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At least 1,495 records · Page 83

Investigation of heat transfer in zirconium potassium perchlorate at low temperature: A study of the failure mechanism of the NASA standard initiator

The objective of this work was to study the reasons for the failure of pyrotechnic initiators at very low temperatures (10 to 100 K). A two-dimensional model of the NASA standard initiator was constructed to model heat transfer from the electrically heated stainless steel bridgewire to the zirconium potassium perchlorate explosive charge and the alumina charge cup. Temperature dependent properties were used in the model to simulate initiator performance over a wide range of initial temperatures (10 to 500 K). A search of the thermophysical property data base showed that pure alumina has a very high thermal conductivity at low temperatures. It had been assumed to act as a thermal insulator in all previous analyses. Rapid heat transfer from the bridgewire to the alumina at low initial temperatures was shown to cause failure of the initiators if the wire did not also make good contact with the zirconium potassium perchlorate charge. The mode is able to reproduce the results of the tests that had been conducted to investigate the cause for failure. It also provides an explanation for previously puzzling results and suggests simple design changes that will increase reliability at very low initial temperatures.

Varghese, Philip L.↗

Rancor-HUNTER: A Virtual Plant and Operator Environment for Predicting Human Performance

Advances in simulation capabilities to model physical systems have outpaced the development of simulations for humans using those physical systems. There is an argument that the infinite span of potential human behaviors inherently render human modeling more challenging than physical systems. Despite this challenge, the need for modeling humans interacting with these complex systems is paramount. As technologies have improved, many of the failure modes originating from the physical systems have been solved. This means the overall proportion of human errors has increased, such that it is not uncommon to be the primary driver of system failure in modern complex systems. Moreover, technologies such as automated systems may introduce emerging contexts that can cause new, unanticipated modes of human error. Therefore, it is now more important than ever to develop models of human behavior to realize overall system error reductions and achieve established safety margins. To support new and novel concepts of operations for the anticipated wave of advanced nuclear reactor deployments, human factors and human reliability analysis researchers need to develop advanced simulation-based approaches. This talk presents a simulation environment suitable to both collect data and then perform Monte Carlo simulations to evaluate human performance and develop better models of human behavior. Specifically, the Rancor Microworld Simulator models a complex energy production system in a simplified manner. Rancor includes computer-based procedures, which serve as a framework to automatically classify human behaviors without manual, subjective experimenter coding during scenarios. This method supports a detailed level of analysis at the task level. It is feasible for collecting large sample sizes required to develop quantitative modelling elements that have historically challenged traditional full-scope simulator study approaches. Additionally, the other portion of this experimental platform, the Human Unimodel for Nuclear Technology to Enhance Reliability (HUNTER), is presented to show how the collected data can be used to evaluate novel scenarios based on the contextual factors, or performance shaping factors, derived from Rancor simulations. Rancor-HUNTER is being used to predict operator performance with new procedures, such as results from control room modernization or new-build situations. Rancor-HUNTER is also proving a useful surrogate platform to model human performance for other complex systems.

99 GENERAL AND MISCELLANEOUS↗

Regional surrogates for predictive control of digital twins

Digital twins of complex systems must involve a model that is fast, generalizable, and usable for real-time control. For example, high-fidelity nonlinear multiphysics simulations can capture laser-material interactions, but are too slow for optimization or model predictive control (MPC). Reduced-order models, used to accelerate such computation, frequently fail to generalize to unseen inputs or control states. We show theoretically that this failure is intrinsic, i.e., that a learned model is non-unique outside the sampled subspace when its low-rank structure arises from limited excitation and clustered eigenvalues, rather than from a user-imposed truncation alone. Motivated by this result, we propose a control-ready regional surrogate-construction framework for both autonomous and nonautonomous dynamics; it employs Koopman lifting to represent nonlinearities, while preserving spatial locality. We illustrate our approach by constructing a control-ready surrogate for the digital twin of a thermal component of additive-manufacturing process. Our surrogate, localized in space through a von Neumann stencil, is learned from noisy high-fidelity simulations that emulate thermal-camera images collected during the manufacturing. It is linear in thermo-physically augmented states so that MPC reduces to a convex quadratic program. The surrogate requires no online correction, generalizes to unseen scan paths and power profiles of the laser, and is more than three orders of magnitude faster than a finite-difference solver. Furthermore, when the MPC sequence computed on the digital twin is applied to this solver, closed-loop temperature regulation is recovered, showing that the surrogate preserves control-relevant input-output behavior.

Data-driven model↗

Objective Motion Cueing Criteria Investigation Based on Three Flight Tasks

This paper intends to help establish fidelity criteria to accompany the simulator motion system diagnostic test specified by the International Civil Aviation Organization. Twelve air- line transport pilots flew three tasks in the NASA Vertical Motion Simulator under four different motion conditions. The experiment used three different hexapod motion configurations, each with a different tradeoff between motion filter gain and break frequency, and one large motion configuration that utilized as much of the simulator's motion space as possible. The motion condition significantly affected: 1) pilot motion fidelity ratings, and sink rate and lateral deviation at touchdown for the approach and landing task, 2) pilot motion fidelity ratings, roll deviations, maximum pitch rate, and number of stick shaker activations in the stall task, and 3) heading deviation after an engine failure in the takeoff task. Significant differences in pilot-vehicle performance were used to define initial objective motion cueing criteria boundaries. These initial fidelity boundaries show promise but need refinement.

pilot training↗

Comparison of Adhesion and Retention Forces for Two Candidate Docking Seal Elastomers

To successfully mate two pressurized vehicles or structures in space, advanced seals are required at the interface to prevent the loss of breathable air to the vacuum of space. A critical part of the development testing of candidate seal designs was a verification of the integrity of the retaining mechanism that holds the silicone seal component to the structure. Failure to retain the elastomer seal during flight could liberate seal material in the event of high adhesive loads during undocking. This work presents an investigation of the force required to separate the elastomer from its metal counter-face surface during simulated undocking as well as a comparison to that force which was necessary to destructively remove the elastomer from its retaining device. Two silicone elastomers, Wacker 007-49524 and Esterline ELASA-401, were evaluated. During the course of the investigation, modifications were made to the retaining devices to determine if the modifications improved the force needed to destructively remove the seal. The tests were completed at the expected operating temperatures of -50, +23, and +75 C. Under the conditions investigated, the comparison indicated that the adhesion between the elastomer and the metal counter-face was significantly less than the force needed to forcibly remove the elastomer seal from its retainer, and no failure would be expected.

Hartzler, Brad D.↗

Electro-Thermal Simulation Studies of SiC Junction Diodes Containing Screw Dislocations Under High Reverse-Bias Operation

The objective of this work was to conduct a modeling study of SiC P-N junction diodes operating under high reverse biased conditions. Analytical models and numerical simulation capabilities were to be developed for self-consistent electro-thermal analysis of the diode current-voltage (I-V) characteristics. Data from GRC indicate that screw dislocations are unavoidable in large area SiC devices, and lead to changes in the SiC diode electrical response characteristics under high field conditions. For example, device instability and failures linked to internal current filamentation have been observed. The physical origin of these processes is not well understood, and quantitative projections of the electrical behavior under high field and temperature conditions are lacking. Thermal calculations for SiC devices have not been reported in the literature either. So estimates or projections of peak device temperatures and power limitations do not exist. This numerical study and simulation analysis was aimed at resolving some of the above issues. The following tasks were successfully accomplished: (1) Development of physically based models using one- and two-dimensional drift-diffusion theory for the transport behavior and I-V characteristics; (2) One- and two-dimensional heat flow to account for internal device heating. This led to calculations of the internal temperature profiles, which in turn, were used to update the electrical transport parameters for a self-consistent analysis. The temperature profiles and the peak values were thus obtainable for a given device operating condition; (3) Inclusion of traps assumed to model the presence of internal screw dislocations running along the longitudinal direction; (4) Predictions of the operating characteristics with and without heating as a function of applied bias with and without traps. Both one and two-dimensional cases were implemented; (5) Assessment of device stability based on the operating characteristics. The presence of internal non-uniformities, particularly filamentary structures, was probed and demonstrated; (6) Cause and physical origins of filamentary behavior and unstable I-V characteristics were made transparent; (7) It was demonstrated that diodes containing defects would be more prone to thermal breakdown associated with the temperature dependent decrease in the thermal conductivity; and (8) Finally, negative differential resistance (S-shaped NDR) which can potential lead to device instability and filamentary behavior was shown to occur for diodes containing a line of defects such as could be associated with a screw dislocation line.

Joshi, R. P.↗

Controlling Tensegrity Robots Through Evolution

Tensegrity structures (built from interconnected rods and cables) have the potential to offer a revolutionary new robotic design that is light-weight, energy-efficient, robust to failures, capable of unique modes of locomotion, impact tolerant, and compliant (reducing damage between the robot and its environment). Unfortunately robots built from tensegrity structures are difficult to control with traditional methods due to their oscillatory nature, nonlinear coupling between components and overall complexity. Fortunately this formidable control challenge can be overcome through the use of evolutionary algorithms. In this paper we show that evolutionary algorithms can be used to efficiently control a ball-shaped tensegrity robot. Experimental results performed with a variety of evolutionary algorithms in a detailed soft-body physics simulator show that a centralized evolutionary algorithm performs 400 percent better than a hand-coded solution, while the multi-agent evolution performs 800 percent better. In addition, evolution is able to discover diverse control solutions (both crawling and rolling) that are robust against structural failures and can be adapted to a wide range of energy and actuation constraints. These successful controls will form the basis for building high-performance tensegrity robots in the near future.

Robot↗

Towards a unified nonlocal, peridynamics framework for the coarse-graining of molecular dynamics data with fractures

Molecular dynamics (MD) has served as a powerful tool for designing materials with reduced reliance on laboratory testing. However, the use of MD directly to treat the deformation and failure of materials at the mesoscale is still largely beyond reach. In this work, we propose a learning framework to extract a peridynamics model as a mesoscale continuum surrogate from MD simulated material fracture data sets. Firstly, we develop a novel coarse-graining method, to automatically handle the material fracture and its corresponding discontinuities in the MD displacement data sets. Inspired by the weighted essentially non-oscillatory (WENO) scheme, the key idea lies at an adaptive procedure to automatically choose the locally smoothest stencil, then reconstruct the coarse-grained material displacement field as the piecewise smooth solutions containing discontinuities. Then, based on the coarse-grained MD data, a two-phase optimization-based learning approach is proposed to infer the optimal peridynamics model with damage criterion. In the first phase, we identify the optimal nonlocal kernel function from the data sets without material damage to capture the material stiffness properties. Then, in the second phase, the material damage criterion is learnt as a smoothed step function from the data with fractures. As a result, a peridynamics surrogate is obtained. As a continuum model, our peridynamics surrogate model can be employed in further prediction tasks with different grid resolutions from training, and hence allows for substantial reductions in computational cost compared with MD. We illustrate the efficacy of the proposed approach with several numerical tests for the dynamic crack propagation problem in a single-layer graphene. Our tests show that the proposed data-driven model is robust and generalizable, in the sense that it is capable of modeling the initialization and growth of fractures under discretization and loading settings that are different from the ones used during training.

97 MATHEMATICS AND COMPUTING↗

DEM analysis of the effect of interface transition zone on dynamic splitting tensile behavior of high-strength concrete based on multi-phase model

Highlights: • Crushable aggregates with the real geometry shape are generated by using clump-cluster method. • Flat-Joint Model is adopted as the constitutive law. • The tensile strength is almost not affected by ITZ strength when its strength exceeds 0.8 times that of mortar. • A modified formula that can reflect the functional relationship between the ITZ strength and the TDIF is proposed. The tensile strength is one of the main parameters in the design of concrete structures and has an important influence on the cracking performance and durability of concrete materials. As the weak region in concrete, the strength of the interface transition zone (ITZ) directly affects the dynamic mechanical response of concrete. Meanwhile, considering that the tensile performance of concrete is far weaker than its compressive performance, the study of the strength of ITZ is of great significance to the dynamic tensile fracture characteristics and mechanical properties of concrete. In this paper, a method combining 3D scanning technology and Clump-Cluster was proposed to generate a real geometry shape model of crushable aggregate. On this basis, the 3D discrete element model (DEM) of high-strength concrete was constructed using the Flat-Joint Model (FJM). The effects of the ITZ strength on the failure mode, number of microcracks, tensile strength and strain rate effect of high-strength concrete under strain rates from 0.01/s to 100/s were studied by splitting tensile test. The simulation results indicate that the number of microcracks generated decreases with the increase of ITZ strength, and the proportion of ITZ cracks decreases obviously. When the ITZ strength exceeds the critical value of 0.8 times that of mortar, the tensile strength is almost not affected by ITZ strength. In addition, based on the numerical simulation results, a modified formula that can reflect the functional relationship between the ITZ strength and the dynamic increasing factor of the concrete tensile strength (TDIF) is proposed, and the rationality of the TDIF modified formula is verified.

36 MATERIALS SCIENCE↗

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects by Incorporating Machine Learning Techniques

The overall objective of this project is to develop a framework for reliable characterization and prediction of the state of stress in the overburden and underburden (including the basement) in CO 2 storage reservoirs using machine learning and integrated geomechanics and geophysical methods. Specifically, we propose to develop workflow encompassing of technologies and/or methods to predict stress and pressure changes due to CO 2 injection in an active tertiary recovery site and their impacts on subtle fault activation, fractures and occurrence of microseismic events and compare responses to field observations. In this project, we anticipate using dataset from the Farnsworth field Unit (FWU) which is operated by Purdure Petroleum. A novel elastic-waveform VSP inversion technique will be used to estimate high-resolution spatial and temporal changes of elastic moduli in CO 2 storage reservoirs, which will be combined with velocity-stress relationship derived from laboratory tests to obtain subsurface pressure and stress. Clustered microseismic data will be jointly inverted for improved focal mechanisms. Least-squares reverse-time migration of microseismic waveform data will be performed to directly image fracture/fault zones. Additionally, a deep neural network machine learning technique with convolutional and recurrent layers will be used for learning the spectro-temporal structures in microseismic waveforms. The results of this geotechnical data analysis will be integrated to develop a high-resolution 3D mechanical earth model extending from the overburden sealing formations to the underburden including the basement. Mechanical properties will be derived through integration of mechanical logs, tests, available results from chemo-mechanical laboratory tests, and elastic inversion of seismic data using a combination of Bayesian and stochastic methods as well as machine learning technique. Failure features (faults/fractures) will be represented and/or modeled based on seismic and core data analysis. A transient hydrodynamic-geomechanical model will be developed through coupling with the calibrated FWU reservoir simulation model. The full physics coupled model will be used to train a reduced order proxy model using machine learning algorithm for estimating stress which will then be used with appropriate constitutive relationships and forward seismological models to simulate pressure changes and induced microseismicity. An advanced optimization framework will be developed to perform a history match to minimize error between field observations and simulated. The history matched proxy model will be verified against the full-physics equivalent. The field observations that will be used in the coupled model calibration process include pressure/stress inverted from VSP, moment magnitude from microseismic analysis, real time downhole pressure measurements, production and injection data. Parameter sensitivity and uncertainty analysis will be performed to characterize the impact of model parameter uncertainty on stress estimates. The proposed project will have significant impact on future field implementation of the proposed technology. Because the project field site is an ongoing CO 2 EOR development, the value of the new technology will be demonstrated in an operational context and evaluated as a viable risk mitigation strategy. Cost/benefit will be evaluated together with the various commercial incentives for CO 2 sequestration available to oil and gas operators. The extensive available dataset and ongoing data acquisition under the SWP Phase III work plan provides flexibility for investigation of multiple approaches and reduces technical risk.

58 GEOSCIENCES↗

SPS large array simulation

The computer programming efforts were directed primarily to beam pattern analysis. The computer programs used for simulation provide: verification of the reference design; definition of feasible departures such as quantized distributions; the study of far-out sidelobe roll-off characteristics; the analysis of errors and failures; illumination function analysis to develop beam patterns for efficient collection; and beam shaping synthesis to meet environmental constraints.

Rathjen, S.↗

Flight test configuration for verifying inertial sensor redundancy management techniques

The Redundant Strapdown Inertial Measurement Unit presently tested in flight configuration consists of a semioctahedral array of four dynamically tuned, two-degree-of-freedom (TDOF) gyros and four TDOF accelerometers which can provide dual, fail-operational performance for integrated avionics systems. Attention is given to the multilevel algorithm used for the detection and isolation of three ranges of sensor failure in an integrated avionics context. A technique for the generation of accelerometer and gyro error thresholds which is sensitive to dynamic sensor errors and separation effects is presented, together with simulation results. Emphasis is placed on the ensuring of highly reliable data for flight control/navigation functions, while minimizing false or missed alarms.

Bryant, W. H.↗

Design and development of ceramic components

The development of the AGT 100 turbine components in structural ceramic materials is described. Development is defined as the complete and iterative cycle from design, analysis, test, and design refinement culminating in successful demonstration of the design requirements. The components are analyzed by a linear elastic probabilistic approach, which involves finite element (three- and/or two-dimensional) simulation of the component combined with a Weibull characterization of the brittle ceramic material strength distribution to calculate a probability of survival for the component in the operating environment. Component test failure investigation has resulted in design modifications, and an improvement in component reliability has been demonstrated. Engine testing (over 570 h to date) continues to assess design/development of structural ceramic components.

Holtman, R. L.↗

Test Results of the RS-44 Integrated Component Evaluator Liquid Oxygen/Hydrogen Rocket Engine

An advanced LOX/LH2 expander cycle rocket engine, producing 15,000 lbf thrust for Orbital Transfer Vehicle missions, was tested to determine ignition, transition, and main stage characteristics. Detail design and fabrication of the pump fed RS44 integrated component evaluator (ICE) was accomplished using company discretionary resources and was tested under this contracted effort. Successful demonstrations were completed to about the 50 percent fuel turbopump power level (87,000 RPM), but during this last test, a high pressure fuel turbopump (HPFTP) bearing failed curtailing the test program. No other hardware were affected by the HPFTP premature shutdown. The ICE operations matched well with the predicted start transient simulations. The tests demonstrated the feasibility of a high performance advanced expander cycle engine. All engine components operated nominally, except for the HPFTP, during the engine hot-fire tests. A failure investigation was completed using company discretionary resources.

Sutton, R. F.↗

Evaluation of Transport in the Lower Tropical Stratosphere in a Global Chemistry and Transport Model

Off-line models of the evolution of stratospheric constituents use meteorological information from a general circulation model (GCM) or from a data assimilation system (DAS). Here we focus on transport in the tropics and between the tropics and middle latitudes. Constituent fields from two simulations are compared with each other and with observations. One simulation uses winds from a GCM and the second uses winds from a DAS that has the same GCM at its core. Comparisons of results from the two simulations with observations from satellite, aircraft, and sondes are used to judge the realism of the tropical transport. Faithful comparisons between simulated fields and observations for O3, CH4, and the age-of-air are found for the simulation using the GCM fields. The same comparisons for the simulation using DAS fields show rapid upward tropical transport and excessive mixing between the tropics and middle latitudes. The unrealistic transport found in the DAS fields may be due to the failure of the GCM used in the assimilation system to represent the quasi-biennial oscillation. The assimilation system accounts for differences between the observations and the GCM by requiring implicit forcing to produce consistency between the GCM and observations. These comparisons suggest that the physical consistency of the GCM fields is more important to transport characteristics in the lower tropical stratosphere than the elimination bias with respect to meteorological observations that is accomplished by the DAS. The comparisons presented here show that GCM fields are more appropriate for long-term calculations to assess the impact of changes in stratospheric composition because the balance between photochemical and transport terms is likely to be represented correctly.

Douglass, Anne R.↗

Multiscale Modeling of Intergranular Fracture in Aluminum: Constitutive Relation For Interface Debonding

Intergranular fracture is a dominant mode of failure in ultrafine grained materials. In the present study, the atomistic mechanisms of grain-boundary debonding during intergranular fracture in aluminum are modeled using a coupled molecular dynamics finite element simulation. Using a statistical mechanics approach, a cohesive-zone law in the form of a traction-displacement constitutive relationship, characterizing the load transfer across the plane of a growing edge crack, is extracted from atomistic simulations and then recast in a form suitable for inclusion within a continuum finite element model. The cohesive-zone law derived by the presented technique is free of finite size effects and is statistically representative for describing the interfacial debonding of a grain boundary (GB) interface examined at atomic length scales. By incorporating the cohesive-zone law in cohesive-zone finite elements, the debonding of a GB interface can be simulated in a coupled continuum-atomistic model, in which a crack starts in the continuum environment, smoothly penetrates the continuum-atomistic interface, and continues its propagation in the atomistic environment. This study is a step towards relating atomistically derived decohesion laws to macroscopic predictions of fracture and constructing multiscale models for nanocrystalline and ultrafine grained materials.

Yamakov, V.↗

Simulation Assisted Risk Assessment Applied to Launch Vehicle Conceptual Design

A simulation-based risk assessment approach is presented and is applied to the analysis of abort during the ascent phase of a space exploration mission. The approach utilizes groupings of launch vehicle failures, referred to as failure bins, which are mapped to corresponding failure environments. Physical models are used to characterize the failure environments in terms of the risk due to blast overpressure, resulting debris field, and the thermal radiation due to a fireball. The resulting risk to the crew is dynamically modeled by combining the likelihood of each failure, the severity of the failure environments as a function of initiator and time of the failure, the robustness of the crew module, and the warning time available due to early detection. The approach is shown to support the launch vehicle design process by characterizing the risk drivers and identifying regions where failure detection would significantly reduce the risk to the crew.

Mathias, Donovan L.↗

The Emergency Landing Planner Experiment

In previous work, we described an Emergency Landing Planner (ELP) designed to assist pilots in choosing the best emergency landing site when damage or failures occur in an aircraft. In this paper, we briefly describe the system, but focus on the integration of this system into the cockpit of a 6 DOF full-motion simulator and a study designed to evaluate the ELP. We discuss the results of this study, the lessons learned, and some of the issues involved in advancing this work further.

Meuleau, Nocolas F.↗