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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 289 records · Page 16

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NASA NTRS2016

The Cognitive Challenges of Flying a Remotely Piloted Aircraft

A large variety of Remotely Piloted Aircraft (RPA) designs are currently in production or in development. These aircraft range from small electric quadcopters that are flown close to the ground within visual range of the operator, to larger systems capable of extended flight in airspace shared with conventional aircraft. Before RPA can operate routinely and safely in civilian airspace, we need to understand the unique human factors associated with these aircraft. The task of flying an RPA in civilian airspace involves challenges common to the operation of other highly-automated systems, but also introduces new considerations for pilot perception, decision-making, and action execution. RPA pilots participated in focus groups where they were asked to recall critical incidents that either presented a threat to safety, or highlighted a case where the pilot contributed to system resilience or mission success. Ninety incidents were gathered from focus-groups. Human factor issues included the impact of reduced sensory cues, traffic separation in the absence of an out-the-window view, control latencies, vigilance during monotonous and ultra-long endurance flights, control station design considerations, transfer of control between control stations, the management of lost link procedures, and decision-making during emergencies. Some of these concerns have received significant attention in the literature, or are analogous to human factors of manned aircraft. The presentation will focus on issues that are poorly understood, and have not yet been the subject of extensive human factors study. Although many of the reported incidents were related to pilot error, the participants also provided examples of the positive contribution that humans make to the operation of highly-automated systems.

remote pilot station↗

DOE OSTI2022

Deep Reinforcement Learning From Demonstrations to Assist Service Restoration in Islanded Microgrids

Microgrids can be operated in island mode during utility grid outages to support service restoration and improve system resilience. To schedule and dispatch distributed energy resources (DERs) in an islanded microgrid, conventional model-based methods rely on accurate distribution network models and lack generalization and adaptability. Data-driven methods are promising for DER coordination but face practical challenges such as potential hazards to microgrids during online training and insufficient online training opportunities due to low outage rates. This paper presents a novel two-stage learning framework that builds on the deep deterministic policy gradient from demonstrations to identify an optimal restoration strategy. At the pre-training stage, imitation learning is applied to equip the control agent with expert experiences to guarantee acceptable initial performance. At the online training stage, action clipping, reward shaping, and expert demonstrations are leveraged to ensure safe exploration while accelerating the training process. In conclusion, the proposed method is illustrated using the IEEE 123-node system and compared with a representative model-based method and the standard deep deterministic policy gradient method to prove solution accuracy and demonstrate increased computational efficiency.

Du, Yan↗

NASA NTRS2018

A Prognostics Framework Development for Swarm Satellite Formations

Prognostics is the science of predicting the failure(s) of a component or a system and understanding how the performance will change in the event of a failure or degradation mechanism. With accurate predictions of possible failures, autonomous mitigative actions can be taken to correct/repair any issues or alert human operators of a failure threshold exceedance requiring condition-based maintenance. Although there is extensive research on failure predictions for a component or a system, there are significantly more opportunities to foray into failure predictions and prognostics for a system of systems such as an airspace consisting of multiple aircraft, a fleet of unmanned aerial vehicles, and a swarm of intelligent satellite systems. Failure prediction and mitigation are particularly important in autonomous systems such as satellite swarm systems that need effective resource management and minimal human interactions. Based on NASA's decadal survey, there is a clear need to prioritize the development of satellite swarm technology for studies of space physics and Earth science. The science community will propose future missions that return in-situ measurements from a 3-D (three-dimensional) volume of space, with relative spacecraft motion and inter-satellite baselines controlled according to the mission objectives. For such multi-spacecraft missions, it is required that ground operations resources do not scale with the number of satellites, thus compromising the swarm or leading to inefficiencies in resource allocation. Swarms of tens or hundreds of small satellites will require autonomy in attitude control, navigation and failure. Although significant research has been conducted in the areas of autonomous formation flying algorithms, less attention has been given to the development of resilient systems robust to failures.The focus of this research paper is the integration of model-based prognostics into the swarm dynamics control and decision-making algorithms. We simulate swarm management strategies for a subsystem failure to demonstrate the importance of failure predictions by comparing two cases: (i) no health information is provided to the system and utilized in the decision-making process and (2) system health information is obtained using prognostics and employed by the control system. One example scenario presented is for the GPS (Global Positioning System) system of an individual satellite to perform off-nominally due to increasing estimated error. In this scenario, the keep-out zone for that satellite would become more conservative, thereby decreasing the risk of collision. This is achieved via tuning the individual artificial repulsive functions assigned to each satellite.This paper is structured as follows. First we provide an overview of current swarm technology development, where we specifically use the term swarm to define multiple satellites flying in formation in similar orbits, with cross-link communication and station-keeping capabilities. Second, we give an introduction to the Swarm Orbital Dynamics Advisor (SODA), a tool that accepts high-level configuration commands and provides the orbital maneuvers required to achieve the prescribed formation configuration. Third, we provide the details of the model-based prognostics algorithm implementation in SODA. Finally, we present different case studies for potential component/subsystem failures and the swarm responses based with and without failure prediction information.

prognostics↗

NASA NTRS2016

C2-Related Incidents Reported by UAS Pilots

unmanned aircraft systems↗

NASA NTRS2016

Pilot Critical Incident Reports as a Means to Identify Human Factors of Remotely Piloted Aircraft

It has been estimated that aviation accidents are typically preceded by numerous minor incidents arising from the same causal factors that ultimately produced the accident. Accident databases provide in-depth information on a relatively small number of occurrences, however incident databases have the potential to provide insights into the human factors of Remotely Piloted Aircraft System (RPAS) operations based on a larger volume of less-detailed reports. Currently, there is a lack of incident data dealing with the human factors of unmanned aircraft systems. An exploratory study is being conducted to examine the feasibility of collecting voluntary critical incident reports from RPAS pilots. Twenty-three experienced RPAS pilots volunteered to participate in focus groups in which they described critical incidents from their own experience. Participants were asked to recall (1) incidents that revealed a system flaw, or (2) highlighted a case where the human operator contributed to system resilience or mission success. Participants were asked to only report incidents that could be included in a public document. During each focus group session, a note taker produced a de-identified written record of the incident narratives. At the end of the session, participants reviewed each written incident report, and made edits and corrections as necessary. The incidents were later analyzed to identify contributing factors, with a focus on design issues that either hindered or assisted the pilot during the events. A total of 90 incidents were reported. Human factor issues included the impact of reduced sensory cues, traffic separation in the absence of an out-the-window view, control latencies, vigilance during monotonous and ultra-long endurance flights, control station design considerations, transfer of control between control stations, the management of lost link procedures, and decision-making during emergencies. Pilots participated willingly and enthusiastically in the study, and generally had little difficulty recalling critical incidents. The results suggest that pilot interviews can be a productive method of gathering information on incidents that might not otherwise be reported. Some of the issues described in the reports have received significant attention in the literature, or are analogous to human factors of manned aircraft. In other cases, incident reports involved human factors that are poorly understood, and have not yet been the subject of extensive study. Although many of the reported incidents were related to pilot error, the participants also provided examples of the positive contribution that humans make to the operation of highly-automated systems.

unmanned aircraft systems↗

DOE OSTI2022

Defensive Islanding to Enhance the Resilience of Distribution Systems Against Cyber-Induced Failures

The extensive integration of communication, computation, and control technologies into cyber-physical power systems (CPPSs) has increased the vulnerabilities of CPPSs to cyberattacks. This calls for developing solutions that assess and reduce the impacts of cyber-induced failures on CPPSs. This paper proposes a defensive islanding strategy to isolate impacted parts of the CPPS and form self-sufficient islanded grids with an objective of minimum load curtailment. The defensive islanding aims to split a power system into smaller grids to improve its resilience against a potential extreme event. A clustering approach that leverages the hierarchical spectral clustering method is utilized for the optimal defensive islanding. The proposed approach captures the fragility behavior and loading conditions of power system components due to cyber-induced failures. A graphical-based coupling framework is used to map the impacts of cyber failures into operation of power system components. The proposed method is demonstrated on a modified 33-node distribution feeder system integrated with distributed energy resources. The amount of load curtailment and radiality constraints have been used to evaluate the performance of the proposed clustering strategies. The results show the capability of the proposed algorithm to create islands considering the cyber-induced failures for enhanced resilience.

cyber-induced failures↗

DOE OSTI2026

The global policy landscape of ISO 50001 energy management systems

While many options exist to improve industrial demand-side energy efficiency, energy management systems (EnMSs)—particularly those aligned with ISO 50001—are proven to drive continuous and meaningful energy performance improvements. Governments leverage these EnMSs in their policies to advance national objectives including enhancing industrial competitiveness and achieving environmental goals. Existing research has focused on the impact of EnMSs at the company level, while comprehensive work on EnMSs in a global policy context is lacking. We seek to close this gap by investigating the extent to which current national policies incorporate the utilization of EnMSs, particularly the ISO 50001 standard. Our paper employs a hybrid approach, combining a literature review and expert interviews across 28 governments representing > 86% of global primary energy consumption. We dissect policy mechanisms, governance levels, underlying motivations, and trends in present EnMS policies. We find that > 96% of the investigated countries include EnMSs within their policy scope; 90% of policies including EnMSs utilize the ISO 50001 standard in some capacity. Primary policy motivations include decarbonization, energy savings for industrial competitiveness, and energy system resilience. We highlight that in the EnMS context, policy mixes—combining economic incentives, regulatory instruments, and information-based approaches—are more effective than standalone measures. Our work provides a novel global overview of governmental EnMS policies, moving beyond whether EnMS should be adopted to focus on how they can be implemented most effectively.

Moreno, Francisco Luis↗

DOE OSTI2026

Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling as Catalysts for Next-Generation Breakthroughs

The Presidential Symposium (PRES) at the 2025 Fall Meeting, hosted by the President’s Office and Energy and Fuels Division, American Chemical Society (ACS) in Washington, DC, brought together a diverse group of chemists, engineers, and materials scientists working in battery materials & systems, automation and artificial intelligence from academia, industry, and national laboratories. The accelerating demand for high-performance, scalable, and sustainable energy storage has catalyzed a paradigm shift in how materials are dis-covered, devices are engineered, and systems are optimized. This Presidential Symposium, entitled “Revolutionizing Energy Storage: AI, Automation, and Advanced Modeling Driving Next-Gen Breakthroughs”, brings together global leaders to unveil transformative strategies anchored in the AAA framework: Artificial Intelligence, Automation, and Advanced Modeling. Artificial Intelligence is redefining the frontiers of energy storage by enabling predictive design, real-time optimization, and intelligent control across diverse chemistries and architectures. Automation is streamlining the synthesis, characterization, and testing of battery materials, dramatically accelerating innovation cycles and unlocking scalable solutions for grid and mobility applications. Advanced Modeling, spanning atomic to system-level scales, provides unprecedented insight into electrochemical dynamics, degradation pathways, and thermal behavior, particularly when coupled with physics-informed machine learning and digital twin technologies. Digital twins, in turn, leverage the AAA framework by integrating real-time data, physics-based models, and AI predictions into dynamic virtual replicas, enabling proactive diagnostics, optimization, and system resilience. Together, these synergistic pillars are not only re-shaping the scientific landscape but also forging a new era of reproducible, data-driven, and resilient energy storage innovation. In conclusion, this symposium marks a pivotal moment in the convergence of computational intelligence and experimental rigor, charting the course for next-generation breakthroughs in lithium-ion, solid-state, and flow battery technologies.

Artificial Intelligence (AI)↗

DOE OSTI2022

Consensus-Based Approach for Active Power Control and Reserve Estimation in Distributed PV Systems

With the increased adoption of distributed energy resources (DER), they are expected to contribute to power system reliability services and enhance power system stability. This paper presents a distributed consensus control approach for the real-time active power reserve estimation and power management in distributed PV (photovoltaic) systems. The proposed method estimates the cumulative active power reserve from numerous PV generators using only the sparse communication network for a DER aggregator to provide active power regulation services. The real-time active power reserve estimation using the proposed approach can be used by DER aggregators to manage curtailment in distributed PV systems to maintain stipulated reserves and further to provide power system frequency regulation. Using the proposed approach, the DER aggregator only requires measurements at the feeder substation and it does not require information from individual DER units, thereby improving system resiliency. The proposed distributed consensus control method is validated on IEEE 123 testbed using PSCAD simulations.

active power reserve↗

DOE OSTI2024

Security Constrained Distributed Transaction Model for Multiple Prosumers

Massive access of renewable energy has prompted demand-side distributed resources to participate in regulation and improve flexibility of power systems. With large-scale access of massive, decentralized, and diverse distributed resources, demand-side market members have transformed from traditional “consumers” to “prosumers”. To explore the distributed transaction model of prosumers, in this paper, a multi-prosumer distributed transaction model is proposed, and the Conditional Value-at-Risk (CVaR) theory is applied to quantify potential risks caused by the stochastic characteristics inherited from renewable energy. First, a prosumer model under constraints of the distribution network including photovoltaic units, fuel cells, energy storage system, central air conditioning and flexible loads is established, and a multi-prosumer distributed transaction strategy is proposed to achieve power sharing among multiple prosumers. Second, a prosumer transaction model based on CVaR is constructed to measure risks inherited from the uncertainty of PV output within the prosumer and ensure safety of system operation in extreme PV output scenarios. Then, the alternating direction multiplier method (ADMM) is utilized to solve the constructed model efficiently. Finally, distributed transaction costs of prosumers are distributed fairly based on the generalized Nash equilibrium to maximize social benefits. Simulation results show the multi-prosumer distributed transaction mechanism established under the proposed generalized Nash equilibrium method can encourage power sharing among prosumers, increasing their own income and social benefits. Also, the CVaR can assist decision making of prosumers in weighting the risks and benefits, improving system resilience through energy management of prosumers.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Techno-Economic Analysis: Best Practices and Assessment Tools

A team at Sandia National Laboratories (SNL) recognized the growing need to maintain and organize the internal community of Techno - Economic Assessment analysts at the lab . To meet this need, an internal core team identified a working group of experienced, new, and future analysts to: 1) document TEA best practices; 2) identify existing resources at Sandia and elsewhere; and 3) identify gaps in our existing capabilities . Sandia has a long history of using techno - economic analyses to evaluate various technologies , including consideration of system resilience . Expanding our TEA capabilities will provide a rigorous basis for evaluating science, engineering and technology - oriented projects, allowing Sandia programs to quantify the impact of targeted research and development (R&D), and improving Sandia's competitiveness for external funding options . Developing this working group reaffirms the successful use of TEA and related techniques when evaluating the impact of R&D investments, proposed work, and internal approaches to leverage deep technical and robust, business - oriented insights . The main findings of this effort demonstrated the high - impact TEA has on future cost, adoption for applications and impact metric forecasting insights via key past exemplar applied techniques in a broad technology application space . Recommendations from this effort include maintaining and growing the best practices approaches when applying TEA, appreciating the tools (and their limits) from other national laboratories and the academic community, and finally a recognition that more proposals and R&D investment decision s locally at Sandia , and more broadly in the research community from funding agencies , require TEA approaches to justify and support well thought - out project planning.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Financing Federal Microgrids [Slides]

A microgrid can enhance a site’s electrical power system during normal operations, as well as provide reliable backup power to critical loads when electric utility power is interrupted. When components of a microgrid (and potentially the entire system) can be justified economically and paid for out of energy savings or avoided costs, implementation by one of several privately financed federal procurement mechanisms is possible. However, it is typically difficult to achieve enough savings and avoided costs to cover the design, equipment, and installation of certain microgrid components that are required to integrate the system. This presentation explores procurement options and agreements that may be useful to federal agencies interested in implementing microgrids at their sites. This information will be most useful to agencies when they are exploring electric energy system resilience options and/or considering different procurement options to meet their needs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Hydrogen Storage for Flexible Fossil Fuel Power Generation: Integration of Underground Hydrogen Storage with Gas Turbine (Final Report)

As the nation continues to encourage, through market structures and financial incentives, the proliferation of intermittent renewable electricity, how to optimize the ever-changing electric grid and identify means to retain and improve resilience, while ensuring continued reductions in GHG emissions, will be critical. According to Bloomberg, wind & solar generated 10.5% of US electricity in 2020 and that percentage continues to grow. In support of expanding renewable energy use, and to address its intermittent nature, this project will develop the Hydrogen Storage for Flexible Fossil Fuel Power Generation platform that is dispatchable, reliable, repeatable and have the ability to produce zero or negative carbon power while interfacing with geology capable of CO2 and hydrogen storage. GTI Energy (GTIE) and team members Illinois State Geological Survey (ISGS), Mitsubishi Heavy Industries America (MHIA), Ameren Illinois, Hexagon Purus, and the Low Carbon Resources Initiative (LCRI) completed a Phase I Conceptual Study under contract DE-FE0032012 for Hydrogen Storage for Flexible Fossil Fuel Power Generation: Integration of Underground Hydrogen Storage with Gas Turbine. The Hydrogen Storage for Flexible Fossil Fuel Power Generation platform addresses the intermittent nature of the expanding use of Variable Renewable Energy (VRE) generation. The low cost of the electricity (COE) generated results in greater dispatch and more operation at higher power levels (higher efficiency), fewer short intervals, and fewer start/stop cycles. The reliable, resilient system can produce zero carbon power and store hydrogen. It will demonstrate hydrogen storage in geologic formations like those used in natural gas underground storage thus enabling large scale storage of hydrogen in sedimentary strata across the United States rather than in geographically restricted salt caverns. The Phase I study confirmed the system is feasible and generates power at lower cost than other low carbon approaches. The demonstration defines the pathway for broad commercial application and will accelerate the development of larger systems suitable for centralized utility scale electricity production. The study advanced the maturity of the H 2 storage-based system with flexible power generation by completing a Pre-FEED study (Phase II). The Pre-FEED focused on the selected Energy Farm on the University of Illinois Urbana-Champaign (UIUC) site that includes above ground and underground hydrogen storage, low-carbon hydrogen production (GTI’s Compact Hydrogen Generator, CHG) with underground CO2 sequestration, and a 40-MW class gas turbine. The Pre-FEED addressed the entire system and its interconnection to the natural gas and electric grid and mitigation of key risks, such as storage behavior, load-following, and system operation. During Phase 1 of the project, the team completed key tasks, which moved the entire demonstration project, specific components and approaches closer to commercialization. These Phase I Accomplishments include: Completing System Requirements Review; Completing System Layout and Modeling - Heat & Mass Balance and Process Flow Diagram; Completing modelling of 9 turbine performance cases; Evaluating rock strata for underground storage of hydrogen and sequestration of carbon dioxide; Completing initial modelling of underground storage of hydrogen and withdrawal with evaluation of loss and water production; Identifying roadable storage for above ground hydrogen storage; Identifying existing electrical infrastructure for receiving/delivering electricity; Identifying existing gas supply infrastructure for receiving natural gas; Document concept design/development plans in required reports. Conclusions: The 12-month Feasibility study in Phase I study was completed and confirmed the system is feasible and generates power at lower cost than other low carbon approaches and even lower cost than the reference NGCC plant without carbon capture when taking advantage of 45Q carbon credits. The study enabled the fidelity of the concept to be improved and allowed identification of the requirements for the system. Defining the individual system and component requirements was performed via the system requirements review with the whole team. These requirements were then incorporated into and iterated with our Heat & Mass Balance process model and process flow diagrams were generated to reflect the overall system. This information was then used to complete the TEA and show economic feasibility. Large scale non-salt geologic storage of hydrogen is an enabling technology for a hydrogen-fired turbine that can be retrofitted into large-scale electric generating units (EGU). Our demonstration will include 428 MWh or ~4 hours full load of hydrogen storage (above and underground). Carbon capture inherent to the CHG process can capture 90% CO 2 (with upgrades to >98%). This system provides a COE of 23% savings relative to an NGCC with a post combustion amine system. Our proposed storage system decouples carbon capture and hydrogen production from power production; therefore, we expect our proposed system’s efficiency and variable COE to be superior resulting in overall higher dispatch and reduced deep cycling. Our demonstration will be full to multi-day hydrogen storage and has the potential for longer (seasonal) duration commercially. The demonstration defines the pathway for broad commercial application and will accelerate the development of larger systems suitable for centralized utility scale electricity production.

03 NATURAL GAS↗

DOE OSTI2024

U.S. DOE Midwest Combined Heat and Power Technical Assistance Partnership (Midwest CHP TAP) (Final Technical Report)

The University of Illinois Chicago (UIC) was awarded the U.S. DOE Midwest Combined Heat and Power Technical Assistance Partnership (Midwest CHP TAP) program to provided technical and policy expertise to support local opportunities to promote CHP, waste heat to power, district energy, and microgrids in the Midwest and Central regions of the U.S. that included the states of Illinois, Indiana, Iowa, Kansas, Michigan, Minnesota, Missouri, Nebraska, Ohio, and Wisconsin. During this contract period, UIC, through the Midwest CHP TAP activities, provided significant regional support to the U.S. strategic goals of: 1) Stimulating America’s Energy Revolution and Promoting Energy Independence; 2) Promoting Jobs and Manufacturing Competitiveness; 3) Supporting a Positive Trade Balance; 4) Enhancing Energy System Resiliency and Energy Security; and 5) Improving the Nation’s Infrastructure. UIC met the annual go/no-go metrics each year and either met and/or exceeded the milestones each year.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2025

Estimates of the Economic Impacts of Long-Duration, Widespread Power Disruptions in Puerto Rico

A typical electricity customer in Puerto Rico experienced nearly 27 hours of power interruptions in 2023–with many customers experiencing extremely long duration outages during a single event (i.e., greater than one month). This project involved conducting state-of-the-art surveying to assess the direct costs of power outages occurring across Puerto Rico, developing customer-specific models to estimate future costs over varying outage durations, and comparing these estimates to FEMA’s Value of Unit Service for Electricity. We estimate that a territory-wide power outage may cost customers $\$1$, $\$5$ and $\$29$ billion during one-, 14-, and 30-day interruptions, respectively. However, these are lower-bound estimates because our study focused on direct economic costs and, by necessity, did not fully incorporate (1) indirect impacts to the economy; (2) costs to repair or replace damaged utility infrastructure; and (3) the broader societal consequences including increased morbidity- and mortality-related costs. The information contained in this study can be used to estimate the direct economic value of past or proposed investments in power system resilience. We conclude with a discussion of this study’s limitations and suggest additional research to improve stakeholder understanding of the impacts of power outages across Puerto Rico.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2024

Cybersecurity Baselines for Electric Distribution Systems and DER

The National Association of Regulatory Utility Commissioners (NARUC) has partnered with the Department of Energy (DOE) to develop a set of cybersecurity baselines for electric distribution systems and the distributed energy resources (DERs) that connect to them. Cybersecurity is an integral underpinning of power system resilience, and this initiative builds on work that states have undertaken over the last decade to mitigate cybersecurity risk across their critical infrastructures.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Hydrogen Education for a Decarbonized Global Economy (H 2 EDGE) (Final Technical Report)

The energy sector is undergoing rapid growth and transformation, creating urgent demand for a skilled workforce to support emerging technologies and resilient systems. Hydrogen is an emerging solution for “hard to abate” sectors, including heavy industry and transportation that also provides optionality for the electric system and enables long‑duration energy storage. As hydrogen scales from traditional industrial uses to new applications, success depends on knowledgeable engineers, technicians, planners, and operators safely deploying hydrogen technologies across the full value chain: production, delivery, storage, and end use. The H 2 EDGE initiative, funded by the U.S. Department of Energy’s Hydrogen and Fuel Cell Technologies Office from 2020 to 2025, was launched to prepare people for careers hydrogen and related technologies. Through its interactive approach, H 2 EDGE equipped stakeholders with knowledge and tools to build a reliable and sustainable energy future together. H 2 EDGE built a national network of academic and industry partners to deliver modular training, share open-access curricula, and engage diverse talent pipelines. The program leveraged EPRI’s extensive industry membership and expanded on the train-the-trainer model of the GridEd program to connect educators, employers, and community organizations across all regions of the U.S. New methods were introduced to more systematically map hydrogen competencies and assess curricula using traditional and AI-assisted approaches. Outcomes included delivery of professional short courses, developing university curriculum, sponsoring faculty and student projects, and engaging stakeholders through workshops, site tours, and webinars.

08 HYDROGEN↗

DOE OSTI2025

Exponential Backoff and Its Security Implications for Safety-Critical OT Protocols over TCP/IP Networks

The convergence of Operational Technology (OT) and Information Technology (IT) networks has become increasingly prevalent with the growth of Industrial Internet of Things (IIoT) applications. This shift, while enabling enhanced automation, remote monitoring, and data sharing, also introduces new challenges related to communication latency and cybersecurity. Oftentimes, legacy OT protocols were adapted to the TCP/IP stack without an extensive review of the ramifications to their robustness, performance, or safety objectives. To further accommodate the IT/OT convergence, protocol gateways were introduced to facilitate the migration from serial protocols to TCP/IP protocol stacks within modern IT/OT infrastructure. However, they often introduce additional vulnerabilities by exposing traditionally isolated protocols to external threats. This study investigates the security and reliability implications of migrating serial protocols to TCP/IP stacks and the impact of protocol gateways, utilizing two widely used OT protocols: Modbus TCP and DNP3. Our protocol analysis finds a significant safety-critical vulnerability resulting from this migration, and our subsequent tests clearly demonstrate its presence and impact. A multi-tiered testbed, consisting of both physical and emulated components, is used to evaluate protocol performance and the effects of device-specific implementation flaws. Through this analysis of specifications and behaviors during communication interruptions, we identify critical differences in fault handling and the impact on time-sensitive data delivery. The findings highlight how reliance on lower-level IT protocols can undermine OT system resilience, and they inform the development of mitigation strategies to enhance the robustness of industrial communication networks.

DNP3↗