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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 595 records · Page 33

Electricity Rate Designs for Large Loads: Evolving Practices and Opportunities 2026 Update

Electricity demand from large-load customers such as data centers is projected to grow significantly in the near term. While these large loads play an important role in advancing technology innovation and economic growth in the United States, meeting their energy needs requires utilities and regulators to consider important operational and financial risks, such as insufficient energy supply or underutilized investments, that can impact all customers. This paper builds on similar research published in January 2025, providing an overview of how utilities and regulators are managing these risks through different tariffs, including rate structures and electric service agreements. Regulators, utilities, customers, and other stakeholders can use this paper as a foundation when discussing issues and sharing perspectives on developing or reviewing large-load tariffs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

An expert system for simulating electric loads aboard Space Station Freedom

Space Station Freedom will provide an infrastructure for space experimentation. This environment will feature regulated access to any resources required by an experiment. Automated systems are being developed to manage the electric power so that researchers can have the flexibility to modify their experiment plan for contingencies or for new opportunities. To define these flexible power management characteristics for Space Station Freedom, a simulation is required that captures the dynamic nature of space experimentation; namely, an investigator is allowed to restructure his experiment and to modify its execution. This changes the energy demands for the investigator's range of options. An expert system competent in the domain of cryogenic fluid management experimentation was developed. It will be used to help design and test automated power scheduling software for Freedom's electric power system. The expert system allows experiment planning and experiment simulation. The former evaluates experimental alternatives and offers advice on the details of the experiment's design. The latter provides a real-time simulation of the experiment replete with appropriate resource consumption.

Kukich, George↗

An expert system for simulating electric loads aboard Space Station Freedom

Space Station Freedom will provide an infrastructure for space experimentation. This environment will feature regulated access to any resources required by an experiment. Automated systems are being developed to manage the electric power so that researchers can have the flexibility to modify their experiment plan for contingencies or for new opportunities. To define these flexible power management characteristics for Space Station Freedom, a simulation is required that captures the dynamic nature of space experimentation; namely, an investigator is allowed to restructure his experiment and to modify its execution. This changes the energy demands for the investigator's range of options. An expert system competent in the domain of cryogenic fluid management experimentation, was developed. It will be used to help design and test automated power scheduling software for Freedom's electric power system. The expert system allows experiment planning and experiment simulation. The former evaluates experimental alternatives and offers advice on the details of the experiment's design. The latter provides a real-time simulation of the experiment replete with appropriate resource consumption.

Kukich, George↗

Changes in Exercise Data Management

The suite of exercise hardware aboard the International Space Station (ISS) generates an immense amount of data. The data collected from the treadmill, cycle ergometer, and resistance strength training hardware are basic exercise parameters (time, heart rate, speed, load, etc.). The raw data are post processed in the laboratory and more detailed parameters are calculated from each exercise data file. Updates have recently been made to how this valuable data are stored, adding an additional level of data security, increasing data accessibility, and resulting in overall increased efficiency of medical report delivery. Questions regarding exercise performance or how exercise may influence other variables of crew health frequently arise within the crew health care community. Inquiries over the health of the exercise hardware often need quick analysis and response to ensure the exercise system is operable on a continuous basis. Consolidating all of the exercise system data in a single repository enables a quick response to both the medical and engineering communities. A SQL server database is currently in use, and provides a secure location for all of the exercise data starting at ISS Expedition 1 - current day. The database has been structured to update derived metrics automatically, making analysis and reporting available within minutes of dropping the inflight data it into the database. Commercial tools were evaluated to help aggregate and visualize data from the SQL database. The Tableau software provides manageable interface, which has improved the laboratory's output time of crew reports by 67%. Expansion of the SQL database to be inclusive of additional medical requirement metrics, addition of 'app-like' tools for mobile visualization, and collaborative use (e.g. operational support teams, research groups, and International Partners) of the data system is currently being explored.

Buxton, R. E.↗

Scenario Planning Management Actions to Restore Cold Water Stream Habitat: Comparing Mechanistic and Statistical Modeling Approaches

ABSTRACT Under the United States Clean Water Act, states are required to periodically assess state waters to determine compliance with water quality criteria (including temperature) and then to develop total maximum daily loads (TMDLs) for impaired waters as necessary to bring them into compliance. We compared the performance of mechanistic stream temperature models (HeatSource, QUAL2K, and QUAL2Kw) applied to the mainstem of three TMDL watersheds (Middle Fork John Day, OR; Wind River, WA; South Fork Nooksack, WA) with that of spatial stream network (SSN) models applied to the full watersheds and used these to evaluate the potential effectiveness of restoration strategies. SSN models performed well with slightly lesser accuracy (RMSE = 0.47–0.87) for mainstem predictions than mechanistic models (RMSE = 0.4) but provided additional benefits to inform management, including information on spatial and temporal heterogeneity of restoration effectiveness throughout the watershed. Of the four scenarios considered (restoration of riparian zones to potential natural vegetation, channel narrowing, increasing flow by restricting irrigation withdrawals, and combined applications), riparian zone restoration was consistently the most effective in reducing temperatures at the outlet, mainstem, and throughout the watersheds. Predicted restoration effectiveness for thermal regimes varied significantly both within and among watersheds. A focus on water quality criteria exceedance only at the watershed outlet or along the mainstem reach can obscure knowledge of restoration potential for fish habitat in tributaries and headwaters, potential for creation of thermal refuge areas along the mainstem critical for maintaining migration corridors, and thermal regime heterogeneity across space and time.

Fuller, M. R.↗

Uncertainty quantification of a physics-informed model based on sparse identification of a Thermal Energy Distribution System

Integrated energy systems (IES)s are crucial for enhancing the economy and efficiency of power generation sources (e.g., nuclear energy) necessary to unleash American energy dominance. These systems can be integrated with thermal energy storage (TES) and intermittent renewable energies to optimize overall energy use, peak-load regulation, and demand-side responses. However, the stabilization of energy generation, transport, and utilization introduces operational complexities that exceed the challenges of managing each sub-component individually. Currently, though IESs rely on human operators for efficiency and stability, reducing human error risk and enhancing performance through automation is highly desirable. Recent advances at Idaho National Laboratory have demonstrated successful control of the Thermal Energy Distributed System (TEDS). However, the automatic control system depends on a deterministic Sparse Identification of Nonlinear Dynamics with Control (SINDyC) model, which are trained based on simulation data from physics-based simulations. Because of uncertainties in physics-based simulation, SINDyC model results in large discrepancies against experimental data and cannot be reliably used in automatic control. In this paper, we present an innovative approach to address these discrepancies by quantifying uncertainties and developing a more robust model. We first generated trajectories by using first-principles physics codes to encapsulate the experiment. Next, we trained thousands of models by randomly sampling these trajectories. We then collapsed all those models into one probabilistic SINDyC by fitting a multivariate Gaussian distribution onto the resulting coefficient’s distribution. Despite its simplicity, our approach successfully produced 95% confidence intervals that captured the experimental trajectories. It even did so with a higher probability and better U-pooling score across six of the seven relevant quantities of interest (QoIs), as compared to other classical approaches. In conclusion, ongoing research is focusing on generating new experimental trajectories to validate this approach, and on employing Bayesian calibration to refine parametric uncertainties and guide future model development efforts.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Traffic sharing algorithms for hybrid mobile networks

In a hybrid (terrestrial + satellite) mobile personal communications networks environment, a large size satellite footprint (supercell) overlays on a large number of smaller size, contiguous terrestrial cells. We assume that the users have either a terrestrial only single mode terminal (SMT) or a terrestrial/satellite dual mode terminal (DMT) and the ratio of DMT to the total terminals is defined gamma. It is assumed that the call assignments to and handovers between terrestrial cells and satellite supercells take place in a dynamic fashion when necessary. The objectives of this paper are twofold, (1) to propose and define a class of traffic sharing algorithms to manage terrestrial and satellite network resources efficiently by handling call handovers dynamically, and (2) to analyze and evaluate the algorithms by maximizing the traffic load handling capability (defined in erl/cell) over a wide range of terminal ratios (gamma) given an acceptable range of blocking probabilities. Two of the algorithms (G & S) in the proposed class perform extremely well for a wide range of gamma.

Arcand, S.↗

Human Factors Research Needs for In-Time Aviation Safety Management Systems (IASMS) Design: Enabling the NASA “Sky for All” Future Airspace Vision

Integrated safety management will be paramount for safely enabling the envisioned transformations of the future National Airspace System. Addressing the increasing need for advanced data analytics and fusion of aviation safety data, managed by human decision-makers, is essential for realizing the vision. The proposal, if accepted, will discuss safety management system challenges and how the concept of In-time Aviation Safety Management Systems addresses the need. It will also discuss human factors challenges involved in future integrated safety management, including trust, over-reliance, human-optimized data visualization, human-autonomy teaming, training, communication and dissemination of data, situation awareness, task load, and accountability.

Lawrence J Prinzel III↗

Improved PV System Control Strategies to Reduce Power Management Costs in Nanogrids

An improved PV system control method is proposed to reduce nanogrid operation costs in this paper. A model including it various components such as photovoltaic (PV) systems, energy storage systems (ESSs), gateways, and household loads is considered with the constraints of the ESS, PV irradiance from real data, and household load. We designed an optimal economic dispatch strategy with an improved PV system control method. Combining the proposed optimal economic dispatch and PV system control strategies, it can improve the control performance for both transient and steady-state responses thereby enabling the maximum power to be extracted from the PV. Consequently, the PV power is maximized, which allows the ESS to use less power and sell the surplus to external power sources, which means the proposed method decreases the nanogrid operation costs. Furthermore, this performance is verified via nanogrid simulations and PV experimental kit.

PV system control↗

The Software Design for the Wide-Field Infrared Explorer Attitude Control System

The Wide-Field Infrared Explorer (WIRE), currently scheduled for launch in September 1998, is the fifth of five spacecraft in the NASA/Goddard Small Explorer (SMEX) series. This paper presents the design of WIRE's Attitude Control System flight software (ACS FSW). WIRE is a momentum-biased, three-axis stabilized stellar pointer which provides high-accuracy pointing and autonomous acquisition for eight to ten stellar targets per orbit. WIRE's short mission life and limited cryogen supply motivate requirements for Sun and Earth avoidance constraints which are designed to prevent catastrophic instrument damage and to minimize the heat load on the cryostat. The FSW implements autonomous fault detection and handling (FDH) to enforce these instrument constraints and to perform several other checks which insure the safety of the spacecraft. The ACS FSW implements modules for sensor data processing, attitude determination, attitude control, guide star acquisition, actuator command generation, command/telemetry processing, and FDH. These software components are integrated with a hierarchical control mode managing module that dictates which software components are currently active. The lowest mode in the hierarchy is the 'safest' one, in the sense that it utilizes a minimal complement of sensors and actuators to keep the spacecraft in a stable configuration (power and pointing constraints are maintained). As higher modes in the hierarchy are achieved, the various software functions are activated by the mode manager, and an increasing level of attitude control accuracy is provided. If FDH detects a constraint violation or other anomaly, it triggers a safing transition to a lower control mode. The WIRE ACS FSW satisfies all target acquisition and pointing accuracy requirements, enforces all pointing constraints, provides the ground with a simple means for reconfiguring the system via table load, and meets all the demands of its real-time embedded environment (16 MHz Intel 80386 processor with 80387 coprocessor running under the VRTX operating system). The mode manager organizes and controls all the software modules used to accomplish these goals, and in particular, the FDH module is tightly coupled with the mode manager.

Anderson, Mark O.↗

Health Monitor for Multitasking, Safety-Critical, Real-Time Software

Health Manager can detect Bad Health prior to a failure occurring by periodically monitoring the application software by looking for code corruption errors, and sanity-checking each critical data value prior to use. A processor s memory can fail and corrupt the software, or the software can accidentally write to the wrong address and overwrite the executing software. This innovation will continuously calculate a checksum of the software load to detect corrupted code. This will allow a system to detect a failure before it happens. This innovation monitors each software task (thread) so that if any task reports "bad health," or does not report to the Health Manager, the system is declared bad. The Health Manager reports overall system health to the outside world by outputting a square wave signal. If the square wave stops, this indicates that system health is bad or hung and cannot report. Either way, "bad health" can be detected, whether caused by an error, corrupted data, or a hung processor. A separate Health Monitor Task is started and run periodically in a loop that starts and stops pending on a semaphore. Each monitored task registers with the Health Manager, which maintains a count for the task. The registering task must indicate if it will run more or less often than the Health Manager. If the task runs more often than the Health Manager, the monitored task calls a health function that increments the count and verifies it did not go over max-count. When the periodic Health Manager runs, it verifies that the count did not go over the max-count and zeroes it. If the task runs less often than the Health Manager, the periodic Health Manager will increment the count. The monitored task zeroes the count, and both the Health Manager and monitored task verify that the count did not go over the max-count.

Zoerner, Roger↗

Architectural constructs of Ampex DST

The DST 800 automated library is a high performance, automated tape storage system, developed by AMPEX, providing mass storage to host systems. Physical Volume Manager (PVM) is a volume server which supports either a DST 800, DST 600 stand alone tape drive, or a combination of DST 800 and DST 600 subsystems. The objective of the PVM is to provide the foundation support to allow automated and operator assisted access to the DST cartridges with continuous operation. A second objective is to create a data base about the media, its location, and its usage so that the quality and utilization of the media on which specific data is recorded and the performance of the storage system may be managed. The DST tape drive architecture and media provides several unique functions that enhance the ability to achieve high media space utilization and fast access. Access times are enhanced through the implementation of multiple areas (called system zones) on the media where the media may be unloaded. This reduces positioning time in loading and unloading the cartridge. Access times are also reduced through high speed positioning in excess of 800 megabytes per second. A DST cartridge can be partitioned into fixed size units which can be reclaimed for rewriting without invalidating other recorded data on the tape cartridge. Most tape management systems achieve space reclamation by deleting an entire tape volume, then allowing users to request a 'scratch tape' or 'nonspecific' volume when they wish to record data to tape. Physical cartridge sizes of 25, 75, or 165 gigabytes will make this existing process inefficient or unusable. The DST cartridge partitioning capability provides an efficient mechanism for addressing the tape space utilization problem.

Johnson, Clay↗

A neural-network-enhanced parameter-varying framework for multi-objective model predictive control applied to buildings

Management of the electrical grid is becoming more complex due to the increased penetration of alternative energy generation technologies and a broadening diversity of electric loads. This complexity creates challenges in balancing demand and generation that can increase the potential for grid instabilities. One effective way to address this issue is to leverage previously unexploited demand flexibility through advanced control strategies. In this work, we propose an advanced control method, called adaptive neural parameter-varying model predictive control (ANPV-MPC), to control the temperature and energy consumption of a building via its Heating, Ventilation, and Air Conditioning system. ANPV-MPC combines key ideas in parameter-varying control, adaptive control, and online learning strategies to bridge the gap between computationally efficient linear model predictive control and more accurate nonlinear model predictive control. The novelty in ANPV-MPC is the use of a physics-inspired Bayesian neural network to estimate the coefficients of the parameter-varying linear control model. The Bayesian neural network additionally provides uncertainty estimates, triggering online training to capture evolving building system conditions. We show that ANPV-MPC can approximate the building system dynamics with a 28.39% higher accuracy than traditional linear model predictive control, resulting in 36.23% better control performance without increasing complexity of the optimal control problem. ANPV-MPC also adapts in real time to previously unseen conditions using online learning, further improving its performance.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Machine learning-enhanced MPC for demand flexibility in small commercial buildings: An experimental study

Small- and medium-sized commercial buildings (SMCBs) represent the majority of U.S. commercial building stock and a significant share of peak electricity demand, yet they often lack centralized building automation systems, representing a significant untapped resource for urban energy management. This infrastructure gap makes advanced control implementation challenging, limiting the potential for widespread demand flexibility. Model Predictive Control (MPC) has shown strong potential for load shifting, peak demand reduction, and cost savings, but its effectiveness is hindered by unmeasured disturbances such as internal heat gains. This paper presents a Hybrid MPC framework that integrates a physics-based gray-box building thermal model, identified using a lumped disturbance (LD) approach, with a machine learning (ML) model for forecasting unmeasured disturbances. The hybrid approach is designed for buildings with multiple individually controlled heat pump and thermostat pairs, common in SMCBs, and aims to optimize coordinated scheduling of multiple heat pumps under dynamic electricity pricing while respecting comfort constraints. The methodology is validated through both simulations of case study buildings and experimental studies at a highly-instrumented test facility. Simulation results show that the Hybrid MPC achieves substantial load shifting and peak demand reduction, approaching the performance of an ideal MPC with perfect disturbance knowledge, and outperforming a conventional MPC without disturbance forecasting. In experiments, the Hybrid MPC reduced daily HVAC energy costs by 8.7%, peak-price time load (load shifting) by 41.7%, and peak demand by 29.2% compared to baseline control, demonstrating comparable benefits to the 11.6% cost savings, 42.9% load shifting, and 23.2% peak reduction of the ideal MPC. These results demonstrate that the proposed hybrid modeling approach can significantly improve MPC performance in real-world SMCB applications without requiring additional disturbance measurements.

Demand Flexibility↗

Salt Hydrate Eutectic Thermal Energy Storage for Building Thermal Regulation (Final Technical Report)

Thermal energy storage is anticipated to play an important role in developing the power grid of the future - a power grid that meets increasing demands of users, is resistant to disruptions, but also allows for greater penetration of renewable resources. Specifically, thermal energy storage materials can be integrated into HVAC systems and building envelopes, where they can be used to shift power demands for building climate control from periods of peak demand to periods of low demand. Phase change materials (PCMs) are compelling as low-cost, high energy density thermal energy storage materials for building thermal management. However, there is a lack of high performance low-cost PCMs within the specific temperature ranges which would most effectively allow for power load shifting. Inorganic salt hydrates represent a promising class of PCMs, but their inherent limitations cause them to be currently unavailable for reliable building applications. The overarching goals of this research effort are to: 1) Discover low-cost, high volumetric density salt hydrate eutectic PCMs to store low-quality heat (10 to 40 °C); 2) Introduce a high thermal conductivity matrix to reduce the time constant for energy storage to ~0.1 to 1 hr, incorporate nucleation catalysts to decrease undercooling, and utilize microencapsulation and shape stabilization approaches, minimizing moisture loss/gain, mitigating phase separation, and maintaining stable melting behavior over the lifetime of the compounds; 3) Evaluate the impact these systems have on peak load shifting, and the potential for overall energy savings under different climatic scenarios and building configurations. These goals will be achieved by an integrated research program consisting of six cohesive research subtasks: 1) Materials discovery of eutectic salt hydrate PCMs by using computationally predicted thermodynamic equilibria, coupled with high-throughput experimental validation, 2) Rapid experimental screening of nucleation catalysts identified through robust computational databases, 3) Embedding salt hydrate PCM into a low cost and scalable high conductivity matrix, 4) Microencapsulation of salt hydrate microspheres using hybrid inorganic-polymer microencapsulation approach, 5) Shape stabilization by thermoreversible salt hydrate salogels, and 6) Analysis of end-use using thermal simulations, and characterization of mock-up energy storage finished components.

25 ENERGY STORAGE↗

Space Power Management and Distribution Status and Trends

An overview of space power management and distribution (PMAD) is provided which encompasses historical and current technology trends. The PMAD components discussed include power source control, energy storage control, and load power processing electronic equipment. The status of distribution equipment comprised of rotary joints and power switchgear is evaluated based on power level trends in the public, military, and commercial sectors. Component level technology thrusts, as driven by perceived system level trends, are compared to technology status of piece-parts such as power semiconductors, capacitors, and magnetics to determine critical barriers.

Reppucci, G. M.↗

Analog simulation of flux-summing servo-model, phases 1 and 2

The analog simulation was developed for a closed-loop system having an electrohydraulic flux-summing servo valve and actuator with associated inertial load. One-fourth of the system's total forward gain is carried by each of four channels. The present study successfully applied failure mode management techniques to the problem of channel failure. Digital logic circuitry was developed to maintain the overall forward gain of the system at a constant value, in the presence of channel failure. Finally, the stability of the system was verified, and performance characteristics were determined through the use of frequency response methods.

Hriber, E. J.↗

Forestry Vehicle

Power Pack II provides an economical means of moving a power source into remote roadless forest areas. It was developed by Prof. Miles and his associates, working in cooperation with the University of California's Department of Forestry. The team combined its own design of an all-terrain vehicle with a suspension system based on the NASA load equalization technology. Result is an intermediate-sized unit which carries a power source and the powered tools to perform a variety of forest management tasks which cannot be done economically with current equipment. Power Pack II can traverse very rough terrain and climb a 60 degree slope; any one of the wheels can move easily over an obstacle larger than itself. Work is being done on a more advanced Power Pack III.

Source record↗