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At least 37 records · Page 2

Efficiency and reliability enhancements in propulsion flowfield modeling

The implementation of traditional CFD algorithms in practical propulsion related flowfields often leads to dramatic reductions in efficiency and/or robustness. The present research is directed at understanding the reasons for this deterioration and finding methods to circumvent it. Work to date has focussed on low Mach number regions, viscous dominated regions, and high grid aspect ratios. Time derivative preconditioning, improved definition of the local time stepping, and appropriate application of boundary conditions are employed to decrease the required time to obtain a solution, while maintaining accuracy. A number of cases having features typical of rocket engine flowfields are computed to demonstrate the improvement over conventional methods. These cases include laminar and turbulent high Reynolds number flat plate boundary layers, flow over a backward-facing step, a diffusion flame, and wall heat-flux calculations in a turbulent converging-diverging nozzle. Results from these cases show convergence that is virtually independent of the local Mach number and the grid aspect ratio, which translates to a convergence speed-up of up to several orders of magnitude over conventional algorithms. Current emphasis is in extending these results to three-dimensional flows with highly stretched grids.

Buelow, Philip E. O.

Some Aspects of the Failure Mechanisms in BaTiO3-Based Multilayer Ceramic Capacitors

The objective of this presentation is to gain insight into possible failure mechanisms in BaTiO3-based ceramic capacitors that may be associated with the reliability degradation that accompanies a reduction in dielectric thickness, as reported by Intel Corporation in 2010. The volumetric efficiency (microF/cm3) of a multilayer ceramic capacitor (MLCC) has been shown to not increase limitlessly due to the grain size effect on the dielectric constant of ferroelectric ceramic BaTiO3 material. The reliability of an MLCC has been discussed with respect to its structure. The MLCCs with higher numbers of dielectric layers will pose more challenges for the reliability of dielectric material, which is the case for most base-metal-electrode (BME) capacitors. A number of MLCCs manufactured using both precious-metal-electrode (PME) and BME technology, with 25 V rating and various chip sizes and capacitances, were tested at accelerated stress levels. Most of these MLCCs had a failure behavior with two mixed failure modes: the well-known rapid dielectric wearout, and so-called 'early failures." The two failure modes can be distinguished when the testing data were presented and normalized at use-level using a 2-parameter Weibull plot. The early failures had a slope parameter of Beta >1, indicating that the early failures are not infant mortalities. Early failures are triggered due to external electrical overstress and become dominant as dielectric layer thickness decreases, accompanied by a dramatic reduction in reliability. This indicates that early failures are the main cause of the reliability degradation in MLCCs as dielectric layer thickness decreases. All of the early failures are characterized by an avalanche-like breakdown leakage current. The failures have been attributed to the extrinsic minor construction defects introduced during fabrication of the capacitors. A reliability model including dielectric thickness and extrinsic defect feature size is proposed in this presentation. The model can be used to explain the Intel-reported reliability degradation in MLCCs with respect to the reduction of dielectric thickness. It can also be used to estimate the reliability of a MLCC based on its construction and microstructure parameters such as dielectric thickness, average grain size, and number of dielectric layers. Measures for preventing early failures are also discussed in this document.

Liu, David Donhang

Reliability prediction for a class of highly reliable digital systems

Three theorems which show that the reliability of a popular class of systems can be computed using small and simple models are presented. This class consists of systems that are assemblages of subsystems where each subsystem is a majority-voting threeplex plus spares or majority-voting fourplex plus spares. The theorems are error bounds for model reduction and simplification. The error bounds are given in terms of readily available system parameters. The three theorems have been applied to a system that has been used as an example that generates extremely large reliability models; the system considered is one version of AIPS (Advanced Information Processing System) for IAPSA (Integrated Airframe Propulsion System Architecture).

White, Allan L.

Recognition and characterization of hierarchical interstellar structure. II - Structure tree statistics

A new method of image analysis is described, in which images partitioned into 'clouds' are represented by simplified skeleton images, called structure trees, that preserve the spatial relations of the component clouds while disregarding information concerning their sizes and shapes. The method can be used to discriminate between images of projected hierarchical (multiply nested) and random three-dimensional simulated collections of clouds constructed on the basis of observed interstellar properties, and even intermediate systems formed by combining random and hierarchical simulations. For a given structure type, the method can distinguish between different subclasses of models with different parameters and reliably estimate their hierarchical parameters: average number of children per parent, scale reduction factor per level of hierarchy, density contrast, and number of resolved levels. An application to a column density image of the Taurus complex constructed from IRAS data is given. Moderately strong evidence for a hierarchical structural component is found, and parameters of the hierarchy, as well as the average volume filling factor and mass efficiency of fragmentation per level of hierarchy, are estimated. The existence of nested structure contradicts models in which large molecular clouds are supposed to fragment, in a single stage, into roughly stellar-mass cores.

Houlahan, Padraig

Development of thermomechanical life prediction models for thermal barrier coatings

Thermal barrier coatings (TBCs) for turbine airfoils in high-performance engines represent an advanced materials technology with both performance and durability benefits. The foremost TBC benefit is the reduction of heat transferred into air-cooled components. To achieve these benefits, however, the TBC system must be reliable. Mechanistic thermomechanical and thermochemical life models and statistically significant design data are therefore required for the reliable exploitation of TBC benefits on gas turbine airfoils. Garrett's NASA-HOST Program (NAS3-23945) is designed to fulfill these requirements. This program focuses on predicting the lives of two types of strain-tolerant and oxidation-resistant TBC systems that are produced by commercial coating suppliers to the gas turbine industry. The plasma-sprayed TBC system, composed of a low-pressure plasma-spray (LPPS) applied oxidation resistant NiCrAlY bond coating, and an air-plasma-sprayed yttria partially stabilized zirconia insulated layer is applied by both Chromalloy and Klock. The second type of TBC is applied by the electron beam-physical vapor deposition process by Temescal. Thermomechanical life models are being tailored to predict TBC strain tolerance in terms of materials, engine, and mission parameters. Continuum and fracture mechanics approaches and statistical methods are being evaluated to develop tensile and compressive strain functions required to drive a mission analysis capable thermomechanical life model for TBCs. Results of initial testing to calibrate these life models will be presented.

Strangman, T. E.

Digraph reliability model processing advances and applications

This paper describes a new algorithm, called SourceDoubls, which efficiently solves for singletons and doubletons of a digraph reliability model. Compared with previous methods, the SourceDoubls algorithm provides up to a two order of magnitude reduction in the amount of time required to solve large digraph models. This significant increase in model solution speed allows complex digraphs containing thousands of nodes to be used as knowledge bases for real time automated monitoring and diagnosis applications. Currently, an application to provide monitoring and diagnosis of the Space Station Freedom Data Management System is under development at NASA/Ames Research Center and NASA/Johnson Space Center. This paper contains an overview of this system and provides details of how it will use digraph models processed by the SourceDoubls algorithm to accomplish its task.

Iverson, D. L.

A Thermal Runaway Failure Model for Low-Voltage BME Ceramic Capacitors with Defects

Reliability of base metal electrode (BME) multilayer ceramic capacitors (MLCCs) that until recently were used mostly in commercial applications, have been improved substantially by using new materials and processes. Currently, the inception of intrinsic wear-out failures in high quality capacitors became much greater than the mission duration in most high-reliability applications. However, in capacitors with defects degradation processes might accelerate substantially and cause infant mortality failures. In this work, a physical model that relates the presence of defects to reduction of breakdown voltages and decreasing times to failure has been suggested. The effect of the defect size has been analyzed using a thermal runaway model of failures. Adequacy of highly accelerated life testing (HALT) to predict reliability at normal operating conditions and limitations of voltage acceleration are considered. The applicability of the model to BME capacitors with cracks is discussed and validated experimentally.

reliability

Heat Transfer Analysis in Wire Bundles for Aerospace Vehicles

Design of wiring for aerospace vehicles relies on an understanding of "ampacity" which refers to the current carrying capacity of wires, either, individually or in wire bundles. Designers rely on standards to derate allowable current flow to prevent exceedance of wire temperature limits due to resistive heat dissipation within the wires or wire bundles. These standards often add considerable margin and are based on empirical data. Commercial providers are taking an aggressive approach to wire sizing which challenges the conventional wisdom of the established standards. Thermal modelling of wire bundles may offer significant mass reduction in a system if the technique can be generalized to produce reliable temperature predictions for arbitrary bundle configurations. Thermal analysis has been applied to the problem of wire bundles wherein any or all of the wires within the bundle may carry current. Wire bundles present analytical challenges because the heat transfer path from conductors internal to the bundle is tortuous, relying on internal radiation and thermal interface conductance to move the heat from within the bundle to the external jacket where it can be carried away by convective and radiative heat transfer. The problem is further complicated by the dependence of wire electrical resistivity on temperature. Reduced heat transfer out of the bundle leads to higher conductor temperatures and, hence, increased resistive heat dissipation. Development of a generalized wire bundle thermal model is presented and compared with test data. The steady state heat balance for a single wire is derived and extended to the bundle configuration. The generalized model includes the effects of temperature varying resistance, internal radiation and thermal interface conductance, external radiation and temperature varying convective relief from the free surface. The sensitivity of the response to uncertainties in key model parameters is explored using Monte Carlo analysis.

S L Rickman

The Sun among stars. IV - Albedos of Uranus and Neptune and the solar color

Geometric albedos in 48 adjacent 50 A bands from 3250 to 5600 A have been derived from observations of Uranus and Neptune. The solar analog found in earlier papers (Hardorp 1978, 1980) was chosen for these reductions, so these albedos are more reliable systematically than earlier ones and allow a choice among the scattering models of Savage et al. (1980). Green methane bands are stronger on Neptune. Strong solar absorption lines are found to be partially filled in by Raman-scattering. Neglect of this effect caused Croft et al. (1972) to find a solar color that is too blue. It probably also affected the classification of G-type stars in the Michigan Spectral Catalogue as well as Garrison's (1979) interpretation of IUE observations.

Hardorp, J.

Optimization of life support systems and their systems reliability

The identification, analysis, and optimization of life support systems and subsystems have been investigated. For each system or subsystem that has been considered, the procedure involves the establishment of a set of system equations (or mathematical model) based on theory and experimental evidences; the analysis and simulation of the model; the optimization of the operation, control, and reliability; analysis of sensitivity of the system based on the model; and, if possible, experimental verification of the theoretical and computational results. Research activities include: (1) modeling of air flow in a confined space; (2) review of several different gas-liquid contactors utilizing centrifugal force: (3) review of carbon dioxide reduction contactors in space vehicles and other enclosed structures: (4) application of modern optimal control theory to environmental control of confined spaces; (5) optimal control of class of nonlinear diffusional distributed parameter systems: (6) optimization of system reliability of life support systems and sub-systems: (7) modeling, simulation and optimal control of the human thermal system: and (8) analysis and optimization of the water-vapor eletrolysis cell.

Fan, L. T.

Understanding and Estimating Error Propagation in Neural Networks for Scientific Data Analysis

Neural networks are increasingly integrated into scientific discovery, where input data reduction and model quantization play a key role in accelerating inference. However, understanding and mitigating the impact of these techniques on output error is critical for ensuring reliable results, particularly in tasks demanding high numerical precision. This paper introduces a comprehensive framework for optimizing neural network inference in scientific computing by combining data reduction and weight quantization while maintaining error-controlled outcomes. We develop theoretical analyses to bound error propagation under these reductions and propose a framework that balances computational performance with error constraints. Evaluation on real-world learning-based combustion simulations and satellite image classification demonstrates that our derived error bounds accurately predict observed errors while enabling significant computational speedup under our framework. This work highlights the potential for further leveraging advancements in modern lossy compression algorithms and hardware accelerators that support lower-precision formats.

He, Weiming [New Jersey Institute of Technology]

Markov reliability models for digital flight control systems

The reliability of digital flight control systems can often be accurately predicted using Markov chain models. The cost of numerical solution depends on a model's size and stiffness. Acyclic Markov models, a useful special case, are particularly amenable to efficient numerical solution. Even in the general case, instantaneous coverage approximation allows the reduction of some cyclic models to more readily solvable acyclic models. After considering the solution of single-phase models, the discussion is extended to phased-mission models. Phased-mission reliability models are classified based on the state restoration behavior that occurs between mission phases. As an economical approach for the solution of such models, the mean failure rate solution method is introduced. A numerical example is used to show the influence of fault-model parameters and interphase behavior on system unreliability.

Mcgough, John

Uncertainty Quantification and Sensitivity Analysis of Low-Dimensional Manifold via Co-Kurtosis PCA in Combustion Modeling

For multi-scale multi-physics applications e.g., the turbulent combustion code Pele, robust and accurate dimensionality reduction is crucial to solving problems at exascale and beyond. A recently developed technique, Co-Kurtosis based Principal Component Analysis (CoK-PCA) which leverages principal vectors of co-kurtosis, is a promising alternative to traditional PCA for complex chemical systems. To improve the effectiveness of this approach, we employ Artificial Neural Networks for reconstructing thermo-chemical scalars, species production rates, and overall heat release rates corresponding to the full state space. Our focus is on bolstering confidence in this deep learning based non-linear reconstruction through Uncertainty Quantification (UQ) and Sensitivity Analysis (SA). UQ involves quantifying uncertainties in inputs and outputs, while SA identifies influential inputs. One of the noteworthy challenges is the computational expense inherent in both endeavors. To address this, we employ the Monte Carlo methods to effectively quantify and propagate uncertainties in our reduced spaces while managing computational demands. Our research carries profound implications not only for the realm of combustion modeling but also for a broader audience in UQ. By showcasing the reliability and robustness of CoK-PCA in dimensionality reduction and deep learning predictions, we empower researchers and decision-makers to navigate complex combustion systems with greater confidence.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Effect of Data Reduction and Fiber-Bridging on Mode I Delamination Characterization of Unidirectional Composites

Reliable delamination characterization data for laminated composites are needed for input in analytical models of structures to predict delamination onset and growth. The double-cantilevered beam (DCB) specimen is used to measure fracture toughness, GIc, and strain energy release rate, GImax, for delamination onset and growth in laminated composites under mode I loading. The current study was conducted as part of an ASTM Round Robin activity to evaluate a proposed testing standard for Mode I fatigue delamination propagation. Static and fatigue tests were conducted on specimens of IM7/977-3 and G40-800/5276-1 graphite/epoxies, and S2/5216 glass/epoxy DCB specimens to evaluate the draft standard "Standard Test Method for Mode I Fatigue Delamination Propagation of Unidirectional Fiber-Reinforced Polymer Matrix Composites." Static results were used to generate a delamination resistance curve, GIR, for each material, which was used to determine the effects of fiber-bridging on the delamination growth data. All three materials were tested in fatigue at a cyclic GImax level equal to 90% of the fracture toughness, GIc, to determine the delamination growth rate. Two different data reduction methods, a 2-point and a 7-point fit, were used and the resulting Paris Law equations were compared. Growth rate results were normalized by the delamination resistance curve for each material and compared to the nonnormalized results. Paris Law exponents were found to decrease by 5.4% to 46.2% due to normalizing the growth data. Additional specimens of the IM7/977-3 material were tested at 3 lower cyclic GImax levels to compare the effect of loading level on delamination growth rates. The IM7/977-3 tests were also used to determine the delamination threshold curve for that material. The results show that tests at a range of loading levels are necessary to describe the complete delamination behavior of this material.

Murri, Gretchen B.

Adaptive Optimization of Aircraft Engine Performance Using Neural Networks

Preliminary results are presented on the development of an adaptive neural network based control algorithm to enhance aircraft engine performance. This work builds upon a previous National Aeronautics and Space Administration (NASA) effort known as Performance Seeking Control (PSC). PSC is an adaptive control algorithm which contains a model of the aircraft's propulsion system which is updated on-line to match the operation of the aircraft's actual propulsion system. Information from the on-line model is used to adapt the control system during flight to allow optimal operation of the aircraft's propulsion system (inlet, engine, and nozzle) to improve aircraft engine performance without compromising reliability or operability. Performance Seeking Control has been shown to yield reductions in fuel flow, increases in thrust, and reductions in engine fan turbine inlet temperature. The neural network based adaptive control, like PSC, will contain a model of the propulsion system which will be used to calculate optimal control commands on-line. Hopes are that it will be able to provide some additional benefits above and beyond those of PSC. The PSC algorithm is computationally intensive, it is valid only at near steady-state flight conditions, and it has no way to adapt or learn on-line. These issues are being addressed in the development of the optimal neural controller. Specialized neural network processing hardware is being developed to run the software, the algorithm will be valid at steady-state and transient conditions, and will take advantage of the on-line learning capability of neural networks. Future plans include testing the neural network software and hardware prototype against an aircraft engine simulation. In this paper, the proposed neural network software and hardware is described and preliminary neural network training results are presented.

Simon, Donald L.

Large Vehicle Lunar Landing Surface Interaction and In-Situ Resource Based Risk Mitigation: Landing & Launch Pads

A key capability required for the exploration of planetary bodies is the ability to land on the surface. Previous work performed by NASA and other institutions has primarily focused on landing small spacecraft on planetary surfaces and the associated small-to-medium thrusters required for the soft landing. In the case of human exploration—particularly the establishment of long duration exploration and habitation outposts—the ability to land large landers, such as the SpaceX Starship, is necessary. These larger landing systems require the use of more powerful engines, with higher engine exhaust temperatures and higher landing loads. Understanding the excavation of material by the engines, as well as the potential for the landing legs to sink into the subsurface, is key in ensuring reliable and safe landings. A further improvement in landing reliability can be achieved by constructing landing / launch pads, especially with in-situ resources. Some material excavation by the plume is inevitable, leaving at least a portion of the surface scoured and uneven under the lander and ejecting regolith particles and rocks at very high velocities. One possible solution would be to robotically build landing / launch pads (ideally autonomously) at the destination using in-situ materials. In this case, the first one or few landers will need to land on unimproved surfaces at higher risk; however, they would bring the required equipment to build the landing pads with mostly local resources, thus increasing the reliability of safe landing for subsequent larger landers. A number of methods to build in-situ landing and launch pads have already been developed. These methods include no or some addition of required binder additives to the local regolith material, different processing approaches and result in varying landing pad strengths. A sub-scale rocket engine plume, was used to simulate some of the conditions of a landing on the Moon to assess the effectiveness of various materials for an in-situ built landing pad, The GO2/GCH4 rocket engine fired on 1m2 area coupons of representative pad materials. The results will allow continued development towards materials that satisfy the landing pad properties required for the effective risk reduction and increased reliability for landing people and equipment on the lunar surface. This work contained two parts: (1) computer modeling of a large rocket engine plume interacting with regolith on the Moon, using the Granular Gas Flow Solver (GGFS) provided by CFD Research Corporation as well as other computational fluid dynamics codes (CFD) such as Loci/CHEM. (2) Developing landing/launch pad materials that could be used for in-situ construction on the lunar surface in the future, to mitigate the calculated effects of a large vehicle rocket engine landing and launching on the Moon. The resulting computed values of plume impingement surface temperature, stagnation pressure, gas velocity, shear stress and heat flux were then matched as closely as possible in the Earth’s atmosphere in a sub-scale rocket engine GO2/CH4 test which was provided by Masten Space Systems in Mojave, California. The rocket engine was mounted on a test stand with vertical translation capabilities so that the landing operations of a lander could be simulated (Figure 1).The pad materials test coupons were placed at the surface of a large bin containing simulated lunar basalt regolith and subjected to a test firing as shown in Figure 2. The results of this testing will be presented with related findings, analysis and discussion.

Plume Surface Interaction

Large Vehicle Lunar Landing Surface Interaction and In-Situ Resource Based Risk Mitigation: Landing & Launch Pads

A key capability required for the exploration of planetary bodies is the ability to land on the surface. Previous work performed by NASA and other institutions has primarily focused on landing small spacecraft on planetary surfaces and the associated small-to-medium thrusters required for the soft landing. In the case of human exploration—particularly the establishment of long duration exploration and habitation outposts—the ability to land large landers, such as the SpaceX Starship, is necessary. These larger landing systems require the use of more powerful engines, with higher engine exhaust temperatures and higher landing loads. Understanding the excavation of material by the engines, as well as the potential for the landing legs to sink into the subsurface, is key in ensuring reliable and safe landings. A further improvement in landing reliability can be achieved by constructing landing / launch pads, especially with in-situ resources. Some material excavation by the plume is inevitable, leaving at least a portion of the surface scoured and uneven under the lander and ejecting regolith particles and rocks at very high velocities. One possible solution would be to robotically build landing / launch pads (ideally autonomously) at the destination using in-situ materials. In this case, the first one or few landers will need to land on unimproved surfaces at higher risk; however, they would bring the required equipment to build the landing pads with mostly local resources, thus increasing the reliability of safe landing for subsequent larger landers. A number of methods to build in-situ landing and launch pads have already been developed. These methods include no, or some, addition of required binder additives to the local regolith material, different processing approaches and result in varying landing pad strengths. A sub-scale rocket engine plume, was used to simulate some of the conditions of a landing on the Moon to assess the effectiveness of various materials for an in-situ built landing pad, The GO2/GCH4rocket engine fired on a 1m2area coupons of representative pad materials. The results will allow continued development towards materials that satisfy the landing pad properties required for the effective risk reduction and increased reliability for landing people and equipment on the lunar surface. This work contained two parts: (1) computer modeling of a large rocket engine plume interacting with regolith on the Moon, using the Granular Gas Flow Solver (GGFS) provided by CFD Research Corporation as well as other computational fluid dynamics codes (CFD) such as Loci/CHEM. (2) Developing landing/launch pad materials that could be used for in-situ construction on the lunar surface in the future, to mitigate the calculated effects of a large vehicle rocket engine landing and launching on the Moon.

Lunar

Validation methods for flight crucial systems

Research to develop techniques that can aid in determining the reliability and performance of digital electronic fault-tolerant systems, that have probability of catastrophic system failure on the order of 10 to the -9th at 10 hours, is reviewed. The computer-aided reliability estimation program (CARE III) provides general-purpose reliability analysis and a design tool for fault-tolerant systems; large reduction of state size; and a fault-handling model based on probabilistic description of detection, isolation, and recovery mechanisms. The application of design proof techniques as part of the design and development of the software implemented fault-tolerance computer is mentioned. Emulation techniques and experimental procedures are verified using specimens of fault-tolerant computers and the capabilities of the validation research laboratory, AIRLAB.

Holt, H. M.