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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 811 records · Page 45
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Building Energy Systems as Behind-the-Meter Resources for Grid Services: Intelligent load control and transactive control and coordination

To mitigate the impacts of climate change, significant reductions in emissions from all sectors of the economy are needed. The electricity generation sector has embarked on an ambitious plan to include renewable generation as part of its decarbonization efforts, and many cities and states are mandating all-electric buildings. While renewable resources will reduce emissions, they are not dispatchable, they vary temporally, and their generation is uncertain. Under these conditions, traditional approaches to managing grid reliability, where supply follows demand, will not be efficient and may not be cost-effective. Further, there is a more efficient alternative for balancing the supply–demand imbalance and for absorbing variability and uncertainty of renewable energy using distributed energy resources (DERs) as opposed to reserve generation. Because buildings consume more than 75% of total U.S. annual electricity consumption, behind-the-meter (BTM) DERs have a load flexibility of 77 GW of power and 90 GWh of virtual energy storage capacity nationwide (Kalsi, 2017). Therefore, some portion of the supply–demand imbalance can be met by these DERs at a lower cost compared to business-as-usual solutions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Expanded modelling scenarios to understand the role of offshore wind in decarbonizing the United States

An assessment of decarbonization pathways in energy models reveals fundamental limitations in representing factors that are relevant for practical decision-making. Although these modelling limitations are widely acknowledged, their impact on the deployment of individual power generation types is not well understood. As a result, the societal value from such generation types could be vastly misrepresented. Here we explore a wide spectrum of factors that impact offshore wind deployment in the United States using a detailed capacity expansion model. Many factors prescribe a large future role for offshore wind, yet this diverges from what models often show. We extend the typically narrow modelling context through high spatial resolution, several cost and transmission possibilities and various energy-sector policies. Further, we estimate offshore wind to constitute 1-8% (31-256 gigawatts) of total US generation by 2050. This wide range suggests an uncertain but potentially important regional role. Our expansive scenarios demonstrate how to address many limitations of decarbonization modelling.

17 WIND ENERGY↗
DOE OSTI2024

The Influence of ENSO Diversity on Future Atlantic Tropical Cyclone Activity

El Niño–Southern Oscillation (ENSO) influences seasonal Atlantic tropical cyclone (TC) activity by impacting environmental conditions important for TC genesis. However, the influence of future climate change on the teleconnection between ENSO and Atlantic TCs is uncertain, as climate change is expected to impact both ENSO and the mean climate state. We used the Weather Research and Forecasting Model on a tropical channel domain to simulate 5-member ensembles of Atlantic TC seasons in historical and future climates under different ENSO conditions. Experiments were forced with idealized sea surface temperature configurations based on the Community Earth System Model (CESM) Large Ensemble representing: a monthly varying climatology, eastern Pacific El Niño, central Pacific El Niño, and La Niña. The historical simulations produced fewer Atlantic TCs during eastern Pacific El Niño compared to central Pacific El Niño, consistent with observations and other modeling studies. For each ENSO state, the future simulations produced a similar teleconnection with Atlantic TCs as in the historical simulations. Specifically, La Niña continues to enhance Atlantic TC activity, and El Niño continues to suppress Atlantic TCs, with greater suppression during eastern Pacific El Niño compared to central Pacific El Niño. In addition, we found a decrease in the Atlantic TC frequency in the future relative to historical regardless of ENSO state, which was associated with a future increase in northern tropical Atlantic vertical wind shear and a future decrease in the zonal tropical Pacific sea surface temperature (SST) gradient, corresponding to a more El Niño–like mean climate state. Our results indicate that ENSO will remain useful for seasonal Atlantic TC prediction in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Impacts of sea ice leads on sea salt aerosols and atmospheric chemistry in the Arctic

Abstract. The processes contributing to Arctic cold-season (November–April) sea salt aerosols (SSAs) remain uncertain. Observations from coastal Alaska suggest that emissions from open leads in sea ice, which are not included in climate models, may play a dominant role. Their Arctic-wide significance has not yet been quantified. Here, we create an emission parameterization of SSAs from leads by combining satellite data of lead area (the Advanced Microwave Scanning Radiometer–Earth Observation System (AMSR-E) product) and a chemical transport model (GEOS-Chem) to quantify pan-Arctic SSA emissions from leads during the cold season from 2002 to 2008 and to predict their impacts on atmospheric chemistry, evaluating the results of our simulated SSAs against in situ observations. The AMSR-E product detects large leads with certainty (> 3 km in size), and, hence, our study is limited to quantifying emissions from large leads. Lead emissions vary seasonally and interannually. Simulated total monthly SSA emissions increase by 1.1 %–1.8 % (≥60° N latitude) and 5.6 %–7.5 % (≥75° N) for the 2002–2008 cold seasons. SSA concentrations primarily increase at the location of leads, where standard model concentrations are low. GEOS-Chem overestimates SSA concentrations at Arctic sites compared to ground observations, even when lead emissions are not included, suggesting underestimation of SSA sinks and/or uncertainties in SSA emissions from blowing snow and the open ocean. Multi-year monthly mean surface bromine atom (Br) concentrations increase by 2.8 %–8.8 % due to SSAs from leads for the 2002–2008 cold seasons. Changes in ozone concentrations are negligible. While leads contribute < 10 % to Arctic-wide SSA emissions in the years 2002–2008, these emissions occur in regions of low background aerosol concentrations. Leads may increase in frequency under future climate change, which could increase SSA emissions from leads.

Emme, Erin J. (ORCID:0000000268406352)↗
NASA NTRS1992

High-resolution photoabsorption cross sections of E1Pi - X1Sigma(+) vibrational bands of CO-12 and CO-13

Photodissociation following absorption of extreme-ultraviolet photons is an important factor in determining the abundance and isotropic fractionation of CO in diffuse and translucent interstellar clouds. The principal channel for destruction of CO-13 in such clouds begins with absorption in the (1,0) vibrational band of the E1Pi - X1Sigma(+) system; similarly, absorption in the (0,0) band begins a significant destruction channel for CO-12. Reliable modeling of the CO fractionation process depends critically upon the accuracy of the photoabsorption cross section for these bands. We have measured the cross sections for the relevant isotropic species and for the (1,0) band of CO-12. Our results, which are uncertain by about 10 percent, are for the most part larger than previous measurements.

Stark, G.↗
NASA NTRS2020

Unmasking secondary vegetation dynamics in the Brazilian Amazon

Secondary vegetation (SV) from land abandonment is a common transition phase between agricultural uses following tropical deforestation. The impact of SV on carbon sequestration and habitat fragmentation across tropical forest frontiers therefore depends on SV dynamics and demographics. Here, we used time series of annual MapBiomas land cover data to generate the first estimates of SV extent, age, and net carbon uptake in the Brazilian Amazon between 1985 and 2017. SV increased over time, totaling 12 Mha in 2017, 44% of which was ≤5 years old. Between 1988 and 2017, 19.6 Mha of SV was cleared, adding 45.5% to the area of primary deforestation detected by the Brazilian monitoring system (PRODES). Rates of SV loss have exceeded PRODES deforestation since 2011. Based on the age and extent of gains and losses, SV was a small net carbon sink during this period (8.9 Tg C/yr). As SV is not formally protected by national environmental legislation or monitored by PRODES, long-term benefits from SV in the Brazilian Amazon remain uncertain.

Brazilian Amazon↗
DOE OSTI2022

Uncertainty in Annual Energy Resulting from Uncertain Irradiance Measurements

We report an analysis quantifying the contribution to uncertainty in annual energy projections from uncertainty in ground-measured irradiance. Uncertainty in measured irradiance is quantified for eight instruments by the difference from a well maintained, secondary standard pyranometer which is regarded as truthful. We construct a statistical model of irradiance uncertainty and apply the model to generate a sample of 100 annual time series of irradiance for each instrument. The sample is propagated through a common performance model for a reference photovoltaic system to quantify variation in annual energy. Although the measured irradiance varies from the reference by a few percent (standard deviation of 1-2%) the uncertainty in annual energy is on the order of a fraction of one percent. We propose a model for a factor that represents uncertainty in modeled annual energy that arises from uncertainty in ground-measured irradiance.

14 SOLAR ENERGY↗
NASA NTRS2013

Global Climate Change, Food Security and the U.S. Food System

Climate change influences on the major pillars of food security. Each of the four elements of food security (availability,access,utilization,andstability) is vulnerable to changes in climate. For example,reductions in production related to regional drought influence food availability at multiple scales. Changes in price influences the ability of certain populations to purchase food (access). Utilization maybe affected when production zones shift, reducing the availability of preferred or culturally appropriate types of food within a region. Stability of the food supply may be highly uncertain given an increased incidence of extreme climatic events and their influence on production patterns.

Climate↗
NASA NTRS1988

Robustness analysis based on passivity

A technique of robust stability analysis for multivariable control systems is introduced. Existing tools in the literature are mostly based on small gain type of conditions such as the H(infinity)-norm or mu measure. In contrast, the approach presented is motivated by passivity theory. The natural energy Lyapunov function associated with a passive system allows robustness to be analyzed with Lyapunov stability theory. Consequently, nonlinear and time-varying perturbations can be considered within the same framework. For unstructured uncertainties, the robustness margin is characterized in terms of an index related to the Hermitian part of a transfer function. If the uncertainties contain additional diagonal structure, stability margins are obtained for variations of each uncertain block in both positive and negative directions. Applications of this robustness analysis technique are illustrated.

Wen, John T.↗
DOE OSTI2022

Doubling protected land area may be inefficient at preserving the extent of undeveloped land and could cause substantial regional shifts in land use

Abstract Projection of land use and land‐cover change is highly uncertain yet drives critical estimates of carbon emissions, climate change, and food and bioenergy production. We use new, spatially explicit land availability data in conjunction with a model sensitivity analysis to estimate the effects of additional land protection on land use and land cover. The land availability data include protected land and agricultural suitability and is incorporated into the Moirai land data system for initializing the Global Change Analysis Model. Overall, decreasing land availability is relatively inefficient at preserving undeveloped land while having considerable regional land‐use impacts. Current amounts of protected area have little effect on land and crop production estimates, but including the spatial distribution of unsuitable (i.e., unavailable) land dramatically shifts bioenergy production from high northern latitudes to the rest of the world, compared with uniform availability. This highlights the importance of spatial heterogeneity in understanding and managing land change. Approximately doubling the current protected area to emulate a 30% protected area target may avoid land conversion by 2050 of less than half the newly protected extent while reducing bioenergy feedstock land by 10.4% and cropland and grazed pasture by over 3%. Regional bioenergy land may be reduced (increased) by up to 46% (36%), cropland reduced by up to 61%, pasture reduced by up to 100%, and harvested forest reduced by up to 35%. Only a few regions show notable gains in some undeveloped land types of up to 36%. Half of the regions can reach the target using only unsuitable land, which would minimize impacts on agriculture but may not meet conservation goals. Rather than focusing on an area target, a more robust approach may be to carefully select newly protected land to meet well‐defined conservation goals while minimizing impacts to agriculture.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Robust cooperative control strategy for a platoon of connected and autonomous vehicles against sensor errors and control errors simultaneously in a real-world driving environment

In a real-world driving environment, a platoon of connected and autonomous vehicles (CAVs) is subject to many internal and external disturbances, resulting in uncertain vehicle dynamics. In general, the disturbances can be categorized into two types: disturbances due to vehicle sensor errors (e.g., GPS error) and disturbances due to vehicle control errors (e.g., actuator delay). In the literature, many control strategies have been proposed to improve the robustness of the CAV platoon against uncertain vehicle dynamics induced by these disturbances. However, most of these strategies only consider one type of disturbance and cannot tackle both types of disturbances simultaneously. Furthermore, they are designed to maximize the benefits of each vehicle in the platoon independently, which can deteriorate the performance of the platoon. Here, to address these problems, this study proposes a robust cooperative control (RCC) strategy to maneuver the vehicles in the platoon cooperatively to counteract the impacts of both types of disturbances. The RCC strategy is developed based on a minimax problem, where the maximization subproblem seeks to find the worst inputs for the uncertainty terms in the vehicle dynamics equation to minimize the platoon performance, while the minimization subproblem seeks to find the optimal control decisions for all subsequent vehicles to maximize the platoon performance in the worst case. To solve the minimax problem, this study proposes a globally convergent solution algorithm. It can solve the minimax problem very efficiently to enable real time deployment of the RCC strategy. Numerical application indicates that compared to the existing methods, the RCC strategy can dramatically improve the robustness of the CAV platoon against the uncertain vehicle dynamics induced by both vehicle state detection errors and vehicle control errors. Therefore, it can maneuver the CAV platoon safely and efficiently in a real-world driving environment.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1996

Effects of modeling errors on trajectory predictions in air traffic control automation

Air traffic control automation synthesizes aircraft trajectories for the generation of advisories. Trajectory computation employs models of aircraft performances and weather conditions. In contrast, actual trajectories are flown in real aircraft under actual conditions. Since synthetic trajectories are used in landing scheduling and conflict probing, it is very important to understand the differences between computed trajectories and actual trajectories. This paper examines the effects of aircraft modeling errors on the accuracy of trajectory predictions in air traffic control automation. Three-dimensional point-mass aircraft equations of motion are assumed to be able to generate actual aircraft flight paths. Modeling errors are described as uncertain parameters or uncertain input functions. Pilot or autopilot feedback actions are expressed as equality constraints to satisfy control objectives. A typical trajectory is defined by a series of flight segments with different control objectives for each flight segment and conditions that define segment transitions. A constrained linearization approach is used to analyze trajectory differences caused by various modeling errors by developing a linear time varying system that describes the trajectory errors, with expressions to transfer the trajectory errors across moving segment transitions. A numerical example is presented for a complete commercial aircraft descent trajectory consisting of several flight segments.

Jackson, Michael R. C.↗
NASA NTRS2000

Terrestrial planet and asteroid formation in the presence of giant planets. I. Relative velocities of planetesimals subject to Jupiter and Saturn perturbations

We investigate the orbital evolution of 10(13)- to 10(25) -g planetesimals near 1 AU and in the asteroid belt (near 2.6 AU) prior to the stage of evolution when the mutual perturbations between the planetesimals become important. We include nebular gas drag and the effects of Jupiter and Saturn at their present masses and in their present orbits. Gas drag introduces a size-dependent phasing of the secular perturbations, which leads to a pronounced dip in encounter velocities (Venc) between bodies of similar mass. Plantesimals of identical mass have Venc approximately 1 and approximately 10 m s-1 (near 1 and 2.6 AU, respectively) while bodies differing by approximately 10 in mass have Venc approximately 10 and approximately 100 m s-1 (near 1 and 2.6 AU, respectively). Under these conditions, growth, rather than erosion, will occur only by collisions of bodies of nearly the same mass. There will be essentially no gravitational focusing between bodies less than 10(22) to 10(25) g, allowing growth of planetary embryos in the terrestrial planet region to proceed in a slower nonrunaway fashion. The environment in the asteroid belt will be even more forbidding and it is uncertain whether even the severely depleted present asteroid belt could form under these conditions. The perturbations of Jupiter and Saturn are quite sensitive to their semi-major axes and decrease when the planets' heliocentric distances are increased to allow for protoplanet migration. It is possible, though not clearly demonstrated, that this could produce a depleted asteroid belt but permit formation of a system of terrestrial planet embryos on a approximately 10(6)-year timescale, initially by nonrunaway growth and transitioning to runaway growth after approximately 10(5) years. The calculations reported here are valid under the condition that the relative velocities of the bodies are determined only by Jupiter and Saturn perturbations and by gas drag, with no mutual perturbations between planetesimals. If, while subject to these conditions, the bodies become large enough for their mutual perturbations to influence their velocity and size evolution significantly, the problem becomes much more complex. This problem is under investigation.

NASA Discipline Exobiology↗
DOE OSTI2023

Neglecting Model Parametric Uncertainty Can Drastically Underestimate Flood Risks

Abstract Floods drive dynamic and deeply uncertain risks for people and infrastructures. Uncertainty characterization is a crucial step in improving the predictive understanding of multi‐sector dynamics and the design of risk‐management strategies. Current approaches to estimate flood hazards often sample only a relatively small subset of the known unknowns, for example, the uncertainties surrounding the model parameters. This approach neglects the impacts of key uncertainties on hazards and system dynamics. Here we mainstream a recently developed method for Bayesian inference to calibrate a computationally expensive distributed hydrologic model. We compare three different calibration approaches: (a) stepwise line search, (b) precalibration or screening, and (c) the Fast Model Calibrations (FaMoS) approach. FaMoS deploys a particle‐based approach that takes advantage of the massive parallelization afforded by modern high‐performance computing systems. We quantify how neglecting parametric uncertainty and data discrepancy can drastically underestimate extreme flood events and risks. Precalibration improves prediction skill score over a stepwise line search. The Bayesian calibration improves the uncertainty characterization of model parameters and flood risk projections.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

Development of High Altitude UAV Weather Radars for Hurricane Research

A proposed effort within NASA called (ASHE) over the past few years was aimed at studying the genesis of tropical disturbances off the east coast of Africa. This effort was focused on using an instrumented Global Hawk UAV with high altitude (%Ok ft) and long duration (30 h) capability. While the Global Hawk availability remains uncertain, development of two relevant instruments, a Doppler radar (URAD - UAV Radar) and a backscatter lidar (CPL-UAV - Cloud Physics Lidar), are in progress. The radar to be discussed here is based on two previous high-altitude, autonomously operating radars on the NASA ER-2 aircraft, the ER-2 Doppler Radar (EDOP) at X-band (9.6 GHz), and the Cloud Radar System (CRS) at W- band (94 GHz). The nadir-pointing EDOP and CRS radars profile vertical reflectivity structure and vertical Doppler winds in precipitation and clouds, respectively. EDOP has flown in all of the CAMEX flight series to study hurricanes over storms such as Hurricanes Bonnie, Humberto, Georges, Erin, and TS Chantal. These radars were developed at Goddard over the last decade and have been used for satellite algorithm development and validation (TRMM and Cloudsat), and for hurricane and convective storm research. We describe here the development of URAD that will measure wind and reflectivity in hurricanes and other weather systems from a top down, high-altitude view. URAD for the Global Hawk consists of two subsystems both of which are at X-band (9.3-9.6 GHz) and Doppler: a nadir fixed-beam Doppler radar for vertical motion and precipitation measurement, and a Conical scanning radar for horizontal winds in cloud and at the surface, and precipitation structure. These radars are being designed with size, weight, and power consumption suitable for the Global Hawk and other UAV's. The nadir radar uses a magnetron transmitter and the scanning radar uses a TWT transmitter. With conical scanning of the radar at a 35" incidence angle over an ocean surface in the absence of precipitation, the surface return over a single 360 degree sweep over -25 h-diameter region provides information on the surface wind speed and direction within the scan circle. In precipitation regions, the conical scan with appropriate mapping and analysis provides the 3D structure of reflectivity beneath the plane and the horizontal winds. The use of conical scanning in hurricanes has recently been demonstrated for measuring inner core winds with the IWRAP system flying on the NOAA P3's. In this presentation, we provide a description of the URAD system hardware, status, and future plans. In addition to URAD, NASA SBIR activity is supporting a Phase I study by Remote Sensing Solutions and the University of Massachusetts for a dual-frequency IWRAP for a high altitude UAV that utilizes solid state transmitters at 14 and 35 GHz, the same frequencies that are planned for the radar on the Global Precipitation System satellite. This will be discussed elsewhere at the meeting.

Heymsfield, Gerald↗
NASA NTRSDate not supplied

TPSAS-NF1676L-11455-DND

Adaptive control is well suited for rapidly changing, highly uncertain, and potentially unpredictable, flight dynamics characteristic of upset or damage induced on transport as well as high-performance aircraft. Some of the recent flight experiences of pilot-in-the-loop with an adaptive controller have exhibited unpredicted interactions. In retrospect, this is not surprising once it is realized that there are now two adaptive controllers interacting, the traditional software adaptive control system and the pilot. In order to capture the interaction between the adaptive controller and the pilot, research is being conducted to characterize the pilot as an adaptive controller, to define the interaction between pilots and adaptive controllers, and to then specify the behavior of the controller and the function allocation between the pilot and the adaptive controller during adaptation. This presentation will explain the methodology employed in the current research involving the use of system identification techniques to help characterize pilots and to characterize the interaction of an adaptive controller with a pilot. In particular, system identification appears to be a viable technique for modeling a pilot. Also touched upon in this presentation are possible avenues of augmenting the Hess simplified pursuit model and planned research to further characterize a pilot’s interaction with an adaptive controller.

Anna Trujillo↗
DOE OSTI2020

Commercial building loads providing ancillary services In PJM

The adoption of low carbon energy technologies such as variable renewable energy and electric vehicles, coupled with the efficacy of energy efficiency to reduce traditional base load has increased the uncertainty inherent in the net load shape. Handling this variability with slower, traditional resources leads to inefficient system dispatch, and in some cases may compromise reliability. Grid operators are looking to future energy technologies, such as automated demand response (DR), to provide capacity-based reliability services as the need for these services increase. While DR resources are expected to have the flexibility characteristics operators are looking for, demonstrations are necessary to build confidence in their capabilities. Additionally, building owners are uncertain of the monetary value and operational burden of providing these services. To address this, the present study demonstrates the ability of demand response resources providing two ancillary services in the PJM territory, synchronous reserve and regulation, using an OpenADR 2.0b signaling architecture. The loads under control include HVAC and lighting at a big box retail store and variable frequency fan loads. The study examines performance characteristics of the resource: the speed of response, communications latencies in the architecture, and accuracy of response. It also examines the frequency and duration of events and the value in the marketplace which can be used to examine if the opportunity is sufficient to entice building owners to participate.

MacDonald, Jason↗
DOE OSTI2022

Choices in land representation materially affect modeled biofuel carbon intensity estimates

Estimates of biofuel carbon intensity are uncertain and depend on modeled land use change (LUC) emissions. While analysts have focused on economic and agronomic assumptions affecting the quantity of land converted, researchers have paid less attention to how models classify land into broad categories and designate some categories as ineligible for LUC. To explore the effect of these land representation attributes, we use three versions of a global human and Earth systems model, GCAM, and compute the “carbon intensity of land-use change” (CI-LUC) from increased U.S. corn ethanol production. We consider uncertainty in model parameters along with the choice of land representation and find the latter is one of the most influential parameters on estimated CI-LUC. A version of the model that protects 90% of non-commercial land reduced estimated CI-LUC by an average of 32% across Monte Carlo trials compared to our baseline model. Another version that mimics the GTAP-BIO-ADV land representation, which protects all non-commercial land, reduced CI-LUC by an average of 19%. The results of this experiment suggest that analyses of LUC that exclude non-commercial land categories or assume more land is protected than empirically justified underestimate biofuel induced LUC GHG emissions.

09 BIOMASS FUELS↗