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Results for “driver model”

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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

A data collection scheme for identification of parameters in a driver model

A high gain steering controller to compensate for limitations in a handicapped driver's range of motion is employed when adapting vehicle to his use. A driver/vehicle system can become unstable as vehicle speed is increased, therefore it is desirable to use a computer simulation of the driver/vehicle combination as a design tool to investigate the system response prior to construction of a controller and road testing. Unknown driver parameters must be identified prior to use of the model for system analysis. A means to collect the data necessary for identification of these driver model parameters without extensive instrumentation of a vehicle to measure and record vehicle states is addressed. Initial tests of the procedure identified all of the driver parameters with errors of 6% or less.

Mooring, B. W.↗
NASA NTRS1996

Modeling Global Biogenic Emission of Isoprene: Exploration of Model Drivers

Vegetation provides the major source of isoprene emission to the atmosphere. We present a modeling approach to estimate global biogenic isoprene emission. The isoprene flux model is linked to a process-based computer simulation model of biogenic trace-gas fluxes that operates on scales that link regional and global data sets and ecosystem nutrient transformations Isoprene emission estimates are determined from estimates of ecosystem specific biomass, emission factors, and algorithms based on light and temperature. Our approach differs from an existing modeling framework by including the process-based global model for terrestrial ecosystem production, satellite derived ecosystem classification, and isoprene emission measurements from a tropical deciduous forest. We explore the sensitivity of model estimates to input parameters. The resulting emission products from the global 1 degree x 1 degree coverage provided by the satellite datasets and the process model allow flux estimations across large spatial scales and enable direct linkage to atmospheric models of trace-gas transport and transformation.

Alexander, Susan E.↗
NASA NTRS1975

Computer modeling of arc drivers

Model is generated from description of element connections involved in complete arc network, list of corresponding circuit element values, description of circuit current excitation, and list of out-puts desired. Waveform of current is determined by structure of capacitor storage system, driver geometry, and preset driver conditions.

Dannenberg, R. E.↗
NASA NTRS2022

Scientific Data From Precipitation Driver Response Model Intercomparison Project

This data descriptor reports the main scientific values from General Circulation Models (GCMs) in the Precipitation Driver and Response Model Intercomparison Project (PDRMIP). The purpose of the GCM simulations has been to enhance the scientific understanding of how changes in greenhouse gases, aerosols, and incoming solar radiation perturb the Earth’s radiation balance and its climate response in terms of changes in temperature and precipitation. Here we provide global and annual mean results for a large set of coupled atmospheric-ocean GCM simulations and a description of how to easily extract files from the dataset. The simulations consist of single idealized perturbations to the climate system and have been shown to achieve important insight in complex climate simulations. We therefore expect this data set to be valuable and highly used to understand simulations from complex GCMs and Earth System Models for various phases of the Coupled Model Intercomparison Project

Precipitation Driver Response Model Intercompariso↗
NASA NTRS1977

A control theoretic model of driver steering behavior

A quantitative description of driver steering behavior such as a mathematical model is presented. The steering task is divided into two levels: (1) the guidance level involving the perception of the instantaneous and future course of the forcing function provided by the forward view of the road, and the response to it in an anticipatory open-loop control mode; (2) the stabilization level whereby any occuring deviations from the forcing function are compensated for in a closed-loop control mode. This concept of the duality of the driver's steering activity led to a newly developed two-level model of driver steering behavior. Its parameters are identified on the basis of data measured in driving simulator experiments. The parameter estimates of both levels of the model show significant dependence on the experimental situation which can be characterized by variables such as vehicle speed and desired path curvature.

Donges, E.↗
NASA NTRS1991

Modeling preparation costs for space missions by using major cost drivers

A model is suggested for making long range planning cost estimates for Deep Space Network (DSN) support of future space missions. The model is a function of major mission cost drivers, such as maintenance and operations, downlink frequency upgrade, uplink frequency upgrade, telemetry upgrade, antenna gain/noise temperature, radiometric accuracy upgrade, radio science upgrade, and very long baseline interferometry. The model is derived from actual cost data from three space missions: Voyager (Uranus), Voyager (Neptune), and Magellan. The model allows one to estimate the total cost and the cost over time of a similar future space mission. The model was back tested against the three projects and gave cost estimates that range from 17 pct. below to 19 pct. above actual mission preparation costs. The model was also compared with two other independent projects: Mariner Jupiter/Saturn (MJS later became Voyager) and Viking. The model gave total preparation cost estimates that range from 15 pct. above to 4 pct. below actual total preparation costs for MJS and Viking, respectively.

Sherif, J. S.↗
NASA NTRS1976

A heuristic finite-state model of the human driver in a car-following situation

An approach to modeling human driver behavior in single-lane car following which is based on a finite-state decision structure is considered. The specific strategy at each point in the decision tree was obtained from observations of typical driver behavior. The synthesis of the decision logic is based on position and velocity thresholds and four states defined by regions in the phase plane. The performance of the resulting assumed intuitively logical model was compared with actual freeway data. The match of the model to the data was optimized by adapting the model parameters using a modified PARTAN algorithm. The results indicate that the heuristic model behavior matches actual car-following performance better during deceleration and constant velocity phases than during acceleration periods.

Burnham, G. O.↗
NASA NTRSDate not supplied

Process Drivers, Inter-model Spread, and a Path Forward: What Do We Know About Arctic Amplification?

Over the recent decades, rapid changes have been observed in the Arctic resulting from enhanced surface warming in the Arctic relative to the rest of the globe, a phenomenon called Arctic Amplification. While surface-based amplification of Arctic warming in response to increased CO2 has been established. The driving mechanisms, relevant processes, and the relative roles of local and remote mechanisms to Arctic Amplification remain unclear. Research over the last decade has made it clear that coupling between the atmosphere, sea ice, and ocean play a key role in Arctic Amplification. This presentation summarizes recent research on the fundamental role that atmosphere-sea ice-ocean interactions and energy exchanges play in driving Arctic Amplification, how these interactions manifest as radiative climate feedbacks, and how these processes influence the differences in the projected Arctic climate change across CMIP5 and 6. We hypothesize that models that simulate larger warming do so by generating a larger local atmospheric circulation response that more effectively redistributes energy drawn from the ocean in sea ice retreat regions Arctic-wide and contributing to a larger increase in downwelling long wave radiation. This process is also fundamentally tied to the Arctic lapse rate feedback.

Patrick Charles Taylor↗
NASA NTRSDate not supplied

Process drivers, inter-model spread, and a path forward: What do we know about Arctic Amplification?

Over the recent decades, rapid changes have been observed in the Arctic resulting from enhanced surface warming in the Arctic relative to the rest of the globe, a phenomenon called Arctic Amplification. While surface-based amplification of Arctic warming in response to increased CO2 has been established. The driving mechanisms, relevant processes, and the relative roles of local and remote mechanisms to Arctic Amplification remain unclear. Research over the last decade has made it clear that coupling between the atmosphere, sea ice, and ocean play a key role in Arctic Amplification. This presentation summarizes recent research on the fundamental role that atmosphere-sea ice-ocean interactions and energy exchanges play in driving Arctic Amplification, how these interactions manifest as radiative climate feedbacks, and how these processes influence the differences in the projected Arctic climate change across CMIP5 and 6. We hypothesize that models that simulate larger warming do so by generating a larger local atmospheric circulation response that more effectively redistributes energy drawn from the ocean in sea ice retreat regions Arctic-wide and contributing to a larger increase in downwelling long wave radiation. This process is also fundamentally tied to the Arctic lapse rate feedback.

Arctic amplification↗
NASA NTRSDate not supplied

Process drivers, inter-model spread, and a path forward: What do we know about Arctic Amplification?

Over the recent decades, rapid changes have been observed in the Arctic resulting from enhanced surface warming in the Arctic relative to the rest of the globe, a phenomenon called Arctic Amplification. While surface-based amplification of Arctic warming in response to increased CO2 has been established. The driving mechanisms, relevant processes, and the relative roles of local and remote mechanisms to Arctic Amplification remain unclear. Research over the last decade has made it clear that coupling between the atmosphere, sea ice, and ocean play a key role in Arctic Amplification. This presentation summarizes recent research on the fundamental role that atmosphere-sea ice-ocean interactions and energy exchanges play in driving Arctic Amplification, how these interactions manifest as radiative climate feedbacks, and how these processes influence the differences in the projected Arctic climate change across CMIP5 and 6. We hypothesize that models that simulate larger warming do so by generating a larger local atmospheric circulation response that more effectively redistributes energy drawn from the ocean in sea ice retreat regions Arctic-wide and contributing to a larger increase in downwelling long wave radiation. This process is also fundamentally tied to the Arctic lapse rate feedback.

Patrick C. Taylor↗
NASA NTRS1978

A decision model applied to alcohol effects on driver signal light behavior

A decision model including perceptual noise or inconsistency is developed from expected value theory to explain driver stop and go decisions at signaled intersections. The model is applied to behavior in a car simulation and instrumented vehicle. Objective and subjective changes in driver decision making were measured with changes in blood alcohol concentration (BAC). Treatment levels averaged 0.00, 0.10 and 0.14 BAC for a total of 26 male subjects. Data were taken for drivers approaching signal lights at three timing configurations. The correlation between model predictions and behavior was highly significant. In contrast to previous research, analysis indicates that increased BAC results in increased perceptual inconsistency, which is the primary cause of increased risk taking at low probability of success signal lights.

Schwartz, S. H.↗
NASA NTRSDate not supplied

A Systematic Framework for Investigating Climate Impact-Drivers in NASA GISS ModelE Configurations: Towards Improving ESM Development for Impact Applications

Earth System Model (ESM) development benefits from attention to the downstream applications for nature and society. The evaluation of ESMs often focuses on a limited set of climatic impact-drivers (CIDs)1 and numerous large-scale parameters that are not directly relevant for impact analysis. To address this limitation, we propose a comprehensive framework for impact-relevant model version comparison. This framework explores both the intended and unintended consequences of shifts in model components, parameters, and resolutions, emphasizing the perspectives of the climate impacts community. We have selected a core set of CIDs as a basis for comparing model versions.

earth system models↗
NASA NTRS2019

Arctic Amplification Response to Individual Climate Drivers

The Arctic is experiencing rapid climate change in response to changes in greenhouse gases, aerosols and other climate drivers. Emission changes in general, as well as geographical shifts in emissions and transport pathways of shortlived climate forcers, make it necessary to understand the influence of each climate driver on the Arctic. In the Precipitation Driver Response Model Intercomparison Project, ten global climate models perturbed five different climate drivers separately (CO2, CH4, the solar constant, BC and SO4). We show that the annual mean Arctic amplification (defined as the ratio between Arctic and the global mean temperature change) at the surface is similar between climate drivers, ranging from 1.9 (± an intermodel standard deviation of 0.4) for the solar to 2.3 (± 0.6) for the SO4 perturbations, with minimum amplification in the summer for all drivers. The vertical and seasonal temperature response patterns indicate that the Arctic is warmed through similar mechanisms for all climate drivers except BC. For all drivers, the precipitation change per degree global temperature change is positive in the Arctic, with a seasonality following that of the Arctic amplification. We find indications that SO4 perturbations produce a slightly stronger precipitation response than the other drivers, particularly compared to CO2.

greenhouse gases↗
NASA NTRS1982

Features of a reattaching turbulent shear layer subject to an adverse pressure gradient

Experimental data have been obtained in an incompressible turbulent flow over a rearward-facing step with superimposed adverse pressure gradient. Mean velocities, Reynolds stresses and triple-products measured by a laser Doppler velocimeter are presented for two cases of adverse pressure gradient. Mixing lengths, eddy viscosities, production, convection, turbulent diffusion, and dissipation terms are extracted from the data. These data are compared with various mixing length and eddy-viscosity turbulence models. Numerical calculations incorporating the k-epsilon and the algebraic-stress turbulence models are compared with the data. When determining quantities of engineering interest, the modified algebraic-stress model (ASM) is a significant improvement over the unmodified ASM and the unmodified k-epsilon model

Driver, D. M.↗
NASA NTRS2021

Maximum entropy modeling to identify physical drivers of shallow snowpack heterogeneity using unpiloted aerial system (UAS) lidar

Understanding the spatial variability of the snowpack is valuable for hydrologists and ecologists seeking to predict hydrological processes in a cold region. Snow distribution is a function of interactions among static variables, such as terrain, vegetation, and soil properties, and dynamic meteorological variables, such as solar radiation, wind speed and direction, and soil moisture. However, identifying the dominant physical drivers responsible for spatial patterns of the snowpack, particularly for ephemeral, shallow snowpacks, has been challenging due to the lack of the high-resolution snowpack and physical variables with high vertical accuracy as well as inherent limitations in traditional approaches. This study uses an Unpiloted Aerial System (UAS) lidar-based snow depth and static variables (1-m spatial resolution) to analyze field-scale spatial structures of snow depth and apply the Maximum Entropy (MaxEnt) model to identify primary controls over open terrain and forests at the University of New Hampshire Thompson Farm Research Observatory, New Hampshire, United States. We found that, among nine topographic and soil variables, plant functional type and terrain roughness contribute up to 80% and 76% of relative importance in the MaxEnt framework to predict locations of deeper or shallower snowpacks, respectively, across a mixed temperate forested and field landscape. Soil variables, such as organic matter and saturated hydraulic conductivity, were also important controls (up to 70% and 81%) on snow depth spatial variations for both open and forested landscapes suggesting spatial variations in soil variables under snow can control thermal transfer among soil, snowpack, and surface-atmosphere. This work contributes to improving land surface and snow models by informing parameterization of the sub-grid scale snow depths, down-scaling remotely sensed snow products, and understanding field scale snow states.

Eunsang Cho↗
NASA NTRS2022

Anthropogenic Sulfate Aerosol Pollution in South and East Asia Induces Increased Summer Precipitation Over Arid Central Asia

Precipitation has increased across the arid Central Asia region over recent decades. However, the underlying mechanisms of this trend are poorly understood. Here, we analyze multi-model simulations from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP) to investigate potential drivers of the observed precipitation trend. We find that anthropogenic sulfate aerosols over remote polluted regions in South and East Asia lead to increased summer precipitation, especially convective and extreme precipitation, in arid Central Asia. Elevated concentrations of sulfate aerosols over remote polluted Asia cause an equatorward shift of the Asian Westerly Jet Stream through a fast response to cooling of the local atmosphere at mid-latitudes. This shift favours moisture supply from low-latitudes and moisture flux convergence over arid Central Asia, which is confirmed by a moisture budget analysis. High levels of absorbing black carbon lead to opposing changes in the Asian Westerly Jet Stream and reduced local precipitation, which can mask the impact of sulfate aerosols. This teleconnection between arid Central Asia precipitation and anthropogenic aerosols in remote Asian polluted regions highlights long-range impacts of anthropogenic aerosols on atmospheric circulations and the hydrological cycle.

Atmospheric dynamics↗
NASA NTRS1981

Stability analysis of automobile driver steering control

In steering an automobile, the driver must basically control the direction of the car's trajectory (heading angle) and the lateral deviation of the car relative to a delineated pathway. A previously published linear control model of driver steering behavior which is analyzed from a stability point of view is considered. A simple approximate expression for a stability parameter, phase margin, is derived in terms of various driver and vehicle control parameters, and boundaries for stability are discussed. A field test study is reviewed that includes the measurement of driver steering control parameters. Phase margins derived for a range of vehicle characteristics are found to be generally consistent with known adaptive properties of the human operator. The implications of these results are discussed in terms of driver adaptive behavior.

Allen, R. W.↗
NASA NTRS2015

Ringberg15: Earth's Climate Sensitivities

To assess gaps in understanding of Earth's climate sensitivities a workshop was organised under the auspices of the WCRP (World Climate Research Programme) Grand Science Challenge on Clouds, Circulation and Climate Sensitivity (Ringberg15). The workshop took place in March 2015 and gathered together over thirty experts from around the world for one week. Attendees each gave short presentations and participated in moderated discussions of specific questions related to understanding Earth's climate sensitivities. Most of the time was focused on understanding of the equilibrium climate sensitivity, defined as the equilibrium near-surface warming associated with a doubling of atmospheric carbon dioxide. The workshop produced nine recommendations, many of them focusing on specific research avenues that could be exploited to advance understanding of climate sensitivity. Many of these dealt, in one fashion or another, with the need to more sharply focus research on identifying and testing story lines for a high (larger than 4 degrees Kelvin) or low (less than 2 degrees Kelvin) equilibrium climate sensitivity. Additionally, a subset of model intercomparison projects (CFMIP (Cloud Feedback Model Intercomparison Project), PMIP (Palaeoclimate Modelling Intercomparison Project), PDRMIP (Precipitation Driver and Response Model Intercomparison Project), RFMIP (Radiative Forcing Model Intercomparison Project) and VolMIP (Volcanic Forcings Model Intercomparison Project)) that have been proposed for inclusion within CMIP were identified as being central to resolving important issues raised at the workshop; for this reason modelling groups were strongly encouraged to participate in these projects. Finally the workshop participants encouraged the WCRP to initiate and support an assessment process lead by the Grand Science Challenge on Clouds, Circulation and Climate Sensitivity on the topic of Earth's Climate Sensitivities, culminating in a report that will be published in 2019, forty years after the seminal report by Charney and co-authors.

Sensitivity↗