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DOE OSTI2022

Predictive models enhance feedstock quality of corn stover via air classification

Feedstock heterogeneity is a fundamental obstacle to cost-competitive biobased products. Agricultural products like corn stover have anatomical components that vary in their chemical composition, mechanical properties, structure, and response to chemical and biological treatments. A technique that can enrich streams in select anatomical fractions would allow a tailored deconstruction approach to increase overall process efficiency. Air classification can be leveraged for such refining, however, fundamental characterization and understanding of the particle properties that underly the physics of air classification are only modestly documented. Here, we determine fundamental particle properties including mass-to-area ratio, drag coefficient, and partition velocity that describe how anatomical tissues of corn stover behave during air classification. In this work, mass-to-area ratios of anatomical tissues vary by nearly two orders of magnitude from 2.3 mg/mm 2 for cob to 0.04 mg/mm 2 for leaf. Drag coefficients of longer, fibrous materials (i.e., rind, husk, and sheath) are shown to correlate with particle area (p-value < 0.001) whereas granular tissues (i.e., cob, pith, and leaf) correlate better with mass-to-area ratio (p-values < 0.001). When compared to experimental observations, a simulated two-stage air classification and size reduction scenario predicts the overall partitioning of anatomical tissues within 15% for pith, husk, rind, and cob tissues. The model predicts an air-classified fraction preferentially enriched in cob (purity = 20%), rind (purity = 74%), and pith (purity = 4.5%) with a mass yield of 47%. Empirical relations for these properties can be used to predict the partitioning of corn stover during air classification based on anatomical type and size.

09 BIOMASS FUELS↗

DOE OSTI2020

Computational modelling and experimental tank testing of the multi float WaveSub under regular wave forcing

A submerged wave device generates energy from the relative motion of floating bodies. In WaveSub, three floats are joined to a reactor; each connected to a spring and generator. Electricity generated damps the orbital movements of the floats. The forces are non-linear and each float interacts with the others. Tuning to the wave climate is achieved by changing the line lengths, so there is a need to understand the performance trade-offs for a large number of configurations. This requires an efficient, large displacement, multidirectional, multi-body numerical scheme. Results from a 1/25 scale wave basin experiment are described. Here, we show that a time domain linear potential flow formulation (Nemoh, WEC-Sim) can match the tank testing provided that suitably tuned drag coefficients are employed. Inviscid linear potential models can match some wave device experiments; however, additional viscous terms generally provide better accuracy. Scale experiments are also prone to mechanical friction, and we estimate friction terms to improve the correlation further. The resulting error in mean power between numerical and physical models is approximately 10%. Predicted device movement shows a good match. Overall, drag terms in time domain wave energy modelling will improve simulation accuracy in wave renewable energy device design. to understand the performance trade-offs for a large number of configurations. This requires an efficient, large displacement, multidirectional, multi-body numerical scheme. Results from a 1/25 scale wave basin experiment are described. Here, we show that a time domain linear potential flow formulation (Nemoh, WEC-Sim) can match the tank testing provided that suitably tuned drag coefficients are employed. Inviscid linear potential models can match some wave device experiments; however, additional viscous terms generally provide better accuracy. Scale experiments are also prone to mechanical friction, and we estimate friction terms to improve the correlation further. The resulting error in mean power between numerical and physical models is approximately 10%. Predicted device movement shows a good match. Overall, drag terms in time domain wave energy modelling will improve simulation accuracy in wave renewable energy device design.

16 TIDAL AND WAVE POWER↗

DOE OSTI2023

Deep learning closure models for large-eddy simulation of flows around bluff bodies

Near-wall flow simulation remains a central challenge in aerodynamics modelling: Reynolds-averaged Navier–Stokes predictions of separated flows are often inaccurate, and large-eddy simulation (LES) can require prohibitively small near-wall mesh sizes. A deep learning (DL) closure model for LES is developed by introducing untrained neural networks into the governing equations and training in situ for incompressible flows around rectangular prisms at moderate Reynolds numbers. The DL-LES models are trained using adjoint partial differential equation (PDE) optimization methods to match, as closely as possible, direct numerical simulation (DNS) data. They are then evaluated out-of-sample – for aspect ratios, Reynolds numbers and bluff-body geometries not included in the training data – and compared with standard LES models. The DL-LES models outperform these models and are able to achieve accurate LES predictions on a relatively coarse mesh (downsampled from the DNS mesh by factors of four or eight in each Cartesian direction). We study the accuracy of the DL-LES model for predicting the drag coefficient, near-wall and far-field mean flow, and resolved Reynolds stress. A crucial challenge is that the LES quantities of interest are the steady-state flow statistics; for example, a time-averaged velocity component $\langle {u}_i\rangle (x) = \lim _{t \rightarrow \infty } ({1}/{t}) \int _0^t u_i(s,x)\, {\rm d}s$ . Calculating the steady-state flow statistics therefore requires simulating the DL-LES equations over a large number of flow times through the domain. It is a non-trivial question whether an unsteady PDE model with a functional form defined by a deep neural network can remain stable and accurate on $t \in [0, \infty )$ , especially when trained over comparatively short time intervals. Our results demonstrate that the DL-LES models are accurate and stable over long time horizons, which enables the estimation of the steady-state mean velocity, fluctuations and drag coefficient of turbulent flows around bluff bodies relevant to aerodynamics applications.

Mechanics↗

DOE OSTI2024

Note on two formulations of Crank-Nicolson method for Navier-Stokes equations

Here, we consider two formulations of the Crank-Nicolson (CN) method for the Navier-Stokes equations (NSE). The “natural” way of implementing CN for NSE is formally second order accurate in time for both velocity and pressure, whereas another formulation approximates pressure with only first order accuracy in time. Both versions of the method are applied to the benchmark problem of computing drag and lift in the flow around a cylinder. We show that the presumably more accurate version of the CN can create a solution with nonphysical oscillations and give incorrect predictions for the maximal drag coefficient, whereas the other formulation of the method predicts the drag and lift coefficients more accurately and does not introduce nonphysical oscillations. We locate the source of the issue and suggest several remedies.

Crank-Nicolson↗

DOE OSTI2020

Analytic model of the remobilization of pinned glide dislocations: Including dislocation drag from phonon wind

Here, we discuss the effect of a non-constant dislocation drag coefficient on the very high strain rate regime within an analytic model describing mobile-immobile dislocation intersections applicable to fcc polycrystals. Based on previous work on dislocation drag, we estimate its temperature and pressure dependence and its effects on stress–strain rate relations. In the high temperature regime, we show that drag can remain the dominating effect even down to intermediate strain rates. We also discuss the consequences of having a limiting dislocation velocity, a feature which is typically predicted by analytic models of dislocation drag, but which is somewhat under debate because a number of MD simulations predict supersonic dislocations.

42 ENGINEERING↗

DOE OSTI2023

Revisiting the empirical particle-fluid coupling model used in DEM-CFD by high-resolution DEM-LBM-IMB simulations: A 2D perspective

The work investigates the applicability of the unresolved Computational Fluid Dynamics and Discrete Element Method (CFDDEM) technique based on empirical equations for fluid-particle coupling. We first carry out a series of representative volume element simulations using the high-resolution particle-resolved Lattice Boltzmann method and Discrete Element Method (LBMDEM) coupled by an Immersed Moving Boundary (IMB) scheme. Then, we compare the results obtained by both LBMDEM and empirical equations used in unresolved CFDDEM with analytical solutions. It is found that the existing empirical equations used in solving fluid-particle interactions in 2D CFDDEM fail to accurately calculate the hydrodynamic force applied to solid particles. The underlying reason is that the existing empirical models are obtained based on 3D experimental results and thus are not applicable to 2D problems. Based on the simulation results, a new drag coefficient model is then proposed. The estimated drag forces using the new model are compared favourably with the simulated ones, indicating the good performance of the proposed model.

42 ENGINEERING↗

DOE OSTI2020

Water Energy Resource Innovation on the Cavitation Characteristics

The main purpose of this study is to numerically correlate the amount of generated vapor over a hydrofoil to the lift and drag coefficients acting on it. As such, cavitation characteristics were investigated of a hydrofoil in the cavitating, sub-cavitating, and non-cavitating flows for different angles of attacks (AoA) with the high upstream flow velocity. The hydrofoil was tested in a square water tunnel with water entering the tunnel at various velocities for each AoA ranges from 9.1 m/s to 12.2 m/s. It was found that lift and drag forces acting on the hydrofoil follow the trend of the experimental data quite closely. While the cavitation can be identified by a unique number (averaged vapor volume fraction), the work done created an inverse correlation between this number and the cavitation number at the same angle of attack. The lift force declines with the increase in the vapor content on the hydrofoil surface, meanwhile the drag force peaks at certain vapor volume fraction, and then, a huge reduction occurs with the considerable decrease in the corresponding cavitation number. A fourth-order correlation generated between the lift to drag (L/D) and the cavitation number (σ). It was found the lift-to-drag ratio decreases by the formation of the cavitation over the hydrofoil, thus causing a drop in the efficiency of the turbomachines.

42 ENGINEERING↗

DOE OSTI2023

Hydrodynamics and Survivability during Post-main-sequence Planetary Engulfment

The engulfment of substellar bodies (SBs), such as brown dwarfs and planets, by giant stars is a possible explanation for rapidly rotating giants, lithium-rich giants, and the presence of SBs in close orbits around subdwarfs and white dwarfs. We perform three-dimensional hydrodynamical simulations of the flow in the vicinity of an engulfed SB. We model the SB as a rigid body with a reflective surface because it cannot accrete. This reflective boundary changes the flow morphology to resemble that of engulfed compact objects with outflows. We measure the drag coefficients for the ram-pressure and gravitational drag forces acting on the SB, and use them to integrate its trajectory inside the star. We find that engulfment can increase the luminosity of a 1 M ⊙ star by up to a few orders of magnitude. The time for the star to return to its original luminosity is up to a few thousand years when the star has evolved to ≈10 R ⊙ and up to a few decades at the tip of the red giant branch (RGB). No SBs can eject the envelope of a 1 M ⊙ star before it evolves to ≈10 R ⊙ if the orbit of the SB is the only energy source contributing to the ejection. In contrast, SBs as small as ≈10 MJup can eject the envelope at the tip of the RGB. The numerical framework we introduce here can be used to study planetary engulfment in a simplified setting that captures the physics of the flow at the scale of the SB.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Misaligned Wind‐Waves Behind Atmospheric Cold Fronts

Abstract Atmospheric fronts embedded in extratropical cyclones are high‐impact weather phenomena, contributing significantly to mid‐latitude winter precipitation. The three vital characteristics of the atmospheric fronts, high wind speeds, abrupt change in wind direction, and rapid translation, force the induced surface waves to be misaligned with winds exclusively behind the cold fronts. The effects of the misaligned waves under atmospheric cold fronts on air‐sea fluxes remain undocumented. Using the multi‐year in situ near‐surface observations and direct covariance flux measurements from the Pioneer Array off the coast of New England, we find that the majority of the passing cold fronts generate misaligned waves behind the cold front. Once generated, the waves remain misaligned, on average, for about 8 hr. The parameterized effect of misaligned waves in a fully coupled model significantly increases the roughness length (185%), drag coefficient (19%), and air‐sea momentum flux (11%). The increased surface drag reduces the wind speeds in the surface layer. The upward turbulent heat flux is weakly decreased by the misaligned waves because of the decrease in temperature and humidity scaling parameters being greater than the increase in friction velocity. The misaligned wave effect is not accurately represented in a commonly used wave‐based bulk flux algorithm. Yet, considering this effect in the current formulation improves the overall accuracy of parameterized momentum flux estimates. The results imply that better representing a directional wind‐wave coupling in the bulk formula of the numerical models may help improve the air‐sea interaction simulations under the passing atmospheric fronts in the mid‐latitudes.

Oceanography↗

DOE OSTI2026

OC7 phase I: CFD investigation of viscous forces on rectangular members of semisubmersibles

In Phase I of the Offshore Code Comparison Collaboration 7 (OC7) project, we aim to address key questions related to the modeling of viscous hydrodynamic loads on floating platforms. Here, this paper presents results from a collaborative effort within Phase I of the OC7 project. We investigate viscous forces acting on the rectangular members of semisubmersible platforms using high-fidelity computational fluid dynamics (CFD) simulations. The parametric CFD analyses include two-and-a-half-dimensional (2.5D) simulations of pontoon sections of two different semisubmersible platform designs (the VolturnUS-S and the INO WINDMOOR) and full three-dimensional (3D) structure simulations of the VolturnUS-S platform. We extract both the added mass and drag coefficients that are typically used in engineering-level hydrodynamic models from the 2.5D forced oscillation simulations with various Keulegan-Carpenter numbers and compare them to the coefficients from the 3D forced oscillation simulations. We observe consistent variation of the coefficients along the pontoon legs due to 3D platform and free-surface effects. With the breadth of the simulations and component-level detailed analyses, this work establishes a useful database and several empirical formulas for selecting hydrodynamic coefficients when modeling semisubmersible platforms in engineering tools.

13 HYDRO ENERGY↗

DOE OSTI2024

Heave Plate Hydrodynamic Coefficients for Floating Offshore Wind Turbines - A Compilation of Data

The National Renewable Energy Laboratory's OpenFAST software is utilized by academics and industry professionals alike to simulate offshore wind turbines. The software's modeling of hydrodynamic loads on heave plates attached to these structures relies on user-specified hydrodynamic coefficients. To guide the proper selection of these coefficients and potentially develop a new functionality within OpenFAST that automatically prescribes and/or adjusts the heave-plate hydrodynamic coefficients, we review past literature to examine the dependence of the added mass, damping, and drag coefficients on various relevant nondimensional parameters, including the Keulegan-Carpenter number, the frequency parameter, and the plate thickness ratio. Existing data in the literature show strong dependence of the hydrodynamic coefficients on the Keulegan-Carpenter number. We observe consistent trends across a range of different plate geometry, plate porosity, and flow conditions. Secondary dependence of the coefficients on the frequency parameter and plate thickness ratio is also present.

added mass↗

DOE OSTI2024

Heave-Plate Hydrodynamic Coefficients for Floating Offshore Wind Turbines - A Compilation of Data: Preprint

The National Renewable Energy Laboratory's OpenFAST software is utilized by academics and industry professionals alike to simulate offshore wind turbines. The software's modeling of hydrodynamic loads on heave plates attached to these structures relies on user specified hydrodynamic coefficients. To guide the proper selection of these coefficients and potentially develop a new functionality within OpenFAST that automatically prescribes and/or adjust the heave-plate hydrodynamic coefficients, this paper reviews past literature to examine the dependence of the added mass, damping, and drag coefficients on various relevant non-dimensional parameters, including the Keulegan-Carpenter number, the frequency parameter, and the plate thickness ratio. Existing data in the literature show strong dependence of the hydrodynamic coefficients on the Keulegan-Carpenter number. Consistent trends are observed across a range of different plate geometry, plate porosity, and flow conditions. Secondary dependence of the coefficients on the frequency parameter and plate thickness ratio is also present.

added mass↗

DOE OSTI2025

Development and Evaluation of a General Drag Model for Gas-Solid Flows via Deep Learning

This project presents the development and evaluation of a general drag model for gas–solid multiphase flows using deep learning techniques. A comprehensive database of more than 4,000 experimental and numerical data points for spherical and non spherical particles was compiled, incorporating geometric features such as sphericity, aspect ratio, and orientation. Several predictive approaches—including traditional em pirical correlations, machine learning, and deep neural networks—were benchmarked, with the proposed Drag Coefficient Correlation-aided Deep Neural Network (DCC DNN) demonstrating superior accuracy. To account for particle–particle interactions, additional drag data were generated using CFD-based simulations of packed and flu idized beds, leading to the development of a retrained model capable of incorporat ing volume fraction effects. Integration of the trained model with the MFiX CFD solver was achieved using FTorch, enabling drag predictions during discrete element method (DEM) simulations. Validation against experimental data for single particles and fluidized beds confirmed the model’s improved predictive ability, particularly for non-spherical geometries. While the model performed strongly under fluidized con ditions, limitations remained in unfluidized regimes, suggesting a need for expanded datasets. Overall, this study demonstrates the feasibility of combining deep learning with physics-informed CFD to improve drag modeling for gas–solid flows, with promis ing implications for scaling multiphase simulations in industrial applications.

42 ENGINEERING↗

DOE OSTI2022

Dynamic Pressure Drag on Rising Buoyant Thermals in a Neutrally Stable Environment

Abstract This study examines dynamic pressure drag on rising dry buoyant thermals. A theoretical expression for drag coefficient C d as a function of several other nondimensional parameters governing thermal dynamics is derived based on combining the thermal momentum budget with the similarity theory of Scorer. Using values for these nondimensional parameters from previous studies, the theory suggests drag on thermals is small relative to that on solid spheres in laminar or turbulent flow. Two sets of numerical simulations of thermals in an unstratified, neutrally stable environment using an LES configuration of the Cloud Model 1 (CM1) are analyzed. One set has a relatively low effective Reynolds number R e and the other has an order-of-magnitude-higher R e ; these produce laminar and turbulent resolved-scale flows, respectively. Consistent with the theoretical C d , the magnitude of drag is small in all simulations. However, whereas the laminar thermals have C d ≈ 0.01, the turbulent thermals have weakly negative drag ( C d ≈ −0.1). This difference is explained by the laminar thermals having near vertical symmetry but the turbulent thermals exhibiting considerable vertical asymmetry of their azimuthally averaged flows. In the laminar thermals, buoyancy rapidly becomes concentrated around the main centers of rotation located along the horizontal central axis, leading to expansion of thermals via baroclinic vorticity generation but doing little to break vertical symmetry of the flow. Vertical asymmetry of the azimuthally averaged flow of turbulent thermals is attributed mainly to small-scale resolved eddies that are concentrated in the upper part of the thermals.

Meteorology & Atmospheric Sciences↗

DOE OSTI2025

Applying a Compact Porous Media Model to Numerically Derive Resistance Coefficients for Lattice Structures

Additive Manufacturing allows for exploring various geometries to achieve specific engineering criteria. Lattices are one geometry with unique properties, including being periodically repeating structures which allow flow through them to be represented as a porous media according to Darcy-Forchheimer equations. These equation’s coefficients are generally experimentally derived, but this work demonstrates the ability to numerically derive them with CFD. Simulations were performed using three-dimensional stead state Reynolds-averaged Navier-Stokes with a k-ω Shear Stress Transport turbulence model using Ansys Fluent. Three lattice geometries were investigated and drag coefficients were derived. The method was validated against externally published data for similar geometries demonstrating strong agreement, and grid convergence for all simulations was calculated with a Grid Convergence Index method. Wall roughness is demonstrated to have a non-negligible impact on results and roughness values are considered for the primary focus Octahedral geometry where both smooth wall and rough wall coefficients were derived. The porosity coefficients for the Octahedral geometry at 1.0 [m/s] were found to be 2.89×10 6 and 2.90×10 6 [1/(Pa*m*s)] for the permeability coefficients, 6.37×10 1 and 5.44×10 1 [m 2 /kg] for the inertial resistance coefficients, and with a max pressure drop of 5116.7 [Pa] and 4429.5 [Pa] for the smooth walls and rough walls, respectively. The derived numerical method enables rapid exploration and optimization of new lattice designs for diverse engineering applications.

42 ENGINEERING↗

DOE OSTI2022

Modeling of Cube Array Roughness: RANS, Large Eddy Simulation, and Direct Numerical Simulation

Abstract Flow over arrays of cubes is an extensively studied model problem for rough wall turbulent boundary layers. While considerable research has been performed in computationally investigating these topologies using direct numerical simulation (DNS) and large eddy simulation (LES), the ability of sublayer-resolved Reynolds-averaged Navier–Stokes (RANS) to predict the bulk flow phenomena of these systems is relatively unexplored, especially at low and high packing densities. Here, RANS simulations are conducted on six different packing densities of cubes in aligned and staggered configurations. The packing densities investigated span from what would classically be defined as isolated, up to those in the d-type roughness regime, filling in the gap in the present literature. Three different sublayer-resolved turbulence closure models were tested for each case: a low Reynolds number k–ϵ model, the Menter k–ω SST model, and a full Reynolds stress model. Comparisons of the velocity fields, secondary flow features, and drag coefficients are made between the RANS results and existing LES and DNS results. There is a significant degree of variability in the performance of the various RANS models across all comparison metrics. However, the Reynolds stress model demonstrated the best accuracy in terms of the mean velocity profile as well as drag partition across the range of packing densities.

Engineering↗

DOE OSTI2024

The advancing wave front on a sloping channel covered by a rod canopy following an instantaneous dam break

The drag coefficient Cd for a rigid and uniformly distributed rod canopy covering a sloping channel following the instantaneous collapse of a dam was examined using flume experiments. The measurements included space x and time t high resolution images of the water surface h(x, t) for multiple channel bed slopes So and water depths behind the dam Ho along with drag estimates provided by sequential load cells. Using these data, an analysis of the Saint-Venant equation (SVE) for the front speed was conducted using the diffusive wave approximation. An inferred Cd=0.4 from the h(x, t) data near the advancing front region, also confirmed by load cell measurements, is much reduced relative to its independently measured steady-uniform flow case. This finding suggests that drag reduction mechanisms associated with transients and flow disturbances are more likely to play a dominant role when compared to conventional sheltering or blocking effects on Cd examined in uniform flow. The increased air volume entrained into the advancing wave front region as determined from an inflow–outflow volume balance partly explains the Cd reduction from unity.

Mechanics↗

DOE OSTI2020

Six Degrees of Freedom (6DOF) Simulations of Supersonic Fragment Trajectories

In this report a process using existing technologies at Sandia National Laboratories (SNL) to simulate the six degrees-of-freedom (6DOF) trajectories of explosive fragments is described and tested. First, aerodynamic forces and moments as functions of orientation are computed using the SIERRA/Aero supersonic flow solver. The forces and moments are normalized and tabulated in a database. Second, this the aerodynamic coefficient database is imported into a 6DOF rigid body dynamics solver in order to compute the resulting trajectories. The supersonic flow simulations are tested for simple geometries and show good agreement with literature values. The simulation procedure is then demonstrated for an example fragment. The results of the example fragment indicate that the distance traveled in the early ight (from 2.5 km/s until decreasing down to 1 km/s) varies widely depending on the initial orientations. The fragment trajectory distribution and steady tumbling rate is explored. The study indicates that a 6DOF analysis will yield information about a spread of possible trajectories, while using an average drag coefficient can only represent the most likely trajectory.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗