary and publication, the Los Alamos National Laboratory and Lawrence Livermore National Laboratory authors of this report subdivided the inventory into five areas corresponding to the principal geographic test centers at the NNSS. The five areas roughly correspond to Underground Test Area “Corrective Action Units” (CAUs) for remediation of groundwater. In addition, the inventory is further subdivided for the Yucca Flat region by tests where the working point depth is more than 328 feet (100 meters) above the water table and tests that were detonated below that level. Water levels used were those from the U. S. Department of Energy, Nevada Operations Office (1997), now called the Nevada Field Office. Curie activities and atoms are reported as of September 30, 2012. This inventory is strictly a compilation of the residual radiologic inventory remaining from the underground nuclear tests conducted by Lawrence Livermore National Laboratory, Los Alamos National Laboratory and the Department of the Defense from 1951 to 1992 and does not include radioactivity from other types of nuclear testing (e.g., atmospheric, reactors, rocket engines). A companion classified report (Miller et al., 2002) contains test-specific data for each test performed at the NNSS. This work has been sponsored by the U. S. Department of Energy, National Nuclear Security Administration Nevada Field Office.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Toward Wireless Smart Grid Communications: An Evaluation of Protocol Latencies in an Open-Source 5G Testbed

Fifth-generation networks promise wide availability of wireless communication with inherent security features. The 5G standards also outline access for different applications requiring low latency, machine-to-machine communication, or mobile broadband. These networks can be advantageous to numerous applications that require widespread and diverse communications. One such application is found in smart grids. Smart grid networks, and Operational Technology (OT) networks in general, utilize a variety of communication protocols for low-latency control, data monitoring, and reporting at every level. Transitioning these network communications from wired Wide Area Networks (WANs) to wireless communication through 5G can provide additional benefits to their security and network configurability. However, introducing these wireless capabilities may also result in a degradation of network latency. In this paper, we propose utilizing 5G for smart grid communications, and we evaluate the latency impacts of encapsulating GOOSE, Modbus, and DNP3 for transmission over a 5G network. The OpenAirInterface open-source library is utilized to deploy an in-lab 5G Core Network and gNB for testing with off-the-shelf User Equipment (UE). This creates an effective 5G test platform for experimenting with different OT protocols such as GOOSE. The results are validated by measuring two different Intelligent Electronic Devices’ contact closure times for each network configuration. These tests are also conducted for varying packet sizes in order to isolate different sources of network latency. Our study outlines the latency impact of communication over 5G for time-critical and non-critical applications regarding their transition toward private 5G-based OT network implementations. The conducted experiments illustrate that in the case of GOOSE packets, simple encapsulation may exceed the protocol’s time-critical nature, and, therefore, additional measures must be taken to ensure a viable transition of GOOSE to 5G services. However, non-critical applications are shown to be viable for migration to 5G.

42 ENGINEERING↗

DOE OSTI2015

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↗

DOE OSTI2019

Review of Existing Characterization Data Interim Report for Southeast Regional Carbon Storage Partnership: Offshore Gulf of Mexico

The goal of this effort is to expand the knowledge base required for commercially viable, secure, long-term, large-scale carbon dioxide (CO 2 ) subsea storage in the U.S. Gulf of Mexico (GOM), with or without enhanced hydrocarbon recovery. The effort is intended to support DOE’s long-term objective to ensure a comprehensive assessment of the potential to implement offshore CO 2 subsea storage in the GOM. This is being facilitated by expanding the membership of the Southern States Energy Board’s (SSEB) existing Southeast Offshore Storage Resource Assessment (DE-FE0026082) GOM government-industry partnership.

02 PETROLEUM↗

DOE OSTI2024

A Cybersecurity Testbed for Smart Buildings

Smart buildings are equipped with a plethora of cyber-physical systems, such as Internet of Things (IoT) devices and building automation systems. These devices, especially in commercial buildings, use legacy communications and hardware that were not designed with cybersecurity in mind. With increasing cyber threats in recent years, smart buildings have become an increasing target for attacks, but not enough published data are available from these incidents to study or replicate the scenarios to defend buildings. As part of the U.S. Department of Energy-funded project focusing on developing the Building Intelligence with Layered Defense Using Security-Constrained Optimization and Security Risk Detection (BUILD-SOS) platform, we developed a cybersecurity test bed for smart buildings. This test bed includes a building simulation tool, virtual devices, emulated operational technology networks, and remote hardware-in-the-loop. Using this test bed, we performed different cyberattacks on the smart building model and collected both physical building data, to understand the impacts on the building, and network data, to aid in separating mechanical faults from cyberattacks during the detection. This test bed is a significant tool in protecting smart buildings from cyberattacks because they can aid in both cybersecurity analysis and the evaluation of cyberattack detection tools by testing the tools in a secure environment without impacting the building operations.

alfalfa↗

DOE OSTI2023

A Cybersecurity Testbed for Smart Buildings

Smart buildings are equipped with a plethora of cyber-physical systems, such as Internet of Things (IoT) devices and building automation systems. These devices, especially in commercial buildings, use legacy communications and hardware that were not designed with cybersecurity in mind. With increasing cyber threats in recent years, smart buildings have become an increasing target for attacks, but not enough published data are available from these incidents to study or replicate the scenarios to defend buildings. As part of the U.S. Department of Energy-funded project focusing on developing the Building Intelligence with Layered Defense Using Security-Constrained Optimization and Security Risk Detection (BUILD-SOS) platform, we developed a cybersecurity test bed for smart buildings. This test bed includes a building simulation tool, virtual devices, emulated operational technology networks, and remote hardware-in-the-loop. Using this test bed, we performed different cyberattacks on the smart building model and collected both physical building data, to understand the impacts on the building, and network data, to aid in separating mechanical faults from cyberattacks during the detection. This test bed is a significant tool in protecting smart buildings from cyberattacks because it can aid in both cybersecurity analysis and the evaluation of other cyberattack detection tools by testing the tools in a secure environment without impacting the building operations.

cyber-physical systems↗

DOE OSTI2021

Toward Urban Water Security: Broadening the Use of Machine Learning Methods for Mitigating Urban Water Hazards

Due to the complex interactions of human activity and the hydrological cycle, achieving urban water security requires comprehensive planning processes that address urban water hazards using a holistic approach. However, the effective implementation of such an approach requires the collection and curation of large amounts of disparate data, and reliable methods for modeling processes that may be co-evolutionary yet traditionally represented in non-integrable ways. In recent decades, many hydrological studies have utilized advanced machine learning and information technologies to approximate and predict physical processes, yet none have synthesized these methods into a comprehensive urban water security plan. In this paper, we review ways in which advanced machine learning techniques have been applied to specific aspects of the hydrological cycle and discuss their potential applications for addressing challenges in mitigating multiple water hazards over urban areas. We also describe a vision that integrates these machine learning applications into a comprehensive watershed-to-community planning workflow for smart-cities management of urban water resources.

54 ENVIRONMENTAL SCIENCES↗