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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Real-Time Adaptive Least-Squares Drag Minimization for Performance Adaptive Aeroelastic Wing

This paper contains a simulation study of a real-time adaptive least-squares drag minimization algorithm for an aeroelastic model of a flexible wing aircraft. The aircraft model is based on the NASA Generic Transport Model (GTM). The wing structures incorporate a novel aerodynamic control surface known as the Variable Camber Continuous Trailing Edge Flap (VCCTEF). The drag minimization algorithm uses the Newton-Raphson method to find the optimal VCCTEF deflections for minimum drag in the context of an altitude-hold flight control mode at cruise conditions. The aerodynamic coefficient parameters used in this optimization method are identified in real-time using Recursive Least Squares (RLS). The results demonstrate the potential of the VCCTEF to improve aerodynamic efficiency for drag minimization for transport aircraft.

Aeroservoelasticity↗
NASA NTRS2017

Propulsion Powertrain Real-Time Simulation Using Hardware-in-the-Loop (HIL) for Aircraft Electric Propulsion System

It is essential to design a propulsion powertrain real-time simulator using the hardware-in-the-loop (HIL) system that emulates an electrified aircraft propulsion (EAP) systems power grid. This simulator would enable us to facilitate in-depth understanding of the system principles, to validate system model analysis and performance prediction, and to demonstrate the proof-of-concept of the EAP electrical system. This paper describes how subscale electrical machines with their controllers can mimic the power components in an EAP powertrain. In particular, three powertrain emulations are presented to mimic 1) a gas turbo-=shaft engine driving a generator, consisting of two permanent magnet (PM) motors with brushless motor drives, coupled by a shaft, 2) a motor driving a propulsive fan, and 3) a turbo-shaft engine driven fan (turbofan engine) operation. As a first step towards the demonstration, experimental dynamic characterization of the two motor drive systems, coupled by a mechanical shaft, were performed. The previously developed analytical motor models1 were then replaced with the experimental motor models to perform the real-time demonstration in the predefined flight path profiles. This technique can convert the plain motor system into a unique EAP power grid emulator that enables rapid analysis and real-time simulation performance using hardware-in-the-loop (HIL).

turbo-electric propulsion↗
NASA NTRS2008

Enhanced Self Tuning On-Board Real-Time Model (eSTORM) for Aircraft Engine Performance Health Tracking

A key technological concept for producing reliable engine diagnostics and prognostics exploits the benefits of fusing sensor data, information, and/or processing algorithms. This report describes the development of a hybrid engine model for a propulsion gas turbine engine, which is the result of fusing two diverse modeling methodologies: a physics-based model approach and an empirical model approach. The report describes the process and methods involved in deriving and implementing a hybrid model configuration for a commercial turbofan engine. Among the intended uses for such a model is to enable real-time, on-board tracking of engine module performance changes and engine parameter synthesis for fault detection and accommodation.

Volponi, Al↗
DOE OSTI2023

HCPerf: Driving Performance-Directed Hierarchical Coordination for Autonomous Vehicles

The rapid development of autonomous driving poses new research challenges to the on-vehicle computing system. In particular, the execution time of autonomous driving tasks highly depends on the specific driving environment. For instance, the execution time of configurable sensor fusion increases significantly as the scene becomes complex, which leads to end-to-end deadline misses from sensing to control and may cause accidents. Thus, a framework that can effectively utilize the system resources to guarantee the end-to-end deadlines of autonomous driving tasks as well as effectively prioritize the responsiveness and throughput of the control commands is crucial for autonomous driving. In this paper, we propose HCPerf, a performance-directed hierarchical coordination framework that intelligently coordinates the autonomous driving tasks with high execution time variation and complex dependencies according to the driving performance in real-time. Specifically, HCPerf mainly consists of two coordinators. The internal coordinator intelligently schedules the tasks according to the driving performance of the vehicle in order to help them meet the end-to-end deadlines while well prioritizing the responsiveness and throughput of the control commands. At the same time, the external coordinator dynamically tunes the rates of tasks according to the schedulability in order to efficiently utilize the system resource. We conduct extensive experiments on both simulation and hardware testbeds with the representative autonomous driving application. The results show that HCPerf can effectively improve the driving performance by 7.69%-45.94% in different driving scenarios.

Ma, Jialiang↗
DOE OSTI2020

High Performance Computing Traffic Simulations for Real-Time Traffic Control of Mobility in Chattanooga Region

In 2019, highway congestion wasted over 3 billion gallons of fuel and caused 8.8 billion hours of lost productivity.1 Research has shown that introducing near-real time traffic controls can significantly reduce congestion. Validated and calibrated traffic simulations enable the modeling of transportation systems and the evaluation of different traffic control actions and schemes given a variety of circumstances that represent likely future scenarios. The developed scenarios can inform the deployment of controls in near real-time to improve freight and passenger vehicle congestion and energy use. In this work, we present simulations used to model the traffic in the Chattanooga, Tennessee, metropolitan area. Simulations were constructed and calibrated using a variety of local, data science enhanced, data sources utilizing open source software including the Simulation of Urban Mobility (SUMO) simulator. High-Performance Computing (HPC) provides a scalable platform with enough computing for the high-fidelity simulation of many scenarios and the application of advance data science especially for large-scale systems. Our simulations include microscopic simulations at a corridor level for traffic signal control, and mesoscopic simulations to evaluate regional operational controls and infrastructure.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2020

Evaluation of Performance, Fatigue and Workload during Real-time, Reactive Telerobotic Mission Control Operations

Telerobotic operations involve a user operating a robot from a different location from where the activity is taking place. It can be difficult for humans to maintain performance when faced with physiological stressors, such as fatigue or illness. Operations require vigilance for extended periods, raising safety concerns surrounding operator’s fatigue and workload. Every hour of wakefulness increases the drive to sleep, causing decreased reaction time (RT), increased lapses in attention (RT > 500 ms), and decreased memory capability. The NASA Task Load Index (NASA-TLX) was created to evaluate the multiple attributes surrounding workload (e.g., mental and physical demands). The upcoming Volatiles Investigating Polar Exploration Rover (VIPER) mission involves remotely controlling a lunar vehicle from an Earth-based mission control station. The goal of VIPER is to excavate the moon for volatiles (water) deep in the surface near the South Pole for a 100-day, continuous operation.

Fatigue↗
NASA NTRS1993

Use of high performance networks and supercomputers for real-time flight simulation

In order to meet the stringent time-critical requirements for real-time man-in-the-loop flight simulation, computer processing operations must be consistent in processing time and be completed in as short a time as possible. These operations include simulation mathematical model computation and data input/output to the simulators. In 1986, in response to increased demands for flight simulation performance, NASA's Langley Research Center (LaRC), working with the contractor, developed extensions to the Computer Automated Measurement and Control (CAMAC) technology which resulted in a factor of ten increase in the effective bandwidth and reduced latency of modules necessary for simulator communication. This technology extension is being used by more than 80 leading technological developers in the United States, Canada, and Europe. Included among the commercial applications are nuclear process control, power grid analysis, process monitoring, real-time simulation, and radar data acquisition. Personnel at LaRC are completing the development of the use of supercomputers for mathematical model computation to support real-time flight simulation. This includes the development of a real-time operating system and development of specialized software and hardware for the simulator network. This paper describes the data acquisition technology and the development of supercomputing for flight simulation.

Cleveland, Jeff I., II↗
NASA NTRS2003

Effect of Above Real Time Training and Post Flight Feedback in Training of Novice Pilots in a PC-Based Flight Simulator

The use of Post-Flight Feedback (PFFB) and Above Real-Time Training (ARTT) while training novice pilots to perform a coordinated level turn on a PC-based flight simulator was investigated. One group trained at 1.5 ARTT followed by an equal number of flights at 2.0 ARTT; the second group experienced Real Time Training (RTT). The total number of flights for both groups was equal. Each group was further subdivided into two groups one of which was provided PFFB while the other was not. Then, all participants experienced two challenging evaluation missions in real time. Performance was assessed by comparing root-mean-square error in bank-angle and altitude. Participants in the 1.512.0 ARTT No-PFFB sequence did not show improvement in performance across training sessions. An ANOVA on performance in evaluation flights found that the PFFB groups performed significantly better than those with No-PFFB. Also, the RTT groups performed significantly better than the ARTT groups. Data from two additional groups trained under a 2.011.5 ARTT PFFB and No-PFFB regimes were collected and combined with data from the previously Trainers, Real-time simulation, Personal studied groups and reanalyzed to study the computers, Man-in-the-loop simulation influence of sequence. An ANOVA on test trials found no significant effects between groups. Under training situations involving ARTT we recommend that appropriate PFFB be provided.

Khan, M. Javed↗
NASA NTRS2001

Real-Time Adaptive Control Allocation Applied to a High Performance Aircraft

Abstract This paper presents the development and application of one approach to the control of aircraft with large numbers of control effectors. This approach, referred to as real-time adaptive control allocation, combines a nonlinear method for control allocation with actuator failure detection and isolation. The control allocator maps moment (or angular acceleration) commands into physical control effector commands as functions of individual control effectiveness and availability. The actuator failure detection and isolation algorithm is a model-based approach that uses models of the actuators to predict actuator behavior and an adaptive decision threshold to achieve acceptable false alarm/missed detection rates. This integrated approach provides control reconfiguration when an aircraft is subjected to actuator failure, thereby improving maneuverability and survivability of the degraded aircraft. This method is demonstrated on a next generation military aircraft Lockheed-Martin Innovative Control Effector) simulation that has been modified to include a novel nonlinear fluid flow control control effector based on passive porosity. Desktop and real-time piloted simulation results demonstrate the performance of this integrated adaptive control allocation approach.

Davidson, John B.↗
DOE OSTI2020

Deep Reinforcement Learning for Residential HVAC Control with Consideration of Human Occupancy

The Artificial Intelligence (AI) development described herein uses model-free Deep Reinforcement Learning (DRL) to minimize energy cost during residential heating, ventilation, and air conditioning (HVAC) operation. Building cooling loads and HVAC operation are difficult to accurately model due to complexity, lack of measurements and data, and model specific performance, so online machine learning is used to allow for real-time readjustment in performance. Energy costs for the multi-zone cooling unit shown in this work are minimized by scheduling on/off commands around dynamic prices. By taking advantage of precooling events that take place when the price is low, the agent is able to reduce operational cost without violating user comfort. The DRL controller was tested in simulation where the learner achieved a 43.89% cost reduction when compared to traditional, fixed-setpoint operation. The system is now ready for the next phase of testing in a live, real-time home environment.

Mckee, Evan↗
NASA NTRS1992

Real-Time Optical Correlator Based On GaAs

Apparatus performs correlation between input image and reference image in real time by means of degenerate four-wave mixing in photorefractive crystal, which serves as real-time holographic medium. Gallium arsenide chosen to be photorefractive material in this application because at frame rate and level of illumination used in experiments, offers adequate diffraction efficiency. Frame rates as high as 1,000 s to negative 1st power achievable.

Liu, Tsuen-Hsi↗
NASA NTRS1988

Handling Flight-Research Data In Real Time

Researchers at widely separated locations able to participate in tests and analyze data immediately. Basic data-handling needs common: Communicates with vehicle, pilot, and test team; Acquires, computes, and displays data; knows exact location of research vehicle at all times. Continuing challenge for designers and operators of ground support facilities to perform tasks in real time and present integrated results to research team in real time. Paper presents several approaches to satisfaction of requirements of representative types of aircraft research programs at NASA Western Aeronautical Test Range of Ames Research Center.

Moore, Archie L.↗
NASA NTRS1982

Special report on the data collection programs for the ground based nitrogen washout experiment. Volume 1: User's guide

The Nitrogen Washout System measures nitrogen elimination on a breath basis from the body tissues of a subject breathing pure oxygen. The system serves as a prototype for a Space Shuttle Life Sciences experiment and in the Environmental Physiology Laboratory. Typically, a subject washes out body nitrogen for three hours while breathing oxygen from a mask enclosed in a positive-pressure oxygen tent. A nitrogen washout requires one test operator and the test subject. A DEC LSI-11/02 computer is used to (1) control and calibrate the mass spectrometer and Skylab spirometer, (2) gather and store experimental data and (3) provide limited real time analysis and more extensive post-experiment analysis. Five programs are used to gather and store the experimental data and perform all the real time control and analysis.

Bueker, P. A.↗
NASA NTRS2005

Real-time Enhanced Vision System

Flying in poor visibility conditions, such as rain, snow, fog or haze, is inherently dangerous. However these conditions can occur at nearly any location, so inevitably pilots must successfully navigate through them. At NASA Langley Research Center (LaRC), under support of the Aviation Safety and Security Program Office and the Systems Engineering Directorate, we are developing an Enhanced Vision System (EVS) that combines image enhancement and synthetic vision elements to assist pilots flying through adverse weather conditions. This system uses a combination of forward-looking infrared and visible sensors for data acquisition. A core function of the system is to enhance and fuse the sensor data in order to increase the information content and quality of the captured imagery. These operations must be performed in real-time for the pilot to use while flying. For image enhancement, we are using the LaRC patented Retinex algorithm since it performs exceptionally well for improving low-contrast range imagery typically seen during poor visibility conditions. In general, real-time operation of the Retinex requires specialized hardware. To date, we have successfully implemented a single-sensor real-time version of the Retinex on several different Digital Signal Processor (DSP) platforms. In this paper we give an overview of the EVS and its performance requirements for real-time enhancement and fusion and we discuss our current real-time Retinex implementations on DSPs.

Hines, Glenn D.↗
NASA NTRS1985

Performance analysis of the DSN baseband assembly (Bba) Real-Time Combiner (RTC)

The operation of the BBA Real Time Combiner (RTC) is discussed and its performance investigated in detail. It is shown that each channel of the RTC can be modelled by a simple block diagram in the z-transform domain from which all pertinent transient and steady state behavioral characteristics can be determined. In particular, the characteristic equation of the tracking loop and its equivalent noise bandwidth are found and used to evaluate the closed loop transient response and steady-state mean squared timing jitter. The impact of the totality of these loop jitter contributions on the combiner output SNR is evaluated and illustrated numerically. These results show that for parameters of interest to various space missions, the RTC is capable of providing significant SNR improvement relative to a single receiving antenna.

Simon, M. K.↗
NASA NTRS1984

Performance analysis of the DSN baseband assembly (Bba) Real-Time Combiner (RTC)

The operation of the BBA Real Time Combiner (RTC) is discussed and its performance investigated in detail. It is shown that each channel of the RTC can be modelled by a simple block diagram in the z-transform domain from which all pertinent transient and steady state behavioral characteristics can be determined. In particular, the characteristic equation of the tracking loop and its equivalent noise bandwidth are found and used to evaluate the closed loop transient response and steady state mean squared timing jitter. The impact of the totality of these loop jitter contributions on the combiner output SNR is evaluated and illustrated numerically. These results show that for parameters of interest to various space missions, the RTC is capable of providing significant SNR improvement relative to a single receiving antenna.

Simon, M. K.↗