Capability Of Computational Fluid Dynamics Research Articles

HPC challenges and opportunities of industrial-scale reactive fluidized bed simulation using meshes of several billion cells on the route of Exascale

Inside fluidized bed reactors, gas–solid flows are very complex: multi-scale, coupled, reactive, turbulent and unsteady. Accounting for them in an Euler-nfluid framework induces significantly expensive numerical simulations at academic scales and even more at industrial scales. 3D numerical simulations of gas–particle fluidized beds at industrial scales are limited by the High Performances Computing (HPC) capabilities of Computational Fluid Dynamics (CFD) software and by available computational power. In recent years, pre-Exascale supercomputers came into operation with better energy efficiency and continuously increasing computational resources.The present article is a direct continuation of previous work, Neau et al. (2020) which demonstrated the feasibility of a massively parallel simulation of an industrial-scale polydispersed fluidized-bed reactor with a mesh of 1 billion cells. Since then, we tried to push simulations of these systems to their limits by performing large-scale computations on even more recent and powerful supercomputers, once again using up to the entirety of these supercomputers (up to 286,000 cores). We used the same fluidized bed reactor but with more refined unstructured meshes: 8 and 64 billion cells.This article focuses on efficiency and performances of neptune_cfd code (based on Euler-nfluid approach) measured on several supercomputers with meshes of 1, 8 and 64 billion cells. It presents sensitivity studies conducted to improve HPC at these very large scales.On the basis of these highly-refined simulations of industrial scale systems using pre-Exascale supercomputers with neptune_cfd, we defined the upper limits of simulations we can manage efficiently in terms of mesh size, count of MPI processes and of simulation time. One billion cells computations are the most refined computation for production. Eight billion cells computations perform well up to 60,000 cores from a HPC point of view with an efficiency >85% but are still very expensive. The size of restart and mesh files is very large, post-processing is complicated and data management becomes near-impossible. 64 billion cells computations go beyond all limits: solver, supercomputer, MPI, file size, post-processing, data management. For these reasons, we barely managed to execute more than a few iterations.Over the last 30 years, neptune_cfd HPC capabilities improved exponentially by tracking hardware evolution and by implementing state-of-the-art techniques for parallel and distributed computing. However, our last findings show that currently implemented MPI/Multigrid approaches are not sufficient to fully benefit from pre-Exascale system. This work allows us to identify current bottlenecks in neptune_cfd and to formulate guidelines for an upcoming Exascale-ready version of this code that will hopefully be able to manage even the most complex industrial-scale gas–particle systems.

STUDY OF HEAT AND MASS TRANSFER IN WOOD-COMPOSITE MATERIALS BY MEANS OF COMPUTATIONAL FLUID DYNAMICS

Wood-composite materials (WCM), undergoes complex heat and mass transfer processes during its conditioning. Understanding these interactions is crucial for optimizing the conditioning process and ensuring high quality of the final product. This study focuses on the problem of modeling the interactions that occur during WCM conditioning, taking into account their characteristics that depend on temperature, moisture content, and density of the material. In addition, various input parameters are taken into account in the modeling process to set the optimal conditioning conditions. Despite the availability of these parameters in the literature based on the results of real experiments, consolidating this data in computer modeling is still a major problem. To resolve this issue, this study focuses on modeling the heat and mass transfer processes during WCM cooling using computational fluid dynamics (CFD) software such as SolidWorks Flow Simulation. By using the capabilities of CFD, it is relatively possible to utilize technical parameters involved in the WCM conditioning process with relative simplicity. The paper provides a detailed description of the created 3D model of the WCM-conditioning chamber and its main components. In addition, the paper describes the various input parameters used in the modeling process, including temperature, moisture content, and density of WCM. In addition, the operation of the fans was set up and the initial values of temperature, moisture content, and air velocity were set. Based on the simulation, the results obtained include the distribution of the temperature field and moisture content on the surface of the WCM at different material densities and air conditioning parameters. Additionally, the trajectory of air masses and their velocity within the 3D model was obtained. In general, the obtained results provide a better understanding of the influence of various input parameters on the process of heat and mass transfer in WCM during their cooling. Given the comprehensive analysis, this research this work can be useful for improvement of WCM production processes and quality control of final products. In particular, it emphasizes the importance of further research in this area and the need for computer modeling of such processes to further develop effective engineering solutions.

A CFD Methodology for the Modelling of Animal Thermal Welfare in Hybrid Ventilated Livestock Buildings

Computational fluid dynamics (CFD) may aid the design of barn ventilation systems by simulating indoor cattle thermal welfare. In the literature, CFD models of mechanically and naturally ventilated barns are proposed separately. Hybrid ventilation relies on cross effects between air change mechanisms that cannot be studied using existing models. The objective of this study was to develop a CFD methodology for modelling animal thermal comfort in hybrid ventilated barns. To check the capability of CFD as a design evaluation tool, a real case study (with exhaust blowers) and an alternative roof layout (with ridge gaps) were simulated in summer and winter weather. Typical phenomena of natural and mechanical ventilation were considered: buoyancy, solar radiation, and wind together with high-speed fans and exhaust blowers. Cattle thermal load was determined from a daily animal energy balance, and the assessment of thermal welfare was performed using thermohygrometric indexes. Results highlight that the current ventilation layout ensures adequate thermal welfare on average, despite large nonuniformity between stalls. The predicted intensity of heat stress was successfully compared with experimental measurements of heavy breathing duration. Results show strong interactions between natural and mechanical ventilation, underlining the need for an integrated simulation methodology.

Acoustic analysis of chevron nozzle: A CFD approach

Noise pollution from aircraft is a critical environmental issue, affecting not only wildlife but also human health and comfort, especially for populations living near airports. The recent, researchers have been primarily focused on reducing noise pollution in aircraft systems. Among the major contributors to noise pollution are the aircraft engine and nozzle. To address noise in the nozzle, the chevron nozzle, characterized by a sawtooth pattern at its edge, has been commercialized. Thus, there is a need for dependable Computational Fluid Dynamics (CFD) capabilities to swiftly assess initial designs for noise reduction and analyze problems that involve fluid flows. For noise reduction in aircraft systems, CFD capabilities are essential. This study conducts Finite Element Method (FEM) analysis of the chevron nozzle. Additionally, design optimization is performed utilizing the Taguchi method.

Computational Fluid Dynamics Modeling of Concrete Flows in Drilled Shafts

Drilled shafts are cylindrical, cast-in-place concrete deep foundation elements. During construction, anomalies in drilled shafts can occur due to the kinematics of concrete, flowing radially from the center of the shaft to the concrete cover region at the peripheral edge. This radial component of concrete flow develops veins or creases of poorly cemented or high water-cement ratio material, as the concrete flows around the reinforcement cage of rebars and ties, jeopardizing the shaft integrity. This manuscript presents a three-dimensional computational fluid dynamics (CFD) model of the non-Newtonian concrete flow in drilled shaft construction developed using the finite volume method with interface tracking based on the volume of fluid (VOF) method. The non-Newtonian behavior of the concrete is represented via the Carreau constitutive model. The model results are encouraging as the flow obtained from the simulations shows patterns of both horizontal and vertical creases in the concrete cover region, consistent with previously reported field and laboratory experiments. Moreover, the flow exhibits the concrete head differential developed between the inside and the outside of the reinforcement cage, as exhibited in the physical experiments. This head differential induces the radial component of the concrete flow responsible for the creases that develop in the concrete cover region. Results show that the head differential depends on the flowability of the concrete, consistent with field observations. Less viscous concrete tends to reduce the head differential and the formation of creases of poorly cemented material. The model is unique, making use of state-of-the-art numerical techniques and demonstrating the capability of CFD to model industrially relevant concrete flows.

Developing a Performance-Based Approach to the Effect of Roof Features on Fire Safety in Buildings with Atriums

Developing technology, changing social structures, and the threat of resource depletion have changed the design of buildings. Therefore, design approaches are developed to increase user comfort and reduce energy consumption by utilizing natural ventilation and lighting. The design of the distribution of outdoor air and light into the spaces through vertical and horizontal gaps reduces the energy demand of the mechanical systems and increases occupant comfort. The atrium is the preferred vertical gap in modern buildings for distributing natural air and light to interior spaces under appropriate conditions. However, in buildings with atrium, there is a risk of fire spreading in the event of a fire due to the uninterrupted gaps between the rooms. It is necessary to ensure the operability of the design by monitoring the measures to be taken in the early stages of design using performance-based fire safety methods. This study develops design strategies for fire analysis in atrium buildings using computational fluid dynamics (CFD) simulation technology. Atrium height, roof type, and slope characteristics are analyzed for the stack effect, which is the main factor in the movement of smoke and flames. As a result of the numerical analyses consisting of flat, unidirectional, and bidirectional sloping roof type, 10, 20, 30-degree roof slope, and one-meter rising atrium roof variables, the effect degrees for smoke dispersal and temperature control are investigated. Fire Dynamic Simulator, which uses CFD capabilities, and Smokeview software, which can visualize the results, were used for the numerical analysis. Correlation analysis was used to determine the effect of variables on temperature. The results showed that flat roofs and designs with increasing height were effective in delaying the spread of smoke and increasing the stack effect in the atrium, while the contribution of roof slope to fire safety was weak.

Hydrogen, methane and one of their fuel blends combustion: CFD analysis and numerical-experimental comparisons of fixed and mobile applications

The capabilities of Computational Fluid Dynamics (CFD) coupled with detailed chemistry simulations are examined in both steady jet diffusion flames and in an internal combustion engine case fuelled with hydrogen. Different approaches to turbulence-chemistry interaction such as the “Laminar Flame Concept” the “Eddy Dissipation Concept” and the “Turbulent Flame Speed Closure” are considered and tested. The results are compared with the experimental data available. Concerning the jet diffusion flames, the combustion processes of hydrogen, methane and one of their fuel blends are investigated on two burner geometries. Different sensitivities (i.e. mesh, turbulence model, turbulent Schmidt number, chemical mechanism) are performed. The study demonstrates that despite the burner geometry considered and the chemical composition of the fuel, the Complex Chemistry with “Eddy Dissipation Concept” is the model that better describes the behaviour of the turbulent flames. On the other hand, the “Laminar Flame Concept” sub-model is characterized by an higher fuel consumption rate, which causes an overestimation of the temperature peak. As for the in-cylinder unsteady simulations, the hydrogen combustion process is better described by the “Turbulent Flame Speed Closure” sub-model, which, unlike the other two, requires the specification of both laminar and turbulent flame speed. Despite different variations being considered, the “Laminar Flame Concept” adoption leads to an unphysically high burning rate, while the Eddy Dissipation Concept sub-model is characterized by an underestimation of the apparent heat release rate, and thus of the pressure peak inside the combustion chamber.

Experimental and numerical study of an elevated pool fire scenario in a confined and mechanically ventilated compartment

The present work deals with an experimental and numerical investigation of an elevated pool fire scenario in a confined and forced ventilated compartment. Although often encountered in industrial installations or in common buildings, this type of configuration is rarely studied in the literature. This study is supported by a set of two large-scale fire experiments performed in the framework of the OECD-PRISME3 project and numerical simulations (RANS and LES methods) carried out with the CALIF3S-Isis software. The objective is to improve the physical understanding of the phenomena that are experimentally highlighted and to assess the capabilities of Computational Fluid Dynamics (CFD) on this type of configuration. First, the comparison between the two large-scale fire tests (one elevated and its equivalent on the ground) exhibits a strong modification of the fuel mass loss rate associated with a change in the thermal and species stratifications. Then, a preliminary simulation using a predictive approach commonly used and efficient for the case of a ground fire scenario shows by contrast its limitations when applied to the case of the elevated fire. Therefore, in addition to the essential step consisting in the validation of the code with a prescribed approach on this type of elevated fire, the simulations also reveal a specific phenomenology (smoke filling, strong vitiation, oxygen-pumping, …). Finally, taking into account these particularities allows in fine, for the studied case, the improvement of the prediction of the mass loss rate of the fire.

Scour Development Around an Oblong Bridge Pier: A Numerical and Experimental Study

The complex flow structure around bridge piers is challenging for both experimental and numerical studies. Therefore, investigating the capabilities of Computational Fluid Dynamics (CFD) tools in resolving the flow structure and the mechanism of sediment entrainment into and out of the scour hole remains a challenging task. In this study, the scour depth around an oblong bridge pier and the bed shear stress distributions in time and space were numerically investigated using the Computational Fluid Dynamics (CFD) tool Sediment Simulation In Intakes with Multiblock option (SSIIM). Clear water scour conditions and sand of known granulometric composition were considered in accordance with the experimental study carried out. Laboratory data and the results of a scour characterization around a 0.11 m wide oblong bridge pier were considered to calibrate and validate the numerical model. The averaged form of the Navier–Stokes equations was considered to simulate the turbulent flow fields in anticipation of long time scales. The results show that calibrated numerical models can reproduce measured scour depths in the laboratory environment with considerable accuracy, with an average relative error of less than 3%, especially around oblong bridge piers.

Separated and vortical flow in aircraft aerodynamics: a CFD perspective

AbstractIn the early era of aviation, Frederick Lanchester was both an inventor and a theoretician driven by the need for a theory of flight that would reduce the guesswork in designing new aircraft. His book Aerodynamics in 1907 laid down the early foundations of such a theory. The theory with contributions from others, notably Ludwig Prandtl, was refined to become the basis for the sleek designs of WWII aircraft brought about with little guesswork. New technology changed aircraft design radically with the increased speed of jet propulsion reaching into the transonic range with nonlinear aerodynamics. In the late 1940s and early 1950s substantial guesswork returned to aircraft design. The legacy of Lanchester et al., however, lived on with the development of computational fluid dynamics (CFD) that could guide designers through nonlinear transonic effects. This article presents a historical sketch of how CFD developed, illustrated with examples explaining some of the difficulties overcome in the design of the first-generation swept-wing transonic fighters. The historical study is forensic CFD in search for the likely explanation of the designer’s choice for the wing shape that went into production a long time ago. The capability of current CFD applied to the aerodynamics of aircraft with slender wings is surveyed. The cases discussed involve flow patterns with coherent vortices over hybrid wings and wings of moderate sweep. Vortex-flow aerodynamics pertains to understanding the interaction of concentrated vortices with aircraft components. Modern Reynolds-Averaged Navier-Stokes (RANS) technology is useful to predict attached flow. But vortex interaction with other vortices and breakdown lead to unsteady, largely separated flow which has been found out of scope for RANS. Direct simulation of the Navier-Stokes equations is out of computational reach in the foreseeable future, and the need for better physical modeling is evident. Both cruise performance and stalling characteristics are influenced by strong interactions. Two important aspects of wing-flow physics are discussed: separation from a smooth surface that creates a vortex, and vortex bursting, the abrupt breakdown of a vortex with a subsequent loss of lift. Vortex aerodynamics of not-so-slender wings encounter particularly challenging problems, and it is shown how the design of early-generation operational aircraft surmounted these difficulties. Through use of forensic CFD, the article concludes with two case studies of aerodynamic design: how the Saab J29A wing maintains control authority near stall, and how the Saab J32 mitigates pitch-up instability at high incidence.

An Insight into Quasi-Two-Dimensional Flow Features Over Turbine Blading From the Works of Jonathan Paul Gostelow

Abstract The flow through the predominantly two-dimensional geometries of cascades of blades is intrinsically three-dimensional and unsteady. Direct Numerical Simulation, Large Eddy Simulations, and time-resolved Particle Image Velocimetry provide access to the full flow physics, relevant to aerodynamic loss and heat management. Such studies build upon earlier insight drawn from quasi-two-dimensional investigations that identified the key areas where progress in understanding was most needed. These areas stretch across the full passage, from the leading edge of the blade to the passage outflow. Streamwise surface vorticity, transition, the calmed region, shock–boundary layer interaction, and vortex shedding are considered in detail, specifically (i) on what gaps in their physical understanding the works of Jonathan Paul Gostelow exposed and (ii) what gaps were present in the two-dimensional computational approaches used to represent these flows in these works. These useful insights are obtained from the geometrically simpler settings of circular cylinders in cross-flow and from flat plate experiments, as well as from cascades of blades. This paper presents an overview of the physical understanding of the flow features that underpins the more recent time-resolved three-dimensional investigations, led by the late Emeritus Professor Jonathan Paul Gostelow. This work celebrates some of Paul Gostelow’s 50 + years of turbomachinery research achievements and develops awareness about their significance toward reaching a more complete knowledge of the flow physics in turbomachinery, using the more recent time-resolved three-dimensional modeling capability of Computational Fluid Dynamics.

Aeroacoustic sources analysis of wake-ingesting propeller noise

High resolution aeroacoustic source analysis is a prerequisite to address the noise concerns and release the full benefits of wake-ingesting propellers. In this work, the aeroacoustic sources of a two-bladed propeller ingesting the wake of an aerofoil are investigated using large eddy simulation in conjunction with two different source identifying approaches. The first approach is the numerical beamforming that utilizes both the classical and wavelet-based beamforming techniques, which determine the phase variations of sources at the low to mid frequencies and reveal that the high-frequency sources are phase-independent. To further improve the spatial resolution of source identification, a new near-field aeroacoustic source analysis approach based on the acoustic analogy is developed in this work. In particular, the on-surface source terms emanating the far-field noise are derived based on the Ffowcs Williams and Hawkings equation for low Mach number flows and constant rotating propellers. Through the incorporation of the simulation results into the proposed source analysis approach, various types of aeroacoustic sources are identified and studied by visualizing their distributions on the propeller surfaces, correlating to flow features and examining the noise spectra and directivity. While the leading edge sources are highly correlated with the wake interaction process, the sources at the mid-chord and the trailing edge of the blade can maintain their strength across most revolving angles. Overall, the proposed analysis approaches extend the capability of computational fluid dynamics and enable the detailed study of noise generation mechanisms of wake-ingesting propeller noise.

Sensitivity analysis for subcooled flow boiling using Eulerian CFD approach

This paper presents capability of Eulerian CFD (Computational Fluid Dynamics) approach using sensitivity-analysis-based model to predict subcooled boiling flows in the DEBORA experiment, the conditions corresponding to those in PWRs (Pressurized Water Reactors). The main feature of the developed model is a good estimation of the void fraction distribution in a cross section of a heated pipe, not only in the lower void regime but also in the high void regime (>0.5), which is achieved by modifying the lift force coefficients in the model developed by Baglietto’s group. In addition, the Sauter diameter profile is well predicted by employing the MUSIG population balance model, in which the coalescence and breakage factors are tuned to the experiments. A nucleation site density model recently proposed by Li is employed together with the Tolubinsky and Kostanchuk bubble departure diameter model, whose coefficient is again obtained via a sensitivity analysis. The model developed in this work, CTU-PSI model, is expected to be applied to boiling flow simulations in PWRs.

Computational Fluid Dynamics Modeling of Pseudotransient Perforation Erosion in a Limited-Entry Completion Cluster

Summary Hydraulic fracturing in limited-entry (LE) completion designs relies on maintaining a high bottomhole treating pressure (BHTP). LE requires high perforation friction to maintain an even distribution of the hydraulic fracturing slurry. As sand exits the perforations, the perforations start to erode. The erosional change in the perforation alters the desired perforation friction and subsequent BHTP. As operators rely on multistage hydraulic fracturing to generate economic production, the issue of perforation erosion becomes inherently repetitive from stage to stage and cumulatively a significant issue. The industry has seen how a perforation can change from a before-and-after perspective with downhole cameras and imaging techniques before and after treatments. However, a more detailed understanding of the dynamic process of perforation erosion can give a better expectation of perforation performance throughout a hydraulic fracturing treatment and not just pretreatment compared to post-treatment. Computational fluid dynamics (CFD) is a quickly emerging tool in the industry. CFD aims to model fluid flow by numerically solving the Naiver-Stokes equations within a specified domain. Along with modeling fluid systems, CFD has the capability to model dispersed particles within the fluid. Once the particles are introduced into the fluid, the domain can also be eroded away within the CFD model. By utilizing the erosional capabilities of CFD, paired with the flow of a hydraulic fracturing slurry, perforation erosion can be investigated transiently throughout an entire hydraulic fracturing stage. This work presents a better dynamic understanding of perforation erosion rather than just a “before vs. after” comparison. The CFD modeling methodology used to achieve the correct erosional pattern observed in the field is presented. Throughout this work, four different hydraulic fracturing completion parameters are investigated to determine the respective roles in perforation erosion. The four parameters include proppant size, proppant concentration, fracturing fluid viscosity, and proppant concentration ramping schedules. By investigating the impact that controlled design parameters have on perforation erosion, perforation erosion can be better anticipated to deliver improved completion results.

Improvement of a Mathematical Model to Predict CO2 Removal in Hollow Fiber Membrane Oxygenators.

The use of extracorporeal oxygenation and CO2 removal has gained clinical validity and popularity in recent years. These systems are composed of a pump to drive blood flow through the circuit and a hollow fiber membrane bundle through which gas exchange is achieved. Mathematical modeling of device design is utilized by researchers to improve device hemocompatibility and efficiency. A previously published mathematical model to predict CO2 removal in hollow fiber membrane bundles was modified to include an empirical representation of the Haldane effect. The predictive capabilities of both models were compared to experimental data gathered from a fiber bundle of 7.9 cm in length and 4.4 cm in diameter. The CO2 removal rate predictions of the model including the Haldane effect reduced the percent error between experimental data and mathematical predictions by up to 16%. Improving the predictive capabilities of computational fluid dynamics for the design of hollow fiber membrane bundles reduces the monetary and manpower expenses involved in designing and testing such devices.

Characterization of the Finite Element Computational Fluid Dynamics Capabilities in the Multiphysics Object Oriented Simulation Environment

Abstract The multiphysics object-oriented simulation environment (moose) is a code package that couples a variety of physics modules, allowing for highly accessible multiphysics simulations. The physics modules include a finite element Navier–Stokes (N–S) module that is designed to solve laminar fluid dynamics problems. The usage of this module in multiple recent studies coupled with the growing interest in moose for usage in nonlight water reactor safety studies by the Nuclear Regulatory Commission (NRC) prompted the authors to investigate the computational fluid dynamics capabilities of moose. A two-dimensional laminar flow past a circular cylinder scenario is simulated in the moose framework to investigate the effectiveness of the N–S module. Simulations assumed an unsteady laminar flow with a Reynolds number of 200. To verify the results from moose, similar simulations were conducted using the well-utilized simulation of turbulent flow in arbitrary regions—computational continuum mechanics C++ (star-ccm+) finite volume code. Results from both codes are also compared to some results from literature. Velocity and pressure profiles of both transient simulations were compared. The numerical and input errors in moose are also visualized with contour plots to qualitatively understand the evolution of the errors across time and space. The comparisons between moose and star-ccm+ showed nearly perfect agreement between the codes for velocity and pressure, especially after the development of the vortex street in later time-steps. The force coefficients showed excellent agreement after the development of the vortex street, but demonstrated notable discrepancies prior to the vortex street development, which is likely due to how each code simulated the approach to the vortex street in earlier time-steps.

Implementing machine learning to optimize the cost-benefit of urban water clarifier geometrics

Clarification basins are ubiquitous water treatment units applied across urban water systems. Diverse applications include stormwater systems, stabilization lagoons, equalization, storage and green infrastructure. Residence time (RT), surface overflow rate (SOR) and the Storm Water Management Model (SWMM) are readily implemented but are not formulated to optimize basin geometrics because transport dynamics remain unresolved. As a result, basin design yields high costs from hundreds of thousands to tens of million USD. Basin optimization and retrofits can benefit from more robust and efficient tools. More advanced methods such as computational fluid dynamics (CFD), while demonstrating benefits for resolving transport, can be complex and computationally expensive for routine applications. To provide stakeholders with an efficient and robust tool, this study develops a novel optimization framework for basin geometrics with machine learning (ML). This framework (1) leverages high-performance computing (HPC) and the predictive capability of CFD to provide artificial neural network (ANN) development and (2) integrates a trained ANN model with a hybrid evolutionary-gradient-based optimization algorithm through the ANN automatic differentiation (AD) functionality. ANN model results for particulate matter (PM) clarification demonstrate high predictive capability with a coefficient of determination (R2) of 0.998 on the test dataset. The ANN model for total PM clarification of three (3) heterodisperse particle size distributions (PSDs) also illustrates good performance (R2>0.986). The proposed framework was implemented for a basin and watershed loading conditions in Florida (USA), the ML basin designs yield substantially improved cost-effectiveness compared to common designs (square and circular basins) and RT-based design for all PSDs tested. To meet a presumptive regulatory criteria of 80% PM separation (widely adopted in the USA), the ML framework yields 4.7X to 8X lower cost than the common basin designs tested. Compared to the RT-based design, the ML design yields 5.6X to 83.5X cost reduction as a function of the finer, medium, and coarser PSDs. Furthermore, the proposed framework benefits from ANN’s high computational efficiency. Optimization of basin geometrics is performed in minutes on a laptop using the framework. The framework is a promising adjuvant tool for cost-effective and sustainable basin implementation across urban water systems.

Realizing the Vision of CFD in 2030

In 2014, NASA released a report outlining a future state for aerospace computational fluid dynamics (CFD), the CFD Vision 2030 Study (the Study).1 Developed by experts from industry, government, and academia, the Study provided a forecast of CFD capabilities required for turbulent, transitional, and reacting flow simulations across a broad Mach number regime. In addition, the Study provided an aspirational role for future CFD as part of a routine, efficient, and physics-based aerospace design and development process. This future role of CFD was summarized in the Study as follows: “A single engineer/scientist must be able to conceive, create, analyze, and interpret a large ensemble of related simulations in a time-critical period (e.g., 24 hours), without individually managing each simulation, to a prespecified level of accuracy.”

NUMERICAL PREDICTION OF VERTICAL SHIP MOTIONS AND ADDED RESISTANCE

Along with the development of computer technology, the capability of Computational Fluid Dynamics (CFD) to conduct ‘virtual computer experiments’ has increased. CFD tools have become the most important tools for researchers to deal with several complex problems. In this study, the viscous approach called URANS (Unsteady Reynolds Averaged Navier-Stokes) which has a fully non-linear base has been used to solve the vertical ship motions and added resistance problems in head waves. In the solution strategy, the FVM (Finite Volume Method) is used that enables numerical discretization. The ship model DTMB 5512 has been chosen for a series of computational studies at Fn=0.41 representing a high speed case. Firstly, by using CFD tools the TF (Transfer Function) graphs for the coupled heave- pitch motions in deep water have been generated and then comparisons have been made with IIHR (Iowa Institute of Hydraulic Research) experimental results and ordinary strip theory outputs. In the latter step, TF graphs of added resistance for deep water have been generated by using CFD and comparisons have been made only with strip theory.

Data-driven Bayesian inference of turbulence model closure coefficients incorporating epistemic uncertainty

We introduce a framework for statistical inference of the closure coefficients using machine learning methods. The objective of this framework is to quantify the epistemic uncertainty associated with the closure model by using experimental data via Bayesian statistics. The framework is tailored towards cases for which a limited amount of experimental data is available. It consists of two components. First, by treating all latent variables (non-observed variables) in the model as stochastic variables, all sources of uncertainty of the probabilistic closure model are quantified by a fully Bayesian approach. The probabilistic model is defined to consist of the closure coefficients as parameters and other parameters incorporating noise. Then, the uncertainty associated with the closure coefficients is extracted from the overall uncertainty by considering the noise being zero. The overall uncertainty is rigorously evaluated by using Markov-Chain Monte Carlo sampling assisted by surrogate models. We apply the framework to the Spalart–Allmars one-equation turbulence model. Two test cases are considered, including an industrially relevant full aircraft model at transonic flow conditions, the Airbus XRF1. Eventually, we demonstrate that epistemic uncertainties in the closure coefficients result into uncertainties in flow quantities of interest which are prominent around, and downstream, of the shock occurring over the XRF1 wing. This data-driven approach could help to enhance the predictive capabilities of computational fluid dynamics (CFD) in terms of reliable turbulence modeling at extremes of the flight envelope if measured data is available, which is important in the context of robust design and towards virtual aircraft certification. The plentiful amount of information about the uncertainties could also assist when it comes to estimating the influence of the measured data on the inferred model coefficients. Finally, the developed framework is flexible and can be applied to different test cases and to various turbulence models.