Results for “Model Predictive Control” — Page 21

NASA NTRS1986

Controlled impact demonstration airframe bending bridges

The calibration of the KRASH and DYCAST models for transport aircraft is discussed. The FAA uses computer analysis techniques to predict the response of controlled impact demonstration (CID) during impact. The moment bridges can provide a direct correlation between the predictive loads or moments that the models will predict and what was experienced during the actual impact. Another goal is to examine structural failure mechanisms and correlate with analytical predictions. The bending bridges did achieve their goals and objectives. The data traces do provide some insight with respect to airframe loads and structural response. They demonstrate quite clearly what's happening to the airframe. A direct quantification of metal airframe loads was measured by the moment bridges. The measured moments can be correlated with the KRASH and DYCAST computer models. The bending bridge data support airframe failure mechanisms analysis and provide residual airframe strength estimation. It did not appear as if any of the bending bridges on the airframe exceeded limit loads. (The observed airframe fracture was due to the fuselage encounter with the tomahawk which tore out the keel beam.) The airframe bridges can be used to estimate the impact conditions and those estimates are correlating with some of the other data measurements. Structural response, frequency and structural damping are readily measured by the moment bridges.

Soltis, S. J.↗

NASA NTRS1991

System identification requirements for high-bandwidth rotorcraft flight control system design

The application of system identification methods to high-bandwidth rotorcraft flight control system design is examined. Flight test and modeling requirements are illustrated using flight test data from a BO-105 hingeless rotor helicopter. The proposed approach involves the identification of nonparametric (transfer function and state space) model identification. Results for the BO-105 show the need for including coupled body/rotor flapping and lead-lag dynamics in the identification model structure to allow the accurate prediction of control ssytem bandwidth limitations.

Tischler, Mark B.↗

NASA NTRS1986

Acoustic Load Considerations for Spacecraft Structures

An analytical model to predict the space averaged sound pressure levels in the payload bay of the Space Shuttle orbiter vehicle at lift-off was developed. A modified form of the model can also be used to predict vibration levels of the orbiter mid fuselage and to evaluate noise control concepts for the interior of the proposed Aft Cargo Carrier (ACC). The analytical model is presented and predicted payload bay sound pressure levels are compared with launch data for an empty bay. Estimated and measured sound pressure levels for regions above large diameter payloads are found to be significantly higher than those for the empty bay. The use of helium as a purge gas to reduce sound pressure levels in the ACC is proposed.

Wilby, J. F.↗

NASA NTRS1982

Prediction of aircraft handling qualities using analytical models of the human pilot

The optimal control model (OCM) of the human pilot is applied to the study of aircraft handling qualities. Attention is focused primarily on longitudinal tasks. The modeling technique differs from previous applications of the OCM in that considerable effort is expended in simplifying the pilot/vehicle analysis. After briefly reviewing the OCM, a technique for modeling the pilot controlling higher order systems is introduced. Following this, a simple criterion for determining the susceptibility of an aircraft to pilot-induced oscillations (PIO) is formulated. Finally, a model-based metric for pilot rating prediction is discussed. The resulting modeling procedure provides a relatively simple, yet unified approach to the study of a variety of handling qualities problems.

Hess, R. A.↗

NASA NTRS2014

Initial Evaluations of LoC Prediction Algorithms Using the NASA Vertical Motion Simulator

Flying near the edge of the safe operating envelope is an inherently unsafe proposition. Edge of the envelope here implies that small changes or disturbances in system state or system dynamics can take the system out of the safe envelope in a short time and could result in loss-of-control events. This study evaluated approaches to predicting loss-of-control safety margins as the aircraft gets closer to the edge of the safe operating envelope. The goal of the approach is to provide the pilot aural, visual, and tactile cues focused on maintaining the pilot's control action within predicted loss-of-control boundaries. Our predictive architecture combines quantitative loss-of-control boundaries, an adaptive prediction method to estimate in real-time Markov model parameters and associated stability margins, and a real-time data-based predictive control margins estimation algorithm. The combined architecture is applied to a nonlinear transport class aircraft. Evaluations of various feedback cues using both test and commercial pilots in the NASA Ames Vertical Motion-base Simulator (VMS) were conducted in the summer of 2013. The paper presents results of this evaluation focused on effectiveness of these approaches and the cues in preventing the pilots from entering a loss-of-control event.

Pilot Cue↗

NASA NTRS1981

Qualitative comparison of calculated turbulence responses with wind-tunnel measurements for a DC-10 derivative wing with an active control system

Comparisons are presented analytically predicted and experimental turbulence responses of a wind tunnel model of a DC-10 derivative wing equipped with an active control system. The active control system was designed for the purpose of flutter suppression, but it had additional benefit of alleviating gust loads (wing bending moment) by about 25%. Comparisions of various wing responses are presented for variations in active control system parameters and tunnel speed. The analytical turbulence responses were obtained using DYLOFLEX, a computer program for dynamic loads analyses of flexible airplanes with active controls. In general, the analytical predictions agreed reasonably well with the experimental data.

Perry, B., III↗

NASA NTRS1979

Interior noise control prediction study for high-speed propeller-driven aircraft

An analytical model was developed to predict the noise levels inside propeller-driven aircraft during cruise at M = 0.8. The model was applied to three study aircraft with fuselages of different size (wide body, narrow body and small diameter) in order to determine the noise reductions required to achieve the goal of an A-weighted sound level which does not exceed 80 dB. The model was then used to determine noise control methods which could achieve the required noise reductions. Two classes of noise control treatments were investigated: add-on treatments which can be added to existing structures, and advanced concepts which would require changes to the fuselage primary structure. Only one treatment, a double wall with limp panel, provided the required noise reductions. Weight penalties associated with the treatment were estimated for the three study aircraft.

Rennison, D. C.↗

NASA NTRSDate not supplied

Hybrid-Electric Aero-Propulsion Controls Testbed Results

NASA is supporting the development of Electrified Aircraft Propulsion (EAP) technology due to its potential to reduce aircraft fuel burn, emissions, and noise as well as improving safety and performance. One focus of this research is the electrification of conventional turbomachinery propulsion systems, which offers ways to improve the performance and operability of turbine-engine powered aircraft through the addition of electro-mechanical systems. These hybrid-electric turbine engines provide additional actuation and energy management control opportunities for improving stability and transient response behavior. This paper summarizes the results of a Hardware-in-the-Loop (HIL) test performed at the NASA Electric Aircraft Testbed (NEAT) during the summer of 2022. The test demonstrates the feasibility and performance of an advanced energy management control strategy by integrating a simulated turbofan engine with scaled electro-mechanical hardware. A full-scale real-time reference model of a geared turbofan was run alongside a scaled electro-mechanical system representing the electrified turbofan components operating at a megawatt-scale power level. The model was interfaced with the hardware through a novel closed-loop control and scaling algorithm that emulated the dynamic speed and torque response of the turbofan shafts. The control strategy was implemented on the electrical machines connected to the emulated turbomachinery shafts. The results from the testbed are compared against simulations that predict the testbed and geared turbofan model operation. The energy management control strategy successfully changed the operating point of the engine model and improved its stability during throttle transients. These results also demonstrate the success of the novel closed loop control and scaling approach for emulating turbomachinery and elevate the Technology Readiness Level (TRL) of the energy management control strategy.

Aeronautics↗

NASA NTRS2023

Hybrid-Electric Aero-Propulsion Controls Testbed Results

NASA is supporting the development of Electrified Aircraft Propulsion (EAP) technology due to its potential to reduce aircraft fuel burn, emissions, and noise as well as improving safety and performance. One focus of this research is the electrification of conventional turbomachinery propulsion systems, which offers ways to improve the performance and operability of turbine-engine powered aircraft through the addition of electro-mechanical systems. These hybrid-electric turbine engines provide additional actuation and energy management control opportunities for improving stability and transient response behavior. This paper summarizes the results of a Hardware-in-the-Loop (HIL) test performed at the NASA Electric Aircraft Testbed (NEAT) during the summer of 2022. The test demonstrates the feasibility and performance of an advanced energy management control strategy by integrating a simulated turbofan engine with scaled electro-mechanical hardware. A full-scale real-time reference model of a geared turbofan was run alongside a scaled electro-mechanical system representing the electrified turbofan components operating at a megawatt-scale power level. The model was interfaced with the hardware through a novel closed-loop control and scaling algorithm that emulated the dynamic speed and torque response of the turbofan shafts. The control strategy was implemented on the electrical machines connected to the emulated turbomachinery shafts. The results from the testbed are compared against simulations that predict the testbed and geared turbofan model operation. The energy management control strategy successfully changed the operating point of the engine model and improved its stability during throttle transients. These results also demonstrate the success of the novel closed loop control and scaling approach for emulating turbomachinery and elevate the Technology Readiness Level (TRL) of the energy management control strategy.

Aeronautics↗

NASA NTRS2012

Predicting the Inflow Distortion Tone Noise of the NASA Glenn Advanced Noise Control Fan with a Combined Quadrupole-Dipole Model

A combined quadrupole-dipole model of fan inflow distortion tone noise has been extended to calculate tone sound power levels generated by obstructions arranged in circumferentially asymmetric locations upstream of a rotor. Trends in calculated sound power level agreed well with measurements from tests conducted in 2007 in the NASA Glenn Advanced Noise Control Fan. Calculated values of sound power levels radiated upstream were demonstrated to be sensitive to the accuracy of the modeled wakes from the cylindrical rods that were placed upstream of the fan to distort the inflow. Results indicate a continued need to obtain accurate aerodynamic predictions and measurements at the fan inlet plane as engineers work towards developing fan inflow distortion tone noise prediction tools.

Koch, L. Danielle↗

NASA NTRS2012

Predicting the Inflow Distortion Tone Noise of the NASA Glenn Advanced Noise Control Fan with a Combined Quadrupole-Dipole Model

A combined quadrupole-dipole model of fan inflow distortion tone noise has been extended to calculate tone sound power levels generated by obstructions arranged in circumferentially asymmetric locations upstream of a rotor. Trends in calculated sound power level agreed well with measurements from tests conducted in 2007 in the NASA Glenn Advanced Noise Control Fan. Calculated values of sound power levels radiated upstream were demonstrated to be sensitive to the accuracy of the modeled wakes from the cylindrical rods that were placed upstream of the fan to distort the inflow. Results indicate a continued need to obtain accurate aerodynamic predictions and measurements at the fan inlet plane as engineers work towards developing fan inflow distortion tone noise prediction tools.

Koch, L. Danielle↗

NASA NTRS2004

Mission Cycle Life Prediction for C/SiC Composites

The residual strength and life of C/SiC is dominated by carbon interface and fiber oxidation if thermal and mechanical stresses combine with thermal expansion mismatch in a manner such that seal coat and matrix cracks are open to allow oxygen ingress. Under these circumstances life can be predicted by simple oxidation based models based on reaction controlled kinetics at low temperature and gas phase diffusion controlled kinetics at high temperature. Key life governing variables in these models include temperature, applied stress, initial strength, oxygen partial pressure and total pressure. In this paper these models are described and extended to mission cycle life prediction.

Levine, Stanley R.↗

NASA NTRS1990

Payload vibration isolation in a microgravity environment

Many in-space research experiments require the microgravity environment attainable near the center of mass of the Space Station. Disturbances to the structure surrounding an experiment may lead to vibration levels that will degrade the microgravity environment and undermine the experiment's validity. In-flight disturbances will include vibration transmission from nearby equipment and excitation from crew activity. Isolation of these vibration-sensitive experiments is required. Analytical and experimental work accomplished to develop a payload (experiment) isolation system for use in space is described. The isolation scheme allows the payload to float freely within a prescribed boundary while being kept centered with forces generated by small jets of air. The vibration criterion was a maximum payload acceleration of 10 micro-g's (9.81x10(exp -5)m/s(exp 2), independent of frequency. An experimental setup, composed of a cart supported by air bearings on a flat granite slab, was designed and constructed to simulate the microgravity environment in the horizontal plane. Experimental results demonstrate that the air jet control system can effectively manage payload oscillatory response. An analytical model was developed and verified by comparing predicted and measured payload response. The mathematical model, which includes payload dynamics, control logic, and air jet forces, is used to investigate payload response to disturbances likely to be present in the Space Station.

Alexander, Richard M.↗

DOE OSTI2024

Predicting synthetic mRNA stability using massively parallel kinetic measurements, biophysical modeling, and machine learning

Abstract mRNA degradation is a central process that affects all gene expression levels, though it remains challenging to predict the stability of a mRNA from its sequence, due to the many coupled interactions that control degradation rate. Here, we carried out massively parallel kinetic decay measurements on over 50,000 bacterial mRNAs, using a learn-by-design approach to develop and validate a predictive sequence-to-function model of mRNA stability. mRNAs were designed to systematically vary translation rates, secondary structures, sequence compositions, G-quadruplexes, i-motifs, and RppH activity, resulting in mRNA half-lives from about 20 seconds to 20 minutes. We combined biophysical models and machine learning to develop steady-state and kinetic decay models of mRNA stability with high accuracy and generalizability, utilizing transcription rate models to identify mRNA isoforms and translation rate models to calculate ribosome protection. Overall, the developed model quantifies the key interactions that collectively control mRNA stability in bacterial operons and predicts how changing mRNA sequence alters mRNA stability, which is important when studying and engineering bacterial genetic systems.

Cetnar, Daniel P.↗

NASA NTRS1989

Experimental results for labyrinth gas seals with honeycomb stators - Comparisons to smooth-stator seals and theoretical predictions

Experimental measurements are presented for the rotordynamic stiffness and damping coefficients of a teeth-on-rotor labyrinth seal with a honeycomb stator. Inlet circumferential velocity, inlet pressure, rotor speed, and seal clearance are primary variables. Results are compared to data for teeth-on-rotor labyrinth seals with smooth stators and to analytical predictions from a two-control-volume compressible flow model. The experimental results show that the honeycomb-stator configuration is more stable than the smooth-stator configuration at low rator speeds. At high rotor speeds, the stator surface does not affect stability. The theoretical model predicts the cross-coupled stiffness of the honeycomb-stator seal correctly within 25 percent of measured values. The model provides accurate predictions of direct damping for large clearance seals; however, the model predictions and test results diverge with increasing running speed. Overall, the model does not perform as well for low clearance seals as for high clearance seals.

Hawkins, Larry↗

DOE OSTI2025

Results and lessons learned from accelerating radio frequency modeling using machine learning [slides]

The “advanced tokamak” reactor concept is a leading candidate for a steady state fusion pilot plant. An advanced tokamak (AT) sustains a majority of the required plasma current with effects resulting from maintenance of the peaked pressure at the device center. This current is augmented by auxiliary current drive sources. These auxiliary actuators may consist of neutral particle beams and/or radio frequency (RF) systems such as lower hybrid current drive (LHCD) and high harmonic fast wave (HHFW) current drive using radio and microwaves from antennas. The primary focus of this work is to develop models of RF current profile control suitable for use in integrated modeling frameworks and for real-time control in experiments. Direct physics models of RF current drive can be computationally intensive. In order to achieve predictive times appropriate for the thousands of calls needed in real-time control of experiments and for use in integrated models, we will apply modern machine learning (ML) techniques to accelerate these models and interpolate their results. To generate the fast and accurate models for use in control level algorithms and integrated modeling we need to replace present models with high dimensional interpolation of their results. We will perform additional simulations across a broader parameter range for EAST and other tokamaks in different physics regimes (Alcator C-Mod, DIII-D, WEST, CFETR, ARC, ITER) and combine them into a larger database for training and testing of the ML models. Further testing of the control level models with experimental current profile data from EAST and C-Mod tokamaks will provide additional confirmation of the control level model before integration in a tokamak control system or integrated modeling suite. ML will be used to optimize the selection of training data consisting of RF current driven at different values of density profile, temperature profile, plasma current, and wavenumber. ML will also be used to facilitate classification of current drive from these input data. The output of this effort will be a validated classifier capable of determining the current drive profiles for HHFW CD and LHCD on a mille-second timescale. This will provide a breakthrough capability enabling real-time control of RF driven current profiles in experiments including ITER ICRF and use integrated modeling frameworks requiring thousands of current profile calculations in discharge simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1994

Analytical investigation of adaptive control of radiated inlet noise from turbofan engines

An analytical model has been developed to predict the resulting far field radiation from a turbofan engine inlet. A feedforward control algorithm was simulated to predict the controlled far field radiation from the destructive combination of fan noise and secondary control sources. Numerical results were developed for two system configurations, with the resulting controlled far field radiation patterns showing varying degrees of attenuation and spillover. With one axial station of twelve control sources and error sensors with equal relative angular positions, nearly global attenuation is achieved. Shifting the angular position of one error sensor resulted in an increase of spillover to the extreme sidelines. The complex control inputs for each configuration was investigated to identify the structure of the wave pattern created by the control sources, giving an indication of performance of the system configuration. It is deduced that the locations of the error sensors and the control source configuration are equally critical to the operation of the active noise control system.

Risi, John D.↗

NASA NTRSDate not supplied

Modeling Self-Pressurization and Spray Bar Pressure Control of A Cryogenic Storage Tank in Normal Gravity

This paper presents computational fluid dynamics (CFD) models for simulating self-pressurization and spray-bar pressure control processes in a large-scale liquid hydrogen storage tank under normal gravity conditions. For self-pressurization, the model employs the kinetics-based Schrage equation alongside the volume-of-fluid (VOF) method to account for interfacial mass transfer. The CFD predictions of pressure and temperature are compared with experimental data from the Multipurpose Hydrogen Test Bed (MHTB) experiment, and the predicted interfacial mass transfer rates are also presented. A CFD model simulating pressure control using a spray bar has also been developed. An Eulerian-Lagrangian approach models the interactions between discrete droplets and the continuous ullage (vapor) phase. The spray model is coupled with the VOF method by tracking droplets in the ullage and removing them when they reach the liquid interface. The T-sat model calculates droplet-ullage heat and mass transfer, where droplets warm up to the saturation temperature corresponding to the ullage vapor pressure before evaporating while remaining at the saturation temperature. The evolution of tank pressure, vapor temperature, and liquid temperature predicted by the CFD model is validated against data from the MHTB spray-bar mixing experiment. Overall, the CFD models agree with experimental data, demonstrating their capability to simulate self-pressurization and pressure control processes in large-scale cryogenic storage tanks. These models can be valuable tools for designing and optimizing cryogenic fluid management systems in future applications.

Computational Fluid Dynamics↗