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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Regional climate change: consensus, discrepancies, and ways forward

Climate change has emerged across many regions. Some observed regional climate changes, such as amplified Arctic warming and land-sea warming contrasts have been predicted by climate models. However, many other observed regional changes, such as changes in tropical sea surface temperature and monsoon rainfall are not well simulated by climate model ensembles even when taking into account natural internal variability and structural uncertainties in the response of models to anthropogenic radiative forcing. This suggests climate model predictions may not fully reflect what our future will look like. The discrepancies between models and observations are not well understood due to several real and apparent puzzles and limitations such as the “signal-to-noise paradox” and real-world record-shattering extremes falling outside of the possible range predicted by models. Addressing these discrepancies, puzzles and limitations is essential, because understanding and reliably predicting regional climate change is necessary in order to communicate effectively about the underlying drivers of change, provide reliable information to stakeholders, enable societies to adapt, and increase resilience and reduce vulnerability. The challenges of achieving this are greater in the Global South, especially because of the lack of observational data over long time periods and a lack of scientific focus on Global South climate change. To address discrepancies between observations and models, it is important to prioritize resources for understanding regional climate predictions and analyzing where and why models and observations disagree via testing hypotheses of drivers of biases using observations and models. Gaps in understanding can be discovered and filled by exploiting new tools, such as artificial intelligence/machine learning, high-resolution models, new modeling experiments in the model hierarchy, better quantification of forcing, and new observations. Conscious efforts are needed toward creating opportunities that allow regional experts, particularly those from the Global South, to take the lead in regional climate research. This includes co-learning in technical aspects of analyzing simulations and in the physics and dynamics of regional climate change. Finally, improved methods of regional climate communication are needed, which account for the underlying uncertainties, in order to provide reliable and actionable information to stakeholders and the media.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Hanging by a thread? Forests and drought

Trees are the living foundations on which most terrestrial biodiversity is built. Central to the success of trees are their woody bodies, which connect their elevated photosynthetic canopies with the essential belowground activities of water and nutrient acquisition. The slow construction of these carbon-dense, woody skeletons leads to a slow generation time, leaving trees and forests highly susceptible to rapid changes in climate. Other long-lived, sessile organisms such as corals appear to be poorly equipped to survive rapid changes, which raises questions about the vulnerability of contemporary forests to future climate change. The emerging view that, similar to corals, tree species have rather inflexible damage thresholds, particularly in terms of water stress, is especially concerning. This Review examines recent progress in our understanding of how the future looks for forests growing in a hotter and drier atmosphere.

Science & Technology - Other Topics↗
DOE OSTI2022

SAFE-OCC: A novelty detection framework for Convolutional Neural Network sensors and its application in process control

Herein we present a novelty detection framework for Convolutional Neural Network (CNN) sensors that we call Sensor-Activated Feature Extraction One-Class Classification (SAFE-OCC). We show that this framework enables the safe use of computer vision sensors in process control architectures. Emergent control applications use CNN models to map visual data to a state signal that can be interpreted by the controller. Incorporating such sensors introduces a significant system operation vulnerability because CNN sensors can exhibit high prediction errors when exposed to novel (abnormal) visual data. Unfortunately, identifying such novelties in real-time is nontrivial. To address this issue, the SAFE-OCC framework leverages the convolutional blocks of the CNN to create an effective feature space to conduct novelty detection using a desired one-class classification technique. This approach engenders a feature space that directly corresponds to that used by the CNN sensor and avoids the need to derive an independent latent space. We demonstrate the effectiveness of SAFE-OCC via simulated control environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Rapid Viscoelastic Deformation Slows Marine Ice Sheet Instability at Pine Island Glacier

The ice sheets of the Amundsen Sea Embayment (ASE) are vulnerable to the marine ice sheet instability (MISI), which could cause irreversible collapse and raise sea levels by over a meter. The uncertain timing and scale of this collapse depend on the complex interaction between ice, ocean, and bedrock dynamics. The mantle beneath the ASE is likely less viscous (~10 18 Pa s) than the Earth's average mantle (~10 21 Pa s). In this paper we show that an effective equilibrium between Pine Island Glacier's retreat and the response of a weak viscoelastic mantle can reduce ice mass lost by almost 30% over 150 years. Other components of solid Earth response—purely elastic deformations and geoid perturbations—provide less stability than the viscoelastic response alone. Uncertainties in mantle rheology, topography, and basal melt affect how much stability we expect, if any. Our study indicates the importance of considering viscoelastic uplift during the rapid retreat associated with MISI.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Bridge Seismic Screening Tool (BSST), Version 2.0

The Regional Resiliency Assessment Program (RRAP) is a cooperative assessment of specific critical infrastructure within a designated geographic area and a regional analysis of the surrounding infrastructure that addresses a range of infrastructure resilience issues that could have regionally and nationally significant consequences. In 2018, DHS’s Cybersecurity and Infrastructure Security Agency (CISA) sponsored the Oregon Transportation Systems RRAP project in coordination with the Office of the Governor (under the oversight of the state resilience officer), the Oregon Office of Emergency Management (OEM), the Oregon Department of Transportation (ODOT), and other regional stakeholders (CISA 2021). This project focuses on assessing the impacts of a Cascadia Subduction Zone (CSZ) earthquake on state transportation systems and, in particular, how those impacts may affect the ability of emergency response efforts to move supplies into the region. The intended outcome of this analysis is the prioritization of transportation routes and modes for additional planning, investment, hardening, or other activities to enhance their resilience—and therefore, to enhance their ability to support response and recovery efforts following a CSZ earthquake. An important part of this transportation system-level assessment has been to assess the seismic vulnerability of the state highway system. In doing so, the RRAP project team used the Bridge Seismic Screening Tool (BSST) to assess, at a system-level, the potential impacts that a CSZ earthquake could have on state highway bridges (Bergerson et al. 2019).1 Argonne National Laboratory (Argonne), in collaboration with the Washington State Department of Transportation (WSDOT), originally developed the BSST as part of the 2017 Washington State Transportation Systems RRAP project, a sister project to the 2018 Oregon Transportation Systems RRAP project. Argonne updated the BSST during this more recent project in Oregon based on feedback from stakeholders and subject matter experts (SMEs) on the original version of the tool. The first step in the BSST is to assess the seismic vulnerability of roadway bridges following a CSZ earthquake to determine a projected or potential damage state. Damage states then help determine approximate reopening times for bridge crossings.2 This document provides details on the BSST methodology, the implementation of that tool to analyze the projected damage incurred in a CSZ earthquake scenario, and the determination of corresponding reopening times of interstate, state highway, and local bridges following such an event.

58 GEOSCIENCES↗
DOE OSTI2020

Characteristics of locational uncertainty marginal price for correlated uncertainties of variable renewable generation and demands

With the rapid increase of variable renewable energy sources in power systems, how to manage and price the uncertainty of renewable resources’ power outputs is becoming an urgent issue. Current market designs considering the uncertainties are mainly based on the probabilistic scenario set of demand and renewable energy resources power outputs. This consideration makes market designs vulnerable to three significant challenges when put into practice. First, the accurate probability distribution of renewable generation is hard to obtain in real-time. Second, it is challenging to clear the market timely with many scenarios to guarantee accuracy. Third, generation cost recovery cannot be guaranteed for some scenarios. To overcome these challenges, this paper proposes a locational uncertainty marginal price model to price the uncertainty explicitly based on a scenario-free stochastic market-clearing model. Instead of using the probabilistic scenario set, the uncertainty of renewable energy sources and loads is modeled with distributionally-robust chance constraints. The correlation of uncertainties can be endogenously modeled in both the market-clearing and the locational uncertainty marginal price formation. Furthermore, this paper proves that generation cost recovery, revenue adequacy, and partial market equilibrium can be achieved using the locational uncertainty marginal price model. Numerical results from both the small and large systems simulations validate that the generation cost recovery is maintained no matter the generation participates in uncertainty mitigation or not. The transmission congestion surplus is also allocated appropriately among loads, renewable energy sources, and financial transmission right owners.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Advancing Industry 4.0: Multimodal Sensor Fusion for AI-Based Fault Detection in 3D Printing

Additive manufacturing, particularly fused deposition modeling, is transforming modern production by enabling rapid prototyping and complex part fabrication. However, its layer-by-layer process remains vulnerable to faults such as nozzle clogging, filament runout, and layer misalignment, which compromise print quality and reliability. Traditional inspection methods are costly, time-intensive, and often limited to post-process analysis, making them unsuitable for real-time intervention. In this current study, the authors developed a novel, low-cost, and portable faultdetection system that leverages multimodal sensor fusion and artificial intelligence for real-time monitoring in FDM-based 3D printing. The system integrates acoustic, vibration, and thermal sensing into a non-intrusive architecture, capturing complementary data streams that reflect both mechanical and process-related anomalies. Acoustic and thermal sensors operate in a fully contactless manner, while the vibration sensor requires minimal attachment such that it will not interfere with printer hardware, thereby preserving portability and ease of deployment. The multimodal signals are processed into spectrograms and time-frequency features, which are classified using convolutional neural networks for intelligent fault detection. The proposed system advances Industry 4.0 objectives by offering an affordable, scalable, and practical monitoring solution that improves faultdetection accuracy, reduces waste, and supports sustainable, adaptive manufacturing.

42 ENGINEERING↗
DOE OSTI2022

Demographic composition, not demographic diversity, predicts biomass and turnover across temperate and tropical forests

The growth and survival of individual trees determine the physical structure of a forest with important consequences for forest function. However, given the diversity of tree species and forest biomes, quantifying the multitude of demographic strategies within and across forests and the way that they translate into forest structure and function remains a significant challenge. Here, we quantify the demographic rates of 1961 tree species from temperate and tropical forests and evaluate how demographic diversity (DD) and demographic composition (DC) differ across forests, and how these differences in demography relate to species richness, aboveground biomass (AGB), and carbon residence time. We find wide variation in DD and DC across forest plots, patterns that are not explained by species richness or climate variables alone. There is no evidence that DD has an effect on either AGB or carbon residence time. Rather, the DC of forests, specifically the relative abundance of large statured species, predicted both biomass and carbon residence time. Our results demonstrate the distinct DCs of globally distributed forests, reflecting biogeography, recent history, and current plot conditions. Linking the DC of forests to resilience or vulnerability to climate change, will improve the precision and accuracy of predictions of future forest composition, structure, and function.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Vegetation water sources in California's Sierra Nevada (USA) are young and change over time, a multi-isotope ( δ 18 O, δ 2 H, 3 H) tracer approach.

Sierra Nevada forests transpire a significant amount of California's water resources, sparking interest in applying forest management to improve California's water supply. Determining the source water of evapotranspiration enables forest managers to make informed decisions. To this end, a significant interest in critical zone science is to develop new methods to work across time scales to predict subsurface water storage and use. Here, forest vegetation accessed young water and switched sources depending on availability, suggesting that forest drought vulnerability may depend on the range of water sources available (rain, snowmelt and deeply stored water). This finding also suggests that changes in transpiration rates may have immediate effects on water sources in close proximity to vegetation, and delayed effects on storage and runoff. New δ 18 O, δ 2 H and 3 H data were used to track precipitation, runoff, evapotranspiration and storage through the critical zone seasonally, including seasons where evapotranspiration and snowmelt were in phase (winter snowmelt) and out of phase (seasonally dry summer). The main source of this headwater catchment's runoff is derived from its meadow saturated zone water, which was dominated by snowmelt. Water that originated as snowmelt contributed to transpiration, unless other sources, such as recent rain, became available. In cases where xylem δ 18 O and δ 2 H signatures matched those of deeper saturated zone water, 3 H data showed that xylem water was distinctly younger than the deep saturated zone water. During 2016, which experienced relatively normal snowpack in winter and seasonally dry summer conditions, mean summer saturated zone water and vegetation water were similar in δ 18 O, –12.4 ± 0.04 ‰ and – 12.5 ± 0.3 ‰, respectively, but were distinctly different in 3 H, 5.5 ± 0.2 pCi/L and 13.7 ± 1.1 pCi/L, respectively. While δ 18 O shows that vegetation and meadow saturated zone water have similar origins, 3 H shows they have dissimilar ages.

58 GEOSCIENCES↗
DOE OSTI2022

4D electrical resistivity tomography for assessing the influence of vegetation and subsurface moisture on railway cutting condition

Instability of slopes, embankments, and cuttings on the railway network is increasingly prevalent globally. Monitoring vulnerable infrastructure aids in geotechnical asset management, and improvements to transport safety and efficiency. Here, we examine the use of a novel, near-real-time Electrical Resistivity Tomography (ERT) monitoring system for assessing the stability of a railway cutting in Leicestershire, United Kingdom. In 2015, an ERT monitoring system was installed across a relict landslide (grassed) and an area of more stable ground on either side (wooded), to monitor changes in electrical resistivity through time and space, and to assess the influence of different types of vegetation on the stability of transportation infrastructure. Two years of 4-Dimensional ERT monitoring results are presented here, and petrophysical relationships developed in the laboratory are applied to calibrate the resistivity models in order to provide an insight into hydrogeological pathways within a railway cutting. The influence of vegetation type on subsurface moisture pathways and on slope stability is also assessed – here we find that seasonal subsurface changes in moisture content and soil suction are exacerbated by the presence of trees (wooded area). This results in shrink-swell behaviour of the clays comprising the railway cutting, resulting in fissuring and a reduction in shear strength, leading to instability. As such, it is proposed that on slopes comprised of expansive soils, grassed slopes are beneficial for stability. Insights into the use of 4-D ERT for monitoring railway infrastructure gained from this study may be applied to the monitoring of critical geotechnical assets elsewhere.

58 GEOSCIENCES↗
DOE OSTI2023

Oxygen priming induced by elevated CO 2 reduces carbon accumulation and methane emissions in coastal wetlands

Warming temperatures and elevated carbon dioxide (CO 2 ) are inextricably linked global change phenomena, but are rarely manipulated together in field experiments. As a result, ecosystem-level responses to these interacting facets of global change remain poorly understood. In 2017, we started an experiment in a coastal wetland that crosses warming and elevated CO 2 , to better understand how the interactions of these factors affect the plants, biogeochemistry, and overall survival of these ecosystems. However, contrary to our expectations, when elevated CO 2 is combined with warming, the wetland accumulated less carbon, making it more vulnerable to sea-level rise. This was due to the plants transporting more oxygen into the soil, which stimulated aerobic decomposition. At the same time, the increased supply of oxygen reduced net methane (CH 4 ) emissions from the system, even though warming alone substantially increased CH 4 emission. Together, these results demonstrate that ecosystem responses to interacting facets of global change may be mediated by plant traits that regulate the soil environment. Thus, plant responses are critical for predicting future ecosystem survival and climate feedbacks.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Immunity Study: Port Impedance Measurement of PMU and PCI testing under EMP

With the increased requirements of real-time grid monitoring, disturbance location, and situation awareness, Phasor Measurement Units (PMUs) have become more critical for the Wide Area Measurement System (WAMS). However, the vulnerability of PMUs has not been well studied, especially under electromagnetic pulse (EMP) scenarios. The stable operation of the power system will be affected directly once EMP damages them. Therefore, studying their immunity to EMP events is urgent and necessary. In this paper, the effective impedance measurement scheme and pulsed current injection (PCI) testing are proposed for the port impedance measurement and immunity levels of PMUs. The equivalent non-uniform transmission line model is established to eliminate the impact of the fixture in the de-embedding process. Then, the circuit of the pulsed current generator is set to generate a damping sinusoid, and the double exponential wave is applied to the port. Finally, using measured impedance as a generator load, the voltage and current responses of different ports are calculated in the PCI testing simulation. In conclusion, results reveal the characteristics of port impedance, waveforms of voltage and current, and distribution of accumulative energy. The relation between port impedance and the waveforms is discussed.

42 ENGINEERING↗
DOE OSTI2024

Machine-Learning-Based Mapping and Modeling of Solar Energy with Ultra-High Spatiotemporal Granularity

Despite the rapid growth of solar energy, we still lack a dynamic, high-fidelity database that tracks the spatiotemporal variations of solar PVs and their associated infrastructures across different places at a spatially resolved scale. The absence of such data presents a barrier to various applications such as solar PV growth projection, solar energy integration, solar incentive design, and climate risk assessment. In this project, we aim to bridge this gap by developing AI-based algorithms to extract granular information about solar PV installations and their associated infrastructures (i.e., distribution grids) from widely available unstructured data like remote sensing images and street views. As a result, we have built the Solar Energy Atlas, a fine-grained, large-scale geospatial overlay of distributed solar PVs and distribution grids. On top of it, we have advanced the understanding of solar adoption and distribution grid vulnerability to climate-induced extremes. Our major contributions can be summarized as follow: (1) By developing new AI algorithms, we have built the most comprehensive solar PV spatiotemporal database covering the entire US. This is the first time we obtained the exact GPS locations, size, subtype, and installation year information for rooftop solar PVs across the US. This database can be used for solar PV growth projection, solar energy integration, solar energy policy analysis and design, and spatially-resolved climate risk assessment. (2) Leveraging this database, we have uncovered the socioeconomic driving factors that are correlated with earlier onset of solar adoption and higher saturated adoption levels. We have identified the heterogeneity in the effects of different types of financial incentives on solar adoption and provided implications for tailoring incentive design based on local income levels to promote equitable solar adoption. (3) We have developed a distribution grid GIS mapping algorithm which can obtain granular geospatial and topology information about distribution grids using multi-modal open data, reducing the dependency on hard-to-obtain smart meter data of conventional approaches. It shows effectiveness in both the U.S. and Sub-Saharan Africa. Using this algorithm, we have uncovered the non-uniform vulnerability of distribution grids to wildfires in California in the aspects of undergrounding protection and Distributed Energy Resources (DER) preparedness. This has provided important implications for improving the affordability and equity of grid adaptation approaches. (3) We have made our produced database publicly available and provided user-friendly interface to enable various stakeholders and the general public to interact with the data. We have also integrated the produced data into the Data Commons platform to enable the public to access the data and correlate it with other location-specific characteristics simply using natural language as queries. The impact of our project is three-fold: (1) New algorithms for mapping solar PVs and distribution grids across space and time, which are open source to facilitate researchers and industry; (2) New databases of solar PVs and distribution grids that have been made publicly available for engineering, social, and policy applications; (3) New understandings and actionable insights on the potential approaches to promoting solar adoption and reducing energy infrastructure vulnerabilities. In this report, we start by discussing the project background and motivation (section 5), followed by the overview of project objectives (section 6). Results and discussion for each task are presented in section 7. Significant accomplishments are summarized in section 8. This report will be concluded by discussing the paths forwards (section 9), products (section 10), and team roles (section 11).

14 SOLAR ENERGY↗
DOE OSTI2021

The Effects of Climate Change on Interregional Electricity Market Dynamics on the U.S. West Coast

The United States (U.S.) West Coast power system is strongly influenced by variability and extremes in air temperatures (which drive electricity demand) and streamflows (which constrain hydropower production). As hydroclimate changes across the West Coast, a combination of forces may work in tandem to make its bulk power system more vulnerable to physical reliability issues and market price shocks. In particular, a warmer climate is expected to increase summer cooling (electricity) demands and shift the average timing of peak streamflow (hydropower production) away from summer to the spring and winter, depriving power systems of hydropower when it is needed the most. Here, we investigate how climate change could alter interregional electricity market dynamics on the West Coast, including the potential for hydroclimatic changes in one region (e.g. Pacific Northwest (PNW)) to “spill over” and cause price and reliability risks in another (e.g. California). We find that the most salient hydroclimatic risks for the PNW power system are changes in streamflow, while risks for the California system are driven primarily by changes in summer air temperatures, especially extreme heat events that increase peak system demand. Altered timing and amounts of hydropower production in the PNW do alter summer power deliveries into California but show relatively modest potential to impact prices and reliability there. Instead, it is future climate conditions (extreme heat) in California that may exert a stronger significant influence on prices and reliability in the PNW, especially if California continues to rely on its northern neighbor for imported power to meet higher summer demands.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

A Photovoltaic MPPT Charge Controller Real-Time Testbed for Cybersecurity Applications

The increasing deployment of distributed energy resources (DER) over the last decade is a great ally to combat climate change and strengthen the grid during increasingly common extreme weather events. However, DER systems, combined with the ongoing transition to a digital power grid, also pose substantial cybersecurity threats. One of the most common communication protocols used in DER integration is the Distributed Network Protocol 3 (DNP3), which is known to have many security vulnerabilities. Thus, it is essential to investigate cyberattack behaviors and mitigation on power systems using DNP3. In this paper, we designed and implemented a cybersecurity testbed for a simulated photovoltaic (PV) maximum power point tracking (MPPT) charge controller. Our testbed uses an MPPT charge controller simulated on a Typhoon HIL602+ real-time simulator with a real DNP3 communication connection over TCP/IP, allowing for safe and efficient monitoring and manipulation of data traffic between the simulated hardware and supervisory control and data acquisition (SCADA) systems.

14 SOLAR ENERGY↗
DOE OSTI2020

Assessing the Vulnerability of Unmanned Aircraft Systems to Directed Acoustic Energy

The increasingly large payloads of Unmanned Aircraft Systems (UASs) are exponentially increasing the threat to the nuclear enterprise. Current mitigation using RF interference is effective, but not feasible for fully autonomous systems and is prohibited in many areas. A new approach to UAS threat mitigation is needed that does not create radio interference but is effective against any type of vehicle. At the present time there is no commercial counter-UAS system that directly assaults the mems gyros and accelerometers in the Inertial Measurement Unit on the aircraft. But lab testing has revealed resonances in some IMUs that make them susceptible to moderate amplitude acoustic monotones. Sandia's energetic materials facility has enabled a quick and thorough exploration of UAS vulnerability to directed acoustic energy by using intense acoustic impulses to destabilize or down a UAS. We have: 1) detonated/deflagrated explosive charges of various sizes; 2) accurately measured impulse pressure and pulse duration; 3) determined what magnitude of acoustic insult to the IMU disrupts flight and for how long and; 4) determined if the air blast/shock wave on aircraft/propellers disrupts flight.

42 ENGINEERING↗
DOE OSTI2024

A late glacial paleoenvironmental and climate record from the Sierra de Juarez, Baja California

Ciénegas are desert wetlands that are strongly correlated with the stability of the hydrologic cycle in arid landscapes. However, these environments are particularly vulnerable to climate change, drought, water diversion, and fire suppression which all have contributed to the degradation of ciénegas along the U.S.-Mexican borderlands. Therefore, identifying the timing of precipitation patterns in this region is of particular interest because of its relationship to many ecological responses of the landscape such as groundwater recharge and fire. Here, we present the first-ever fire paleoenvironmental record from Ciénega Chimeneas, a ciénega complex in the Sierra de Juárez of Baja California. We explore how changes in the amount and seasonality of moisture affected ciénega complexes and fire activity from across the southwestern North American region over the past 45,000 years. Further, our record suggests that during the late glacial period, 41,000–21,000 cal yr BP, the increase of Larrea and Quercus indicate an increase in summer precipitation. Subsequently, when summer precipitation increased, pollen preservation and pollen accumulation rates (PAR) also increased. Increased vegetation allowed for increased fire activity during the late glacial period. Regionally, most of the comparison sites also indicated wet conditions during the full glacial period. However, around 21,000 cal yr BP, effective moisture decreased resulting in a dramatic change in the vegetation assemblage. Specifically, the summer wet taxa disappeared, while pollen preservation and PAR decreased, suggesting a dry period until ~14,000 cal yr BP. Little fire activity is recorded after 21,000 cal yr BP, likely due to the absence of fuels. At ~14,000 cal yr BP, Larrea and Quercus reappear suggesting increased summer precipitation. However, the appearance of Cyperaceae and increases in grasses suggest increased winter precipitation. We suggest that the combination of summer wet and winterwet taxa ~14,000 cal yr BP represents an increase in ENSO conditions, while the summer moisture controls remained relatively constant.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Developing a Supply Chain Security Program

Amid growing concerns over foreign manufacturing for components and devices deployed in critical energy infrastructure, this research from the national labs will highlight best practices for developing and maintaining a supply chain security program. Tools for asset inventory, tips for developing and maintaining software- and hardware-bills-of-materials (SBOMs and HBOMs), recommended contractual language for vendor agreements, and identification of responsibilities will be shared. We discuss the one-time requirements to enable a successful supply chain security program and the best ways to operationalize this program for maximum impact, including development of robust practices for vulnerability tracking, patch management, and workarounds, with understanding of the reliability and uptime requirements for utilities. The recommendations shared are based on a cyber-informed engineering approach to identification of high-consequence impacts and the engineering controls related to supply chain management that can best mitigate these impacts. This approach allows for prioritization of resources. Additionally, we highlight relative up-front and ongoing costs associated with recommended controls. Viewers will leave with an understanding what a supply chain security program is, and what steps, prioritized for resource-constrained organizations, can build a robust program.

14 SOLAR ENERGY↗