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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 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Modeling Key Predictors of Airport Runway Configurations Using Learning Algorithms

Advanced traffic flow management automation will need accurate predictions of airport runway configurations. Terminal area weather and traffic demand are generally considered to be the most significant factors in predicting runway configuration. Weather information is forecasted across multiple features, including wind direction, wind speed, gusts, cloud ceilings, visibility, temperature, and precipitation, among many others. We use machine learning techniques on historical weather and runway data to determine weather features that correlate well with runway configurations. We analyze the predictive capability of weather features using different learning models trained on data from four major U.S. airports: Atlanta (ATL), Washington – Dulles (IAD), New York – Kennedy (JFK), and San Francisco (SFO). Wind direction alone is strongly correlated with runway configurations above all other examined factors, as expected. This correlation is the most significant component of the ~80% prediction accuracy in selecting between the two most frequently used runway configurations. However, individual airports show variations on how well the runway configuration decisions correlate with wind direction. While wind direction was identified as the most significant indicator of configuration decisions in ATL, IAD, and JFK, it did not emerge as such at SFO. Traffic demand was not found to be a strong factor in predicting runway configurations at any of the airports analyzed. In rare instances, when high demand cannot be accommodated within the current configuration, temporary changes are likely to be attributable to demand. However, these occurrences are so limited in number that their overall effect is not sufficient to consider traffic demand as a major indicator of runway configuration at the airports analyzed.

Bilimoria, Karl D.↗
NASA NTRS2000

BOREAS AES MARSII Surface Meteorological Data

Canadian AES personnel collected several data sets related to surface and atmospheric meteorological conditions over the BOREAS region. This data set contains 15-minute meteorological data from six MARSII meteorology stations in the BOREAS region in Canada. Parameters include site, time, temperature, dewpoint, visibility, wind speed, wind gust, wind direction, two cloud groups, precipitation, and station pressure. Temporally, the data cover the period of May to September 1994. Geo-graphically, the stations are spread across the provinces of Saskatchewan and Manitoba. The data are provided in tabular ASCII files, and are classified as AFM-Staff data.

Atkinson, G. Barrie↗
NASA NTRS2010

Modified Adaptive Control for Region 3 Operation in the Presence of Wind Turbine Structural Modes

Many challenges exist for the operation of wind turbines in an efficient manner that is reliable and avoids component fatigue and failure. Turbines operate in highly turbulent environments resulting in aerodynamic loads that can easily excite turbine structural modes, possibly causing component fatigue and failure. Wind turbine manufacturers are highly motivated to reduce component fatigue and failure that can lead to loss of revenue due to turbine down time and maintenance costs. The trend in wind turbine design is toward larger, more flexible turbines that are ideally suited to adaptive control methods due to the complexity and expense required to create accurate models of their dynamic characteristics. In this paper, we design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed horizontal axis wind turbine operating in Region 3. The objective of the adaptive pitch controller is to regulate generator speed, accommodate wind gusts, and reduce the excitation of structural modes in the wind turbine. The control objective is accomplished by collectively pitching the turbine blades. The adaptive collective pitch controller for Region 3 was compared in simulations with a baseline classical Proportional Integrator (PI) collective pitch controller. The adaptive controller will demonstrate the ability to regulate generator speed in Region 3, while accommodating gusts, and reducing the excitation of certain structural modes in the wind turbine.

Frost, Susan Alane↗
NASA NTRS2020

Simulation and Modeling of Flow Generated by Gust Generator in a Wind Tunnel

A computational study of a gust field generated by a gust generator in a low-speed wind tunnel. The gust generator is designed for the University of Washington Aeronautical Laboratory (UWAL) Kirsten wind tunnel for a gust load alleviation (GLA) control experiment of a Common Research Model (CRM) flexible wing utilizing the Variable Camber Continuous Trailing Edge Flap (VCCTEF). The gust generator comprises four horizontal NACA 0015 gust generator vanes placed upstream of the test section. Computational fluid dynamics simulations using a two-dimensional (2D) Unsteady-Reynolds-Averaged-Navier-Stokes (URANS) with k-ω Shear Stress Transport (SST) turbulence model provide detailed time-resolved information about the generated flow by the gust generator under prescribed sinusoidal motion. The characteristics of the induced flow by the gust generator are analyzed. A gust propagation model of the gust field is investigated. An unsteady lift model is developed using a varying-fidelity approach which includes a 2D interference aerodynamic model of the combined gust generator-wing system. The computed integrated unsteady lift is compared to experimental data for validation of the unsteady lift model. Both the amplitude and transport delay are found to be accurately captured by the unsteady lift model.

Nhan, Nguyen↗
NASA NTRS1983

Natural environment considerations for Shuttle system development support

Natural environments were determined for each of the Shuttle mission phases as a guide to design and operational decisions. The phases were categorized as mission planning, prelaunch, launch/ascent, booster recovery, on-orbit, and descent and landing. The wind criteria included magnitude/height, gust factors, turbulence spectra, wind shear, and vector properties for all flight and ground phases. A maximum design risk of 1 percent was permitted for the windiest two weeks the Shuttle would have to stay on the pad at either KSC or Vandenberg. The ascent wind profile was determined with the Jimsphere Vector Wind profiles, which cover the wind speeds, shears, gusts, and turbulence up to 18 km altitude. The models used to define the environmental situations of the Shuttle comprised wind, thermodynamic, space, lightning, sea state, mission analysis, and ET ice data base formulations.

Vaughan, W. W.↗
NASA NTRS2010

Augmented Adaptive Control of a Wind Turbine in the Presence of Structural Modes

Wind turbines operate in highly turbulent environments resulting in aerodynamic loads that can easily excite turbine structural modes, potentially causing component fatigue and failure. Two key technology drivers for turbine manufacturers are increasing turbine up time and reducing maintenance costs. Since the trend in wind turbine design is towards larger, more flexible turbines with lower frequency structural modes, manufacturers will want to develop methods to operate in the presence of these modes. Accurate models of the dynamic characteristics of new wind turbines are often not available due to the complexity and expense of the modeling task, making wind turbines ideally suited to adaptive control. In this paper, we develop theory for adaptive control with rejection of disturbances in the presence of modes that inhibit the controller. We use this method to design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed wind turbine operating in Region 3. The objective of the adaptive pitch controller is to regulate generator speed, accommodate wind gusts, and reduce the interference of certain structural modes in feedback. The control objective is accomplished by collectively pitching the turbine blades. The adaptive pitch controller for Region 3 is compared in simulations with a baseline classical Proportional Integrator (PI) collective pitch controller.

Frost, Susan A.↗
NASA NTRS2010

A Comparison of Tropical Storm (TS) and Non-TS Gust Factors for Assessing Peak Wind Probabilities at the Eastern Range

Knowledge of peak wind speeds is important to the safety of personnel and flight hardware at Kennedy Space Center (KSC) and the Cape Canaveral Air Force Station (CCAFS), but they are more difficult to forecast than mean wind speeds. Development of a reliable model for the gust factor (GF) relating the peak to the mean wind speed motivated a previous study of GF in tropical storms. The same motivation inspired a climatological study of non-TS peak wind speed statistics without the use of GF. Both studies presented their respective statistics as functions of mean wind speed and height. The few comparisons of IS and non-TS GF in the literature suggest that the non-TS GF at a given height and mean wind speed are smaller than the corresponding TS GF. The investigation reported here converted the non-TS peak wind statistics mentioned above to the equivalent GF statistics and compared the results with the previous TS GF results. The advantage of this effort over all previously reported studies of its kind is that the TS and non-TS data are taken from the same towers in the same locations. That eliminates differing surface attributes, including roughness length and thermal properties, as a major source of variance in the comparison. The results are consistent with the literature, but include much more detailed, quantitative information on the nature of the relationship between TS and non-TS GF as a function of height and mean wind speed. In addition, the data suggest the possibility of providing an operational model for non-TS GF as a function of height and wind speed in a manner similar to the one previously developed for TS GF.

Merceret, Francis J.↗
NASA NTRS1978

An analysis of maximum horizontal wind speeds and associated parameters recorded at NASA's 150-Meter Ground Winds Tower facility at Kennedy Space Center, Florida

Continuous horizontal wind speed measurements were processed and classified as a function of tower level (10, 18, 60, and 150 meters) and period of reference day, month, season: winter (October through March) and summer (April through September), and annual. Tabulations were made of the daily maximum horizontal wind speed, time of ocurrence, and five associated parameters: mean horizontal wind speed, maximum vertical gusts (i.e., updraft and downdraft), and mean and instantaneous directions. Analyses using these data included means, extremes, standard deviations, and frequency distributions. Comparisons of intensity of maximum horizontal wind speeds determined in this year of data are made with maximum values recorded at Kennedy Space Center during another non-hurricane-occurrence year (1967) and with values during 1966 through 1972 when six hurricanes affected the area after the Ground Winds Tower facility became operational. Wind flow in the lowest 150 meters of the atmosphere was measured for the identification of hazards involved in wind shear encounter relative to ascent and descent of the space shuttle and conventional aircraft.

Alexander, M. B.↗
NASA NTRS1990

Automatic detection of low altitude wind shear due to gust fronts in the terminal Doppler weather radar operational demonstration

A gust front is the leading edge of the cold air outflow from a thunderstorm. Wind shears and turbulence along the gust front may produce potentially hazardous conditions for an aircraft on takeoff or landing such that runway operations are significantly impacted. The Federal Aviation Administration (FAA) has therefore determined that the detection of gust fronts in the terminal environment be an integral part of the Terminal Doppler Weather Radar (TDWR) system. Detection of these shears by the Gust Front Algorithm permits the generation of warnings that can be issued to pilots on approach and departure. In addition to the detection capability, the algorithm provides an estimate of the wind speed and direction following the gust front (termed wind shift) and the forecasted location of the gust front up to 20 minutes before it impacts terminal operations. This has shown utility as a runway management tool, alerting runway supervisors to approaching wind shifts and the possible need to change runway configurations. The formation and characteristics of gust fronts and their signatures in Doppler radar data are discussed. A brief description of the algorithm and its products for use by Air Traffic Control (ATC), along with an assessment of the algorithm's performance during the 1988 Operational Test and Evaluation, is presented.

Klingle-Wilson, Diana↗
NASA NTRS2008

Peak Wind Tool for General Forecasting

This report describes work done by the Applied Meteorology Unit (AMU) in predicting peak winds at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The 45th Weather Squadron requested the AMU develop a tool to help them forecast the speed and timing of the daily peak and average wind, from the surface to 300 ft on KSC/CCAFS during the cool season. Based on observations from the KSC/CCAFS wind tower network , Shuttle Landing Facility (SLF) surface observations, and CCAFS sounding s from the cool season months of October 2002 to February 2007, the AMU created mul tiple linear regression equations to predict the timing and speed of the daily peak wind speed, as well as the background average wind speed. Several possible predictors were evaluated, including persistence , the temperature inversion depth and strength, wind speed at the top of the inversion, wind gust factor (ratio of peak wind speed to average wind speed), synoptic weather pattern, occurrence of precipitation at the SLF, and strongest wind in the lowest 3000 ft, 4000 ft, or 5000 ft.

Barrett, Joe H., III↗
NASA NTRS1983

Significant events in low-level flow conditions hazardous to aircraft

Atmospheric parameters recorded during high surface winds are analyzed to determine magnitude, frequency, duration, and simultaneity of occurrence of low level flow conditions known to be hazardous to the ascent and descent of conventional aircraft and the space shuttle. Graphic and tabular presentations of mean and extreme values and simultaneous occurrences of turbulence (gustiness and a gust factor), wind shear (speed and direction), and vertical motion (updrafts and downdrafts), along with associated temperature inversions are included as function of tower height, layer and/or distance for six 5 sec intervals (one interval every 100 sec) of parameters sampled simultaneously at the rate of 10 speeds, directions and temperatures per second during an approximately 10 min period.

Alexander, M. B.↗
NASA NTRS1983

Low-level flow conditions hazardous to aircraft

Low level flow conditions known to be hazardous to aircraft during takeoff/climbout and approach/landing operations are turbulence, wind shear, and vertical motion. These conditions can and frequently do occur separately and in combinations. The identification and selection were completed of representative data cases to determine magnitude, frequency, duration, and simultaneity of occurrence of turbulence (gustiness and gust factor), wind shear (speed and direction), and vertical motion (updraft and downdraft), along with temperature inversions. New representations of temporal and spatial variations in the atmospheric boundary layer were developed. Efforts continued relative to low level flow conditions where published results imply strong vertical shear with virtually no horizontal shear and where order of magnitude analyses of the equations of motion for an aircraft illustrates that low values of horizontal shear (along the flight path) are much more hazardous than larger values of vertical wind shear (altitude).

Alexander, M. B.↗
NASA NTRS2001

Wind Advisory System

The present invention is a two-part wind advisory system comprising a ground station at an airfield and an airborne unit placed inside an aircraft. The ground station monitors wind conditions (wind speed, wind direction, and wind gust) at the airfield and transmits the wind conditions and an airfield ID to the airborne unit. The airborne unit identifies the airfield by comparing the received airfield ID with airfield IDs stored in a database. The airborne unit also calculates the headwind and crosswind for each runway in both directions at the airfield using the received wind conditions and runway information stored in the database. The airborne unit then determines a recommended runway for takeoff and landing operations of the aircraft based on th~ runway having the greatest headwind value and displays the airfield ID, wind conditions, and recommended runway to the pilot. Another embodiment of the present invention includes a wireless internet based airborne unit in which the airborne unit can receive the wind conditions from the ground station over the internet.

Curto, Paul A.↗
NASA NTRS2008

Forecasting Cool Season Daily Peak Winds at Kennedy Space Center and Cape Canaveral Air Force Station

The expected peak wind speed for the day is an important element in the daily 24-Hour and Weekly Planning Forecasts issued by the 45th Weather Squadron (45 WS) for planning operations at Kennedy Space Center (KSC) and Cape Canaveral Air Force Station (CCAFS). The morning outlook for peak speeds also begins the warning decision process for gusts ^ 35 kt, ^ 50 kt, and ^ 60 kt from the surface to 300 ft. The 45 WS forecasters have indicated that peak wind speeds are a challenging parameter to forecast during the cool season (October-April). The 45 WS requested that the Applied Meteorology Unit (AMU) develop a tool to help them forecast the speed and timing of the daily peak and average wind, from the surface to 300 ft on KSC/CCAFS during the cool season. The tool must only use data available by 1200 UTC to support the issue time of the Planning Forecasts. Based on observations from the KSC/CCAFS wind tower network, surface observations from the Shuttle Landing Facility (SLF), and CCAFS upper-air soundings from the cool season months of October 2002 to February 2007, the AMU created multiple linear regression equations to predict the timing and speed of the daily peak wind speed, as well as the background average wind speed. Several possible predictors were evaluated, including persistence, the temperature inversion depth, strength, and wind speed at the top of the inversion, wind gust factor (ratio of peak wind speed to average wind speed), synoptic weather pattern, occurrence of precipitation at the SLF, and strongest wind in the lowest 3000 ft, 4000 ft, or 5000 ft. Six synoptic patterns were identified: 1) surface high near or over FL, 2) surface high north or east of FL, 3) surface high south or west of FL, 4) surface front approaching FL, 5) surface front across central FL, and 6) surface front across south FL. The following six predictors were selected: 1) inversion depth, 2) inversion strength, 3) wind gust factor, 4) synoptic weather pattern, 5) occurrence of precipitation at the SLF, and 6) strongest wind in the lowest 3000 ft. The forecast tool was developed as a graphical user interface with Microsoft Excel to help the forecaster enter the variables, and run the appropriate regression equations. Based on the forecaster's input and regression equations, a forecast of the day's peak and average wind is generated and displayed. The application also outputs the probability that the peak wind speed will be ^ 35 kt, 50 kt, and 60 kt.

Barrett, Joe, III↗
NASA NTRS1993

The gust-front detection and wind-shift algorithms for the Terminal Doppler Weather Radar system

The Federal Aviation Administration's (FAA) Terminal Doppler Weather Radar (TDWR) system was primarily designed to address the operational needs of pilots in the avoidance of low-altitude wind shears upon takeoff and landing at airports. One of the primary methods of wind-shear detection for the TDWR system is the gust-front detection algorithm. The algorithm is designed to detect gust fronts that produce a wind-shear hazard and/or sustained wind shifts. It serves the hazard warning function by providing an estimate of the wind-speed gain for aircraft penetrating the gust front. The gust-front detection and wind-shift algorithms together serve a planning function by providing forecasted gust-front locations and estimates of the horizontal wind vector behind the front, respectively. This information is used by air traffic managers to determine arrival and departure runway configurations and aircraft movements to minimize the impact of wind shifts on airport capacity. This paper describes the gust-front detection and wind-shift algorithms to be fielded in the initial TDWR systems. Results of a quantitative performance evaluation using Doppler radar data collected during TDWR operational demonstrations at the Denver, Kansas City, and Orlando airports are presented. The algorithms were found to be operationally useful by the FAA airport controllers and supervisors.

Hermes, Laurie G.↗
NASA NTRS2009

Gaussian and Lognormal Models of Hurricane Gust Factors

A document describes a tool that predicts the likelihood of land-falling tropical storms and hurricanes exceeding specified peak speeds, given the mean wind speed at various heights of up to 500 feet (150 meters) above ground level. Empirical models to calculate mean and standard deviation of the gust factor as a function of height and mean wind speed were developed in Excel based on data from previous hurricanes. Separate models were developed for Gaussian and offset lognormal distributions for the gust factor. Rather than forecasting a single, specific peak wind speed, this tool provides a probability of exceeding a specified value. This probability is provided as a function of height, allowing it to be applied at a height appropriate for tall structures. The user inputs the mean wind speed, height, and operational threshold. The tool produces the probability from each model that the given threshold will be exceeded. This application does have its limits. They were tested only in tropical storm conditions associated with the periphery of hurricanes. Winds of similar speed produced by non-tropical system may have different turbulence dynamics and stability, which may change those winds statistical characteristics. These models were developed along the Central Florida seacoast, and their results may not accurately extrapolate to inland areas, or even to coastal sites that are different from those used to build the models. Although this tool cannot be generalized for use in different environments, its methodology could be applied to those locations to develop a similar tool tuned to local conditions.

Merceret, Frank↗
NASA NTRS2010

A Comparison of Tropical Storm (TS) and Non-TS Gust Factors for Assessing Peak Wind Probabilities at the Eastern Range

Peak wind speed is an important forecast element to ensure the safety of personnel and flight hardware at Kennedy Space Center (KSC) and the Cape Canaveral Air Force Station (CCAFS) in East-Central Florida. The 45th Weather Squadron (45 WS), the organization that issues forecasts for the KSC/CCAFS area, finds that peak winds are more difficult to forecast than mean winds. This difficulty motivated the 45 WS to request two independent studies. The first (Merceret 2009) was the development of a reliable model for gust factors (GF) relating the peak to the mean wind speed in tropical storms (TS). The second (Lambert et al. 2008) was a climatological study of non-TS cool season (October-April) mean and peak wind speeds by the Applied Meteorology Unit (AMU; Bauman et al. 2004) without the use of GF. Both studies presented their statistics as functions of mean wind speed and height. Most of the few comparisons of TS and non-TS GF in the literature suggest that non-TS GF at a given height and mean wind speed are smaller than the corresponding TS GF. The investigation reported here converted the non-TS peak wind statistics calculated by the AMU to the equivalent GF statistics and compared them with the previous TS GF results. The advantage of this effort over all previously reported studies of its kind is that the TS and non-TS data were taken from the same towers in the same locations. This eliminates differing surface attributes, including roughness length and thermal properties, as a major source of variance in the comparison. The goal of this study is two-fold: to determine the relationship between the non-TS and TS GF and their standard deviations (GFSD) and to determine if models similar to those developed for TS data in Merceret (2009) could be developed for the non-TS environment. The results are consistent with the literature, but include much more detailed, quantitative information on the nature of the relationship between TS and non-TS GF and GFSD as a function of height and mean wind speed.

Merceret, Francis J.↗