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DOE OSTI2022

Fast and accurate influenza forecasting in the United States with Inferno

Infectious disease forecasting is an emerging field and has the potential to improve public health through anticipatory resource allocation, situational awareness, and mitigation planning. By way of exploring and operationalizing disease forecasting, the U.S. Centers for Disease Control and Prevention (CDC) has hosted FluSight since the 2013/14 flu season, an annual flu forecasting challenge. Since FluSight’s onset, forecasters have developed and improved forecasting models in an effort to provide more timely, reliable, and accurate information about the likely progression of the outbreak. While improving the predictive performance of these forecasting models is often the primary objective, it is also important for a forecasting model to run quickly, facilitating further model development and improvement while providing flexibility when deployed in a real-time setting. In this vein I introduce Inferno, a fast and accurate flu forecasting model inspired by Dante, the top performing model in the 2018/19 FluSight challenge. When pseudoprospectively compared to all models that participated in FluSight 2018/19, Inferno would have placed 2nd in the national and regional challenge as well as the state challenge, behind only Dante. Inferno, however, runs in minutes and is trivially parallelizable, while Dante takes hours to run, representing a significant operational improvement with minimal impact to performance. Forecasting challenges like FluSight should continue to monitor and evaluate how they can be modified and expanded to incentivize the development of forecasting models that benefit public health.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Cybersecurity for Distance Relay Protection

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

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

DEEP Solar: Data DrivEn Modeling and Analytics for Enhanced System Layer ImPlementation

Realizing the SETO 2030 mission of reducing solar energy costs to 3-5 c/kWh will require innovative enabling research on effective, cost-efficient integration of local PV within distribution systems. However, the intermittent and variable nature of PVs compels operators to impose conservative hosting capacity constraints. Given the extremely high variability of (intermittent and unpredictable) solar energy generation, relaxing the capacity constraints (which are currently around 15%) and achieving 100% or greater integration of renewables will require a fundamental transformation of the power grid via the utilization of exponentially larger amounts of AMI enabled fine-grained data. To address the challenges in increasing the penetration of renewable energy based DERs, this project envisions an Enhanced System Layer (ESL) at the distribution network level that is reliable, cost-effective and scalable to millions of Distributed Energy Resources (DERs)/devices. This includes developing: 1) Transformative and highly scalable machine learning based predictive analytics tools that plug into distribution system planning and provide real-time situational awareness at the distribution level for short and long-term operational planning. The tools will be built using novel data-driven energy models of millions of active nodes with AMI, 2) Adaptive stochastic analysis and optimization algorithms for real-time grid operations, 3) Dynamic Scenario Analysis using parallel Cloudenabled implementations with < 1 minute computational cycle times.

14 SOLAR ENERGY↗
DOE OSTI2020

GEMINI Case Study

Sandia's GEMINI-Scout Mine Rescue Robot is an unmanned ground vehicle designed to enter potentially hazardous environments to explore, assess, and evaluate dangerous situations first responders may face when conducting a rescue mission. GEMINI is approximately four feet long and two feet tall, which enables the robot to maneuver through small locations on rough terrains caused by earthquakes, fires, or radiological incidents. GEMINI uses track propulsion to climb stairs, travel through gravel and sand pits, pivot in place, and traverse 45-degree climbs with few problems. Furthermore, the vehicle's dual tracked-chassis design allows it to operate in hostile, dark, muddy, high-temperature, and explosive debris-strewn environments, while maintaining efficient ground mobility. The mobility and modularity of the vehicle allow for easy integration of sensors to conduct gas and temperature sensing and offers pan/tilt, zoom color, and thermal camera video streaming capabilities. The vehicle is also able to carry a payload of about 50 pounds of batteries and can handle an additional 200 pounds of payload, whether for additional diagnostics, supplies, or clothing for those trapped in an effected area. GEMINI is remotely operated through a wireless connection and an onboard computer running a customized embedded control application, which directly communicates to all onboard components except for the audio and video systems. When line of sight is not possible, operators use a shockresistant fiber optic cable to ensure continuous functionality of the vehicle. This allows for direct local control of the vehicle, which streams collected data back to the operator for enhanced situational awareness. In addition, the vehicle incorporates safety features such as explosion proof housing to ensure safe electronic operations in hazardous gas or flooded environments; a four-channel video link and two-way audio to ensure located survivors can communicate with operators; and an MSHA-approved multi-gas sensor to monitor air quality.

42 ENGINEERING↗
DOE OSTI2020

Gamma & Neutron Field-Data Recommendations [Slides]

Summary: The three spectra types desired are: IPC, background, known source; Source-to-detector distance should be stated clearly and photographed if possible; 300 sec is the minimum desired count time; A background spectrum provides a baseline against which to compare the IPC spectrum; Photographs and an event / scenario description can provide situational awareness

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Optimal Distribution System Voltage Regulation using State Estimation and DER Grid-Support Functions

Increasing solar energy penetrations may create challenges for distribution system operations because production variability can lead to large voltage deviations or protection system miscoordination. Instituting advanced management systems on distribution systems is one promising method for combating these challenges by intelligently controlling distribution assets to regulate voltage and ensure protection safety margins. While it is generally not the case today, greater deployment of power system sensors and interoperable distributed energy resources (DER)e.g., photovoltaic (PV) inverters, energy storage systems (ESS), electric vehicles (EVs)will enable situational awareness, control, and optimization of distribution systems. In this work, a control system was created which measures power system parameters to estimate the status of a feeder, forecasts the distribution state over a short-term horizon, and issues optimal set point commands to distribution-connected equipment to regulate voltage and protect the system. This two-year project integrated multiple research innovations into a management system designed to safely allow PV penetrations of 50% or greater. The integrated software was demonstrated through extensive real-time (RT) and power hardware-in-the-loop studies and a field demonstration on a live power system with a 684 kVA PV system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Quantifying Graph Uncertainty from Communication Data

Graphs are a widely used abstraction for representing a variety of important real-world problems including emulating cyber networks for situational awareness, or studying social networks to understand human interactions or pandemic spread. Communication data is often converted into graphs to help understand social and technical patterns in the underlying communication data. However, prior to this project, little work had been performed analyzing how best to develop graphs from such data. Thus, many critical, national security problems were being performed against graph representations of questionable quality. Herein, we describe our analyses that were precursors to our final statistically grounded technique for creating static graph snapshots from a stream of communication events. The first analyzes the statistical distribution properties of a variety of real-world communication datasets generally fit best by Pareto, log normal, and extreme value distributions. The second derives graph properties that can be estimated given the expected statistical distribution for communication events and the communication interval to be viewed node observability, edge observability, and expected accuracy of node degree. Unfortunately, as that final process is under review for publication, we can't publish it here at this time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

A Closed-Loop Distribution System Restoration Tool for Natural Disaster Recovery. Final CRADA report

We propose to continue the development of the restoration algorithms and the tool’s user interface, both of which have been developed under the GMLC-0131 project. This project aims to develop a distribution restoration decision support tool that will assist utilities in performing distribution restoration after extreme weather events in an optimal and efficient manner. The tool will integrate the weather information/forecasts and system fragility assessment together with the field measurement data to improve the situational awareness and estimate the system damage status. Advanced optimization models will be leveraged to dispatch repair crews and associated resources. New resources (e.g., automatic switches and distributed generators (DGs)) enabled by distribution automation and smart grid development will be utilized to reconfigure distribution grids and pick up loads promptly to reduce the outage sizes and durations. The closed-loop feature of the tool will make the tool adaptive to the evolving weather events and varying restoration capabilities. In this CRADA, we will collaborate with S&C Electric Company (S&C) to refine ANL-1060 (07/17/2019) the restoration algorithms that can be potentially applicable for any utility systems and vendor products, including: 1) Customizable information from both utility users and vendor users; 2) User interface design.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Report for Task 11 & 12: Components and Capabilities of the Resiliency Driven Outage Management and Feeder Restoration System (Deliverable D8))

This report provides progress update for the development of a outage management, feeder restoration, and restoration action feasibility check modules as part of the AGGREGATE project. Details for integration with controllability module, data driven situational awareness of network and distributed energy resources as well cyber security plan for these modules integrated with GE ADMS are also presented in the report. These three modules for outage management, feeder restoration, and restoration action feasibility check modules are developed in MATLAB and validated with a modified IEEE 123-node feeder. Results demonstrate ability of these new modules to improve the restoration process post-disaster to enhance the system resilience.

42 ENGINEERING↗
DOE OSTI2021

Design Considerations for Distributed Energy Resource Honeypots and Canaries

There are now over 2.5 million Distributed Energy Resource (DER) installations connected to the U.S. power system. These installations represent a major portion of American electricity critical infrastructure and a cyberattack on these assets in aggregate would significantly affect grid operations. Virtualized Operational Technology (OT) equipment has been shown to provide practitioners with situational awareness and better understanding of adversary tactics, techniques, and procedures (TTPs). Deploying synthetic DER devices as honeypots and canaries would open new avenues of operational defense, threat intelligence gathering, and empower DER owners and operators with new cyber-defense mechanisms against the growing intensity and sophistication of cyberattacks on OT systems. Well-designed DER canary field deployments would deceive adversaries and provide early-warning notifications of adversary presence and malicious activities on OT networks. In this report, we present progress to design a high-fidelity DER honeypot/canary prototype in a late-start Laboratory Directed Research and Development (LDRD) project.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Securing Inverter Communication: Proactive Intrusion Detection and Mitigation System to Tap, Analyze, and Act

The electric grid has undergone rapid, revolutionary changes in recent years; from the addition of advanced smart technologies to the growing penetration of distributed energy resources (DERs) to increased interconnectivity and communications. However, these added communications, access interfaces, and third-party software to enable autonomous control schemes and interconnectivity also expand the attack surface of the grid. To address the gap of DER cybersecurity and secure the grid-edge to motivate a holistic, defense-in-depth approach, a proactive intrusion detection and mitigation system (PIDMS) device was developed to secure PV smart inverter communications. The PIDMS was developed as a distributed, flexible bump-in-the-wire (BITW) solution for protecting PV smart inverter communications. Both cyber (network traffic) and physical (power system measurements) are processed using network intrusion monitoring tools and custom machinelearning algorithms for deep packet analysis and cyber-physical event correlation. The PIDMS not only detects abnormal events but also deploys mitigations to limit or eliminate system impact; the PIDMS communicates with peer PIDMSs at different locations using the MQTT protocol for increased situational awareness and alerting. The details of the PIDMS methodology and prototype development are detailed in this report as well as the evaluation results within a cyber-physical emulation environment and subsequent industry feedback.

14 SOLAR ENERGY↗
DOE OSTI2020

Regional Oscillation Source Localization: Implementation in the ESAMS Tool

In recent years, utilities have made great strides in the use of high-speed wide-area measurements collected from within their footprints. However, it is increasingly clear that analyses at wider scales are needed. On January 11, 2019 an oscillation with significant amplitude observable across the Eastern Interconnection persisted for approximately 18 minutes. The generator responsible for the oscillation was only identified after it tripped itself offline. This event, along with several other similar events, demonstrated the need for increased coordination among utilities to effectively mitigate system-wide oscillations and avoid unnecessary or detrimental operator actions. In response to this need, the Eastern Interconnection Situational Awareness Monitoring System (ESAMS) was upgraded to allow the region where an oscillation is originating to be identified. This report documents the algorithms developed for this task and describes how they were integrated into the ESAMS tool. Results from simulation- and measurement-based tests demonstrate the reliability of the approaches.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Coordinated Ramping Product and Regulation Reserve Procurements in CAISO and MISO using Multi-Scale Probabilistic Solar Power Forecasts (Pro2R)

How can probabilistic solar forecasts lower costs and improve reliability for independent system operator (ISO) markets? We tackle this question in three steps. First, we enhance an existing solar forecasting system to provide well-calibrated hours-ahead probabilistic forecasts. We then relate the degree of uncertainty in those forecasts to error distributions for net load ramps for the California ISO (CAISO) using statistical and machine learning methods. Projected net load errors conditioned on solar uncertainty are translated into flexible ramp requirements that therefore reflect real-time meteorological and solar conditions, improving on typical ISO procedures. Finally, a multi-period look-ahead production cost model quantifies how conditional ramp requirements can a) decrease operating costs by lowering requirements compared to often conservative unconditional methods, and b) reduce generation scarcity events and consequently improve reliability by increasing flexibility requirements at times when unconditional forecast-based requirements understate actual ramp uncertainty. In addition to the products just described (quantification of solar uncertainty, its translation into requirements for ramp capability product, and quantification of the benefits of more accurate ramp requirements), this project also developed a visualization system that alerts system operators of ramp and uncertainty conditions within the network based on solar forecasts. The system is called Resource Forecast and Ramp Visualization for Situational Awareness (RaVIS). These four products represent significant advances in the state-of-the-art of probabilistic solar forecasting, development of weather-informed reserve requirements, production costing methods for estimating the benefits of more accurate reserve requirements, and visualization of system status, respectively. Yet the products are also practical and can be immediately implemented, potentially enabling system operators to save millions of dollars in ramp product procurement costs per year.

14 SOLAR ENERGY↗
DOE OSTI2022

Small Hydropower Interconnections: State Interconnection Processes

Small hydropower projects with rated power output between 0 to 20 MW have been the predominant source of hydropower growth over the past decade in the United States (DOE 2016; Johnson et al. 2018). However, interconnection to electricity distribution and transmission grids is a persistent barrier. Interconnection of an electricity generating unit is overseen by the distribution or transmission owner, who use interconnection standards and requirements that vary by state. The differences between standards in standards may affect the final cost, timeline, and success of a small hydropower project. Small hydropower project developers across the United States have found interconnection procedures to be fraught with cost surprises and schedule overruns. System operators have struggled to understand impacts to overburdened or rapidly evolving transmission and distribution grids. The results of these shortcomings have been stranded costs and unrealized small hydropower potential. Though regulatory actions and policy recommendations at the state level have increased the situational awareness of interconnection challenges, the remote locations of small hydropower resources and the relatively small revenues associated with energy production through small hydropower facilities continue to make interconnection processes and requirements confusing and costly. Noting these challenges, the U.S. Department of Energy Water Power Technologies Office enlisted Pacific Northwest National Laboratory (PNNL) and Oak Ridge National Laboratory (ORNL) to investigate the small hydropower interconnection landscape across the United States. The second in a series, this paper investigates the interconnection process in each state in the U.S. to compare their attributes. Subsequent papers in the series will analyze these interconnection processes (“Small Hydropower Interconnections: Analysis of Interconnection Processes”) and present best practices (“Small Hydropower Interconnections: Best Practices”) that will help overcome barriers to future small hydropower development. The first paper in the series examined the state of small hydropower projects in the United States (“Small Hydropower Interconnections: Small Hydropower in the United States”) to understand the industry characteristics.

13 HYDRO ENERGY↗
DOE OSTI2022

TCF-20-20213: Advanced Power Distribution Sensing and Communications through the Cable TV Broadband Network (Final Report. Period of Performance: June 2020 to June 2022)

To enable the rapid, widespread commercial availability of secondary distribution grid voltage and phase angle data, the DOE OE Technology Commercialization Fund (TCF) project: 1) created a new American National Standard for next-generation grid power quality sensing and communications, 2) created a new prototype broadband-based standard-compliant grid power sensing system for use by utilities and others, and 3) improved by several orders of magnitude the spatiotemporal scale of the in-progress DOE CESER project: Situational Awareness of Grid Anomalies (SAGA) for Visual Analytics.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

WISP: Watching grid Infrastructure Stealthily through Proxies (Final Technical Report)

The complex interdependencies of cyber systems (sensors and communications), physical grids and associated electricity market operations make protecting electric power grids a significant challenge. The energy sector is constantly under new, targeted, advanced and dangerous cyber-attacks that have the potential to result in the loss of human life. These threats are further exacerbated by our need to modernize the grid. One focus of cyber security research in smart grids is the securing of the SCADA system through advanced intrusion detection systems (IDS) and bad data detection algorithms in state estimation. These methods either require full knowledge of the system topology and parameters or fail to understand the physical behaviors under attack. WISP (Watching grid Infrastructure Stealthily through Proxies) is designed to provide additional protection to the power grid using only publicly available data. In particular, WISP exploits the spatio-temporal nature of the real time locational marginal prices (LMPs), in conjunction with other information such as bids, weather, outages and load data to analyze anomalous power pricing behaviors and then correlate those observations to localize regions of interest and identify potential cyber events. WISP is non-intrusive as the tool is deployed as a service in the Cloud or on premise and provides reliable information to system operators for enhanced situational awareness, without impeding energy delivery functions. The WISP technology comprises three modules: the data-driven anomaly detection core, the vulnerability and risk analysis and the root cause analysis. The data-driven anomaly detection core performs the tasks of feature selection, anomaly detection and attack region localization. The vulnerability and risk analysis module provides system level information of the vulnerable variables and times, assisting the operators in selecting monitoring and protection nodes. The root cause analysis module takes the detection results and identifies potential operational conditions that contribute to the detected anomalies. In Phase I, we have demonstrated the feasibility and effectiveness of WISP. We developed a realistic electricity market simulator capable of generating normal and attack market data under various operational conditions. We developed a series of cyber-attack detection and analysis algorithms and evaluated them under multiple data sources. Finally, we integrated all modules into an end-to-end software, providing functions for data management, data analytics and visualization. Specifically, we have achieved: (i) real-time data acceptance from external utility interfaces with >99% acceptance rate; (ii) high performance anomaly detection algorithms with >98% detection accuracy and <0.1% false alarm rate; and (iii) ultra-low computing delay <50 milliseconds. Additionally, our team developed algorithms to identify the vulnerable variables in electricity market operations and root cause analysis functions to identify major contributors to the price spikes. These ancillary modules are necessary when deploying WISP in real world industry environment. In Phase II, we have demonstrated the effectiveness of WISP software on realistic largescale power systems. We performed red team testing for the Phase I WISP software and identified software vulnerabilities and implemented corresponding mitigation solutions. We adapted the electricity market simulator for the Texas synthetic 2000-bus system and generated datasets for the false data injection attacks. We created database and visualization interfaces for the Texas system and the ISO New England system. We performed software optimization in terms of operation efficiency, computing speed and detection accuracy. Finally, we tested the software on the Texas system and the ISO New England system and evaluated the detection performance. Overall, we achieved above 89% detection rate, below 3% false alarm rate and below 37 seconds of end-to-end detection delay.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Sensing Electrical Networks Securely & Economically (SENSE)

The growing adoption of distributed energy resources (DERs) like battery energy storage systems and roof top solar/PV and the rapid penetration of electric vehicles (EVs), the electric grid is undergoing a major transformation with elevated stress on legacy grid assets. Despite a lot of expenditure to address these challenges, both in dollars and manpower, utilities have not been able to receive the value that was promised. The gains have been most visible at the transmission and substation level, especially where the main objective was improving operational and economic efficiency for the utility. Improving visibility and control at a few select points enhances the existing and established paradigm of centralized command and control. With changing load patterns, load types and the overall transition to an “active grid”, the centralized control and coordination paradigm gets challenged. To address the challenges, a new architecture and mechanism is needed, one that supports decentralized control and decision making, extracting value streams at the grid edge, particularly as the changes are fueled by transitions occurring in the distribution system. To address this, a communications and data processing platform, “GAMMA” was developed and demonstrated through the project. At the heart of the platform, are distributed, intelligent edge nodes with sensing and compute capabilities, that can record and analyze information locally. They are embedded in sensors and actuators specific to different distribution system applications. Phase 1 of the project focused on developing novel sensor technology that can be used for monitoring utility pole top distribution transformers. The sensors were designed with the objective of being low-cost, communicating with the GAMMA cloud using novel “delay-tolerant” networking using Bluetooth and a secure mobile application. They were non-intrusive in nature so that they can be installed quickly in the field, resulting in overall low cost of deployment and operations. Following the successful completion of Phase 1, the team manufactured 100 units for a field demonstration in Phase 2. The field demonstration was carried out on two real feeder systems with the local utility partner. In total, 100 sensors were installed and operated over a period of 6 months in the state of Georgia. The platform is operational end to end, with the cloud infrastructure deployed on a distributed, serverless environment that can serve multiple data streams, an analytics engine and a portal to securely view the data from multiple assets. The data collected through the GAMMA Mobile Phone app showcased the viability of the novel delay tolerant networking architecture, and the data processing algorithms developed through the course of the project, were successful in extracting important information about the overall network, improving the utility’s visibility and situational awareness in the distribution feeder.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Smart Packaging for Critical Energy Shipment (SPaCES)

Recent technical advances have brought forth revolutionary Smart Packaging (SP) technology. SP incorporates multiple electronics, chemical, and mechanical sensing technologies into packaging materials, and utilizes them to monitor and display package content status. SP can also employ embedded micro actuators to react to undesirable package conditions such as moisture/temperature anomalies or harmful chemical reactions and neutralize it. When further integrated with wireless sensing and secure networking, SP provides wholistic system-wide remote situation awareness capability for real-time crisis management. Finally, we also see that SP can be further integrated with 3D printing technology to offer form-factor customization and application specific solutions suitable for DOE (Department of Energy) NNSA’s (National Nuclear Security Administration) R/N (radiological/nuclear) material shipment and management needs; this has the potential to improve safety, security, and overall operation process quality. This report surveys SP technology as the state of the art (SOTA) and analyzes how it can integrate with cybersecurity and 3D printing to address NNSA’s critical R/N material shipment and storage requirements. This report further presents our FY23/24 investigation plan describing project background, goal, motivation, proposed work, and statement of work and cost.

47 OTHER INSTRUMENTATION↗