arXiv subjects

Kevin Patrick Griffin

Publications and source records attributed to Kevin Patrick Griffin.

9 recordsLinked to original sources

arXiv2026

Improving boundary-layer separation prediction by an IDDES turbulence model using a pressure-gradient sensor

This work extends a pressure-gradient sensor for boundary-layer separation originally developed for the $k-ω$ shear-stress transport Reynolds-averaged Navier-Stokes (RANS) model (Griffin et al., 2025, J. Turb.) to the Improved Delayed Detached Eddy Simulation (IDDES) turbulence model of Gritskevich et al. (2012, Flow Turbul. Combust.). The pressure-gradient sensor identifies local regions of strong adverse pressure-gradient where the eddy-viscosity is reduced, as in the original RANS model. Additionally, to promote separation in the IDDES model, the elevation term in the IDDES length scale, designed to augment the RANS-mode Reynolds stress in attached flow regions, is turned off where the pressure-gradient sensor is active. The model is applied on various airfoils representative of both wind energy and aerospace applications, and is used in fully turbulent and transitional IDDES model variants. The proposed model improves the prediction of stall onset and post-stall regimes relative to the baseline IDDES model without significant degradation of attached-flow regimes relative to state-of-the-art RANS models or deep-stall regimes relative to state-of-the-art IDDES models. Significant overall improvements are observed in predictions of lift and drag polars across 90 degrees of angle of attack, yielding a unified model able to predict various (two- and three-dimensional) flow regimes. Shortcomings are identified to be related to the underlying RANS pressure-gradient sensor rather than the extension of the sensor to the IDDES model, which is the focus of this work.

physics.flu-dyn↗

arXiv2026

Performance evaluation of an offshore wave measurement buoy in monochromatic waves

The accurate measurement of waves underpins marine energy resource characterization, device design, and project development. Datawell wave buoys are widely deployed around the world and have long served as a trusted standard for wave measurements. We quantify the measurement performance, including wave elevation and energy flux estimation, of a Datawell DWR-MkIII buoy using prescribed monochromatic heave motions on a large-amplitude six-degree-of-freedom motion platform at the National Laboratory of the Rockies, assuming the buoy behaves as an ideal wave follower. Commanded motions were validated with an optical motion tracking system while buoy elevation and raw acceleration were recorded. Wave elevations were propagated to wave energy flux estimation using four methods, including one frequency-domain method and three time-domain methods. The Bayesian optimization was applied for design of experiments, and records from three test sites were also applied and evaluated in the present study. Results show two error regions within the nominal period range of 1.6s to 30s}. For wave periods between 5s and 25s, the buoy provides accurate wave height measurements. For short periods less than 5s, the 1.28Hz sampling frequency induces sub-Nyquist artifacts that bias elevation and can drive maximum energy flux estimation errors above 100%. For long periods exceeding 25s, the buoy reported elevation is underpredicted with error depending on period but relatively independent of wave height, with maximum wave height and wave energy flux errors reaching 64% and 87%, respectively. The analysis of field data also indicates that the currently recommended method for estimating wave energy flux may underestimate the wave energy flux.

physics.ins-det↗

arXiv2025

Improved pressure-gradient sensor for the prediction of separation onset in RANS models

We improve upon two key aspects of the Menter shear stress transport (SST) turbulence model: (1) We propose a more robust adverse pressure gradient sensor based on the strength of the pressure gradient in the direction of the local mean flow; (2) We propose two alternative eddy viscosity models to be used in the adverse pressure gradient regions identified by our sensor. Direct numerical simulations of the Boeing Gaussian bump are used to identify the terms in the baseline SST model that need correction, and a posteriori Reynolds-averaged Navier-Stokes calculations are used to calibrate coefficient values, leading to a model that is both physics driven and data informed. The two sensor-equipped models are applied to two thick airfoils representative of modern wind turbine applications, the FFA-W3-301 and the DU00-W-212. The proposed models improve the prediction of stall (onset of separation) with respect to the prediction of the baseline SST model.

physics.flu-dyn↗

arXiv2025

Adaptive Computing for Scale-up Problems

Adaptive Computing is an application-agnostic outer loop framework to strategically deploy simulations and experiments to guide decision making for scale-up analysis. Resources are allocated over successive batches, which makes the allocation adaptive to some objective such as optimization or model training. The framework enables the characterization and management of uncertainties associated with predictive models of complex systems when scale-up questions lead to significant model extrapolation. A key advancement of this framework is its integration of multi-fidelity surrogate modeling, uncertainty management, and automated orchestration of various computing and experimentation resources into a single integrated software package. This enables efficient multi-fidelity modeling across multiple computing resources by incorporating real-world constraints such as relative queue times and throughput on individual machines into the multi-fidelity sampling decision. We discuss applications of this framework to problems in the renewable energy space, including biofuels production, material synthesis, perovskite crystal growth, and building electrical loads.

math.OC↗

arXiv2023

Near-wall model for compressible turbulent boundary layers based on an inverse velocity transformation

In this work, a near-wall model, which couples the inverse of a recently developed compressible velocity transformation [Griffin, Fu, & Moin, PNAS, 118:34, 2021] and an algebraic temperature-velocity relation, is developed for high-speed turbulent boundary layers. As input, the model requires the mean flow state at one wall-normal height in the inner layer of the boundary layer and at the boundary-layer edge. As output, the model can predict mean temperature and velocity profiles across the entire inner layer, as well as the wall shear stress and heat flux. The model is tested in an a priori sense using a wide database of direct numerical simulation high-Mach-number turbulent channel flows, pipe flows, and boundary layers (48 cases with edge Mach numbers in the range of 0.77--11 and semi-local friction Reynolds numbers in the range of 170--5700). The present model is significantly more accurate than the classical ordinary differential equation (ODE) model for all cases tested. The model is deployed as a wall model for large-eddy simulations in channel flows with bulk Mach numbers in the range of 0.7--4 and friction Reynolds numbers in the range of 320--1800. When compared to the classical framework, in the a posteriori sense, the present method greatly improves the predicted heat flux, wall stress, and temperature and velocity profiles, especially in cases with strong heat transfer. In addition, the present model solves one ODE instead of two and has a similar computational cost and implementation complexity as the commonly used ODE model.

physics.flu-dyn↗

arXiv2021

Velocity transformation for compressible wall-bounded turbulent flows with and without heat transfer

In this work, a transformation, which maps the mean velocity profiles of compressible wall-bounded turbulent flows to the incompressible law of the wall is proposed. Unlike existing approaches, the proposed transformation successfully collapses, without specific tuning, numerical simulation data from fully developed channel and pipe flows, and boundary layers with or without heat transfer. In all these cases, the transformation is successful across the entire inner layer of the boundary layer (including the viscous sublayer, buffer layer, and logarithmic layer), recovers the asymptotically exact near-wall behavior in the viscous sublayer, and is consistent with the near balance of turbulence production and dissipation in the logarithmic region of the boundary layer. The performance of the transformation is verified for compressible wall-bounded flows with edge Mach numbers ranging from 0 to 15 and friction Reynolds numbers ranging from 200 to 2000. Based on physical arguments, we show that such a general transformation exists for compressible wall-bounded turbulence regardless of the wall thermal condition.

physics.flu-dyn↗

arXiv2021

General method for determining the boundary layer thickness in nonequilibrium flows

While the computation of the boundary-layer thickness is straightforward for canonical equilibrium flows, there are no established definitions for general non-equilibrium flows. In this work, a method is developed based on a local reconstruction of the "inviscid" velocity profile $U_I[y]$ resulting from the application of the Bernoulli equation in the wall-normal direction. The boundary-layer thickness $δ_{99}$ is then defined as the location where $U/U_I = 0.99$, which is consistent with its classical definition for the zero-pressure-gradient boundary layers (ZPGBLs). The proposed local-reconstruction method is parameter free and can be deployed for both internal and external flows without resorting to an iterative procedure, numerical integration, or numerical differentiation. The superior performance of the local-reconstruction method over various existing methods is demonstrated by applying the methods to laminar and turbulent boundary layers and two flows over airfoils. Numerical experiments reveal that the local-reconstruction method is more accurate and more robust than existing methods, and it is applicable for flows over a wide range of Reynolds numbers.

physics.flu-dyn↗

arXiv2021

Grid-point and time-step requirements for direct numerical simulation and large-eddy simulation

We revisit the grid-point requirement estimates in Choi and Moin [Phys. Fluid, 24, 011702 (2012)] and establish more general grid-point requirements for direct numerical simulations (DNS) and large-eddy simulations (LES) of a spatially developing turbulent boundary layer. We show that, by allowing the local grid spacing to scale with the local Kolmogorov length scale, the grid-point requirement for DNS of a spatially developing turbulent boundary layer is $N\sim Re_{L_x}^{2.05}$ rather than $N\sim Re_{L_x}^{2.64}$ as suggested by Choi and Moin, where $N$ is the number of grid points and $L_x$ is the length of the plate. In addition to the grid-point requirement, we estimate the time-step requirement for DNS and LES. We show that, for a code that treats the convective term explicitly, the time steps required to get converged statistics are $N_t\sim Re_{L_x}/Re_{x_0}^{6/7}$ for wall-modeled LES and $N_t\sim Re_{L_x}/Re_{x_0}^{1/7}$ for wall-resolved LES and DNS (with different prefactors), where $Re_{x_0}$ is the inlet Reynolds number. The grid-point and time-step requirement estimates allow us to estimate the overall cost of DNS and LES. According to present estimates, the costs of DNS, wall-resolved LES and wall-modeled LES scale as $Re_{L_x}^{2.91}$, $Re_{L_x}^{2.72}$, and $Re_{L_x}^{1.14}$.

physics.flu-dyn↗

arXiv2020

A new ODE-based turbulence wall model accounting for pressure gradient and Reynolds number effects

In wall-modeled large-eddy simulations (WMLES), the near-wall model plays a significant role in predicting the skin friction, although the majority of the boundary layer is resolved by the outer large-eddy simulation (LES) solver. In this work, we aim at developing a new ordinary differential equation (ODE)-based wall model, which is as simple as the classical equilibrium model yet capable of capturing non-equilibrium effects and low Reynolds number effects. The proposed model reformulates the classical equilibrium model by introducing a new non-dimensional mixing-length function. The new mixing-length function is parameterized in terms of the boundary layer shape factor instead of the commonly used pressure-gradient parameters. As a result, the newly introduced mixing-length function exhibits great universality within the viscous sublayer, the buffer layer, and the log region (i.e., $0 < y < 0.1δ$, where the wall model is typically deployed in a WMLES setup). The performance of the new model is validated by predicting a wide range of canonical flows with the friction Reynolds number between 200 and 5200, and the Clauser pressure-gradient parameter between -0.3 and 4. Compared to the classical equilibrium wall model, remarkable error reduction in terms of the skin friction prediction is obtained by the new model. Moreover, since the new model is ODE-based, it is straightforward to be deployed for predicting flows with complex geometries and therefore promising for a wide range of applications.

physics.flu-dyn↗