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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Infrared-Fused Vision-Based Thermoregulation Performance Estimation for Personal Thermal Comfort-Driven HVAC System Controls

Thermal comfort is one of the primary factors influencing occupant health, well-being, and productivity in buildings. Existing thermal comfort systems require occupants to frequently communicate their comfort vote via a survey which is impractical as a long-term solution. Here, we present a novel thermal infrared-fused computer vision sensing method to capture thermoregulation performance in a non-intrusive and non-invasive manner. In this method, we align thermal and visible images, detect facial segments (i.e., nose, eyes, face boundary), and accordingly read the temperatures from the appropriate coordinates in the thermal image. We focus on the human face since it is often clearly visible to cameras and is not merged into a hot background (unlike hands). We use a regularized Gaussian Mixture model to track the thermoregulation changes over time and apply a heuristic algorithm to extract hot and cold indices. We present a personalized and a generalized comfort modeling method, selected based on the availability of the occupant historical indices measurements in a neutral environment, and use the time-series of the hot and cold indices to define corrections to HVAC system operations in the form of setpoint constraints. To evaluate the efficacy of our proposed approach in responding to thermal stimuli, we designed a series of controlled experiments to simulate exposure to cold and hot environments. While applying personalized modeling showed an acceptable average accuracy of 91.3%, the generalized model’s average accuracy was only 65.2%. This shows the importance of having access to physiological records in modeling and assessing comfort. We also found that individual differences should be considered in selecting the cooling and heating rates when some knowledge of the occupant’s overall thermal preference is available.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Historical evaluation and future projections of compound heatwave and drought extremes over the conterminous United States in CMIP6 *

Abstract Independently, both droughts and heatwaves can induce severe impacts on human and natural systems. However, when these two climate extremes occur concurrently in a given region, their compound impacts are often more pronounced. With the improvement in both the spatiotemporal resolution and representation of complex climate processes in the global climate models (GCMs), they are increasingly used to study future changes in these extremes and associated regional impacts. However, GCM selection for such impact assessments is generally based on historical performance and/or future mean changes, without considering individual or compound extremes. In contrast, this study evaluates historical performance and projected changes in heatwaves, droughts, and compound heatwave-droughts using an ensemble of GCMs from the latest Phase 6 of Coupled Models Intercomparison Project at a regional scale across the conterminous United States. Additionally, we explore the inter-model differences in the projected changes that are associated with various characteristics of extremes and the choice of drought indices. Our analysis reveals considerable variation among the GCMs, as well as substantial differences in the projected changes based on the choice of drought indices and region of interest. For example, the projected increases in both the frequency and intensity of drought and associated compound extreme days, based on the standardized precipitation evapotranspiration index far exceed those derived from the standard precipitation index. Further, the largest changes in the frequency of compound extremes are projected over the Southwest, South Central, and parts of the Southeast while the smallest changes are projected over the Northeast. Overall, this study provides important insights for the interpretation and selection of GCMs for future assessment studies that are crucial for the development of regional adaptation strategies in the face of climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The Potential of Hydrogeodesy to Address Water-Related and Sustainability Challenges

Increasing climatic and human pressures are changing the world's water resources and hydrological processes at unprecedented rates. Understanding these changes requires comprehensive monitoring of water resources. Hydrogeodesy, the science that measures the Earth's solid and aquatic surfaces, gravity field, and their changes over time, delivers a range of novel monitoring tools that are complementary to traditional hydrological methods. It encompasses geodetic technologies such as Altimetry, Interferometric Synthetic Aperture Radar (InSAR), Gravimetry, and Global Navigation Satellite Systems (GNSS). Beyond quantifying these changes, there is a need to understand how hydrogeodesy can contribute to more ambitious goals dealing with water-related and sustainability sciences. Addressing this need, we combine a meta-analysis of over 3,000 articles to chart the range, trends, and applications of satellite-based hydrogeodesy with an expert elicitation that systematically assesses the potential of hydrogeodesy. We find a growing body of literature relating to the advancements in hydrogeodetic methods, their accuracy and precision, and their inclusion in hydrological modeling, with a considerably smaller portion related to understanding hydrological processes, water management, and sustainability sciences. The meta-analysis also shows that while lakes, groundwater and glaciers are commonly monitored by these technologies, wetlands or permafrost could benefit from a wider range of applications. In turn, the expert elicitation envisages the potential of hydrogeodesy to help solve the 23 Unsolved Questions of the International Association of Hydrological Sciences and advance knowledge as guidance toward a safe operating space for humanity. It also highlights how this potential can be maximized by combining hydrogeodetic technologies simultaneously, exploiting artificial intelligence, and accurately integrating other Earth science disciplines. Finally, we call for a coordinated way forward to include hydrogeodesy in tertiary education and broaden its application to water-related and sustainability sciences in order to exploit its full potential.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Climate Forcing & Feedbacks by Fires, Forests, Fossil Energy & Food Production: Observations are Key to Predictions [Slides]

Human emitted GHGs (long lived, cumulative) that trap more heat (IR) and aerosols (short lived, steady) that reflect sunlight (Vis) have altered Earth’s radiation budget and warmed our climate measurably and predictably. Our complex dynamic climate system has trapped 400 ZettaJ (10 21 ) and has many positive feedbacks. Regions are changing at unprecedented rates and crossing thresholds as BAU will lock us into 8.5 W m -2 in 2100.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

ML based control systems for nuclear physics experiments

The Experimental Physics Software and Computing Infrastructure (EPSCI) group at Jefferson Lab is leading the use of machine learning (ML) to enhance control systems in nuclear physics experiments. Collaborating closely with domain experts and data scientists, we have developed an ML-based control system that uses a Gaussian process to dynamically adjust the high voltage of the GlueX Central Drift Chamber. This results in stable detector performance by adapting to environmental changes, thereby reducing the offline calibration effort. Furthermore, we are developing ML-driven systems for optimizing the polarization of photon beams and polarized cryotargets. These systems will maintain the optimal microwave frequency in cryogenic targets and make real-time adjustments to diamond radiators for polarized photon sources, tasks traditionally handled by human operators. By automating these functions, we aim to optimize the polarization, reduce downtime, and minimize human error. This talk will highlight the development of reliable ML-based control systems and the policies to ensure they are both effective and trustworthy.

Jeske, Torri↗
DOE OSTI2023

Evaluating the Interplay between Trajectory Segmentation and Mode Inference Error

Travel behavior changes are essential to transportation decarbonization. Travel diaries, consisting of sequences of trips between places, are typically used to instrument human travel behavior. However, these diaries are only as accurate as the underlying methods used to construct them. Travel diary algorithms have been a popular research topic since the advent of Global Positioning System tracking surveys. These algorithms have typically been validated using prompted recall of presegmented trips, thus disregarding the continuity of mode inference. Phone operating systems have adopted battery-conserving techniques, but the resulting data collection errors have not been studied extensively. We introduce a framework to evaluate the accuracy of trip length computations and mode inference by analyzing continuous mode-segmented trajectories for groups of trips. We then use the framework to identify the input data quality and the impact of postprocessing. Our primary inputs to this evaluation are MobilityNet, a public dataset containing information from three artificial timelines covering 15 different travel modes, and sample open-source travel diary creation algorithms from the OpenPATH project. Our framework concretely shows that the variance of the distance error drops from (0.217, 0.0848) to (o.011, 0.0407) (Android, iOS) after postprocessing. Similarly, the weighted F-scores for mode inference increase from (0.25, 0.29) to (0.60, 0.74) (iOS, Android) between random forest and geographic information system-based models. We hope that this standardized method will be adapted to evaluate other, potentially proprietary, travel diary algorithms. Finally, the results can be used to understand and improve the state of the art in the travel diary creation field.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Building a machine learning surrogate model for wildfire activities within a global Earth system model

Abstract. Wildfire is an important ecosystem process, influencing land biogeophysical and biogeochemical dynamics and atmospheric composition. Fire-driven loss of vegetation cover, for example, directly modifies the surface energy budget as a consequence of changing albedo, surface roughness, and partitioning of sensible and latent heat fluxes. Carbon dioxide and methane emitted by fires contribute to a positive atmospheric forcing, whereas emissions of carbonaceous aerosols may contribute to surface cooling. Process-based modeling of wildfires in Earth system land models is challenging due to limited understanding of human, climate, and ecosystem controls on fire counts, fire size, and burned area. Integration of mechanistic wildfire models within Earth system models requires careful parameter calibration, which is computationally expensive and subject to equifinality. To explore alternative approaches, we present a deep neural network (DNN) scheme that surrogates the process-based wildfire model with the Energy Exascale Earth System Model (E3SM) interface. The DNN wildfire model accurately simulates observed burned area with over 90 % higher accuracy with a large reduction in parameterization time compared with the current process-based wildfire model. The surrogate wildfire model successfully captured the observed monthly regional burned area during validation period 2011 to 2015 (coefficient of determination, R2=0.93). Since the DNN wildfire model has the same input and output requirements as the E3SM process-based wildfire model, our results demonstrate the applicability of machine learning for high accuracy and efficient large-scale land model development and predictions.

58 GEOSCIENCES↗
DOE OSTI2024

Plant synthetic biology as a tool to help eliminate hidden hunger

Agricultural systems are under increasing pressure from declining environmental conditions, a growing population, and changes in consumer preferences, resulting in widespread malnutrition-related illnesses. Improving plant nutritional content through biotechnology techniques such as synthetic biology is a promising strategy to help combat hidden hunger caused by the lack of affordable and healthy foods in human diets. Production of compounds usually found in animal-rich diets, such as vitamin D or omega-3 fatty acids, has been recently demonstrated in planta. Here, we review recent biotechnological approaches to biofortifying plants with vitamins, minerals, and other metabolites, and summarise synthetic biology advances that offer the opportunity to build on these early biofortification efforts.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Comparative analysis of SARS-CoV-2 neutralization titers reveals consistency between human and animal model serum and across assays

The evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires ongoing monitoring to judge the ability of newly arising variants to escape the immune response. A surveillance system necessitates an understanding of differences in neutralization titers measured in different assays and using human and animal serum samples. We compared 18 datasets generated using human, hamster, and mouse serum and six different neutralization assays. Datasets using animal model serum samples showed higher titer magnitudes than datasets using human serum samples in this comparison. Fold change in neutralization of variants compared to ancestral SARS-CoV-2, immunodominance patterns, and antigenic maps were similar among serum samples and assays. Most assays yielded consistent results, except for differences in fold change in cytopathic effect assays. Hamster serum samples were a consistent surrogate for human first-infection serum samples. These results inform the transition of surveillance of SARS-CoV-2 antigenic variation from dependence on human first-infection serum samples to the utilization of serum samples from animal models.

Cell Biology↗
DOE OSTI2024

Enhanced Safety of Heavy-Duty Vehicles on Highways through Automatic Speed Enforcement – A Simulation Study

Highway safety remains a significant concern, especially in mixed traffic scenarios involving heavy-duty vehicles (HDV) and smaller passenger cars. The vulnerability of HDVs following closely behind smaller cars is evident in incidents involving the lead vehicle, potentially leading to catastrophic rear-end collisions. Here, this paper explores how automatic speed enforcement systems, using speed cameras, can mitigate risks for HDVs in such critical situations. While historical crash data consistently demonstrates the reduction of accidents near speed cameras, this paper goes beyond the conventional notion of crash occurrence reduction. Instead, it investigates the profound impact of driver behavior changes within desired travel speed distribution, especially around speed cameras, and their contribution to the safety of trailing vehicles, with a specific focus on heavy-duty trucks in accident-prone scenarios. To conduct this analysis, we utilize SUMO, an open-source microscopic traffic simulator, enabling realistic simulations of real-world driving behaviors with and without speed cameras. The simulations also consider empirical distributions of desired headway gaps and reaction times exhibited by human drivers. This study offers a fresh perspective on highway safety by examining how the influence of automatic speed enforcement systems on driver behavior enhances the safety of HDV when faced with challenging situations. By shedding light on these dynamics, we contribute valuable insights to the ongoing research efforts on using technology to create safer roadways, ultimately promoting safer coexistence between heavy-duty and passenger vehicles.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

A permafrost implementation in the simple carbon–climate model Hector v.2.3pf

Abstract. Permafrost currently stores more than a fourth of global soil carbon. A warming climate makes this carbon increasingly vulnerable to decomposition and release into the atmosphere in the form of greenhouse gases. The resulting climate feedback can be estimated using land surface models, but the high complexity and computational cost of these models make it challenging to use them for estimating uncertainty, exploring novel scenarios, and coupling with other models. We have added a representation of permafrost to the simple, open-source global carbon–climate model Hector, calibrated to be consistent with both historical data and 21st century Earth system model projections of permafrost thaw. We include permafrost as a separate land carbon pool that becomes available for decomposition into both methane (CH4) and carbon dioxide (CO2) once thawed; the thaw rate is controlled by region-specific air temperature increases from a preindustrial baseline. We found that by 2100 thawed permafrost carbon emissions increased Hector’s atmospheric CO2 concentration by 5 %–7 % and the atmospheric CH4 concentration by 7 %–12 %, depending on the future scenario, resulting in 0.2–0.25 ∘C of additional warming over the 21st century. The fraction of thawed permafrost carbon available for decomposition was the most significant parameter controlling the end-of-century temperature change in the model, explaining around 70 % of the temperature variance, and was distantly followed by the initial stock of permafrost carbon, which contributed to about 10 % of the temperature variance. The addition of permafrost in Hector provides a basis for the exploration of a suite of science questions, as Hector can be cheaply run over a wide range of parameter values to explore uncertainty and can be easily coupled with integrated assessment and other human system models to explore the economic consequences of warming from this feedback.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Important Human Actions for Advanced Reactors: Implications for Human Factors

As advanced reactor platforms continue to develop and gain traction in the energy sector there is a need for risk-informed, scalable regulations that match that progress. This is a core component of the U.S. Nuclear Regulatory Commission’s proposed Part 53 Rule Making; the Accelerating Deployment of Versatile, Advanced Nuclear for Clean Energy (ADVANCE) Act; and other efforts that seek to update nuclear power regulations. This paper covers one key aspect of that regulatory evolution: Important Human Actions (IHA). In this paper, we discuss how the understanding and definitions of IHAs have changed and what that means for human factors engagement through the process of developing these technologies. Instead of a narrow focus on control actions that led to an increase in core damage risk, the new focus is on IHAs is “wherever they occur.” What this means is that having a highly automated or passive safety system does not eliminate IHAs. Rather, it shifts the focus point to all the actions that enable these systems. Everything from maintenance, to design, to training can be considered an IHA and that dramatically shifts the efforts and level of engagement necessary for human factors to enable these technologies. We discuss the notions of risk-informed human factors that underpin these efforts, give several examples, and briefly describe the risk assessment methodologies that will be needed. In the past, IHAs were identified and then became a focus point of human factors engineering (HFE) activities to ensure a robust evaluation of the task was completed. The future is less clear. HFE for nuclear energy will need to evolve and become more integrated in technology development than ever before.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Pantex Plant Ogallala Aquifer and Perched Groundwater Contingency Plan

The Pantex Plant Ogallala Aquifer and Perched Groundwater Contingency Plan has been developed in accordance with the requirements identified in the: • Interagency Agreement for the Pantex Superfund Site, Article 8.5 Work to be Performed, • Compliance Plan Provision of Hazardous Waste Permit No. 50284, and • Record of Decision for Groundwater, Soil, and Associated Media, Pantex Plant. A Long‐Term Monitoring System Design has been designed to monitor conditions in the perched groundwater including changes in the perched aquifer as a result of implementing the response actions. Monitoring is required for verifying the effectiveness of perched groundwater response actions (i.e., conditions in the perched aquifer are being affected as intended) and for confirming that the perched aquifer and Ogallala Aquifer characterization as defined in the Resource Conservation and Recovery Act Facility Investigation Report and the Corrective Measure Studies/Feasibility Study remains accurate. If monitoring results obtained through the monitoring network identify an unexpected condition or deviation, contingent actions will be considered and implemented as necessary to ensure continued protection of the Ogallala Aquifer and human health and the environment. Potential deviations to expected technology performance may be encountered for each of the four primary response actions that compose the selected remedy for perched groundwater; Playa 1 Pump and Treat System, Southeast Area Pump and Treat System, Southeast Area In‐Situ Bioremediation System (comprised of the Southeast In‐Situ Bioremediation System Original System, Southeast Area In‐Situ Bioremediation System Extension System, Offsite In‐Situ Bioremediation System, Perchlorate/Chromium ISB, Northeast ISB and County Road 8 ISB), and Zone 11 In‐Situ Bioremediation System. Monitoring will also be conducted to determine if there are deviations to the expected characterization, e.g., contaminants not expected as a result of the RCRA Facility Investigation characterization. Deviations to expected conditions in the Ogallala Aquifer could also be encountered if the response actions in the perched groundwater are not performing as expected, i.e., preventing contaminants from migrating to the Ogallala Aquifer. Currently, Pantex has begun investigation of detections of high explosives above groundwater protection standards in wells on the Texas Tech University property and a plume that is moving to the northeast from that area. Due to those detections, this Plan recognizes the fact that future detections in the Ogallala will be focused on first‐ time detections of analytes. After a remedy is determined, this Plan will require modification to address-deviations and contingent actions. This Plan was developed to identify the contingent actions necessary to mitigate impacts resulting from deviations to site conditions or response action performance. The Plan defines the environmental problem being addressed by the response actions, clarifies the expected conditions and objectives of the response actions, and identifies the potential deviations to the response actions (due to site conditions or technology performance) that could be encountered. The deviations were evaluated to determine the likelihood of occurrence, potential impact, and time to respond to avoid impact. The Plan also identifies the monitoring outlined in the Long‐Term Monitoring System Design Report (Consolidated Nuclear Security, 2024) and Sampling Analysis Plan (PanTeXas Deterrence, 2024) that will be used to detect the deviations. Lastly, the Plan specifies the contingent actions that could be implemented in response to the deviations. Because each response focuses on a discrete portion of the perched aquifer and contaminant plume, each response action has a different set of expected conditions, and therefore differing impacts from deviations to the site and technology expectations. As a result, the contingent actions are identified for each response action and potential deviation including specific constituents, location, and conditions. If deviations are encountered that impact the ability of the response action to meet performance objectives, the contingent actions will be focused on ensuring the response action can meet the performance objective. Contingent actions may be implemented as interim actions (ISMs/removal actions) in accordance with the Record of Decision, Interagency Agreement, and Hazardous Waste Permit‐50284, if warranted by the specific circumstances. For deviations to site characterization expected conditions, the contingent action will focus on determination of the source of the deviation, determination of the appropriate response, and evaluation of additional work to be completed. However, if the deviation to characterization impacts the performance of the response action, the contingent action will again focus on ensuring performance objectives can be met. Early source term removals and cleanup actions have been implemented to protect the Ogallala Aquifer. Because of these actions and based on modeling results, the expected conditions in the Ogallala Aquifer are that constituents of concern will not be detected above the Groundwater Protection Standards (GWPSs) nor will they reach potential points of exposure above the GWPS. The primary deviation of concern for the Ogallala is if constituents are detected in the Ogallala Aquifer near or above GWPSs. If it occurs, this change in expected conditions would require further evaluation of site and contaminant characteristics to determine an appropriate course of action. The evaluation would include additional monitoring, source identification, implementation of interim protective measures (if necessary), and delineation of extent. These evaluations are necessary to determine an appropriate response action for the Ogallala. The primary goal of the Plan is to provide for the continued protection of the Ogallala Aquifer and the health of its consumers. In recognition, this Plan presents a flexible and rational approach for making future decisions associated with confirming the change in perched and Ogallala aquifer conditions and identifying a response (technical activities, changes to response actions, regulatory oversight, and public involvement).

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Impacts of irrigation expansion on moist-heat stress based on IRRMIP results

Irrigation rapidly expanded during the 20 th century, affecting climate via water, energy, and biogeochemical changes. Previous assessments of these effects predominantly relied on a single Earth System Model, and therefore suffered from structural model uncertainties. Here we quantify the impacts of historical irrigation expansion on climate by analysing simulation results from six Earth system models participating in the Irrigation Model Intercomparison Project (IRRMIP). Results show that irrigation expansion causes a rapid increase in irrigation water withdrawal, which leads to less frequent 2-meter air temperature heat extremes across heavily irrigated areas (≥4 times less likely). However, due to the irrigation-induced increase in air humidity, the cooling effect of irrigation expansion on moist-heat stress is less pronounced or even reversed, depending on the heat stress metric. In summary, this study indicates that irrigation deployment is not an efficient adaptation measure to escalating human heat stress under climate change, calling for carefully dealing with the increased exposure of local people to moist-heat stress.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Evaluating the economic impact of water scarcity in a changing world

Abstract Water scarcity is dynamic and complex, emerging from the combined influences of climate change, basin-level water resources, and managed systems’ adaptive capacities. Beyond geophysical stressors and responses, it is critical to also consider how multi-sector, multi-scale economic teleconnections mitigate or exacerbate water shortages. Here, we contribute a global-to-basin-scale exploratory analysis of potential water scarcity impacts by linking a global human-Earth system model, a global hydrologic model, and a metric for the loss of economic surplus due to resource shortages. We find that, dependent on scenario assumptions, major hydrologic basins can experience strongly positive or strongly negative economic impacts due to global trade dynamics and market adaptations to regional scarcity. In many cases, market adaptation profoundly magnifies economic uncertainty relative to hydrologic uncertainty. Our analysis finds that impactful scenarios are often combinations of standard scenarios, showcasing that planners cannot presume drivers of uncertainty in complex adaptive systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Structural basis of divergent substrate recognition and inhibition of human neurolysin

A zinc metallopeptidase neurolysin (Nln) processes diverse bioactive peptides to regulate signaling in the mammalian nervous system. To understand how Nln interacts with various peptides with dissimilar sequences, we determined crystal structures of Nln in complex with diverse peptides including dynorphins, angiotensin, neurotensin, and bradykinin. The structures show that Nln binds these peptides in a large dumbbell-shaped interior cavity constricted at the active site, making minimal structural changes to accommodate different peptide sequences. The structures also show that Nln readily binds similar peptides with distinct registers, which can determine whether the peptide serves as a substrate or a competitive inhibitor. We analyzed the activities and binding of Nln toward various forms of dynorphin A peptides, which highlights the promiscuous nature of peptide binding and shows how dynorphin A (1–13) potently inhibits the Nln activity while dynorphin A (1–8) is efficiently cleaved. Our work provides insights into the broad substrate specificity of Nln and may aid in the future design of small molecule modulators for Nln.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Metabolic Feedback Inhibition Influences Metabolite Secretion by the Human Gut Symbiont Bacteroides thetaiotaomicron

ABSTRACT Microbial metabolism and trophic interactions between microbes give rise to complex multispecies communities in microbe-host systems. Bacteroides thetaiotaomicron ( B. theta ) is a human gut symbiont thought to play an important role in maintaining host health. Untargeted nuclear magnetic resonance metabolomics revealed B. theta secretes specific organic acids and amino acids in defined minimal medium. Physiological concentrations of acetate and formate found in the human intestinal tract were shown to cause dose-dependent changes in secretion of metabolites known to play roles in host nutrition and pathogenesis. While secretion fluxes varied, biomass yield was unchanged, suggesting feedback inhibition does not affect metabolic bioenergetics but instead redirects carbon and energy to CO 2 and H 2 . Flux balance analysis modeling showed increased flux through CO 2 -producing reactions under glucose-limiting growth conditions. The metabolic dynamics observed for B. theta , a keystone symbiont organism, underscores the need for metabolic modeling to complement genomic predictions of microbial metabolism to infer mechanisms of microbe-microbe and microbe-host interactions. IMPORTANCE Bacteroides is a highly abundant taxon in the human gut, and Bacteroides thetaiotaomicron ( B. theta ) is a ubiquitous human symbiont that colonizes the host early in development and persists throughout its life span. The phenotypic plasticity of keystone organisms such as B. theta is important to understand in order to predict phenotype(s) and metabolic interactions under changing nutrient conditions such as those that occur in complex gut communities. Our study shows B. theta prioritizes energy conservation and suppresses secretion of “overflow metabolites” such as organic acids and amino acids when concentrations of acetate are high. Secreted metabolites, especially amino acids, can be a source of nutrients or signals for the host or other microbes in the community. Our study suggests that when metabolically stressed by acetate, B. theta stops sharing with its ecological partners.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Adoption of AI in the Utility T&D Sector: Use Cases, Consequence, Assessment and Benefits

Digital transformation and utilization of artificial intelligence (AI) in the electric grid are fundamentally changing the industry’s approach to common problems and enabling a broader paradigm shift in grid planning and operations. The change in approach is circularly both enabling and driving modernization, with load growth and reliable management of data center and AI infrastructure shifting away from planning approaches with relatively predictable behaviors and toward a mix of consumer and industrial choices that surpass human cognitive abilities to process. This movement has potential to condition humans to not understand the system on which the AI depends, while requiring it for development of the necessary infrastructure. Approaches which would address most likely grid conditions and events, such as faults, aging of equipment, and weather, now must also account for large loads which shift not based upon weather or time of day, but the computational load. Quantifying computational load is independent of the traditional grid forecasting variables, where a data center’s aggregate load is determined by user and AI system behavior and decoupled from normal grid planning and operations. AI is both the cause and solution for these challenges, with new grid planning tools integrating massive amounts of decisions into frameworks.

24 POWER TRANSMISSION AND DISTRIBUTION↗