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At least 541 records · Page 30

All sources NASA NTRS DOE OSTI

NASA NTRS2014

Damage Simulation in Non-Crimp Fabric Composite Plates Subjected to Impact Loads

Progressive failure analysis (PFA) of non-crimp fabric (NCF) composite laminates subjected to low velocity impact loads was performed using the COmplete STress Reduction (COSTR) damage model implemented through VUMAT and UMAT41 user subroutines in the frame works of the commercial finite element programs ABAQUS/Explicit and LS-DYNA, respectively. To validate the model, low velocity experiments were conducted and detailed correlations between the predictions and measurements for both intra-laminar and inter-laminar failures were made. The developed material and damage model predicts the peak impact load and duration very close with the experimental results. Also, the simulation results of delamination damage between the ply interfaces, in-plane matrix damages and fiber damages were all in good agreement with the measurements from the non-destructive evaluation data.

Satyanarayana, Arunkumar↗

NASA NTRS1991

Probabilistic simulation of the human factor in structural reliability

Many structural failures have occasionally been attributed to human factors in engineering design, analyses maintenance, and fabrication processes. Every facet of the engineering process is heavily governed by human factors and the degree of uncertainty associated with them. Factors such as societal, physical, professional, psychological, and many others introduce uncertainties that significantly influence the reliability of human performance. Quantifying human factors and associated uncertainties in structural reliability require: (1) identification of the fundamental factors that influence human performance, and (2) models to describe the interaction of these factors. An approach is being developed to quantify the uncertainties associated with the human performance. This approach consists of a multi factor model in conjunction with direct Monte-Carlo simulation.

Shah, Ashwin R.↗

NASA NTRS1994

Sensor Fault Detection and Diagnosis Simulation of a Helicopter Engine in an Intelligent Control Framework

This paper presents an application of a fault detection and diagnosis scheme for the sensor faults of a helicopter engine. The scheme utilizes a model-based approach with real time identification and hypothesis testing which can provide early detection, isolation, and diagnosis of failures. It is an integral part of a proposed intelligent control system with health monitoring capabilities. The intelligent control system will allow for accommodation of faults, reduce maintenance cost, and increase system availability. The scheme compares the measured outputs of the engine with the expected outputs of an engine whose sensor suite is functioning normally. If the differences between the real and expected outputs exceed threshold values, a fault is detected. The isolation of sensor failures is accomplished through a fault parameter isolation technique where parameters which model the faulty process are calculated on-line with a real-time multivariable parameter estimation algorithm. The fault parameters and their patterns can then be analyzed for diagnostic and accommodation purposes. The scheme is applied to the detection and diagnosis of sensor faults of a T700 turboshaft engine. Sensor failures are induced in a T700 nonlinear performance simulation and data obtained are used with the scheme to detect, isolate, and estimate the magnitude of the faults.

Litt, Jonathan↗

DOE OSTI2025

FIRE: A Failure-Adaptive RL Framework for Edge Computing Migrations

In edge computing, users' service profiles are migrated between edge servers due to user mobility. Reinforcement Learning (RL) frameworks have been proposed to do so, often trained on simulated data. However, existing RL frameworks overlook occasional server failures, which although rare, impact latency-sensitive applications like AR/VR and real- time obstacle detection. These rare failures, being not adequately represented in historical training data, pose a challenge for data-driven RL algorithms. We introduce FIRE, a framework that adapts to rare events by training a RL policy in an edge computing digital twin environment. We propose FIRE-ImRE, an importance sampling-based Q-learning algorithm, which samples rare events proportionally to their impact on the value function. FIRE considers delay, migration, failure, and backup placement costs across individual and shared service profiles. We prove FIRE-ImRE's boundedness and convergence to optimality. Next, we introduce novel deep Q-learning (FIRE-ImDQL) and actor critic (FIRE-ImACRE) versions of our algorithm to enhance scalability. Here, we extend our framework to accommodate users with varying risk tolerances of rare failure events. Through trace-driven experiments, we show that FIRE reduces edge computing costs compared to vanilla RL and the greedy baseline in the event of failures.

Edge computing↗

NASA NTRSDate not supplied

Building and Breaking Carbon Composites with REACTER

Carbon composites have become indispensable for aerospace and other high-performance applications, and a detailed picture of their morphology and failure mechanisms remains difficult to obtain through experiment. REACTER is a versatile computational modeling tool for atomistic molecular dynamics designed to model chemical reactions at the speed and length scales of classical force fields.1 In this work, several recent features of REACTER were applied to the creation and subsequent mechanical testing of two classes of carbon composites, carbon-fiber reinforced polymers (CFRP) and carbon nanotube (CNT) composites. Carbon fiber core morphologies were created by the method of Desai et al.,2 but using the advanced reaction constraints framework of REACTER, their proposed multistep procedure was reduced to a single uninterrupted molecular dynamics simulation. The carbon fiber filler was embedded into a polymer matrix by simulated in situ polymerization of several thermosetting resins, including bismaleimide and polyarylacetylene, to obtain the final CFRP model. To generate the second class of carbon composite, CNT networks were grown dynamically using the new ‘create atoms’ feature of REACTER, and similarly infiltrated with resin to obtain CNT composites. The resulting models were compared directly to experiment using simulated high resolution transmission electron microscopy and x-ray diffraction. Failure mechanisms were elucidated by simulating mechanically induced bond breaking, as characterized by third-order DFT-based tight-binding (DFTB3) simulations, via a reaction constraint on the total potential energy of the involved atoms.

Molecular Dynamics↗

NASA NTRSDate not supplied

Enabling Nuclear and Solar Thermal Propulsion with the Computational Laboratory: Faster and Cheaper Materials Characterization

Nuclear and solar thermal propulsion offer enhanced efficiencies for in-space travel which may open up the outer Solar System to both crewed and automated craft. However, these advanced propulsion systems require cutting-edge materials which are often not easily tested in the laboratory. Ab initio thermodynamics and other computational methods offer a way to test materials at high pressures and temperatures more quickly, and with reduced cost. Here, several case studies are presented which highlight the utility of modern simulation techniques. First, an extensive thermodynamic study was performed at the ab initio level to elucidate the role of hot hydrogen flow on the erosion of four refractory carbides to examine their appropriateness for use as channel coatings. A detailed analysis of reaction products informs estimates of erosion which are validated in comparison with heritage NERVA data. Specific material suggestions are made for both nuclear and solar designs. Secondly, we examined the mechanical behavior and chemical stability of various components of an idealized nuclear cermet core design using techniques spanning from the atomic to microscale. Next, the mechanical and chemical behavior of tungsten (a potential matrix material) and the stability of uranium mononitride (a potential ceramic fuel element), are characterized in the presence of hydrogen and at elevated temperatures with ab initio thermodynamics. Finally, the mechanical response and failure of tungsten under tensile strain is simulated at the micron scale with a combined finite element and dislocation dynamics approach. The resultant stress-strain data agrees well with experiments and leads to a workflow which can incorporate ab initio thermodynamic data into micron-scale simulations and thus provide real-world relevant estimates of erosion and stress-strain behavior. The power of this framework and our plans to use it in the future will be discussed.

William C Tucker↗

DOE OSTI2023

Analyzing Hardware and Software Common Cause Failures in Digital Instrumentation and Control Systems using Dual Error Propagation Method

This paper develops a methodology for quantifying software common cause failures (CCFs) in digital instrumentation and control (I&C) systems of nuclear power plants. To support the transition of analog I&C systems to digital in nuclear power plants, probabilistic risk assessment (PRA) techniques are used. The hardware components of the I&C systems have reliability databases that can be used in the PRA studies. However, the failure data for redundant software components of the systems is sparse. Failure of components constitutes a CCF, wherein two or more components or systems fail due to a single shared cause and coupling mechanism. This paper proposes a quantification approach that can simultaneously model hardware and software components, incorporate the CCFs of software systems in the models, and bridge the gap between the failure quantification of models and the development of CCF parametric databases. We demonstrate the dual error propagation method (DEPM) by developing I&C systems failure models for a representative digital reactor trip system. The DEPM models are built to simulate the control and data flows within the systems and can accommodate failure states. By expanding DEPM to software CCFs, we generated alpha factor parameter estimates for each of the modeled error propagation mechanisms.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Accumulation of collagen molecular unfolding is the mechanism of cyclic fatigue damage and failure in collagenous tissues

Overuse injuries to dense collagenous tissues are common, but their etiology is poorly understood. The predominant hypothesis that micro-damage accumulation exceeds the rate of biological repair is missing a mechanistic explanation. Here, we used collagen hybridizing peptides to measure collagen molecular damage during tendon cyclic fatigue loading and computational simulations to identify potential explanations for our findings. Our results revealed that triple-helical collagen denaturation accumulates with increasing cycles of fatigue loading, and damage is correlated with creep strain independent of the cyclic strain rate. Finite-element simulations demonstrated that biphasic fluid flow is a possible fascicle-level mechanism to explain the rate dependence of the number of cycles and time to failure. Molecular dynamics simulations demonstrated that triple-helical unfolding is rate dependent, revealing rate-dependent mechanisms at multiple length scales in the tissue. The accumulation of collagen molecular denaturation during cyclic loading provides a long-sought “micro-damage” mechanism for the development of overuse injuries.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRSDate not supplied

Mitigation of High Lateral Asymmetry Rates Due to Loss of a Cruise Motor on the X-57 Mod III Aircraft

The X-57 Mod III aircraft utilizes wingtip electric motors to generate thrust. The potential benefit of wingtip propulsion is a reduction in induced drag because wingtip vortices are interrupted. Wingtip propulsors, however, pose the risk of dangerous thrust asymmetry if one of the motors abruptly stops producing full thrust. This paper examines the effects of a full-power, single-motor failure at various phases of flight for the X-57 Mod III aircraft design by way of piloted-in-the-loop simulations conducted by two National Aeronautics and Space Administration test pilots. After determining that a failure during takeoff potentially poses the highest risk of catastrophic consequences, possible mitigations to the failure were explored and evaluated through pilot simulation data, Cooper-Harper ratings, and pilot comments. The preferred mitigation was found to be an automated power reduction system that allowed for a lower pilot workload and quick reduction of the asymmetric thrust.

Ryan Wallace↗

NASA NTRS1973

Failure management of multiple gimbal inertial systems for space shuttle

A failure detection and isolation technique for use with four gimbaled inertial measurement units (IMU) is presented. By using simulated boost and entry shuttle trajectories with specific gimbaled IMU models, failure detection thresholds are developed based on red-line life dependent requirements and warning thresholds within the red-line thresholds based on expected worst case IMU performance. Using these trajectories, established trajectory threshold, and multiple IMU models, various failure detection and isolation techniques are evaluated for application in both powered and unpowered flight phases. The adequacy of the systems for both attitude and velocity detection methods is evaluated and recommendations for space shuttle applications are made.

Dove, D. W.↗

NASA NTRS1992

Analytic redundancy management for large flexible structures

An analytic redundancy management approach for on-line component failure detection is described and illustrated using a simulation of the NASA Langley Spacecaft Control Laboratory Experiment (SCOLE) research facility. The SCOLE experimental apparatus simulated is a functional model of the Space Shuttle with a large, flexible, offset-feed antenna cantilevered from the payload bay. This approach uses a single, active, Kalman filter selected from a bank of filters, each element of which was previously designed to accommodate a specific failure condition. The residuals of this active filter are processed through a sequential probability ratio test (SPRT) filter to identify the failure state of the system and, hence, closing the failure accommodation loop, to select the active filter. Results are presented that illustrate the ability of the system to detect and recover from failures introduced in the angular rate and linear acceleration sensors on the SCOLE facility.

Shenhar, J.↗

NASA NTRS2005

Inductive Learning Approaches for Improving Pilot Awareness of Aircraft Faults

Neural network flight controllers are able to accommodate a variety of aircraft control surface faults without detectable degradation of aircraft handling qualities. Under some faults, however, the effective flight envelope is reduced; this can lead to unexpected behavior if a pilot performs an action that exceeds the remaining control authority of the damaged aircraft. The goal of our work is to increase the pilot s situational awareness by informing him of the type of damage and resulting reduction in flight envelope. Our methodology integrates two inductive learning systems with novel visualization techniques. One learning system, the Inductive Monitoring System (IMS), learns to detect when a simulation includes faulty controls, while two others, Inductive Classification System (INCLASS) and multiple binary decision tree system (utilizing C4.5), determine the type of fault. In off-line training using only non-failure data, IMS constructs a characterization of nominal flight control performance based on control signals issued by the neural net flight controller. This characterization can be used to determine the degree of control augmentation required in the pitch, roll, and yaw command channels to counteract control surface failures. This derived information is typically sufficient to distinguish between the various control surface failures and is used to train both INCLASS and C4.5. Using data from failed control surface flight simulations, INCLASS and C4.5 independently discover and amplify features in IMS results that can be used to differentiate each distinct control surface failure situation. In real-time flight simulations, distinguishing features learned during training are used to classify control surface failures. Knowledge about the type of failure can be used by an additional automated system to alter its approach for planning tactical and strategic maneuvers. The knowledge can also be used directly to increase the pilot s situational awareness and inform manual maneuver decisions. Our multi-modal display of this information provides speech output to issue control surface failure warnings to a lesser-used communication channel and provides graphical displays with pilot-selectable !eve!s of details to issues additional information about the failure. We also describe a potential presentation for flight envelope reduction that can be viewed separately or integrated with an existing attitude indicator instrument. Preliminary results suggest that the inductive approach is capable of detecting that a control surface has failed and determining the type of fault. Furthermore, preliminary evaluations suggest that the interface discloses a concise summary of this information to the pilot.

Spikovska, Lilly↗

NASA NTRS2014

Increased Mach Number Capability for the NASA Glenn 10x10 Supersonic Wind Tunnel

Computational simulations and wind tunnel testing were conducted to explore the operation of the Abe Silverstein Supersonic Wind Tunnel at the NASA Glenn Research Center at test section Mach numbers above the current limit of Mach 3.5. An increased Mach number would enhance the capability for testing of supersonic and hypersonic propulsion systems. The focus of the explorations was on understanding the flow within the second throat of the tunnel, which is downstream of the test section and is where the supersonic flow decelerates to subsonic flow. Methods of computational fluid dynamics (CFD) were applied to provide details of the shock boundary layer structure and to estimate losses in total pressure. The CFD simulations indicated that the tunnel could be operated up to Mach 4.0 if the minimum width of the second throat was made smaller than that used for previous operation of the tunnel. Wind tunnel testing was able to confirm such operation of the tunnel at Mach 3.6 and 3.7 before a hydraulic failure caused a stop to the testing. CFD simulations performed after the wind tunnel testing showed good agreement with test data consisting of static pressures along the ceiling of the second throat. The CFD analyses showed increased shockwave boundary layer interactions, which was also observed as increased unsteadiness of dynamic pressures collected in the wind tunnel testing.

Wind tunnel↗

NASA NTRS2015

Increased Mach Number Capability for the NASA Glenn 10x10 Supersonic Wind Tunnel

Diffuser↗

NASA NTRSDate not supplied

Fracture of Charring Avcoat With Meshfree Material Response-Coupled Fracture Approach

Fracture of thermal protection systems (TPS) is typically unfavorable, but often unavoidable. TPS can fracture during entry, manufacturing or from impact. Many NASA missions use ablative materials for TPS, including the fore-body for Dragonfly (PICA) and Orion for Artemis-I (Avcoat). The material response to thermal and mechanical loads during entry is integral to TPS sizing, design and analysis. The fracture of TPS also depends, and can be caused by, the change of material properties during entry. Simulations that resolve fracture of TPS due to thermo-mechanical forces can identify TPS failure mechanisms and be applied to conditions inaccessible to ground testing. We present simulation work using a mesh-free/Lagrangian approach to solving continuum mechanics, coupled to material response. Two different materials are simulated under different model entry-like boundary conditions. The dynamic crack structure is analyzed and compared across simulations. Crack analyses inform the role of design features, such as entry trajectories and manufacturing-influenced material properties, play in TPS fracture.

Andrew P Santos↗

NASA NTRS1986

Piloted simulation study of the effects of an automated trim system on flight characteristics of a light twin-engine airplane with one engine inoperative

A simulation study was conducted to investigate the piloting problems associated with failure of an engine on a generic light twin-engine airplane. A primary piloting problem for a light twin-engine airplane after an engine failure is maintaining precise control of the airplane in the presence of large steady control forces. To address this problem, a simulated automatic trim system which drives the trim tabs as an open-loop function of propeller slipstream measurements was developed. The simulated automatic trim system was found to greatly increase the controllability in asymmetric powered flight without having to resort to complex control laws or an irreversible control system. However, the trim-tab control rates needed to produce the dramatic increase in controllability may require special design consideration for automatic trim system failures. Limited measurements obtained in full-scale flight tests confirmed the fundamental validity of the proposed control law.

Stewart, E. C.↗

DOE OSTI2020

Tuning the Mechanical Properties of Shape Memory Metallic Glass Composites with Brick and Mortar Designs

We use molecular dynamics simulations to characterize the tensile deformation and failure of shape memory alloy-bulk metallic glass composites (BMGCs). As the failure in BMGCs shifts from the MG matrix to the second phase different strategies are required to further improve their mechanical properties. Results show that a staggered brick BMGC displays enhanced ductility with mild strength loss following a homogeneously distributed plasticity. This demonstrates that judiciously designed BMGCs can effectively synergize the mechanical properties of metallic glasses and shape memory alloys by effectively distributing stress and preventing the generation of critical shear bands and premature failure while preserving strength.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Tuning the mechanical properties of nanoglass-metallic glass composites with brick and mortar designs

We use molecular dynamics simulations to characterize the tensile deformation and failure of metallic glass (MG)-nanoglass (NG) composites designed with a brick and mortar architecture consisting of a 3 nm-grain-size NG matrix and a MG second phase. Results show that the overall strength of the matrix is significantly improved by the second phase without sacrificing the large NG matrix ductility. The mechanical synergy of the two phases is optimized by arranging the MG bricks in a staggered way, which effectively delocalizes the plastic deformation, hindering the buildup of local stress hot spots and the generation of critical shear bands.

36 MATERIALS SCIENCE↗