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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 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

A Wind-Tunnel Parametric Investigation of Tiltrotor Whirl-Flutter Stability Boundaries

A wind-tunnel investigation of tiltrotor whirl-flutter stability boundaries has been conducted on a 1/5-size semispan tiltrotor model known as the Wing and Rotor Aeroelastic Test System (WRATS) in the NASA-Langley Transonic Dynamics Tunnel as part of a joint NASA/Army/Bell Helicopter Textron, Inc. (BHTI) research program. The model was first developed by BHTI as part of the JVX (V-22) research and development program in the 1980's and was recently modified to incorporate a hydraulically-actuated swashplate control system for use in active controls research. The modifications have changed the model's pylon mass properties sufficiently to warrant testing to re-establish its baseline stability boundaries. A parametric investigation of the effect of rotor design variables on stability was also conducted. The model was tested in both the on-downstop and off-downstop configurations, at cruise flight and hover rotor rotational speeds, and in both air and heavy gas (R-134a) test mediums. Heavy gas testing was conducted to quantify Mach number compressibility effects on tiltrotor stability. Experimental baseline stability boundaries in air are presented with comparisons to results from parametric variations of rotor pitch-flap coupling and control system stiffness. Increasing the rotor pitch-flap coupling (delta(sub 3) more negative) was found to have a destabilizing effect on stability, while a reduction in control system stiffness was found to have little effect on whirl-flutter stability. Results indicate that testing in R-134a, and thus matching full-scale tip Mach number, has a destabilizing effect, which demonstrates that whirl-flutter stability boundaries in air are unconservative.

Piatak, David J.↗
DOE OSTI2020

University of Kentucky measurements of wind, temperature, pressure and humidity in support of LAPSE-RATE using multisite fixed-wing and rotorcraft unmanned aerial systems

In July 2018, unmanned aerial systems (UASs) were deployed to measure the properties of the lower atmosphere within the San Luis Valley, an elevated valley in Colorado, USA, as part of the Lower Atmospheric Profiling Studies at Elevation – a Remotely-piloted Aircraft Team Experiment (LAPSE-RATE). Measurement objectives included detailing boundary layer transition, canyon cold-air drainage and convection initiation within the valley. Details of the contribution to LAPSE-RATE made by the University of Kentucky are provided here, which include measurements by seven different fixed-wing and rotorcraft UASs totaling over 178 flights with validated data. The data from these coordinated UAS flights consist of thermodynamic and kinematic variables (air temperature, humidity, pressure, wind speed and direction) and include vertical profiles up to 900 m above the ground level and horizontal transects up to 1500 m in length. These measurements have been quality controlled and are openly available in the Zenodo LAPSE-RATE community data repository (https://zenodo.org/communities/lapse-rate/, last access: 23 July 2020), with the University of Kentucky data available at https://doi.org/10.5281/zenodo.3701845 (Bailey et al., 2020).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1987

A flight investigation of helicopter low-speed response requirements

A flight experiment has been conducted using the Canadian National Aeronautical Establishment's variable-stability airborne simulator to define the dynamic response requirements for operations at hover and low speeds. Fourteen Attitude Command/Attitude Hold, Rate, and Rate Command/Attitude Hold configurations were evaluated by six pilots using both conventional controls and a four-axis integrated sidestick over a low-speed course consisting of precision hover, landing, sidestep, and dash/quickstop tasks. The results indicate that with conventional controls all three response-types were acceptable as long as their response bandwidth was sufficiently high, and higher bandwidths were required in roll than in pitch. With the four-axis sidestick, there was a preference for the Rate systems. The range of acceptable bandwidths was lower, and the spread in pilot ratings smaller, than were found in a similar ground-based simulation.

Mitchell, David G.↗
NASA NTRSDate not supplied

Predicting Airport Runway Configurations for Decision-Support Using Supervised Learning

One of the most challenging tasks for air traffic controllers is runway configuration management (RCM). It deals with the optimal selection of runways to operate on (for arrivals and departures) based on current and forecast of traffic, surface wind speed, wind direction, other environmental variables, noise constraints, and several other airport-specific factors. In this paper, a methodology using supervised learning is developed to build a predictive model for RCM decision-support from large volumes of historical data. Data from two full years (2018 and 2019) related to current and forecast weather, demand/capacity, etc. is collected, analyzed, and fused together. A variety of supervised learning algorithms are tested for predicting runway configuration and hyperparameter tuning is carried out to select the best performing model. The validation process involves two airports of low (Charlotte Douglas International Airport, CLT) and high (Denver International Airport, DEN) complexity of configuration decision-making. The results show significant promise for the two airports with test accuracy of 93% (CLT) and 73% (DEN). The methodology is scalable and generalizable to other airports across the U.S. National Airspace System.

air traffic management↗
NASA NTRSDate not supplied

Predicting Airport Runway Configuration for Decision-Support Using Supervised Learning

One of the most challenging tasks for air traffic controllers is runway configuration management (RCM). It deals with the optimal selection of runways to operate on (for arrivals and departures) based on current and forecast of traffic, surface wind speed, wind direction, other environmental variables, noise constraints, and several other airport-specific factors. In this paper, a methodology using supervised learning is developed to build a predictive model for RCM decision-support from large volumes of historical data. Data from two full years (2018 and 2019) related to current and forecast weather, demand/capacity, etc. is collected, analyzed, and fused together. A variety of supervised learning algorithms are tested for predicting runway configuration and hyperparameter tuning is carried out to select the best performing model. The validation process involves two airports of low (Charlotte Douglas International Airport, CLT) and high (Denver International Airport, DEN) complexity of configuration decision-making. The results show significant promise for the two airports with test accuracy of 93% (CLT) and 73% (DEN). The methodology is scalable and generalizable to other airports across the U.S. National Airspace System.

air traffic management↗
NASA NTRSDate not supplied

Coaxial Rotor CFD Validation and ML Surrogate Model Generation

A fixed-pitch speed-controlled coaxial rotor system was tested in the NASA Langley Transonic Dynamics Tunnel in September 2022. The rotors have a diameter of 1.35 meters and an inter-rotor spacing of 25% of the diameter. Though this test was focused on the NASA New Frontiers Dragonfly mission, the resulting dataset is relevant to a wide array of applications of multirotor vehicles, especially those using fixed-pitch variable-speed rotors. Most notably beyond Dragonfly, perhaps, is the application of coaxial rotor pair configurations for eVTOL and Urban Air Mobility (UAM) aircraft. This work provides a thorough CFD validation study quantifying coaxial rotor performance estimation with accuracy on order 5-10% using an efficient hybrid BEMT-URANS flow solver over a wide range of operating conditions. This accuracy was achieved using novel approaches for the construction of both the C81 airfoil performance lookup tables and the BEMT rotor model. These novel approaches are combined with advanced scripting to further accelerate the commercial off-the-shelf CFD solver on GPU accelerated machines. Finally, the development of machine learning surrogate models is presented to produce highly efficient and accurate rotor performance predictions for fixed-pitch variable-speed multirotor aircraft over the complete flight regime including scout, cruise, climb, descent, as well as limiting cases of vortex-ring and windmill-brake states.

Coaxial↗
NASA NTRS2002

Variability of Winter Air Temperature in Mid-Latitude Europe

The aim of this paper is to report extreme winter/early-spring air temperature (hereinafter temperature) anomalies in mid-latitude Europe, and to discuss the underlying forcing to these interannual fluctuations. Warm advection from the North Atlantic in late winter controls the surface-air temperature, as indicated by the substantial correlation between the speed of the surface southwesterlies over the eastern North Atlantic (quantified by a specific Index Ina) and the 2-meter level air temperatures (hereinafter Ts) over Europe, 45-60 deg N, in winter. In mid-March and subsequently, the correlation drops drastically (quite often it is negative). This change in the relationship between Ts and Ina marks a transition in the control of the surface-air temperature: absorption of insolation replaces the warm advection as the dominant control. This forcing by maritime-air advection in winter was demonstrated in a previous publication, and is re-examined here in conjunction with extreme fluctuations of temperatures in Europe. We analyze here the interannual variability at its extreme by comparing warm-winter/early-spring of 1989/90 with the opposite scenario in 1995/96. For these two December-to-March periods the differences in the monthly mean temperature in Warsaw and Torun, Poland, range above 10 C. Short-term (shorter than a month) fluctuations of the temperature are likewise very strong. We conduct pentad-by-pentad analysis of the surface-maximum air temperature (hereinafter Tmax), in a selected location, examining the dependence on Ina. The increased cloudiness and higher amounts of total precipitable water, corollary effects to the warm low-level advection. in the 1989/90 winter, enhance the positive temperature anomalies. The analysis of the ocean surface winds is based on the Special Sensor Microwave/Imager (SSM/I) dataset; ascent rates, and over land wind data are from the European Centre for Medium-Range Weather Forecasts (ECMWF); maps of 2-m temperature, cloud cover and precipitable water are from the National Centers for Environmental Prediction (NCEP) Reanalysis.

Otterman, J.↗
DOE OSTI2020

A Minimum Principle-Based Algorithm for Energy-Efficient Eco-Driving of Electric Vehicles in Various Traffic and Road Conditions

Our report presents an optimization algorithm for energy-efficient driving of electric vehicles. The algorithm is based on Pontryagin’s Minimum Principle by considering the driving mission as an optimal control problem. On a planned route, diverse application cases may occur due to various physical traits such as powertrain (e.g., switching between motor and generator operation), environmental variations (e.g., terrain grade change), traffic laws (e.g., speed limits), and safety concerns (e.g., headway to the leading vehicle). The proposed algorithm handles these real-world challenges by considering the perturbation to the system dynamics and the constraints to the control and state variables.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1992

Aeroservoelasticity in HiSAIR

The High Speed Airframe Integration Research project is a multidisciplinary effort to bridge disciplinary boundaries in the analysis and design of aircraft. Aeroservoelasticity provides calculations of various critical speeds (such as flutter, divergence, and control reversal), of hump mode dampings, and of the effects of flexibility on vehicle stability and control derivatives. For design iterations, sensitivity derivatives of these characteristics with respect to structural design variables are also calculated. For executing this function, a set of computer programs was developed or adapted to perform routine calculations of basic aeroelastic characteristics. This set of programs, named the Aeroelastic Vehicle Analysis system, has also become a useful tool within the Aeroservoelasticity Branch of NASA's Langley Research Center.

Zeiler, Thomas A.↗
NASA NTRS1981

Control system development for an organic Rankine cycle engine

The development of a control logic to govern the toluene throttle valve and verify the stability of the speed control approach for multiple engines connected to a 1 MWe point focus solar generator installation for distributed applications is presented. The toluene is is pumped by booster and main feed pumps through a regenerator to the parabolic focus receiver, with the flow rate controlled by a valve to remain at critical level of 4.1 MPa. The valve changes the inlet pressure at the turbine nozzle block. Each concentrator would produce 76 kWth and 20 kWe. Dynamic variables in the logic account for insolation variation, fluid temperature, ac grid voltage, the thermal dynamics of the regenerator, and variations in the head supplied by the feed pump. Separate analyses are presented for the turbine shaft speed and toluene loop dynamics. The resulting logic is considered preliminary and suitable only in full insolation conditions. Extension of the model to nonlinear perturbations is indicated.

Bergthold, F. M., Jr.↗
NASA NTRS1989

Investigation of an excited jet diffusion flame at elevated pressure

Experiments are carried out for studying the relationship between flow structure, flow excitation, and the reaction process in the near field of a low-speed coflowing jet diffusion flame. The effect of axial forcing and increasing pressure on the structure and controllability of the flame is studied to elucidate some of the underlying control mechanisms. The experiments are conducted in a variable-pressure flow facility permitting the study of reacting flows in the 10-1000 kPa (0.1-10 atm) pressure range. The flame is excited by a small-amplitude periodic fluctuation added to the central fuel jet exit velocity. Among the varied excitation frequencies employed, a narrow band is found in which several of the flow instabilities seem to be in coincidence, causing periodic breakup of the flame into a series of distinct eddies. This is called the strongly-coupled state. Effects of excitation frequencies at and above the strongly-coupled range are presented.

Strawa, Anthony W.↗
NASA NTRS2006

Variable Frequency Diverter Actuation for Flow Control

The design and development of an actively controlled fluidic actuator for flow control applications is explored. The basic device, with one input and two output channels, takes advantage of the Coanda effect to force a fluid jet to adhere to one of two axi-symmetric surfaces. The resultant flow is bi-stable, producing a constant flow from one output channel, until a disturbance force applied at the control point causes the flow to switch to the alternate output channel. By properly applying active control the output flows can be manipulated to provide a high degree of modulation over a wide and variable range of frequency and duty cycle. In this study the momentary operative force is applied by small, high speed isolation valves of which several different types are examined. The active fluidic diverter actuator is shown to work in several configurations including that in which the operator valves are referenced to atmosphere as well as to a source common with the power stream.

Culley, Dennis E.↗
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 NTRSDate not supplied

Parametric Mechanism Design Through Numerical Optimization and Physics Simulation

Design-Build-Test approaches for developing spaceflight hardware are prohibitively time and cost intensive and often lead to suboptimal mechanism designs. Approaches that couple machine learning and high-fidelity physics simulation could eliminate the need for hardware prototyping and dramatically accelerate the engineering design cycle, ultimately reducing cost. This work presents a modular NASA-developed toolchain to optimize hardware mechanisms in a virtual environment using numerical optimization and multi-body physics simulation. The toolchain enables multi-objective optimization, generates parametric CAD files that can be further post-processed by an end user, and can be expanded to optimize full systems and non-mechanical parameters such as feedback control variables. We demonstrate the toolchain through an independently verifiable design problem that optimizes wheel radius to achieve a desired linear velocity in a rigid-body physics environment when the wheel rotates at a constant angular speed, and then post-process the parametric CAD file of the optimal design generated by the tool before ultimately manufacturing it via 3D printing. We end with a discussion of how the toolchain can incorporate other analysis tools, including finite element analysis, computational fluid dynamics, and granular media simulations.

Optimization↗
NASA NTRSDate not supplied

An Optimization-Based Toolchain for Parametric Mechanism Design

Design-Build-Test approaches for developing spaceflight hardware are prohibitively time and cost intensive and often lead to suboptimal mechanism designs. Approaches that couple machine learning and high-fidelity physics simulation could eliminate the need for hardware prototyping and dramatically accelerate the engineering design cycle, ultimately reducing cost. This work presents a modular NASA-developed toolchain to optimize hardware mechanisms in a virtual environment using numerical optimization and multi-body physics simulation. The toolchain enables multi-objective optimization, generates parametric CAD files that can be further post-processed by an end user, and can be expanded to optimize full systems and non-mechanical parameters such as feedback control variables. We demonstrate the toolchain through an independently verifiable design problem that optimizes wheel radius to achieve a desired linear velocity in a rigid-body physics environment when the wheel rotates at a constant angular speed, and then post-process the parametric CAD file of the optimal design generated by the tool before ultimately manufacturing it via 3D printing. We end with a discussion of how the toolchain can incorporate other analysis tools, including finite element analysis, computational fluid dynamics, and granular media simulations.

Optimization↗
DOE OSTI2023

Deep generative models for vehicle speed trajectories

Generating realistic vehicle speed trajectories is a crucial component in evaluating vehicle fuel economy and in predictive control of self-driving cars. Traditional generative models rely on Markov chain methods and can produce accurate synthetic trajectories but are subject to the curse of dimensionality. They do not allow to include conditional input variables into the generation process. In this paper, we show how extensions to deep generative models allow accurate and scalable generation. Proposed architectures involve recurrent and feed-forward layers and are trained using adversarial techniques. Our models are shown to perform well on generating vehicle trajectories using a model trained on GPS data from Chicago metropolitan area.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS1961

Flight Investigation using Variable-Stability Airplanes of Minimum Stability Requirements for High-Speed, High-Altitude Vehicles

The pilot opinion of the flying qualities of vehicles covering a wide range of longitudinal dynamic characteristics has been determined by the use of a variable-stability airplane. Particular emphasis has been placed on determining the minimum level of stability and control characteristics that the pilot can cope with. There was considerable pilot learning associated with operation in the regions of poor stability characteristics. In the statically stable region the maximum acceptable value of time to damp to half amplitude of the longitudinal mode for normal operation was about 1 second. For emergency conditions the damping could be reduced to zero over most of the frequency range. The extreme lim it of controllability corresponded to a time to double amplitude of the oscillation of about 1 - 1/2 seconds. In the statically unstable region somewhat shorter times to double amplitude were acceptable to the pilots. The boundary for emergency operation corresponded roughly to time to double amplitude of about 2/3 second and the limit of controllability of about l/3 second.

McFadden, Norman M.↗