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At least 163 records · Page 9

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NASA NTRS1992

Advances in fatigue life prediction methodology for metallic materials

The capabilities of a plasticity-induced crack-closure model to predict small- and large-crack growth rates, and in some cases total fatigue life, for four aluminum alloys and three titanium alloys under constant-amplitude, variable-amplitude, and spectrum loading are described. Equations to calculate a cyclic-plastic-zone corrected effective stress-intensity factor range from a cyclic J-integral and crack-closure analysis of large cracks were reviewed. The effective stress-intensity factor range against crack growth rate relations were used in the closure model to predict small- and large-crack growth under variable-amplitude and spectrum loading. Using the closure model and microstructural features, a total fatigue life prediction method is demonstrated for three aluminum alloys under various load histories.

Newman, J. C., Jr.↗

NASA NTRS1996

A model for closing the inviscid form of the average passage equation system

A mathematical model for closing or mathematically completing the system of equations is proposed. The model describes the time average flow field through the blade passages of multistage turbomachinery. These average-passage equation systems govern a conceptual model useful in turbomachinery aerodynamic design and analysis. The closure model was developed to insure a consistency between these equations and the axisymmetric through-flow equations. The closure model was incorporated into a calculation code for use in the simulation of the flow field about a high-speed counter rotating propeller and a high-speed fan stage.

Adamczyk, John J.↗

NASA NTRS1990

Turbulence modeling: Near-wall turbulence and effects of rotation on turbulence

Many Reynolds averaged Navier-Stokes solvers use closure models in conjunction with 'the law of the wall', rather than deal with a thin, viscous sublayer near the wall. This work is motivated by the need for better models to compute near wall turbulent flow. The authors use direct numerical simulation of fully developed channel flow and one of three dimensional turbulent boundary layer flow to develop new models. These direct numerical simulations provide detailed data that experimentalists have not been able to measure directly. Another objective of the work is to examine analytically the effects of rotation on turbulence, using Rapid Distortion Theory (RDT). This work was motivated by the observation that the pressure strain models in all current second order closure models are unable to predict the effects of rotation on turbulence.

Shih, T.-H.↗

NASA NTRS1985

Separated transonic airfoil flow calculations with a nonequilibrium turbulence model

Navier-Stokes transonic airfoil calculations based on a recently developed nonequilibrium, turbulence closure model are presented for a supercritical airfoil section at transonic cruise conditions and for a conventional airfoil section at shock-induced stall conditions. Comparisons with experimental data are presented which show that this nonequilibrium closure model performs significantly better than the popular Baldwin-Lomax and Cebeci-Smith equilibrium algebraic models when there is boundary-layer separation that results from the inviscid-viscous interactions.

King, L. S.↗

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 NTRS1989

Second-Order Modeling of Low-Reynolds-Number Turbulence Near Walls

This paper presents a set of second-order closure models for low-Reynolds-number turbulence near the wall. Existing closure models for the Reynolds-stress equations were modified to show proper near-wall behavior. A dissipation-rate equation for the turbulent kinetic energy is also reformulated. The proposed models satisfy realizability and will not produce unphysical behavior. Fully developed channel flows are used for model testing. The equations are solved for the mean velocity, the Reynolds stresses, and the dissipation rate of the turbulent kinetic energy. The calculations are compared with both direct numerical simulations and with measurements. It is shown that the present models perform well in predicting the behavior of the turbulence near a wall. Significant improvements over previous models in predicting the components of the Reynolds stress tensor are obtained in the present models.

Shih, T.-H.↗

NASA NTRS1985

A model for closing the inviscid form of the average-passage equation system

A mathematical model is proposed for closing or mathematically completing the system of equations which describes the time average flow field through the blade passages of multistage turbomachinery. These equations referred to as the average passage equation system govern a conceptual model which has proven useful in turbomachinery aerodynamic design and analysis. The closure model is developed so as to insure a consistency between these equations and the axisymmetric through flow equations. The closure model was incorporated into a computer code for use in simulating the flow field about a high speed counter rotating propeller and a high speed fan stage. Results from these simulations are presented.

Adamczyk, J. J.↗

NASA NTRS1986

A model for closing the inviscid form of the average-passage equation system

Adamczyk, J. J.↗

DOE OSTI2020

Probing interfacial momentum closures in two-phase bubbly flow with machine learning-aided methods

Computational fluid dynamics (CFD) approach has already reached a high level of maturity for single-phase flows, however the development of closure models for two-phase flow requires additional attention. Multiphase CFD (M-CFD) methods resolve the conservation equations for mass, momentum and energy while differing in the approaches and strategies adopted in the physical closure models. The most widely adopted framework for M-CFD is the Eulerian-Eulerian two-fluid approach which assumes that all phases are co-existing inside each computational cell. For each fluid, the full set of conservation equations is solved; therefore, each fluid has a different velocity field. For adiabatic two-phase flow, the mechanisms of the interfacial momentum transfer are modeled by the interfacial forces representing different physical mechanisms. One of the crucial issues in the development and application of two-fluid model is the understanding of the interfacial momentum closures which determines the bubble distribution and migration behaviors. Dedicated experiments are performed to support the physical understanding and drive the closures’ development. However, limitations exist due to the uncertainties in the experimental measurement and the simplified analytical assumptions which have difficulties on representing the complex non-linear flow fields. In this paper, a data-driven approach, Feature Similarity Measurement (FSM), is developed and proposed to resolve the challenges of modeling the interfacial forces closures. Case study is performed with two-phase flow scenarios where the high-fidelity experimental data is available. Within the Eulerian-Eulerian two-fluid framework, only momentum equations for gas and liquid phases are solved and reduced-order interfacial momentum closures are aided with FSM. Predictions of void fraction and velocity fields are analyzed and demonstrate the potential of machine learning-driven interfacial forces closures.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1992

Turbulence modeling and experiments

The best way of verifying turbulence is to do a direct comparison between the various terms and their models. The success of this approach depends upon the availability of the data for the exact correlations (both experimental and DNS). The other approach involves numerically solving the differential equations and then comparing the results with the data. The results of such a computation will depend upon the accuracy of all the modeled terms and constants. Because of this it is sometimes difficult to find the cause of a poor performance by a model. However, such a calculation is still meaningful in other ways as it shows how a complete Reynolds stress model performs. Thirteen homogeneous flows are numerically computed using the second order closure models. We concentrate only on those models which use a linear (or quasi-linear) model for the rapid term. This, therefore, includes the Launder, Reece and Rodi (LRR) model; the isotropization of production (IP) model; and the Speziale, Sarkar, and Gatski (SSG) model. Which of the three models performs better is examined along with what are their weaknesses, if any. The other work reported deal with the experimental balances of the second moment equations for a buoyant plume. Despite the tremendous amount of activity toward the second order closure modeling of turbulence, very little experimental information is available about the budgets of the second moment equations. Part of the problem stems from our inability to measure the pressure correlations. However, if everything else appearing in these equations is known from the experiment, pressure correlations can be obtained as the closing terms. This is the closest we can come to in obtaining these terms from experiment, and despite the measurement errors which might be present in such balances, the resulting information will be extremely useful for the turbulence modelers. The purpose of this part of the work was to provide such balances of the Reynolds stress and heat flux equations for the buoyant plume.

Shabbir, Aamir↗

NASA NTRS1980

A Navier-Stokes fast solver for turbulence modeling applications

A computer code for the evaluation and/or optimization of the predicative potential of second order turbulent closure models in simple two dimensional flow configurations is discussed. A procedure for the numerical solution of the steady constant property Navier-Stokes equations are described together with algebraic, one dimensional and two dimensional equations of turbulence closure models. Four turbulence models are compared with several sets of experimental data. The effects of initial conditions and boundary conditions are also described. The effects of purely numerical parameters, such as mesh size, boundary locations, and convergence criteria are presented.

Murphy, J. D.↗

NASA NTRS1992

Center for Modeling of Turbulence and Transition (CMOTT): Research Briefs, 1992

The progress is reported of the Center for Modeling of Turbulence and Transition (CMOTT). The main objective of the CMOTT is to develop, validate and implement the turbulence and transition models for practical engineering flows. The flows of interest are three-dimensional, incompressible and compressible flows with chemical reaction. The research covers two-equation (e.g., k-e) and algebraic Reynolds-stress models, second moment closure models, probability density function (pdf) models, Renormalization Group Theory (RNG), Large Eddy Simulation (LES) and Direct Numerical Simulation (DNS).

Liou, William W.↗

NASA NTRS1995

Turbulence program for propulsion systems

Program goals at the Center for Modeling of Turbulence and Transition (CMOTT), NASA Lewis Research Center, are (1) to develop reliable turbulence (including bypass transition) and combustion models for complex flows in propulsion systems and (2) to integrate developed models into deliverable CFD tools for propulsion systems in collaboration with industry. This viewgraph presentation covers the following topics: development of turbulence and combustion models; collaboration with industry and technology transfer; isotropic eddy viscosity models; algebraic Reynolds stress models; scalar turbulence models; second order closure models; multiple scale k-epsilon models; and PDF modeling of turbulent reacting flows.

Shih, Tsan-Hsing↗

DOE OSTI2020

A priori analysis on deep learning of subgrid-scale parameterizations for Kraichnan turbulence

In the present study, we investigate different data-driven parameterizations for large eddy simulation of two-dimensional turbulence in the a priori settings. These models utilize resolved flow field variables on the coarser grid to estimate the subgrid-scale stresses. We use data-driven closure models based on localized learning that employs a multilayer feedforward artificial neural network with point-to-point mapping and neighboring stencil data mapping, and convolutional neural network fed by data snapshots of the whole domain. The performance of these data-driven closure models is measured through a probability density function and is compared with the dynamic Smagorinksy model (DSM). The quantitative performance is evaluated using the cross-correlation coefficient between the true and predicted stresses. We analyze different frameworks in terms of the amount of training data, selection of input and output features, their characteristics in modeling with accuracy, and training and deployment computational time. We also demonstrate computational gain that can be achieved using the intelligent eddy viscosity model that learns eddy viscosity computed by the DSM instead of subgrid-scale stresses. Here, we detail the hyperparameters optimization of these models using the grid search algorithm.

42 ENGINEERING↗

NASA NTRSDate not supplied

Modeling Pore Closure in the Hot Isostatic Pressing of Additively Manufactured Inconel 718 Samples

Additive manufacturing provides opportunity for a new world of possibilities for metallic component design and fabrication; however, as-built part quality is notoriously variable, anisotropic, and degraded by porous defects. To improve quality, parts are commonly post processed using a variety of techniques including hot isostatic pressing (HIP). During HIP, high temperature and pressure is employed to improve microstructure and reduce pore volume by inducing visco-plastic deformation in the metallic substrate. Validated computational capabilities can provide predictions to guide the selection of processing condition, expected pore reduction, and the effects of varying entrapped gas in the pores. This discussion describes a micro-scale finite element structural model developed to predict pore closure due to HIP in as-built additively manufactured Inconel 718 samples produced by the laser powder bed fusion process. The model accounts for plastic deformation, creep, and internal pressure for a single pore. Pores are characterized in physical samples before and after HIP, and model predictions are compared to this measured data.

defect model prediction↗

NASA NTRS1992

On explicit algebraic stress models for complex turbulent flows

Explicit algebraic stress models that are valid for three-dimensional turbulent flows in noninertial frames are systematically derived from a hierarchy of second-order closure models. This represents a generalization of the model derived by Pope who based his analysis on the Launder, Reece, and Rodi model restricted to two-dimensional turbulent flows in an inertial frame. The relationship between the new models and traditional algebraic stress models -- as well as anistropic eddy visosity models -- is theoretically established. The need for regularization is demonstrated in an effort to explain why traditional algebraic stress models have failed in complex flows. It is also shown that these explicit algebraic stress models can shed new light on what second-order closure models predict for the equilibrium states of homogeneous turbulent flows and can serve as a useful alternative in practical computations.

Gatski, T. B.↗

NASA NTRS2021

Self-Consistent Implementation of a Zero-Equation Transport Model Into a Predictive Model for a Hall Effect Thruster

The performance of an axisymmetric multi-fluid Hall thruster code that incorporates a self-consistent, data-driven closure model for the anomalous electron transport is investigated. Five different operating conditions of the H9 magnetically shielded Hall thruster are simulated with the Jet Propulsion Laboratory’s Hall2De. In order to capture the inherent uncertainty associated with the closure model, O(100) simulations are run for each condition, each of using a coefficient set sampled randomly from a probability distribution. The results of these simulations provide probabilistic predictions of thruster performance quantities including thrust, and discharge current, as well as several component efficiencies and centerline plasma properties. The model is found to yield converged solutions at all conditions, with large 10 kHzrange oscillations and performance trends with voltage and flow rate similar to experiment. The model under-predicts the thrust by 15-25% and over-predicts the discharge current by 20% on average compared to experiments at the same discharge voltage and mass flow rate. This performance discrepancy is due to lower beam utilization, mass utilization, and divergence efficiency than experiment, resulting from high Hall parameters in the acceleration region, which lead to a protracted ion acceleration region. The physical processes underlying this result are discussed in the context of future data-driven modeling efforts.

Jorns, Benjamin A.↗

DOE OSTI2021

Data assimilation empowered neural network parametrizations for subgrid processes in geophysical flows

In the past couple of years, there has been a proliferation in the use of machine learning approaches to represent subgrid-scale processes in geophysical flows with an aim to improve the forecasting capability and to accelerate numerical simulations of these flows. Despite its success for different types of flow, the online deployment of a data-driven closure model can cause instabilities and biases in modeling the overall effect of subgrid-scale processes, which in turn leads to inaccurate prediction. To tackle this issue, we exploit the data assimilation technique to correct the physics-based model coupled with the neural network as a surrogate for unresolved flow dynamics in multiscale systems. In particular, we use a set of neural network architectures to learn the correlation between resolved flow variables and the parametrizations of unresolved flow dynamics and formulate a data assimilation approach to correct the hybrid model during their online deployment. We illustrate our framework in a set of applications of the multiscale Lorenz 96 system for which the parametrization model for unresolved scales is exactly known, and the two-dimensional Kraichnan turbulence system for which the parametrization model for unresolved scales is not known a priori. Our analysis, therefore, comprises a predictive dynamical core empowered by (i) a data-driven closure model for subgrid-scale processes, (ii) a data assimilation approach for forecast error correction, and (iii) both data-driven closure and data assimilation procedures. We show significant improvement in the long-term prediction of the underlying chaotic dynamics with our framework compared to using only neural network parametrizations for future prediction. Moreover, we demonstrate that these data-driven parametrization models can handle the non-Gaussian statistics of subgrid-scale processes, and effectively improve the accuracy of outer data assimilation workflow loops in a modular nonintrusive way.

42 ENGINEERING↗