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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 973 records · Page 54
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

MiGRIDS

MiGRIDS is a software that models islanded microgrid power systems with different controls and components. For example, using load and resource data from a microgrid, you could model it with additional wind turbines, battery etc. You could also try out different dispatch schemes to see which one worked best. MiGRIDS is designed to help optimize the size and dispatch of grid components in a microgrid. While a grid connect feature is expected to be added in the future, islanded operation is the focus. Note that this is a basic implementation and more features and functionality (such as a GUI) are coming! MiGRIDS runs time-step energy balance simulations for different grid components and controls. In smaller microgrid environments, dispatch decisions are being made on the order of seconds. In order to fully capture their effect, this tool lets you run simulations on the order of seconds. The end result is a more realistic representation of what can be achieved by integrating different components and control strategies in a grid.

Morgan, Tawna↗
DOE OSTI2024

Cloud-based Testbed for Adaptive Under-Frequency Load Shedding with High DER Penetration

Increasing penetration of distributed energy resources and behind-the-meter renewables may soon disrupt the efficacy of critical protection schemes, such as under-frequency load shedding (UFLS). Improved data exchange and coordination across the transmission-distribution boundary will be required to maintain reliability of bulk electric system. Standards-based data integration platforms using agreed-upon semantic vocabularies, such as the Common Information Model, will be key to enabling adaptive protection schemes requiring synthesized data from both the bulk power system and behind-the-meter resources. This paper introduces a cloud-based open-source data integration environment and UFLS clustering algorithm being developed to enable adaptive relay coordination between transmission and distribution utilities in the state of Vermont.

Anderson, Alexander A.↗
NASA NTRS1984

A study of environmental characterization of conventional and advanced aluminum alloys for selection and design. Phase 2: The breaking load test method

A technique is demonstrated for accelerated stress corrosion testing of high strength aluminum alloys. The method offers better precision and shorter exposure times than traditional pass fail procedures. The approach uses data from tension tests performed on replicate groups of smooth specimens after various lengths of exposure to static stress. The breaking strength measures degradation in the test specimen load carrying ability due to the environmental attack. Analysis of breaking load data by extreme value statistics enables the calculation of survival probabilities and a statistically defined threshold stress applicable to the specific test conditions. A fracture mechanics model is given which quantifies depth of attack in the stress corroded specimen by an effective flaw size calculated from the breaking stress and the material strength and fracture toughness properties. Comparisons are made with experimental results from three tempers of 7075 alloy plate tested by the breaking load method and by traditional tests of statistically loaded smooth tension bars and conventional precracked specimens.

Sprowls, D. O.↗
DOE OSTI2021

Load Forecasting for the Moroccan Electricity Sector

The Moroccan electricity sector is undergoing rapid transformation as it seeks to increase its utilization of renewable energy from its abundant domestic supply. Key to implementing variable renewable energy is understanding current electricity demand and forecasting this demand on the long, medium, and short timescales. This report leverages existing Moroccan electricity sector data to build basic load forecasts on these timescales. Taking these forecasts, the report recommends next steps in terms of additional algorithms, mathematical models, data collection, and scenarios (such as vehicle electrification or high levels of distributed generation) that should be examined for advanced load forecasts.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2016

Comparison of RTA Vibratory Loading in the 40- by 80-Foot Wind Tunnel and 80- by 120-Foot Wind Tunnel at the National Full-Scale Aerodynamics Complex

This paper presents data taken in the 80- by 120-Foot Wind Tunnel in 1992 to data taken in the 40- by 80-Foot Wind Tunnel in 2016 at the NFAC. In both sets of data, the RTA was equipped with an identical set of S-76 helicopter blades. These data sets were compared to determine the repeatability of the RTA as a testing device, and to quantify differences in 40- by 80-Foot Wind Tunnel vs. 80- by 120-Foot Wind Tunnel results. The contents include an overview of the RTA and test facility, as well as a discussion of the methodology used. Vibratory load data is presented for a variety of wind and RPM conditions in various test section configurations. Data presented in this report quantifies the repeatability of the RTA.

NFAC↗
NASA NTRS1999

The Effect of Spaceflight on Bone Cell Cultures

Understanding the response of bone to mechanical loading (unloading) is extremely important in defining the means of adaptation of the body to a variety of environmental conditions such as during heightened physical activity or in extended explorations of space or the sea floor. The mechanisms of the adaptive response of bone are not well defined, but undoubtedly they involve changes occurring at the cellular level of bone structure. This proposal has intended to examine the hypothesis that the loading (unloading) response of bone is mediated by specific cells through modifications of their activity cytoskeletal elements, and/or elaboration of their extracellular matrices. For this purpose, this laboratory has utilized the results of a number of previous studies defining molecular biological, biochemical, morphological, and ultrastructural events of the reproducible mineralization of a primary bone cell (osteoblast) culture system under normal loading (1G gravity level). These data and the culture system then were examined following the use of the cultures in two NASA shuttle flights, STS-59 and STS-63. The cells collected from each of the flights were compared to respective synchronous ground (1G) control cells examined as the flight samples were simultaneously analyzed and to other control cells maintained at 1G until the time of shuttle launch, at which point they were terminated and studied (defined as basal cells). Each of the cell cultures was assayed in terms of metabolic markers- gene expression; synthesis and secretion of collagen and non-collagenous proteins, including certain cytoskeletal components; assembly of collagen into macrostructural arrays- formation of mineral; and interaction of collagen and mineral crystals during calcification of the cultures. The work has utilized a combination of biochemical techniques (radiolabeling, electrophoresis, fluorography, Western and Northern Blotting, and light microscopic immunofluorescence) and structural methods (conventional and high voltage electron microscopy, inununocytochemistry, stereomicroscopy, and 3D image reconstruction). The studies have provided new knowledge of aspects of bone cell development and structural regulation, extracellular matrix assembly, and mineralization during spaceflight and under normal gravity. The information has contributed to insights into the means in general by which cells respond and adapt to different conditions of gravity (loading). The data may as well have suggested an underlying basis for the observed loss of bone by vertebrates, including man, in microgravity; and these scientific results may have implications for understanding bone loss following fracture healing and extended periods of inactivity such as during long-term bedrest.

Landis, William J.↗
DOE OSTI2023

Spatiotemporal Super-Resolution with Generative Machine Learning for Creating Renewable Energy Resource Data Under Climate Change Scenarios

As we plan for a future with higher penetrations of renewables and increasing electrification, it becomes more important to understand how the electricity grid will operate under a variety of weather events. We must also consider that the weather our future grid will experience will be different and possibly more extreme than the historical weather that we have extensive data for. We can use data from global climate models (GCMs) to help understand how our climate may change over the next several decades, but there is often a significant gap between the low-resolution GCM data and the high-resolution weather data required to study power systems under specific weather events. Therefore, our objective in this work is to develop tools that can bridge this gap by using low-resolution GCM data to create realistic high-resolution weather datasets that can be used to study renewable energy generation and electricity demand. To accomplish this objective, we have developed a set of generative machine learning models that can rapidly downscale GCM daily average output data at an approximate grid resolution of 100km to hourly data at an approximate 4 km grid resolution. The models can be used to create high resolution data from nearly any GCM included in the Coupled Model Intercomparison Project (CMIP) Phase 5 or 6. Our methods include all datasets regularly used to study the integration of wind and solar power plants as well as changes in electricity demand due to heating and cooling loads. These models and datasets enable power systems modelers to study climate change-influenced weather events and their impact on the grid. We have downscaled and validated wind, solar, temperature, and humidity data with very promising results. The generative machine learning methods are computationally efficient and produce data that has similar statistical characteristics to current state-of-the-art historical datasets. We have trained initial generative models and produced an initial dataset collectively referred to as Sup3rCC: Super-Resolved Renewable Energy Resource Data with Climate Change Impacts. The data covers a (mostly) historical period from 2015-2025 and a future period from 2050-2059. We have also taken hypothetical high-electrification load data and scaled the heating and cooling loads with respect to the 2050-2059 high-resolution Sup3rCC meteorology. The results show how future levels of renewable energy generation and electrified load may be impacted by climate change, setting the stage for capacity expansion models to consider a dynamic climate through model years.

climate change↗
NASA NTRS1979

Ultimate strength of high-load-capacity composite bolted joints

Presented are the results of a series of tests initiated to obtain baseline data on the load-carrying capacity of bolted joints designed to carry large loads, specifically up to 222 kN (50 kips). The major testing purposes were to determine the load carrying capacity as a function of the width and thickness of the joint and the diameter and number of bolts, and to observe the failure mode. A total of 100 tests were conducted on three different specimen configurations. The specimens were fabricated from a T300/5208 fiber/resin system in a quasi-isotropic lay-up. The results presented indicate that for a given ratio of specimen width to hole diameter, the specimens with the smaller holes sustained a higher net-section tensile stress before failure. In addition, for a given ratio of specimen width to hole diameter, the thinner specimens withstood a higher net-section stress. No attempt has been made to correlate the results with theoretical predictions.

Hyer, M. W.↗
NASA NTRS2011

Biomechanical Analysis of Treadmill Locomotion on the International Space Station

Treadmill locomotion exercise is an important aspect of ISS exercise countermeasures. It is widely believed that an optimized treadmill exercise protocol could offer benefits to cardiovascular and bone health. If training heart rate is high enough, treadmill exercise is expected to lead to improvements in aerobic fitness. If impact or bone loading forces are high enough, treadmill exercise may be expected to contribute to improved bone outcomes. Ground-based research suggests that joint loads increase with increased running speed. However, it is unknown if increases in locomotion speed results in similar increases in joint loads in microgravity. Although data exist regarding the biomechanics of running and walking in microgravity, a majority were collected during parabolic flight or during investigations utilizing a microgravity analog. The Second Generation Treadmill (T2) has been in use on the International Space Station (ISS) and records the ground reaction forces (GRF) produced by crewmembers during exercise. Biomechanical analyses will aid in understanding potential differences in typical gait motion and allow for modeling of the human body to determine joint and muscle forces during exercise. By understanding these mechanisms, more appropriate exercise prescriptions can be developed that address deficiencies. The objective of this evaluation is to collect biomechanical data from crewmembers during treadmill exercise prior to and during flight. The goal is to determine if locomotive biomechanics differ between normal and microgravity environments and to determine how combinations of subject load and speed influence joint loading during in-flight treadmill exercise. Further, the data will be used to characterize any differences in specific bone and muscle loading during locomotion in these two gravitational conditions. This project maps to the HRP Integrated Research Plan risks including Risk of Bone Fracture (Gap B15), Risk of Early Onset Osteoporosis Due to Spaceflight (Gap B15), Risk of Impaired Performance Due to Reduced Muscle Mass, Strength, and Endurance (Gaps M3, M4, M6, Ml, M8, M9) and Risk of reduced Physical Performance Capabilities Due to Reduce Aerobic Capacity (Gaps M7, M8, M9).

De Witt, J. K.↗
DOE OSTI2021

A meta-learning based distribution system load forecasting model selection framework

This paper presents a meta-learning based, automatic distribution system load forecasting model selection framework. Furthermore, the framework includes the following processes: feature extraction, candidate model preparation and labeling, offline training, and online model recommendation. Using load forecasting needs and data characteristics as input features, multiple metalearners are used to rank the candidate load forecast models based on their forecasting accuracy. Then, a scoring-voting mechanism is proposed to weights recommendations from each meta-leaner and make the final recommendations. Heterogeneous load forecasting tasks with different temporal and technical requirements at different load aggregation levels are set up to train, validate, and test the performance of the proposed framework. Simulation results demonstrate that the performance of the meta-learning based approach is satisfactory in both seen and unseen forecasting tasks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1991

Aeroelastic loads and stability investigation of a full-scale hingeless rotor

An analytical investigation was conducted to study the influence of various parameters on predicting the aeroelastic loads and stability of a full-scale hingeless rotor in hover and forward flight. The CAMRAD/JA (Comprehensive Analytical Model of Rotorcraft Aerodynamics and Dynamics, Johnson Aeronautics) analysis code is used to obtain the analytical predictions. Data are presented for rotor blade bending and torsional moments as well as inplane damping data obtained for rotor operation in hover at a constant rotor rotational speed of 425 rpm and thrust coefficients between 0.0 and 0.12. Experimental data are presented from a test in the wind tunnel. Validation of the rotor system structural model with experimental rotor blade loads data shows excellent correlation with analytical results. Using this analysis, the influence of different aerodynamic inflow models, the number of generalized blade and body degrees of freedom, and the control-system stiffness at predicted stability levels are shown. Forward flight predictions of the BO-105 rotor system for 1-G thrust conditions at advance ratios of 0.0 to 0.35 are presented. The influence of different aerodynamic inflow models, dynamic inflow models and shaft angle variations on predicted stability levels are shown as a function of advance ratio.

Peterson, Randall L.↗
NASA NTRS1988

Cyclic uniaxial and biaxial hardening of type 304 stainless steel modeled by the viscoplasticity theory based on overstress

The isotropic theory of viscoplasticity based on overstress does not use a yield surface or a loading and unloading criterion. The inelastic strain rate depends on overstress, the difference between the stress and the equilibrium stress, and is assumed to be rate dependent. Special attention is paid to the modeling of elastic regions. For the modeling of cyclic hardening, such as observed in annealed Type 304 stainless steel, and additional growth law for a scalar quantity which represents the rate independent asymptotic value of the equilibrium stress is added. It is made to increase with inelastic deformation using a new scalar measure which differentiates between nonproportional and proportional loading. The theory is applied to correlate uniaxial data under two step amplitude loading including the effect of further hardening at the high amplitude and proportional and nonproportional cyclic loadings. Results are compared with corresponding experiments.

Yao, David↗
NASA NTRS2017

Systems and Methods for Data Visualization Using Three-Dimensional Displays

Data visualization systems and methods for generating 3D visualizations of a multidimensional data space are described. In one embodiment a 3D data visualization application directs a processing system to: load a set of multidimensional data points into a visualization table; create representations of a set of 3D objects corresponding to the set of data points; receive mappings of data dimensions to visualization attributes; determine the visualization attributes of the set of 3D objects based upon the selected mappings of data dimensions to 3D object attributes; update a visibility dimension in the visualization table for each of the plurality of 3D object to reflect the visibility of each 3D object based upon the selected mappings of data dimensions to visualization attributes; and interactively render 3D data visualizations of the 3D objects within the virtual space from viewpoints determined based upon received user input.

Djorgovski, Stanislav G.↗
NASA NTRSDate not supplied

TPSAS-NF1676L-33992-DND

The CERES Science Team integrates and fuses observations from 6 CERES instruments aboard the Terra, Aqua, S-NPP, and NOAA-20 missions with data from more than 20 other unique data sources. Following the November 2017 launch of CERES Flight Model 6 (FM6) onboard NOAA20, CERES has now amassed over 80 instrument-years of valuable Earth radiation budget data. The rapidly growing volume of CERES data coupled with the introduction of new data products alongside improvements to existing science algorithms fosters the requirement for faster, more flexible, and scalable data production and orchestration. New virtualized, cloud-centric compute hardware hosted by the NASA Langley Research Center’s (LaRC) Atmospheric Sciences Data Center (ASDC) provides an ideal environment for these ever-increasing data production demands for CERES. This poster discusses updates to the implementation of the CERES Data Management Team’s (DMT) CERES AuTomAted job Loading sYSTem (CATALYST), a custom data processing workflow engine for CERES, to use on-demand computing resources to perform automated CERES data production processing in a Linux-based container environment. Linux containers provide CERES the flexibility to build multiple production environments in containers tailored for specific workloads and allow effortless provisioning of resources based on the CERES Science Team’s data production requirements.

Thomas N. Hillyer↗
DOE OSTI2022

Load Margin Constrained Moving Target Defense against False Data Injection Attacks

Cyber physical security of power systems with high penetration of renewable generation has attracted attention from researchers. One critical issue is that cyber-physical attacks, disguised as uncertain renewable generation, can target conventional power system state estimation (SE). Moving target defense (MTD) is a promising defense strategy to detect stealthy false data injection (FDI) attacks against SE. However, all existing studies myopically perturb the reactance of transmission lines equipped with distributed flexible AC transmission system (D-FACTS) devices without adequately considering the system voltage stability. Exacerbated by the renewable generation uncertainty, existing MTD may cause voltage instability when the power grid is under stress. To address this issue, we propose a novel MTD framework that explicitly considers system voltage stability by using continuation power flow. We utilize the sensitivity matrix of power injection to line impedance, on which an optimization problem for maximizing load margin is formulated. This framework is validated on the IEEE 14-bus system and the IEEE 118-bus system, in which net load redistribution attacks are launched by sophisticated attackers. Steady-state simulations and dynamic simulations on PSS/E show the effectiveness of the proposed framework in circumventing the voltage instability while maintaining the detection effectiveness of MTD. The impact of the proposed method on attack detection effectiveness is also revealed.

Zhang, Hang↗
NASA NTRS1977

Force testing manual for the Langley 20-inch Mach 6 tunnel

Data reduction and procedures for conducting force tests in a 20 inch Mach 6 tunnel are described. A discussion of pretest and testing phases are included. Items that are to be checked during model design and construction are outlined as well as safety requirements, starting loads tests, instructions for data acquisition and model installation. Measurement of balance and model misalignment and instructions for calibrating the angle of attack screen are covered. Procedures for making reference pressure, attitude tare, and data runs are included. The 20 inch tunnel force program is examined, and a description of data recording system input and load contrast sheets is given. An appendix presents a description, operating characteristics, and Mach number calibration of the tunnel, as well as tunnel characteristics.

Keyes, J. W.↗
DOE OSTI2023

Adaptive cold-load pickup considerations in 2-stage microgrid unit commitment for enhancing microgrid resilience

In an extended main grid outage spanning multiple days, load shedding serves as a critical mechanism for islanded microgrids to maintain essential power and energy reserves that are indispensable for fulfilling reliability and resiliency mandates. However, using load shedding for such purposes leads to increasing occurrence of cold load pickup (CLPU) events. Here, this study presents an innovative adaptive CLPU model that introduces a method for determining and incorporating parameters related to CLPU power and energy requirements into a two-stage microgrid unit commitment (MGUC) algorithm. In contrast to the traditional fixed-CLPU-curve approach, this model calculates CLPU duration, power, and energy demands by considering outage durations and ambient temperature variations within the MGUC process. By integrating the adaptive CLPU model into the MGUC problem formulation, it allows for the optimal allocation of energy resources throughout the entire scheduling horizon to fulfill the CLPU requirements when scheduling multiple CLPU events. The performance of the enhanced MGUC algorithm considering CLPU needs is assessed using actual load and photovoltaic (PV) data. Simulation results demonstrate significant improvements in dispatch optimality evaluated by the amount of load served, customer comfort, energy storage operation, and adherence to energy schedules. These enhancements collectively contribute to reliable and resilient microgrid operation.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

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↗