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Thermal Structure Analysis of SIRCA Tile for X-34 Wing Leading Edge TPS
This paper will describe in detail thermal/structural analyses of SIRCA tiles which were performed at NASA Ames under the The Tile Analysis Task of the X-34 Program. The analyses used the COSMOS/M finite element software to simulate the material response in arc-jet tests, mechanical deflection tests, and the performance of candidate designs for the TPS system. Purposes of the analysis were to verify thermal and structural models for the SIRCA tiles, to establish failure criteria for stressed tiles, to simulate the TPS response under flight aerothermal and mechanical load, and to confirm that adequate safety margins exist for the actual TPS design.
Closed-Loop Simulation Study of the Ares I Upper Stage Thrust Vector Control Subsystem for Nominal and Failure Scenarios
As a replacement to the current Shuttle, the Ares I rocket and Orion crew module are currently under development by the National Aeronautics and Space Administration (NASA). This new launch vehicle is segmented into major elements, one of which is the Upper Stage (US). The US is further broken down into subsystems, one of which is the Thrust Vector Control (TVC) subsystem which gimbals the US rocket nozzle. Nominal and off-nominal simulations for the US TVC subsystem are needed in order to support the development of software used for control systems and diagnostics. In addition, a clear and complete understanding of the effect of off-nominal conditions on the vehicle flight dynamics is desired. To achieve these goals, a simulation of the US TVC subsystem combined with the Ares I vehicle as developed. This closed-loop dynamic model was created using Matlab s Simulink and a modified version of a vehicle simulation, MAVERIC, which is currently used in the Ares I project and was developed by the Marshall Space Flight Center (MSFC). For this report, the effects on the flight trajectory of the Ares I vehicle are investigated after failures are injected into the US TVC subsystem. The comparisons of the off-nominal conditions observed in the US TVC subsystem with those of the Ares I vehicle flight dynamics are of particular interest.
Reconfigurable Control with Neural Network Augmentation for a Modified F-15 Aircraft
Description of the performance of a simplified dynamic inversion controller with neural network augmentation follows. Simulation studies focus on the results with and without neural network adaptation through the use of an F-15 aircraft simulator that has been modified to include canards. Simulated control law performance with a surface failure, in addition to an aerodynamic failure, is presented. The aircraft, with adaptation, attempts to minimize the inertial cross-coupling effect of the failure (a control derivative anomaly associated with a jammed control surface). The dynamic inversion controller calculates necessary surface commands to achieve desired rates. The dynamic inversion controller uses approximate short period and roll axis dynamics. The yaw axis controller is a sideslip rate command system. Methods are described to reduce the cross-coupling effect and maintain adequate tracking errors for control surface failures. The aerodynamic failure destabilizes the pitching moment due to angle of attack. The results show that control of the aircraft with the neural networks is easier (more damped) than without the neural networks. Simulation results show neural network augmentation of the controller improves performance with aerodynamic and control surface failures in terms of tracking error and cross-coupling reduction.
Adaptive Control Using Neural Network Augmentation for a Modified F-15 Aircraft
Description of the performance of a simplified dynamic inversion controller with neural network augmentation follows. Simulation studies focus on the results with and without neural network adaptation through the use of an F-15 aircraft simulator that has been modified to include canards. Simulated control law performance with a surface failure, in addition to an aerodynamic failure, is presented. The aircraft, with adaptation, attempts to minimize the inertial cross-coupling effect of the failure (a control derivative anomaly associated with a jammed control surface). The dynamic inversion controller calculates necessary surface commands to achieve desired rates. The dynamic inversion controller uses approximate short period and roll axis dynamics. The yaw axis controller is a sideslip rate command system. Methods are described to reduce the cross-coupling effect and maintain adequate tracking errors for control surface failures. The aerodynamic failure destabilizes the pitching moment due to angle of attack. The results show that control of the aircraft with the neural networks is easier (more damped) than without the neural networks. Simulation results show neural network augmentation of the controller improves performance with aerodynamic and control surface failures in terms of tracking error and cross-coupling reduction.
Building Booster Separation Aerodynamic Databases for Artemis II
NASA’s Artemis II mission will mark the return of humans to near-lunar space for the first time since Apollo. Shortly after launch on the Space Launch System (SLS), a critical phase of ascent occurs when 16 small rockets fire to push the boosters away from the core. Minimizing the risk of failure during separation requires the construction of multiple 13-dimensional databases, including perturbations in position, flight conditions, and engine thrust. The SLS Computational Fluid Dynamics team used NASA’s FUN3D flow solver on the Pleiades and Electra supercomputers to run 5,780 simulations at nominal conditions and over 8,000 simulations with a core stage engine failure to generate the databases needed to verify the booster separation system for Artemis II.
Adaptive Stress Testing: Using Reinforcement Learning to Find Failures in Safety-Critical Systems
Emerging applications in artificial intelligence, such as driverless cars and autonomous aircraft promise to be more efficient, cheaper to operate, and always available. However, ensuring the safety of these systems remains a major challenge to their certification and adoption. These autonomous systems are expected to routinely make safety-critical decisions where failures can have serious consequences including loss of life and property. Testing and validation techniques aim to identify and diagnose potential failures before the system is deployed. However, finding failure scenarios in autonomous systems can be very challenging due to high-dimensional and continuous state spaces, interaction with large environments over many time steps, and the rarity of failures. This talk presents Adaptive Stress Testing (AST), a simulation-based testing framework for finding the most likely path to a failure event of a safety-critical system. The key idea of AST is that stress testing can be formulated as a Partially Observable Markov Decision Process (POMDP), which enables reinforcement learning techniques to be used for finding failure events. Reinforcement learning algorithms can efficiently explore the search space and have been shown to scale to very large systems. We present applications of AST to find failures in various safety-critical systems including the aircraft collision avoidance systems, autonomous cars, and small unmanned aerial vehicles.
Investigation of Tapered Roller Bearing Damage Detection Using Oil Debris Analysis
A diagnostic tool was developed for detecting fatigue damage to tapered roller bearings. Tapered roller bearings are used in helicopter transmissions and have potential for use in high bypass advanced gas turbine aircraft engines. This diagnostic tool was developed and evaluated experimentally by collecting oil debris data from failure progression tests performed by The Timken Company in their Tapered Roller Bearing Health Monitoring Test Rig. Failure progression tests were performed under simulated engine load conditions. Tests were performed on one healthy bearing and three predamaged bearings. During each test, data from an on-line, in-line, inductance type oil debris sensor was monitored and recorded for the occurrence of debris generated during failure of the bearing. The bearing was removed periodically for inspection throughout the failure progression tests. Results indicate the accumulated oil debris mass is a good predictor of damage on tapered roller bearings. The use of a fuzzy logic model to enable an easily interpreted diagnostic metric was proposed and demonstrated.
Development of GENOA Progressive Failure Parallel Processing Software Systems
A capability consisting of software development and experimental techniques has been developed and is described. The capability is integrated into GENOA-PFA to model polymer matrix composite (PMC) structures. The capability considers the physics and mechanics of composite materials and structure by integration of a hierarchical multilevel macro-scale (lamina, laminate, and structure) and micro scale (fiber, matrix, and interface) simulation analyses. The modeling involves (1) ply layering methodology utilizing FEM elements with through-the-thickness representation, (2) simulation of effects of material defects and conditions (e.g., voids, fiber waviness, and residual stress) on global static and cyclic fatigue strengths, (3) including material nonlinearities (by updating properties periodically) and geometrical nonlinearities (by Lagrangian updating), (4) simulating crack initiation. and growth to failure under static, cyclic, creep, and impact loads. (5) progressive fracture analysis to determine durability and damage tolerance. (6) identifying the percent contribution of various possible composite failure modes involved in critical damage events. and (7) determining sensitivities of failure modes to design parameters (e.g., fiber volume fraction, ply thickness, fiber orientation. and adhesive-bond thickness). GENOA-PFA progressive failure analysis is now ready for use to investigate the effects on structural responses to PMC material degradation from damage induced by static, cyclic (fatigue). creep, and impact loading in 2D/3D PMC structures subjected to hygrothermal environments. Its use will significantly facilitate targeting design parameter changes that will be most effective in reducing the probability of a given failure mode occurring.
Risk and Performance Assessment of Generic Mission Architectures: Showcasing the Artemis Mission
A has initiated a strong push to return face. In this work, we astronaut assess performance and risk for proposed mission architectures using a new Mission Architecture Risk Assessment (MARA) tool. The MARA tool can produce statistics about the availability of components and overall performance of the mission considering potential failures of any of its components. In a Monte Carlo approach, the tool repeats the mission simulation multiple times while a random generator lets modules fail according to their failure rates. The results provide statistically meaningful insights into the overall performance of the chosen architecture. A given mission architecture can be freely replicated in the tool, with the mission timeline and basic characteristics of employed mission modules (habitats, rovers, power generation units, etc.) specified in a configuration file. Crucially, failure rates for each module need to be known or estimated. The tool performs an event-driven simulation of the mission and accounts for random failure events. Failed modules can be repaired, which takes crew time but restores operations. In addition to tracking individual modules, MARA can assess the availability of predefined functions throughout the mission. For instance, the function of resource collection would require a rover to collect the resources, a power generation unit to charge the rover, and a resource processing module. Together, the modules that are required for a given function are called a functional group. Similarly, we can assess how much crew time is available to achieve a mission benefit (e.g. research, building a base, etc) as opposed to spending crew time on repairs. Here we employ the method on the proposed NASA Artemis mission. Artemis aims to return United States astronauts to the lunar surface by 2024. Results provide insights into mission failure probabilities, up- and downtime for individual modules and crew-time resources spent on the repair of failed modules. The tool also allows us to tweak the mission architecture in order to find setups that produce more favorable mission performance. As such, the tool can be an aid in improving the mission architect abling cost-benefit analysis for mission improvement.
Tapered Roller Bearing Damage Detection Using Decision Fusion Analysis
A diagnostic tool was developed for detecting fatigue damage of tapered roller bearings. Tapered roller bearings are used in helicopter transmissions and have potential for use in high bypass advanced gas turbine aircraft engines. A diagnostic tool was developed and evaluated experimentally by collecting oil debris data from failure progression tests conducted using health monitoring hardware. Failure progression tests were performed with tapered roller bearings under simulated engine load conditions. Tests were performed on one healthy bearing and three pre-damaged bearings. During each test, data from an on-line, in-line, inductance type oil debris sensor and three accelerometers were monitored and recorded for the occurrence of bearing failure. The bearing was removed and inspected periodically for damage progression throughout testing. Using data fusion techniques, two different monitoring technologies, oil debris analysis and vibration, were integrated into a health monitoring system for detecting bearing surface fatigue pitting damage. The data fusion diagnostic tool was evaluated during bearing failure progression tests under simulated engine load conditions. This integrated system showed improved detection of fatigue damage and health assessment of the tapered roller bearings as compared to using individual health monitoring technologies.
Dark Lock-in Thermography Identifies Solder Bond Failure as the Root Cause of Series Resistance Increase in Fielded Solar Modules
Correlating the electrical performance of photovoltaic modules to the spatially resolved photoluminescence, electroluminescence, and dark lock-in thermography (DLIT) images is an important long-term goal for developing solar cell technology. These images offer highly sophisticated and detailed information about the spatial distribution and (if imaged at successive time intervals) temporal degradation of local series and shunt resistances. There have been extensive studies to correlate these imaging techniques to local characteristics at the cell level. However, it has been difficult to extract and quantify module-level information from the techniques. In this study, we interpret module current-voltage (I-V) measurements along with corresponding DLIT images within a module-scale simulation framework, demonstrating that series resistance degradation of the module I-V characteristics, in this case, can be attributed to solder bond failures. Our simulations highlight how current crowding associated with a failed solder joint (or a section of the solder pad) translates to the characteristic point-like (asymmetric doublet) heating pattern in neighboring solder joints (or the neighboring regions of the solder pad). Overall, the correlation between series resistance and solder joint degradation could inform expedited diagnosis of field degradation of solar modules.
Numerical and experimental simulations of the postbuckling response of laminated anisotropic panels
Numerical simulations are used in conjuction with experiments to study the buckling and postbuckling responses and failure initiation of flat unstiffened composite panels. The numerical simulations are conducted using two-dimensional shear-flexible finite elements. The effect of the laminate stacking sequence on the buckling and postbuckling responses is studied. Correlation between numerical and experimental results is good through buckling, but the numerical models overestimate the postbuckling stiffness of the panels. To explain the discrepancies in the postbuckling stiffnesses, analytic sensitivity derivatives are calculated and are used to study the sensitivity of the buckling and postbuckling responses to variations in different material and lamination parameters of the panel. Experimental results indicate that failure occurs along a nodal line. Numerical results show that the location of failure initiation corresponds to that of the maximum transverse shear strain energy density in the panel, which occurs at the edge of the panel at a nodal line.
A New Local Failure Model with Application to the Longitudinal Tensile Behavior of Continuously Reinforced Titanium Composites
A new model for local fiber failures in composite materials loaded longitudinally is presented. In developing the model, the goal was to account for the effects of fiber breakage on the global response of a composite in a relatively simple and efficient manner. Towards this end, the model includes the important feature of local stress unloading, even as global loading of the composite continues. The model has been incorporated into NASA Glenn's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) and was employed to simulate the longitudinal tensile deformation and failure behavior of several silicon carbide fiber/titanium matrix (SiC/Ti) composites. The model is shown to be quite realistic and capable of accurate predictions for various temperatures, fiber volume fractions, and fiber diameters. Further- more, the new model compares favorably to Curtin's (1993) effective fiber breakage model, which has also been incorporated into MAC/GMC.
Parametric Failures in COTS Capacitors
Insertion of COTS components into hi-rel systems require extensive environmental testing of the parts that often results in parametric failures. Based on experience with commercial and hi-rel PME and BME ceramic capacitors and polymer and MnO2 cathode tantalum capacitors, this presentation discusses two major reasons for parametric failures. One is due to the marketing pressure that forces manufacturers to squeeze performance of COTS components thus leaving insufficient margin between the rated and actual characteristics. Another, and probably a more serious reason is degradation of characteristics caused by physico-chemical processes in materials under environmental stresses. Reliability assessment requires development of models to predict behavior of the parts during applications based on accelerated testing that might be outside the specified conditions and target applications. Examples of models developed to simulate and predict wear-out failures are presented. Risks associated with overstressing during HALT are discussed.
Developing acceptance limits for measured bearing wear of the Space Shuttle Main Engine high pressure oxidizer turbopump
The probabilistic design approach currently receiving attention for structural failure modes has been adapted for obtaining measured bearing wear limits in the Space Shuttle Main Engine high-pressure oxidizer turbopump. With the development of the shaft microtravel measurements to determine bearing health, an acceptance limit was neeed that protects against all known faiure modes yet is not overly conservative. This acceptance criteria limit has been successfully determined using probabilistic descriptions of preflight hardware geometry, empirical bearing wear data, mission requirements, and measurement tool precision as an input for a Monte Carlo simulation. The result of the simulation is a frequency distribution of failures as a function of preflight acceptance limits. When the distribution is converted into a reliability curve, a conscious risk management decision is made concerning the acceptance limit.
A.I.-based real-time support for high performance aircraft operations
Artificial intelligence (AI) based software and hardware concepts are applied to the handling system malfunctions during flight tests. A representation of malfunction procedure logic using Boolean normal forms are presented. The representation facilitates the automation of malfunction procedures and provides easy testing for the embedded rules. It also forms a potential basis for a parallel implementation in logic hardware. The extraction of logic control rules, from dynamic simulation and their adaptive revision after partial failure are examined. It uses a simplified 2-dimensional aircraft model with a controller that adaptively extracts control rules for directional thrust that satisfies a navigational goal without exceeding pre-established position and velocity limits. Failure recovery (rule adjusting) is examined after partial actuator failure. While this experiment was performed with primitive aircraft and mission models, it illustrates an important paradigm and provided complexity extrapolations for the proposed extraction of expertise from simulation, as discussed. The use of relaxation and inexact reasoning in expert systems was also investigated.
Micromechanics analysis of space simulated thermal stresses in composites. I - Theory and unidirectional laminates. II - Multidirectional laminates and failure predictions
A micromechanics analysis is used to study the effects of constituent properties on thermally induced stresses in continuous fiber reinforced composites. A finite element formulation is described, and results are presented for unidirectional carbon/epoxy laminates. It is shown that significant stresses develop in composites exposed to thermal excursions typical of spacecraft operating environments and that the fiber thermoelastic properties have a minimal effect on the magnitude of these stresses. The finite element micromechanics analysis is then extended to the study of multidirectional laminates using a simple global/local formulation. Damage initiation predictions are compared with experimental data, and factors controlling the initiation of damage are identified. Ways of improving the durability of composites are discussed.