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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Marin County Wildland Fires: Examining Fuel Load and Land Cover Change to Inform Fire Prevention and Suppression Decisions in Marin County, CA

Heightened occurrence of severe wildfires in the Western United States is increasing the need to better understand regions of high potential wildfire severity and develop methodologies for identifying the best locations for fuels reduction and active wildfire suppression, especially in populated regions such as Marin County, California. Marin County, located in the San Francisco Bay Area, has had significant development in the wildland-urban interface and periods of highly wildfire-prone conditions. The NASA DEVELOP team collaborated with Fire Foundry (a Marin-based fire service workforce development program) and the Marin County Fire Department to develop models to assist with fire management. Using data from Sentinel-2A, PlanetScope, ECOSTRESS, a county-wide LiDAR mapping effort, Landsat 7 Enhanced Thematic Mapper (ETM+), and Landsat 8 Operational Land Imager (OLI), our team developed a number of input data layers for three different models to evaluate wildfire severity. One model performed a suitability analysis with weights based on scientific literature; another model utilized a U-Net Convolutional Neural Network trained on previous fires in Marin and neighboring Sonoma County to predict the difference normalized burn severity; and the third inputted data layers into the FlamMap tool that outputs risk categories. We compared model outputs and performed a weighted overlay analysis to identify specific locations where a fireline could be constructed to interrupt the progress of an active fire. These tools will assist partners in preparing for and managing active wildfire situations.

Remote sensing↗
DOE OSTI2016

On the Path to SunShot. Emerging Issues and Challenges in Integrating High Levels of Solar into the Electrical Generation and Transmission System

This report examines how the bulk power system may need to evolve to accommodate the increased photovoltaic (PV) penetration resulting from achievement of the U.S. Department of Energy's SunShot cost targets. The variable and uncertain nature of PV-generated electricity presents grid-integration challenges. For example, the changing net load associated with high midday PV generation and low electricity demand can create 'overgeneration' that requires curtailment of PV output and reduces PV's value and cost-competitiveness. Accommodating the changes in net load resulting from increased variable generation requires enhancements to a power system's 'flexibility,' or ability to balance supply and demand over multiple time scales through options including changes in system operation, flexible generation, reserves from solar, demand response, energy storage, and enhanced transmission and regional coordination. For utility-scale PV with a baseline SunShot levelized cost of electricity (LCOE) of 6 cents/kWh, increasing the annual energy demand met by solar energy from 10% to 20% would increase the marginal LCOE of PV from 6 cents/kWh to almost 11 cents/kWh in a California grid system with limited flexibility. However, increasing system flexibility could minimize solar curtailment and keep PV cost-competitive at penetrations at least as high as 25%. In the longer term, energy storage technologies--such as concentrating solar power with thermal energy storage--could facilitate the cost-effective integration of even higher PV penetration. Efficient deployment of the grid-flexibility options needed to maintain solar's value will require various innovations, from the development of communication, control, and energy storage technologies to the implementation of new market rules and operating procedures.

14 SOLAR ENERGY↗
DOE OSTI2018

Hygrothermal Effect on Composites Under In-Plane Fatigue at Stress Ratios of R = −1 and R = 0.1: An Analysis of Quasi-Isotropic Stitched Carbon Fibers

The aeronautic structures normally operate under high levels of hygroscopic moisture from the surrounding environment at different temperature ranges while in service. Under such conditions, the behavior of laminate composite submitted to cyclic or static loadings can change drastically. In order to understand those effects in stitched fabrics, fatigue tests with open-hole specimens were carried out with a stress ratio of R = −1 and R = 0.1. The specimens were fatigue-tested as provided (environmental conditions) and after exposed to hygrothermal weathering conditions. Based on evidences from recent studies available in the open literature, e.g., effect of water diffusion on epoxy matrix, the overall results indicated a significant reduction in stiffness after the specimens are exposed to hygrothermal effects. The reduction in matrix stiffness, in this case, enhanced the fatigue strength in tension–tension load (R = 0.1) when compared to the specimens in normal conditions. The opposite occurs for the specimens loaded with stress ratio of R = −1, in which the delamination mechanisms changed during the loading reversion from tension to compression that promoted early delamination. Therefore, this process reduced the fatigue life of the specimens under hygrothermal condition. Then, by fractographic investigation, it was verified fracture patterns that regard to mode II damage in R = −1, in which mode II fracture toughness is known to decrease in the presence of water molecules.

36 MATERIALS SCIENCE↗
DOE OSTI2021

OCHRE: The Object-oriented, Controllable, High-resolution Residential Energy Model for Dynamic Integration Studies

Electrification and the growth of distributed energy resources (DERs), including flexible loads, are changing the energy landscape of electric distribution systems and creating new challenges and opportunities for electric utilities. Changes in demand profiles require improvements in distribution system load models, which have not historically accounted for device controllability or impacts on customer comfort. Although building modeling research has focused on these features, there is a need to incorporate them into distribution load models that include DERs and can be used to study grid-interactive buildings. In this paper, we present the Object-oriented, Controllable, High-resolution Residential Energy (OCHRE) model. OCHRE is a controllable thermal-electric residential energy model that captures building thermal dynamics, integrates grid-dependent electrical behavior, contains models for common DERs and end-use loads, and simulates at a time resolution down to 1 minute. It includes models for space heaters, air conditioners, water heaters, electric vehicles, photovoltaics, and batteries that are externally controllable and integrated in a co-simulation framework. Using a proposed zero energy ready community in Colorado, we co-simulate a distribution grid and 498 all-electric homes with a diverse set of efficiency levels and equipment properties. We show that controllable devices can reduce peak demand within a neighborhood by up to 73% during a critical peak period without sacrificing occupant comfort. We also demonstrate the importance of modeling load diversity at a high time resolution when quantifying power and voltage fluctuations across a distribution system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Using Machine Learning Tools to Predict Compressor Stall

Clean energy has become an increasingly important consideration in today’s power systems. As the push for clean energy continues, many coal-fired power plants are being decommissioned in favor of renewable power sources such as wind and solar. However, the intermittent nature of renewables means that dynamic load following traditional power systems is crucial to grid stability. With high flexibility and fast response at a wide range of operating conditions, gas turbine systems are poised to become the main load following component in the power grid. Yet, rapid changes in load can lead to fluid flow instabilities in gas turbine power systems. These instabilities often lead to compressor surge and stall, which are some of the most critical problems facing the safe and efficient operation of compressors in turbomachinery today. Although the topic of compressor surge and stall has been extensively researched, no methods for early prediction have been proven effective. This study explores the utilization of machine learning tools to predict compressor stall. The long short-term memory (LSTM) model, a form of recurrent neural network (RNN), was trained using real compressor stall datasets from a 100 kW recuperated gas turbine power system designed for hybrid configuration. Two variations of the LSTM model, classification and regression, were tested to determine optimal performance. The regression scheme was determined to be the most accurate approach, and a tool for predicting compressor stall was developed using this configuration. Overall, results show that the tool is capable of predicting stalls 5–20 ms before they occur. With a high-speed controller capable of 5 ms time-steps, mitigating action could be taken to prevent compressor stall before it occurs.

42 ENGINEERING↗
DOE OSTI2023

Efficiency and Demand Flexibility in Large Office Buildings: The Potential for Cost Savings and CO 2 Reductions from Lighting and Cooling Measures

This report presents the estimated impact of lighting and cooling efficiency and demand flexibility measures in large office buildings in each state in the contiguous United States. It provides modeled results for three different metrics: bill savings, regional grid operational costs savings, and carbon dioxide (CO 2 ) emissions reductions. Lighting efficiency and demand flexibility are estimated to reduce load by up to 80 MWh/yr in a single large office building. These load reductions result in customer bill savings of up to $8,800/yr per building, with the highest savings in southern and midwestern states. Grid operating cost savings are estimated at up to $3,240/yr/building, with greatest benefit in southern and northeastern states. CO 2 emissions reduction potential is highest in the Dakotas, Nebraska, across the Midwest, in West Virginia, and in Mississippi (<48,200 kg/yr/building). Comparatively, cooling measures are found to have less load reduction potential (<28.5 MWh/yr/building), with the greatest potential in southern states including Texas, which ranks top of the list across several of the metrics studied. In numerous states, shifting cooling load to off-peak hours is found to increase costs and CO 2 emissions because precooling results in increased load during high-cost or high-CO 2 emissions periods. In general, focusing on cooling efficiency and load shedding has the potential for more savings. In all cases, the specific rate structure is a significant determinant in actual bill savings, which are up to $4,000/yr/building. To realize the full potential for bill savings through an energy measure, building operators must identify how the measure will change the building load pattern and the interaction of this load change with the applicable rate tariff. To realize CO 2 emissions reductions, industry and state coordination is needed to verify which fuel source is on the margin and then to create incentives for end users to reduce load during high-CO 2 emissions hours. Regular updates to data sets and analyses are critical. Regulators and policymakers are well positioned to facilitate the necessary coordination between the electric industry and building energy managers to develop appropriate price signals and incentives.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Device-level plug load disaggregation in a zero energy office building and opportunities for energy savings

Along with heating, cooling, ventilation, and lighting, plug loads are one of the principal consumers of energy in commercial buildings. Managing ever-changing plug loads is a great challenge given the quantity and variety of devices in commercial buildings and the cost of monitoring equipment. To address this issue, we propose a method for developing a disaggregated model of an office building's plug loads that utilizes power data from a small portion of monitored devices and a device inventory. Using data from metering and control devices in the Research Support Facility at the National Renewable Energy Laboratory, we compared our model to the building's plug load submeters. We found that the model was effective in predicting the shape of the building's average plug loads; however, it did not account for the entire magnitude of the load. With the disaggregated breakdown, we identified devices that contributed significantly to the building's unoccupied load, such as the audio visual equipment as well as devices that contributed significantly at specific times of the day, such as the microwaves at noon. This disaggregated information enables building owners to make more informed decisions with respect to plug load controls and energy efficiency upgrades. Furthermore, we highlight how the plug loads in the Research Support Facility have changed over time and offer recommendations for implementing this disaggregation method in other buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Fleetwide data-enabled reliability improvement of wind turbines

Wind farms are an indispensable driver toward renewable and nonpolluting energy resources. However, as ideal sites are limited, placement in remote and challenging locations results in higher logistics costs and lower average wind speeds. Therefore, it is critical to increase the reliability of the turbines to reduce maintenance costs. Robust implementation requires a thorough understanding of the loads subject to the turbine's control. Yet, such dynamically changing multidimensional loads are uncommon with other machinery, and generally underresearched. Therefore, a multitiered approach is proposed to investigate the load spectrum occurring in wind farms. Our approach relies on both fundamental research using controllable test rigs, as well as analyses of real-world loading conditions in high-frequency supervisory control and data acquisition data. A method is introduced to detect operational zones in wind farm data and link them with load distributions. Additionally, while focused research further investigates the load spectrum, a method is proposed that continuously optimizes the farm's control protocols without the need to fully understand the loads that occur. A case of gearbox failure is investigated based on a vast body of past experiments and suspect loads are identified. Starting from this evidence on the cause and effects of dynamic loads, the potential of our methods is shown by analyzing real-world farm loading conditions on a steady-state case of wake and developing a preventive row-based control protocol for a case of cascading emergency brakes induced by a storm.

17 WIND ENERGY↗
DOE OSTI2019

Flux Equations for Osmotically Moderated Sorption–Diffusion Transport in Rigid Microporous Membranes

The development of non-aqueous reverse osmosis separations via the use of rigid microporous membrane materials suggests that flux equations originally developed for swellable polymeric membranes should be revisited. This paper demonstrates that the gradient of fractional occupancy of penetrant molecules within the micropores of the membrane is the driving force for permeation without requiring assumptions about pressure within the membrane. Flux equations are derived using both Fickian and Maxwell-Stefan approaches, and different behavior in the permeate flux versus upstream hydraulic pressure relationship is shown to arise as a result of differences in the loading dependence of the single component Maxwell-Stefan diffusivity. Molecular modeling results available in the literature and experimental data obtained from carbon molecular sieve (CMS) membranes showcase that these loading-dependent changes in the Maxwell-Stefan diffusivity are possible. This loading dependence is separated into three regimes: so-called “weak confinement” diffusion and “strong confinement” diffusion, both of which have been discussed at length in the literature, and a new “hybrid confinement” diffusion, which is introduced here. Furthermore, the separation mechanism of solvent molecules through a rigid bimodally microporous membrane is studied using xylene molecules passing through CMS membranes fabricated under different conditions as examples. Altogether, this study provides fundamental insight and guidance into osmotically-moderated sorption-diffusion transport of solvent molecules through rigid microporous membranes.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Using Distributed Dynamic Voltage Restorers to Improve the Frequency Stability of Low-Inertia Networked Microgrids

This paper elucidates the novel concept of using distributed dynamic voltage restorers (DVRs), which are traditionally used to compensate for voltage sags, to improve the frequency stability of low-inertia networked microgrids. During frequency transients, the distributed DVRs rapidly regulate load voltages within an acceptable range, resulting in a fast change of load power consumption and helping improve frequency stability. To enable large-scale network simulation, a phasor-based model of DVRs is developed and validated against real data from a commercially available device. Finally, simulation results of a modified IEEE 123-node test feeder that comprises three microgrids and six DVRs verify the effectiveness of the proposed method.

Du, Wei↗
NASA NTRS1990

Out of plane analysis for composite structures

Simple two dimensional analysis techniques were developed to aid in the design of strong joints for integrally stiffened/bonded composite structures subjected to out of plane loads. It was found that most out of plane failures were due to induced stresses arising from rapid changes in load path direction or geometry, induced stresses due to changes in geometry caused by buckling, or direct stresses produced by fuel pressure or bearing loads. While the analysis techniques were developed to address a great variety of out of plane loading conditions, they were primarily derived to address the conditions described above. The methods were developed and verified using existing element test data. The methods were demonstrated using the data from a test failure of a high strain wingbox that was designed, built, and tested under a previous program. Subsequently, a set of design guidelines were assembled to assist in the design of safe, strong integral composite structures using the analysis techniques developed.

Paul, P. C.↗
DOE OSTI2018

ARC algorithm: A novel approach to forecast and manage daily electrical maximum demand

This paper proposes an innovative algorithm for predicting short-term electrical maximum demand by using historical demand data. The ability to recognize in peak demand pattern for commercial or industrial customers would propose numerous direct and indirect benefits to the customers and utility providers in terms of demand reduction, cost control, and system stability. Prior works in electrical maximum demand forecasting have been mainly focused on seasonal effects, which is not a feasible approach for industrial manufacturing facilities in short-term load forecasting. The proposed algorithm, denoted as the Adaptive Rate of Change (ARC), determines the logarithmic rate-of-change in load profile prior to a peak by postulating the demand curve as a stochastic, mean-reverting process. The rationale behind this analysis, is that the energy efficient program requires not only demand estimation but also to warn the user of imminent maximum peak occurrence. This paper analyzes demand trend data and incorporates stochastic model and mean reverting half-life to develop an electrical maximum demand forecasting algorithm, which is statistically evaluated by cross-table and F-score for three different manufacturing facilities. Lastly, the aggregate results show an overall accuracy of 0.91 and a F-score of 0.43, which indicates that the algorithm is effective predicting peak demand in predicting peak demand.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1985

Fracto-emission from single fibres of Kevlar

Fracto-emission (FE) is the emission of particles (e.g. electrons, ions and photons) during and following fracture. In this paper, we present data on electron emission (EE) and positive ion emission (PIE) from the tensile fracture of Kevlar single fibers. The fibers were initially fractured in pure tension, where a stranded form of fracture was observed, often with multiple peaks spread over several hundred microseconds. The loading condition was then changed by stretching and breaking the fibers over a dull metal edge. With this change in the loading, different forms of fracture were observed, each with distinctive forms of emission curves. When fracture was accompanied by extensive fibril formation, total emission was high and both EE and PIE decay times were long relative to fractures in which little fibril formation occurred. The results of this study suggest that FE has some applicability as a tool for the detection of fracture mechanisms of single fibers.

Dickinson, J. T.↗
NASA NTRS1936

A Flight Investigation of the Spinning of the F4B-2 Biplane with Various Loads and Tail Surfaces

A flight investigation of the spinning of the F4B-2 single-seat fighter airplane was made for the purpose of finding modifications that would eliminate dangerous spin tendencies exhibited by this type of airplane in service. The effects on steady spins and on recoveries of changing the loading, enlarging the fin areas, changing the elevator plan form, and raising the horizontal surfaces, were determined.

Scudder, N F↗
NASA NTRSDate not supplied

Developing Mission Segment-Specific Clinical Data for Impact

Space exploration missions represent a significant future objective for NASA’s human spaceflight operations for the near and long term. By operating missions during longer periods and over further distances, NASA’s mission planning models, hardware systems, and medical capabilities will be stretched beyond their original design constraints. The necessity of medical training and medical supply manifesting for such missions is likely to become incredibly intricate as trade-space analysis is performed over varying mission profiles. For this purpose, IMPACT was created to extend and improve the Integrated Medical Model (IMM) which is used for International Space Station (ISS) medical predications and consists of a probabilistic risk assessment tool that simulates missions to calculate risks given the constraints on crew complement, mission duration and activity (such as Extravehicular Activities), power, communication, mass, volume, and evacuation consideration as well as to predict mission outcomes. Currently, the medical evidence used to support IMPACT remains static, addressing risks of a medical condition and the impacts of the condition during spaceflight only, but is only calculated for a small number of mission parameters. Extended missions will consist of new and varied living environments, changing gravitational loads, and dynamic working requirements. Medical risks are not typically constant but will change depending upon the physical and physiological environment of the body during all phases of a mission. Risks are likely to shift during different mission segments, and understanding how components of a mission profile change risks will assist mission planners to increase chances for mission success.

Christopher Zahner↗
NASA NTRS1983

The linear boom actuator designed for the Galileo spacecraft

Because the linear boom actuator is to be used on a flight spacecraft, as opposed to a ground based application, there is a comprehensive set of requirements. First, of course, the actuator must be capable of positioning and holding the load. Initially the load as predicted to be 4448 N (1000 lb) but with subsequent spacecraft configuration changes the load has been greatly reduced to a constant tensile pull of 1477 N (332 lb) due to centrifugal force. Lesser compressive loads of 1317 N (296 centrifugal lb) may be experienced during launch and deployment. This actuator must have the maximum redundancy possible. Life requirements were defined by the 10.16 to 15.24 cm (4 to 6 in.) total liner travel expected during the five-year flight duration. Liner range required of the actuator was set at plus and minus 5.08 cm to accommodate configuration changes.

Koch, E. F.↗
NASA NTRS1993

Effects on stratospheric ozone from high-speed civil transport: Sensitivity to stratospheric aerosol loading

The potential impact of high-speed civil transport (HSCT) aircraft emissions on stratospheric ozone and the sensitivity of these results to changes in aerosol loading are examined with a two-dimensional model. With aerosols fixed at background levels, calculated ozone changes due to HSCT aircraft emissions range from negligible up to 4-6% depletions in column zone at northern high latitudes. The magnitude of the ozone change depends mainly on the NO(x) increase due to aircraft emissions, which depends on fleet size, cruise altitude, and engine design. The partitioning of the odd nitrogen species in the lower stratosphere among NO, NO2, N2O5, is strongly dependent on the concentration of sulfuric acid aerosol particles, and thus the sensitivity of O3 to NO(x) emissions changes when the stratospheric aerosol loading changes. Aerosol concentrations 4 times greater than background levels have not been unusual in the last 2 decades. Our model results show that a factor of 4 increase in aerosol loading would significantly reduce the calculated ozone depletion due to HSCT emissions. Because of the neutral variabiltiy of stratospheric aerosols, the possible impact of HSCT emissions on ozone must be viewed as a range of possible results.

Weisenstein, Debra K.↗
DOE OSTI2025

Modeled sensitivity of multi-MA accelerator performance to electrode contaminant inventory

Significant particle-in-cell code development has enabled simulations of power flow in multi-MA accelerators to include the desorption of surface contaminants, their ionization into surface plasmas, and the impact of these plasmas on efficiency. The simulations base desorption on an Arrhenius equation, whose most significant unknown is the surface contaminant inventory. The sensitivity of power-flow simulations to this inventory is studied here using Sandia National Laboratories' Z accelerator with a 7-nH MagLIF load [Phys. Plasmas 17, 056303 (2010)]. Simulations are conducted in 3D cylindrical coordinates for the current-adder, or “convolute,” region of Z and in 2D for the final feed only. Simulated contaminant inventories are varied from 1 to 32 monolayers (MLs) in 2D, and 2 to 4 ML in 3D. The results reveal sensitivities to the local ratio of E/B⁠. The high B-field, low E-field region near the short-circuit load is insensitive to the contaminant inventory, where assumed values of 4–32 ML change the load current by ≤ 2%, and agree with experiment to within 2% at peak current. A 1-ML value is the outlier, increasing the load current by 5%, but still within measurement uncertainty. In contrast, the relatively higher E-field, lower B-field convolute region has slower contaminant desorption and higher-magnitude E-field penetration of the surface plasmas. The current loss in the convolute region does increase with contaminant inventory. The loss assuming 4 ML is 12% larger than for 2 ML, with 4 ML being the better match to experiment.

Arrhenius equation↗