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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Approximate simulation model for analysis and optimization in engineering system design

Computational support of the engineering design process routinely requires mathematical models of behavior to inform designers of the system response to external stimuli. However, designers also need to know the effect of the changes in design variable values on the system behavior. For large engineering systems, the conventional way of evaluating these effects by repetitive simulation of behavior for perturbed variables is impractical because of excessive cost and inadequate accuracy. An alternative is described based on recently developed system sensitivity analysis that is combined with extrapolation to form a model of design. This design model is complementary to the model of behavior and capable of direct simulation of the effects of design variable changes.

Sobieszczanski-Sobieski, Jaroslaw↗
NASA NTRS1994

Review of modelling small-crack behavior and fatigue-life predictions for aluminum alloys

The small-crack effect, where small fatigue cracks grow faster and at lower stress-intensity factors than large cracks, has been found to be significant for many materials and loading conditions. In this paper, plasticity effects and crack-closure modelling of small fatigue cracks are reviewed. A crack-closure model with a cyclic-plastic-zone-corrected effective stress-intensity factor range (related to the cyclic J-integral) and microstructural data on crack-initiation sites were used to calculate small-crack growth rates and fatigue lives for unnotched and notched specimens made of two aluminum alloys. The crack-closure transient from the plastic wake was shown to be the dominant cause of the small-crack effect and plasticity effects on the cyclic-plastic-zone-corrected stress-intensity factor range were negligible except at extremely high stress levels. Small-crack growth rates and fatigue lives under both constant-amplitude and spectrum loading from tests and analyses agreed well.

CRACK CLOSURE MODELLING↗
NASA NTRS1994

A Review Of Modelling Small-Crack Behavior And Fatigue-Life Predictions For Aluminum Alloys

The small-crack effect, where small fatigue cracks grow faster and at lower stress-intensity factors than large cracks, has been found to be significant for many materials and loading conditions. In this paper, plasticity effects and crack-closure modelling of small fatigue cracks are reviewed. A crack-closure model with a cyclic-plastic zone-corrected effective stress-intensity factor range (related to the cyclic J-integral) and microstructural data on crack-initiation sites were used to calculate small-crack growth rates and fatigue lives for unnotched and notched specimens made of two aluminum alloys. The crack-closure transient from the plastic wake was shown to be the dominant cause of the small-crack effect and plasticity effects on the cyclic-plastic zone-corrected stress-intensity factor range were negligible except at extremely high stress levels. Small-crack growth rates and fatigue lives under both constant-amplitude and spectrum loading from tests and analyses agreed well.

Newman, J. C., Jr.↗
NASA NTRS2006

Modeling the Stress Strain Behavior of Woven Ceramic Matrix Composites

Woven SiC fiber reinforced SiC matrix composites represent one of the most mature composite systems to date. Future components fabricated out of these woven ceramic matrix composites are expected to vary in shape, curvature, architecture, and thickness. The design of future components using woven ceramic matrix composites necessitates a modeling approach that can account for these variations which are physically controlled by local constituent contents and architecture. Research over the years supported primarily by NASA Glenn Research Center has led to the development of simple mechanistic-based models that can describe the entire stress-strain curve for composite systems fabricated with chemical vapor infiltrated matrices and melt-infiltrated matrices for a wide range of constituent content and architecture. Several examples will be presented that demonstrate the approach to modeling which incorporates a thorough understanding of the stress-dependent matrix cracking properties of the composite system.

Morscher, Gregory N.↗
NASA NTRS1995

Assimilation of Altimeter Data into a Quasigeostrophic Model of the Gulf Stream System: Assimilation Results - Part 2

The improvement in the climatological behavior of a numerical model as a consequence of the assimilation of surface data is investigated. The model used for this study is a quasigeostrophic (QG) model of the Gulf Stream region. The data that have been assimilated are maps of sea surface height that have been obtained as the superposition of sea surface height variability deduced from the Geosat altimeter measurements and a mean field constructed from historical hydrographic data. The method used for assimilating the data is the nudging technique. Nudging has been implemented in such a way as to achieve a high degree of convergence of the surface model fields toward the observations. Comparisons of the assimilation results with available in situ observations show a significant improvement in the degree of realism of the climatological model behavior, with respect to the model in which no data are assimilated. The remaining discrepancies in the model mean circulation seem to be mainly associated with deficiencies in the mean component of the surface data that are assimilated. On the other hand, the possibility of building into the model more realistic eddy characteristics through the assimilation of the surface eddy field proves very successful in driving components of the mean model circulation that are in relatively good agreement with the available observations. Comparisons with current meter time series during a time period partially overlapping the Geosat mission show that the model is able to 'correctly' extrapolate the instantaneous surface eddy signals to depths of approximately 1500 m. The correlation coefficient between current meter and model time series varies from values close to 0.7 in the top 1500 m to values as low as 0.1-0.2 in the deep ocean.

Capotondi, Antonietta↗
NASA NTRS1983

Development of constitutive models for cyclic plasticity and creep behavior of super alloys at high temperature

An uncoupled constitutive model for predicting the transient response of thermal and rate dependent, inelastic material behavior was developed. The uncoupled model assumes that there is a temperature below which the total strain consists essentially of elastic and rate insensitive inelastic strains only. Above this temperature, the rate dependent inelastic strain (creep) dominates. The rate insensitive inelastic strain component is modelled in an incremental form with a yield function, blow rule and hardening law. Revisions to the hardening rule permit the model to predict temperature-dependent kinematic-isotropic hardening behavior, cyclic saturation, asymmetric stress-strain response upon stress reversal, and variable Bauschinger effect. The rate dependent inelastic strain component is modelled using a rate equation in terms of back stress, drag stress and exponent n as functions of temperature and strain. A sequence of hysteresis loops and relaxation tests are utilized to define the rate dependent inelastic strain rate. Evaluation of the model has been performed by comparison with experiments involving various thermal and mechanical load histories on 5086 aluminum alloy, 304 stainless steel and Hastelloy X.

Haisler, W. E.↗
NASA NTRS1988

Contact force history and dynamic response due to the impact of a soft projectile

A series of ballistic impact tests on several different instrumented targets was performed to characterize the dynamic contact force history resulting from the impact of a compliant projectile. The results show that the variation of contact force history with impact velocity does not follow the trends predicted by classical impact models. An empirical model was therefore developed to describe this behavior. This model was then used in a finite-element analysis to estimate the force history and calculate the resulting dynamic strain response in a transversely impacted composite laminate.

Grady, J. E.↗
NASA NTRS1992

Mechanisms of fatigue crack retardation following single tensile overloads in powder metallurgy aluminum alloys

In ingot metallurgy (IM) alloys, the number of delay cycles following a single tensile overload typically increases from a minimum at an intermediate baseline stress intensity range, Delta-K(B), with decreasing Delta-K(B) approaching threshold and increasing Delta-K(B) approaching unstable fracture to produce a characteristic 'U' shaped curve. Two models have been proposed to explain this behavior. One model is based on the interaction between roughness and plasticity-induced closure, while the other model only utilizes plasticity-induced closure. This article examines these models, using experimental results from constant amplitude and single overload fatigue tests performed on two powder metallurgy (PM) aluminum alloys, AL-905XL and AA 8009. The results indicate that the 'U'-shaped curve is primarily due to plasticity-induced closure, and that the plasticity-induced retardation effect is through-thickness in nature, occurring in both the surface and interior regions. However, the retardation effect is greater at the surface, because the increase in plastic strain at the crack tip and overload plastic zone size are larger in the plane-stress surface regions than in the plane-strain interior regions. These results are not entirely consistent with either of the proposed models.

Bray, G. H.↗
NASA NTRS2007

Automatic Command Sequence Generation

Automatic Sequence Generator (Autogen) Version 3.0 software automatically generates command sequences for the Mars Reconnaissance Orbiter (MRO) and several other JPL spacecraft operated by the multi-mission support team. Autogen uses standard JPL sequencing tools like APGEN, ASP, SEQGEN, and the DOM database to automate the generation of uplink command products, Spacecraft Command Message Format (SCMF) files, and the corresponding ground command products, DSN Keywords Files (DKF). Autogen supports all the major multi-mission mission phases including the cruise, aerobraking, mapping/science, and relay mission phases. Autogen is a Perl script, which functions within the mission operations UNIX environment. It consists of two parts: a set of model files and the autogen Perl script. Autogen encodes the behaviors of the system into a model and encodes algorithms for context sensitive customizations of the modeled behaviors. The model includes knowledge of different mission phases and how the resultant command products must differ for these phases. The executable software portion of Autogen, automates the setup and use of APGEN for constructing a spacecraft activity sequence file (SASF). The setup includes file retrieval through the DOM (Distributed Object Manager), an object database used to store project files. This step retrieves all the needed input files for generating the command products. Depending on the mission phase, Autogen also uses the ASP (Automated Sequence Processor) and SEQGEN to generate the command product sent to the spacecraft. Autogen also provides the means for customizing sequences through the use of configuration files. By automating the majority of the sequencing generation process, Autogen eliminates many sequence generation errors commonly introduced by manually constructing spacecraft command sequences. Through the layering of commands into the sequence by a series of scheduling algorithms, users are able to rapidly and reliably construct the desired uplink command products. With the aid of Autogen, sequences may be produced in a matter of hours instead of weeks, with a significant reduction in the number of people on the sequence team. As a result, the uplink product generation process is significantly streamlined and mission risk is significantly reduced. Autogen is used for operations of MRO, Mars Global Surveyor (MGS), Mars Exploration Rover (MER), Mars Odyssey, and will be used for operations of Phoenix. Autogen Version 3.0 is the operational version of Autogen including the MRO adaptation for the cruise mission phase, and was also used for development of the aerobraking and mapping mission phases for MRO.

Fisher, Forest↗
NASA NTRS1986

Some observations on the behavior of the Langley model rotor blade

The design of the model rotor and the comparative study of coupled beam theory and the finite element analysis performed earlier at the Aerostructures Directorate by Robert Hodges and Mark Nixon is examined. Attention is focused upon two matters: (1) an examination of the small discrepancies between twist angle predictions under pure torque and radial loading, and (2) an assessment of nonclassical effects in bending behavior. The primary objective is understanding, particularly with regard to cause and effect relationships. Understanding, together with the simple, affordable nature of the coupled beam analysis, provides a sound basis for design.

Rehfield, L. W.↗
NASA NTRS2010

Modeling Common-Sense Decisions in Artificial Intelligence

A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation of the dynamical models in a parameterized form reduces the task of common-sense-based decision making to a solution of the following hetero-associated-memory problem: store a set of m predetermined stochastic processes given by their probability distributions in such a way that when presented with an unexpected change in the form of an input out of the set of M inputs, the coupled motormental dynamics converges to the corresponding one of the m pre-assigned stochastic process, and a sample of this process represents the decision.

Zak, Michail↗
NASA NTRS1994

(abstract) Automated Constraint Checking of Spacecraft Command Sequences

Making certain that spacecraft command sequences do not violate any constraints is often tedious and expensive in terms of both personnel and software development. To reduce this cost, we have pursued the development of a flexible system for specifying models of spacecraft behavior in response to commands as well as constraints on that behavior. The potential need for modeling complex spacecraft behavior required that the system be designed to be usable both on a conventional workstation and a parallel supercomputer. Finally, it needed to be intuitive enough for the the intended mission operations users to easily design sets of rules and models to automate tedious, resource-consuming constraint checking of commands. We have defined a Specification And Verification Environment (SAVE) for spacecraft flight rules.

automation spacecraft command sequences constraint↗
NASA NTRS1976

A model study of diurnal behavior of the ionosphere and the protonosphere coupling

A new method to study dynamic behavior of the ionosphere-protonosphere coupling within the plasmasphere is developed and used to calculate ion distributions above 500 km using observed electron densities at 500 km. The method is based on the relation between the total magnetic flux tube content of H(+) above some reference height (e.g., 3000 km) and the H(+) flux at that height, which is uniquely determined by the coupled momentum and continuity equations for the quasi-steady state. The O(+) profile is perturbed from diffusive equilibrium only by ion drag with H(+). The time dependency is taken into account by applying self-consistent boundary conditions which are obtained from the solution of the time-dependent equation for the tube content of H(+). Calculations are carried out for two models. The first model deals with the ion dynamics in a tube of force which rotates with the earth. In the second model, effects of the cross-L plasma drifts are considered. Both models produce diurnal variations of H(+) and O(+) densities near 1000 km similar to observational results.

Marubashi, K.↗
NASA NTRS2001

Calculation of the Aerodynamic Behavior of the Tilt Rotor Aeroacoustic Model (TRAM) in the DNW

Comparisons of measured and calculated aerodynamic behavior of a tiltrotor model are presented. The test of the Tilt Rotor Aeroacoustic Model (TRAM) with a single, 1/4-scale V- 22 rotor in the German-Dutch Wind Tunnel (DNW) provides an extensive set of aeroacoustic, performance, and structural loads data. The calculations were performed using the rotorcraft comprehensive analysis CAMRAD II. Presented are comparisons of measured and calculated performance and airloads for helicopter mode operation, as well as calculated induced and profile power. An aerodynamic and wake model and calculation procedure that reflects the unique geometry and phenomena of tiltrotors has been developed. There are major differences between this model and the corresponding aerodynamic and wake model that has been established for helicopter rotors. In general, good correlation between measured and calculated performance and airloads behavior has been shown. Two aspects of the analysis that clearly need improvement are the stall delay model and the trailed vortex formation model.

Johnson, Wayne↗
NASA NTRS2012

A Model-Based Approach to Engineering Behavior of Complex Aerospace Systems

One of the most challenging yet poorly defined aspects of engineering a complex aerospace system is behavior engineering, including definition, specification, design, implementation, and verification and validation of the system's behaviors. This is especially true for behaviors of highly autonomous and intelligent systems. Behavior engineering is more of an art than a science. As a process it is generally ad-hoc, poorly specified, and inconsistently applied from one project to the next. It uses largely informal representations, and results in system behavior being documented in a wide variety of disparate documents. To address this problem, JPL has undertaken a pilot project to apply its institutional capabilities in Model-Based Systems Engineering to the challenge of specifying complex spacecraft system behavior. This paper describes the results of the work in progress on this project. In particular, we discuss our approach to modeling spacecraft behavior including 1) requirements and design flowdown from system-level to subsystem-level, 2) patterns for behavior decomposition, 3) allocation of behaviors to physical elements in the system, and 4) patterns for capturing V&V activities associated with behavioral requirements. We provide examples of interesting behavior specification patterns, and discuss findings from the pilot project.

SysML↗
NASA NTRSDate not supplied

Hybrid Model Based Approaches for Systems Health Management and Prognostics

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision making. In principle, data driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for an effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Hybrid Modeling↗
NASA NTRSDate not supplied

Hybrid Approaches to Systems Health Management and Prognostics

To facilitate and solve the prediction problem, awareness of the current health state of the system is key, since it is necessary to perform condition-based predictions. To accurately predict the future state of any system, it is required to possess knowledge of its current health state and future operational conditions. Latest achievements of data-driven algorithms in regression of complex nonlinear functions and classification tasks have generated a growing interest in artificial intelligence for industrial applications. Complex multi-physics models as well as digital twins, once purely built on physics and corresponding simplified lumped parameter iterations, can now benefit from machine learning algorithms to mitigate the lack of understanding of some complex behavior. Given models of the current and future system behavior, a general approach of model-based prognostics can solve the prediction problem and further decision making. In principle, data driven approaches can replace expensive experimental test-setups as well as reduce the number of simulations needed to explore, e.g., the parametric space of a multi-parameter model. Nonetheless, the limitations of pure data-driven methods came to light rather quickly, at least for some industries. In many industrial applications, data acquisition is costly, and the volume of data that can be collected does not satisfy the requirements for an effective model training and cross-validation. Therefore, some recent works in the area of machine learning is focusing on blending physics with data-driven algorithms, thus mitigating the drawbacks of the two approaches and emphasizing respective advantages. Partial physical knowledge of the problem can aid the learning process by “guiding” the algorithm towards efficient solutions that satisfy the physics driving the system behavior. The result is a hybrid modeling approach combining physical knowledge as well data driven methods to develop a unified hybrid approach. A hybrid framework for fusing information from physics-based performance models along with deep learning algorithms for prognostics of complex safety critical systems is presented. In this framework, physics-based performance models infer unobservable model parameters related to the system's components health solving a calibration problem in the deep learning approach.

Systems Health Management↗