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All sourcesNASA NTRSDOE OSTI
NASA NTRS1977

Experiment and analysis on the flow process dynamics of the NASA-Langley eight foot transonic pressure tunnel

A dynamic response test performed in a eight foot transonic pressure tunnel is described. The dynamics of the flow process of the wind tunnel at transonic conditions were obtained. Descriptions of the test conditions, instrumentation, presentation of raw data, analysis of data, and finally, based on experimental evidences, an attempt to construct an input output relationship of the flow process from the viewpoints of control engineering are included.

Tcheng, P.↗
NASA NTRS1977

Dynamic tooth loads and stressing for high contact ratio spur gears

A time history, closed form solution is presented for a dynamic model of spur gear systems for all practical contact ratios. The analysis determines the dynamic response of the gear system and the associated tooth loads and stressing. The dynamic model assumes the two gears act as a rigid inertia and the teeth act as a variable spring of a dynamic system excited by the meshing action of the teeth. Included in the analysis are the effects of the nonlinearity of the tooth pair stiffness during mesh, the tooth errors, and the tooth profile modifications. Besides reviewing the features, solution, and program of this analysis, preliminary results from applying the analysis are presented, which show that tooth profile modification, system inertia and damping, and system critical speeds can affect the dynamic gear tooth loads and stressing significantly.

Cornell, R. W.↗
NASA NTRSDate not supplied

Soyuz Landing Risk Characterization

INTRODUCTION United States On-orbit Segment (USOS) astronauts have been returning to Earth from the International Space Station (ISS) aboard the Russian Soyuz vehicle since 2003. The energetics associated with Soyuz landings are comparable to our next generation of US space vehicles (Orion, Crew Dragon, and Starliner). Soyuz also lands crew in a similar state of spaceflight deconditioning that is anticipated using the future vehicles. A number of injuries have now been observed during these Soyuz landings. Currently it is unknown how Soyuz landing accelerations and the numbers and types of associated injuries relate to the new occupant protection requirements levied upon future space vehicles. Understanding this relationship will allow better quantification of the risk of injury for future spacecraft designs. METHODS An estimate of the occurrences of injury during Soyuz landings has been determined using data contained in NASA flight medicine databases and supplemented with data collected from crewmembers and flight surgeons. At the time of this abstract, 96 USOS astronauts have returned to Earth in the Soyuz (59 US, 31 International Partner, and 6 spaceflight participants). Of that total, data from 80 individual crew landings has been collected through this study. Injuries are classified as either contusions/abrasions, Class I (minor, no medical follow-up), Class II (moderate, medical follow-up necessary), Class III (severe), and Class IV (life threatening). Current NASA occupant protection standards are primarily based on the Multi-axial Dynamic Response Index (MDRI), which is a simple lumped-parameter spring, mass, damper model tuned to human impact responses in three orthogonal axes. RESULTS Using what is known about Soyuz landing dynamics from airborne and drop test data, the MDRI predicts essentially no Class IV or III injuries, < 1% Class II injuries, and < 5% Class I injuries. Approximately one-third of all USOS crewmembers for whom data has been gathered have suffered some sort of injury related to landing in the Soyuz vehicle. Most of these injuries fall into the contusion/abrasion category (21.3 %). Class I injuries have been sustained by 5.0% of all crew, and Class II injuries have been observed in 3.8%. No Class III or IV injuries have been sustained to date. Forty-three injuries have been documented, with some crewmembers sustaining more than one injury in a single landing. The knee was the most likely area of injury (n=9), followed by the back (n=8), and then the arm (n=7). CONCLUSION Soyuz landing dynamics are the most comparable analog environment for the anticipated loads associated with Orion and commercial crew vehicle landings. The MDRI under predicts the percentage of Class II injuries experienced during Soyuz landings. The MDRI is better at predicting Class I injury occurrences. However, if contusions/abrasions are included in the minor injury Class I category, then the MDRI also vastly under predicts those injuries as well. Given this data, it will be important to re-evaluate the expected injury rates for future vehicles, and work toward improving the predictive tools for spaceflight use. Spaceflight deconditioning may account for some of the under prediction, and work is ongoing to assess the relationship between landing injuries and impact tolerance changes due to spaceflight deconditioning.

N Newby↗
NASA NTRSDate not supplied

Soyuz Landing Risk Characterization

INTRODUCTION United States On-orbit Segment (USOS) astronauts have been returning to Earth from the International Space Station (ISS) aboard the Russian Soyuz vehicle since 2003. The energetics associated with Soyuz landings are comparable to our next generation of US space vehicles (Orion, Crew Dragon, and Starliner). Soyuz also lands crew in a similar state of spaceflight deconditioning that is anticipated using the future vehicles. A number of injuries have now been observed during these Soyuz landings. Currently it is unknown how Soyuz landing accelerations and the numbers and types of associated injuries relate to the new occupant protection requirements levied upon future space vehicles. Understanding this relationship will allow better quantification of the risk of injury for future spacecraft designs. METHODS An estimate of injury occurrence during Soyuz landings has been determined using data contained in NASA flight medicine databases and supplemented with data collected from crewmembers and flight surgeons. At the time of this abstract, 96 USOS astronauts have returned to Earth in the Soyuz (59 US, 31 International Partner, and 6 spaceflight participants). Of that total, data from 80 individual crew landings has been collected through this study as of 2021. Injuries are classified either as contusions/abrasions, Class I (minor, no medical follow-up), Class II (moderate, medical follow-up necessary), Class III (severe), or Class IV (life threatening). Current NASA occupant protection standards are primarily based on the Multi-axial Dynamic Response Index (MDRI), which is a simple lumped-parameter spring, mass, damper model tuned to human impact responses in three orthogonal axes. RESULTS Using what is known about Soyuz landing dynamics from airborne and drop test data, the MDRI predicts essentially no Class IV or III injuries, < 1% Class II injuries, and < 5% Class I injuries. Approximately one-third of all USOS crewmembers for whom data has been gathered have suffered some sort of injury related to landing in the Soyuz vehicle. Most of these injuries fall into the contusion/abrasion category (21.3 %) (n.b. This is the percent for whom contusion/abrasion was the worst injury. Those with class I or II injuries typically also received contusions/abrasions). Class I injuries have been sustained by 5.0% of all crew, and Class II injuries have been observed in 3.8%. No Class III or IV injuries have been sustained to date. Forty-three injuries have been documented, with some crewmembers sustaining more than one injury in a single landing. The knee was the most likely area of injury (n=9), followed by the back (n=8), then the arm (n=7). CONCLUSION Soyuz landing dynamics are the most comparable analog environment for the anticipated loads associated with Orion and commercial crew vehicle landings. The MDRI under predicts the percentage of Class II injuries experienced during Soyuz landings, but it is better at predicting Class I injury occurrences. However, if contusions/abrasions are included in the minor injury Class I category, then the MDRI vastly under predicts those injuries as well. Given this data, it is important to re-evaluate the expected injury rates for future vehicles and work toward improving the predictive tools for spaceflight use. Spaceflight deconditioning may account for some of the under prediction, and work is ongoing to assess the relationship between landing injuries and impact tolerance changes due to spaceflight deconditioning. Future work includes expanding this study to involve private space missions on new vehicles to better characterize the effects of time in flight, suit and seat design, and vehicle dynamics.

N Newby↗
NASA NTRSDate not supplied

Soyuz Landing Risk Characterization

INTRODUCTION United States On-orbit Segment (USOS) astronauts have been returning to Earth from the International Space Station (ISS) aboard the Russian Soyuz vehicle since 2003. The energetics associated with Soyuz landings are comparable to our next generation of US space vehicles (Orion, Crew Dragon, and Starliner). Soyuz also lands crew in a similar state of spaceflight deconditioning that is anticipated using the future vehicles. A number of injuries have now been observed during these Soyuz landings. Currently it is unknown how Soyuz landing accelerations and the numbers and types of associated injuries relate to the new occupant protection requirements levied upon future space vehicles. Understanding this relationship will allow better quantification of the risk of injury for future spacecraft designs. METHODS An estimate of injury occurrence during Soyuz landings has been determined using data contained in NASA flight medicine databases and supplemented with data collected from crew members and flight surgeons. At the time of this abstract, 96 USOS astronauts have returned to Earth in the Soyuz (59 US, 31 International Partner, and 6 spaceflight participants). Of that total, data from 80individual crew landings has been collected through this study as of September 2023. Injuries are classified either as contusions/abrasions, Class I (minor, no medical follow-up), Class II (moderate, medical follow-up necessary), Class III (severe), or Class IV (life threatening). Current NASA occupant protection standards are primarily based on the Multi-axial Dynamic Response Index (MDRI), which is a simple lumped-parameter spring, mass, damper model tuned to human impact responses in three orthogonal axes. RESULTS Using what is known about Soyuz landing dynamics from airborne and drop test data, the MDRI predicts essentially no Class IV or III injuries, < 1% Class II injuries, and < 5% Class I injuries. Approximately one-third of all USOS crewmembers for whom data has been gathered have suffered some sort of injury related to landing in the Soyuz vehicle. Most of these injuries fall into the contusion/abrasion category (21.3%) (n.b. This is the percent for whom contusion/abrasion was the worst injury. Those with class I or II injuries typically also received contusions/abrasions). Class I injuries have been sustained by 5.0% of all crew, and Class II injuries have been observed in 3.8%. No Class III or IV injuries have been sustained to date. Forty-three injuries have been documented, with some crewmembers sustaining more than one injury in a single landing. The knee was the most likely area of injury (n=9), followed by the back (n=8), then the arm (n=7). CONCLUSION Soyuz landing dynamics are the most comparable analog environment for the anticipated loads associated with Orion and commercial crew vehicle landings. The MDRI under predicts the percentage of Class II injuries experienced during Soyuz landings, but it is better at predicting Class I injury occurrences. However, if contusions/abrasions are included in the minor injury Class I category, then the MDRI vastly under predicts those injuries as well. Given this data, it is important to re-evaluate the expected injury rates for future vehicles and work toward improving the predictive tools for spaceflight use. Spaceflight deconditioning may account for some of the under prediction, and work is ongoing to assess the relationship between landing injuries and impact tolerance changes due to spaceflight deconditioning. Future work includes expanding this study to involve private space missions on new vehicles to better characterize the effects of time in flight, suit and seat design, and vehicle dynamics.

N Newby↗
NASA NTRSDate not supplied

Soyuz Landing Risk Characterization

INTRODUCTION United States On-orbit Segment (USOS) astronauts have been returning to Earth from the International Space Station (ISS) aboard the Russian Soyuz vehicle since 2003. The energetics associated with Soyuz landings are comparable to our next generation of US space vehicles (Orion, Crew Dragon, and Starliner). Soyuz also lands crew in a similar state of spaceflight deconditioning that is anticipated using the future vehicles. A number of injuries have now been observed during these Soyuz landings. Currently it is unknown how Soyuz landing accelerations and the numbers and types of associated injuries relate to the new occupant protection requirements levied upon future space vehicles. Understanding this relationship will allow better quantification of the risk of injury for future spacecraft designs. METHODS An estimate of injury occurrence during Soyuz landings has been determined using data contained in NASA flight medicine databases and supplemented with data collected from crewmembers and flight surgeons. At the time of this abstract, 96 USOS astronauts have returned to Earth in the Soyuz (59 US, 31 International Partner, and 6 spaceflight participants). Of that total, data from 80 individual crew landings has been collected through this study as of September 2023. Injuries are classified either as contusions/abrasions, Class I (minor, no medical follow-up), Class II (moderate, medical follow-up necessary), Class III (severe), or Class IV (life threatening). Current NASA occupant protection standards are primarily based on the Multi-axial Dynamic Response Index (MDRI), which is a simple lumped-parameter spring, mass, damper model tuned to human impact responses in three orthogonal axes. RESULTS Using what is known about Soyuz landing dynamics from airborne and drop test data, the MDRI predicts essentially no Class IV or III injuries, < 1% Class II injuries, and < 5% Class I injuries. Approximately one-third of all USOS crewmembers for whom data has been gathered have suffered some sort of injury related to landing in the Soyuz vehicle. Most of these injuries fall into the contusion/abrasion category (21.3 %) (n.b. This is the percent for whom contusion/abrasion was the worst injury. Those with class I or II injuries typically also received contusions/abrasions). Class I injuries have been sustained by 5.0% of all crew, and Class II injuries have been observed in 3.8%. No Class III or IV injuries have been sustained to date. Forty-three injuries have been documented, with some crewmembers sustaining more than one injury in a single landing. The knee was the most likely area of injury (n=9), followed by the back (n=8), then the arm (n=7). CONCLUSION Soyuz landing dynamics are the most comparable analog environment for the anticipated loads associated with Orion and commercial crew vehicle landings. The MDRI under predicts the percentage of Class II injuries experienced during Soyuz landings, but it is better at predicting Class I injury occurrences. However, if contusions/abrasions are included in the minor injury Class I category, then the MDRI vastly under predicts those injuries as well. Given this data, it is important to re-evaluate the expected injury rates for future vehicles and work toward improving the predictive tools for spaceflight use. Spaceflight deconditioning may account for some of the under prediction, and work is ongoing to assess the relationship between landing injuries and impact tolerance changes due to spaceflight deconditioning. Future work includes expanding this study to involve private space missions on new vehicles to better characterize the effects of time in flight, suit and seat design, and vehicle dynamics.

P Greenhalgh↗
NASA NTRS2014

Deducing Electronic Unit Internal Response During a Vibration Test Using a Lumped Parameter Modeling Approach

During random vibration testing of electronic boxes there is often a desire to know the dynamic response of certain internal printed wiring boards (PWBs) for the purpose of monitoring the response of sensitive hardware or for post-test forensic analysis in support of anomaly investigation. Due to restrictions on internally mounted accelerometers for most flight hardware there is usually no means to empirically observe the internal dynamics of the unit, so one must resort to crude and highly uncertain approximations. One common practice is to apply Miles Equation, which does not account for the coupled response of the board in the chassis, resulting in significant over- or under-prediction. This paper explores the application of simple multiple-degree-of-freedom lumped parameter modeling to predict the coupled random vibration response of the PWBs in their fundamental modes of vibration. A simple tool using this approach could be used during or following a random vibration test to interpret vibration test data from a single external chassis measurement to deduce internal board dynamics by means of a rapid correlation analysis. Such a tool might also be useful in early design stages as a supplemental analysis to a more detailed finite element analysis to quickly prototype and analyze the dynamics of various design iterations. After developing the theoretical basis, a lumped parameter modeling approach is applied to an electronic unit for which both external and internal test vibration response measurements are available for direct comparison. Reasonable correlation of the results demonstrates the potential viability of such an approach. Further development of the preliminary approach presented in this paper will involve correlation with detailed finite element models and additional relevant test data.

random vibration response↗
NASA NTRS1996

The dynamic contributions of the otolith organs to human ocular torsion

We measured human ocular torsion (OT) monocularly (using video) and binocularly (using search coils) while sinusoidally accelerating (0.7 g) five human subjects along an earth-horizontal axis at five frequencies (0.35, 0.4, 0.5, 0.75, and 1.0 Hz). The compensatory nature of OT was investigated by changing the relative orientation of the dynamic (linear acceleration) and static (gravitational) cues. Four subject orientations were investigated: (1) Y-upright-acceleration along the interaural (y) axis while upright; (2) Y-supine-acceleration along the y-axis while supine; (3) Z-RED-acceleration along the dorsoventral (z) axis with right ear down; (4) Z-supine-acceleration along the z-axis while supine. Linear acceleration in the Y-upright, Y-supine and Z-RED orientations elicited conjugate OT. The smaller response in the Z-supine orientation appeared disconjugate. The amplitude of the response decreased and the phase lag increased with increasing frequency for each orientation. This frequency dependence does not match the frequency response of the regular or irregular afferent otolith neurons; therefore the response dynamics cannot be explained by simple peripheral mechanisms. The Y-upright responses were larger than the Y-supine responses (P < 0.05). This difference indicates that OT must be more complicated than a simple low-pass filtered response to interaural shear force, since the dynamic shear force along the interaural axis was identical in these two orientations. The Y-supine responses were, in turn, larger than the Z-RED responses (P < 0.01). Interestingly, the vector sum of the Y-supine responses plus Z-RED responses was not significantly different (P = 0.99) from the Y-upright responses. This suggests that, in this frequency range, the conjugate OT response during Y-upright stimulation might be composed of two components: (1) a response to shear force along the y-axis (as in Y-supine stimulation), and (2) a response to roll tilt of gravitoinertial force (as in Z-RED stimulation).

NASA Discipline Neuroscience↗
NASA NTRS2007

Increasing Linear Dynamic Range of a CMOS Image Sensor

A generic design and a corresponding operating sequence have been developed for increasing the linear-response dynamic range of a complementary metal oxide/semiconductor (CMOS) image sensor. The design provides for linear calibrated dual-gain pixels that operate at high gain at a low signal level and at low gain at a signal level above a preset threshold. Unlike most prior designs for increasing dynamic range of an image sensor, this design does not entail any increase in noise (including fixed-pattern noise), decrease in responsivity or linearity, or degradation of photometric calibration. The figure is a simplified schematic diagram showing the circuit of one pixel and pertinent parts of its column readout circuitry. The conventional part of the pixel circuit includes a photodiode having a small capacitance, CD. The unconventional part includes an additional larger capacitance, CL, that can be connected to the photodiode via a transfer gate controlled in part by a latch. In the high-gain mode, the signal labeled TSR in the figure is held low through the latch, which also helps to adapt the gain on a pixel-by-pixel basis. Light must be coupled to the pixel through a microlens or by back illumination in order to obtain a high effective fill factor; this is necessary to ensure high quantum efficiency, a loss of which would minimize the efficacy of the dynamic- range-enhancement scheme. Once the level of illumination of the pixel exceeds the threshold, TSR is turned on, causing the transfer gate to conduct, thereby adding CL to the pixel capacitance. The added capacitance reduces the conversion gain, and increases the pixel electron-handling capacity, thereby providing an extension of the dynamic range. By use of an array of comparators also at the bottom of the column, photocharge voltages on sampling capacitors in each column are compared with a reference voltage to determine whether it is necessary to switch from the high-gain to the low-gain mode. Depending upon the built-in offset in each pixel and in each comparator, the point at which the gain change occurs will be different, adding gain-dependent fixed pattern noise in each pixel. The offset, and hence the fixed pattern noise, is eliminated by sampling the pixel readout charge four times by use of four capacitors (instead of two such capacitors as in conventional design) connected to the bottom of the column via electronic switches SHS1, SHR1, SHS2, and SHR2, respectively, corresponding to high and low values of the signals TSR and RST. The samples are combined in an appropriate fashion to cancel offset-induced errors, and provide spurious-free imaging with extended dynamic range.

Pain, Bedabrata↗
NASA NTRS2016

Pattern Recognition Control Design

Spacecraft control algorithms must know the expected spacecraft response to any command to the available control effectors, such as reaction thrusters or torque devices. Spacecraft control system design approaches have traditionally relied on the estimated vehicle mass properties to determine the desired force and moment, as well as knowledge of the effector performance to efficiently control the spacecraft. A pattern recognition approach can be used to investigate the relationship between the control effector commands and the spacecraft responses. Instead of supplying the approximated vehicle properties and the effector performance characteristics, a database of information relating the effector commands and the desired vehicle response can be used for closed-loop control. A Monte Carlo simulation data set of the spacecraft dynamic response to effector commands can be analyzed to establish the influence a command has on the behavior of the spacecraft. A tool developed at NASA Johnson Space Center (Ref. 1) to analyze flight dynamics Monte Carlo data sets through pattern recognition methods can be used to perform this analysis. Once a comprehensive data set relating spacecraft responses with commands is established, it can be used in place of traditional control laws and gains set. This pattern recognition approach can be compared with traditional control algorithms to determine the potential benefits and uses.

Gambone, Elisabeth↗
NASA NTRS1993

A Simplistic Look at Limit Stresses from Random Loading

Utilizing a continuous beam model, this report compares the potential stresses imposed on the beam from a random environment with those resulting from a typical static load analysis or test simulation. The Miles' equation used to develop peak response accelerations is shown to become a force equation in the hands of strength assessment personnel. This may prove to be unrealistic since hardware dynamic stresses are related to deflection rather than load. Correlation of the stress state for any static analysis or test with the actual dynamic response stress is strictly dependent upon how well the static deflections simulate the predominant dynamic mode shape. The report proposes that the general shape of this predominant mode, along with the peak response accelerations of major masses be used in strength assessments. From these data, a tailored enforced displacement loading may prove to be more effective in reproducing random induced stresses on flight hardware.

Lee, H. M.↗
NASA NTRS1972

Response of a seat-passenger system to impulsive loading.

This paper presents a summary of a study of the dynamic response of an aircraft seat-passenger system to impulsive loading typical of aircraft crash situations. A brief description of the computer model SIMULA is presented, and selected data from 305 separate cases which have been studied are discussed. Maximum system forces, displacements, velocities, and accelerations are presented as functions of velocity change, aircraft deceleration, crash pulse shape, passenger weight, and seat belt slack. Data from both single and coupled parameter studies are included. A correlation of SIMULA results with experimentally obtained data is made.

Collins, J. A.↗
NASA NTRS1972

The responses of the thermosphere due to a geomagnetic storm: A MHD model

A magnetohydrodynamics theory was used to study the dynamic response of the neutral atmosphere to a geomagnetic storm. A full set of magnetohydrodynamic equations appropriate for the present problem is derived and their various orders of approximation are discussed in some detail. In order to demonstrate the usefulness of this theoretical model, the May 1967 geomagnetic storm data were used in the resulting set of nonlinear, time dependent, partial differential magnetohydrodynamic equations to calculate variations of the thermosphere due to the storm. The numerical results are presented for wind speeds, electric field strength, and amount of joule heating at a constant altitude for the data recorded. Data show that the strongest thermospheric responses are at the polar region becoming weaker in the equatorial region. This may lead to the speculation that a thermospheric wave is generated in the polar region due to the geomagnetic storm which propagates towards the equator.

Wu, S. T.↗
NASA NTRS1984

Development of numerical procedures for analysis of complex structures

The paper is concerned with the development of novel numerical procedures for the solution of static, stability, free vibration and dynamic response analysis of large, complex practical structures. Thus, details of numerical algorithms evolved for dynamic analysis of usual non-rotating and also rotating structures as well as finite dynamic elements are presented in the paper. Furthermore, the article provides some description of a general-purpose computer program STARS specifically developed for efficient analysis of complex practical structures.

Gupta, K. K.↗
NASA NTRS2019

Sub-Picometer Dynamic Measurements of a Diffuse Surface

Future space observatory missions are forecasting the need for sensing and controlling wave front error and system alignment stability to picometer scale. Picometer stability performance demands precision knowledge of the mirror and metering structure materials to the same degree. A high-speed electronic speckle pattern interferometer was designed and built to demonstrate measurements of both static and dynamic responses of picometer amplitudes in materials of diffuse surface subjected to very low energy disturbances. This paper describes the details of a test to impart a dynamic disturbance of picometer scale and measure the response of a composite material.The results of the test are also reported and show conclusively that sub-picometer scale effects can be accurately measured in an open test environment outside a vacuum chamber.

Saif, Babak↗
NASA NTRS1995

Meso-beta scale numerical simulation studies of terrain-induced jet streak mass/momentum perturbations

Mesoscale model simulations provide insight into the complex jet streak adjustments on 11-12 July 1981 that preceded the first of two significant gravity wave events to have been generated over the Rocky Mountains in Montana. Simulations employing a variety of terrain treatments indicate that prior to wave formation, geostrophic adjustment processes modified the structure of the mid-upper tropospheric jet streak by creating secondary jetlets to the southeast of the polar jet streak in proximity to the gravity wave generation region. This simulated restructuring of the mid-upper tropospheric jet streak is the result of a four stage process. During stage 1, the wind adjusts to the mass field as the jet streak exit region propagates into the inflection point between the upstream trough and downstream ridge in the height field. Stage 2 is initiated as the mass field is forced to adjust to the new ageostrophic wind field created during stage 1. Stage 3 is defined by a second geostrophic adjustment process occurring in a similar manner but to the south and east of the adjustment which occurs during stage 1. A low-level mesoscale jetlet is formed during stage 4 in response to the low-level pressure falls that are established during stage 3. The perturbation of this jetlet, caused by orographically-induced adiabatic and diabatic physical processes, is the likely mechanism responsible for the generation of the first and second episode of observed gravity waves. The dynamics responsible for this wave episode are discussed as differential surface sensible heating inducing an orographically-forced mountain-plains solenoid, resulting in the formation of additional mesoscale jetlets and internal gravity waves. Also discussed is how convective latent heating modifies the numerically simulated terrain-induced internal gravity waves, especially their amplitude and phase velocities, which provide better agreement with those wave characteristics observed in nature. Finally, the three-dimensional linear response of a zonally uniform barotropic flow in a vertically unbounded, continuously stratified, Boussinesq atmosphere which is perturbed from geostrophic equilibrium is investigated.

Lin, Yuh-Lang↗
NASA NTRS1996

Layerwise Mechanics and Finite Elements for Smart Composite Structures with Piezoelectric Actuators and Sensors

Recent developments on layerwise mechanics for the analysis of composite laminates and structures with piezoelectric actuators and sensors are reviewed. The mechanics implement layerwise representations of displacements and electric potential, and can model both the global and local electromechanical response of smart composite structures. The corresponding finite-element implementations for the static and dynamic analysis of smart piezoelectric composite structures are also summarized. Select application illustrate the accuracy, robustness and capability of the developed mechanics to capture the global and local dynamic response of thin and/or thick laminated piezoelectric plates.

Saravanos, Dimitris A.↗
NASA NTRS2006

Flight Test of an Adaptive Controller and Simulated Failure/Damage on the NASA NF-15B

The method of flight-testing the Intelligent Flight Control System (IFCS) Second Generation (Gen-2) project on the NASA NF-15B is herein described. The Gen-2 project objective includes flight-testing a dynamic inversion controller augmented by a direct adaptive neural network to demonstrate performance improvements in the presence of simulated failure/damage. The Gen-2 objectives as implemented on the NASA NF-15B created challenges for software design, structural loading limitations, and flight test operations. Simulated failure/damage is introduced by modifying control surface commands, therefore requiring structural loads measurements. Flight-testing began with the validation of a structural loads model. Flight-testing of the Gen-2 controller continued, using test maneuvers designed in a sequenced approach. Success would clear the new controller with respect to dynamic response, simulated failure/damage, and with adaptation on and off. A handling qualities evaluation was conducted on the capability of the Gen-2 controller to restore aircraft response in the presence of a simulated failure/damage. Control room monitoring of loads sensors, flight dynamics, and controller adaptation, in addition to postflight data comparison to the simulation, ensured a safe methodology of buildup testing. Flight-testing continued without major incident to accomplish the project objectives, successfully uncovering strengths and weaknesses of the Gen-2 control approach in flight.

Buschbacher, Mark↗