MUST experiment simulations using CFD and integral models

Computational fluid dynamics (CFD) techniques have become an important tool for investigating and predicting flow behavior in many industrial and engineering processes. In the last two decades, CFD has been used for the study, design, and improvement of irrigation equipment. Numerical simulations can be used to predict fluid flow, heat transfer, and chemical reactions within complex systems. The objective of this review is to provide an overview of the uses of CFD in irrigation engineering applications. The paper is organized into two main sections: fundamentals of CFD and irrigation engineering applications. The first section presents the main methods used in numerical simulations, basic equations to predict fluid flow parameters, meshing concerns, and convergence criteria. In the second section, we present applications related to friction and local head losses in pipes, liquid and solid-liquid flow simulation in drippers, chemical scaling, filters, sprinklers, direct-acting pressure-regulating valves, and Venturi injectors. The briefly described applications indicated that CFD modeling can be an accurate, quick, and feasible method for the investigation of flow parameters in irrigation pipes, fittings, emitters, and accessories. The CFD simulations can be useful for designing new products as well as for improving and optimizing existing products. Computational fluid dynamics uses in irrigation engineering must be encouraged, particularly for innovation purposes resulting from the cooperation between academia and irrigation companies.

Perforate-Wash-Cement (P/W/C) is a well plugging technique extensively used by ConocoPhillips in the Greater Ekofisk Area over the last ten years. In Jet-type P/W/C, Tubing Conveyed Perforating (TCP) guns perforate casing in the target interval before the zone is washed and a cross-sectional cement plug is installed using a specialized Bottom Hole Assembly (BHA). The goal is to maximize the cement plug quality through optimizing the BHA and operational process parameters within constraints imposed by the operating conditions. This paper describes application of Computational Fluid Dynamics (CFD) to achieve this objective. CFD is well suited for modeling wash and cement processes including the associated non-Newtonian fluids. A CFD model of these processes employs unsteady multiphase Reynolds Averaged Navier Stokes (RANS) based Volume of Fluid (VOF) approach with a Shear Stress Transport (SST) K-omega turbulence model. BHA translation and rotation are simulated using moving deforming-layering mesh with interface approach. Physical properties of non-Newtonian fluids selected are based on in-situ conditions and derived via lab tests. CFD-specific considerations such as domain size, turbulence model, mesh type and size, and computational timestep are discussed in this paper. The magnitude and duration of the jet-induced "pressure pulse" in the annular space between the formation wall and the casing are a key to efficient displacement during the wash and cementing processes. Displacement efficiency, in terms of the percentage of mud or cement in a control volume as a function of time, depends on perforation size and density, nozzle size/number, flow rate, fluid properties, as the ROP/BHA pulling speed and tool RPM. Key findings from a parametric study to optimize these parameters are presented. To validate CFD nozzle flow predictions and to rule out potential for false results due to cavitation, laboratory tests were performed under pressurized conditions. A comparison of results from CFD simulations using traditional versus optimized parameters are presented, demonstrating significant efficiency improvement achieved. The study initially focused on North Sea application. Encouraged by substantial improvement in process efficiency through parametric optimization, the technique was extended to UK operations and is planned for the Bayu-Undan field. Cementing simulation results for Bayu-Undan specific well configurations are presented, showing how CFD modeling helped reveal less than ideal cementing efficiency. Ultimately, this work provides significant time savings and quality improvement for P&A projects while maintaining a high safety standard.

This study describes a methodology combining a recently proposed renormalization inversion technique with a building‐resolving computational fluid dynamics (CFD) approach for source retrieval in the geometrically complex urban regions. It presents the first application of the renormalization inversion approach to estimate an unknown continuous point release in real situations at an urban scale. The renormalization inversion approach is based on an adjoint source‐receptor relationship and is purely deterministic in nature. The source parameters (i.e., source location and release rate) are reconstructed from a finite set of point measurements of concentration acquired from some sensors and the adjoint functions computed from a CFD model fluidyn‐PANACHE that is able to represent the geometric and flow complexity inherent in the urban regions. The inversion procedure is evaluated for a point source reconstruction using measurements from the Mock Urban Setting Test (MUST) field experiment. Source reconstructions are performed for 20 trials of the MUST experiment of a continuous point release in an idealized urban geometry consisting of a regular array of shipping containers. The steady state flow fields are computed by solving the three‐dimensional Reynolds‐averaged Navier‐Stokes equations by using a finite volume scheme. Then, in each MUST trial adjoint functions are obtained and used for the source identification. Inversion results are presented with both synthetic and real measurements in various atmospheric stabilities varying from neutral to stable and very stable conditions. With real concentration measurements, the point source is retrieved within an average Euclidean distance of 14.6 m from the actual source location. The estimated source intensity is overpredicted by an average factor of 1.37 of the true release rate. In a posterior uncertainty analysis with 10% random noise in measurements, it is demonstrated that standard deviation in the location error and release strength, respectively, varies by 5.22 m and ∼21% from their mean value for all 20 trials. A sensitivity analysis shows that the use of nonzero measurements helps in reducing the uncertainties involved in the source reconstruction. The source reconstruction results in various stability conditions exhibit the reliability of the renormalization inversion methodology coupled with the CFD approach in an urban area. The present methodology can be used by emergency regulators as a tool to detect the unknown accidental or deliberated releases in the complex urban environments.

Computational fluid dynamics (CFD) is a branch of fluid mechanics that uses numerical analysis and data structures to calculate, analyze, and visualize fluid (liquids, gases, and dissolved gases) flows. This document provides general introductions to best practices for CFD modeling in water infrastructure for practitioners, particularly those new to CFD modeling, which is becoming a widely used tool in the design and retrofitting of water, wastewater, and stormwater infrastructure. The method serves as an alternative, or complement, to physical modeling. In recent years, CFD has often been used in evaluating and troubleshooting existing water systems as well as improving future designs. As with the applications in other fields, the popularity of CFD in the water industry has been propelled by a multitude of factors including, but not limited to, the maturity achieved by CFD techniques, the development of stable and reliable numerical schemes, and the ever-improving computer-aided design (CAD) and meshing technologies for real-world complex geometries. This has been accompanied by many commercial and open-source CFD packages that can be run on increasingly more powerful computing hardware. Despite the visible progress in the application of CFD in water infrastructure projects achieved to date, there are still many challenges that hinder the widespread use of CFD techniques in water treatment design. Perhaps more important is that many of these challenges may result in misuse of the tool with dire consequences. It is imperative that CFD practitioners appropriately apply this tool without overpromising capability or accuracy and that reviewers of CFD model results know what to look for in ensuring proper methods have been applied and that results are representative of reality.

This study presents an initial scoping analysis of the application of computational fluid dynamics (CFD) to modeling the flow in an annular centrifugal contactor. The unsteady, turbulent nature of this multi‐phase flow presents significant challenges to quantitative CFD modeling. Existing methods for confronting these obstacles are considered and initial results of the steady‐state flow of a single liquid phase in the annular mixing zone are presented. The flow of particulates and the effects of changes in geometric and operational parameters were also evaluated. Even with simplifying assumptions qualitatively accurate results could be obtained using widely available CFD models.

A Scalable Infrastructure for Online Performance Analysis on CFD Application

This paper gives a discussion on the Computational Fluid Dynamics (CFD) applications in offshore engineering. Accurate hydrodynamic quantities are essential for engineering design. Offshore structures are generally subject to high Reynolds number flows. These high Reynolds number flow conditions (Re > 106 ) are difficult and expensive to achieve in an experimental setup. Therefore, it is attractive to use CFD to provide the essential hydrodynamic quantities for practical design. Verification and validation studies are important for determining the validity of the CFD prediction. A procedure of performing CFD simulation is shown. Different types of turbulence modelling are discussed. Three examples of high Reynolds number CFD simulations, covering flow around offshore structural components and waves past partially-submerged horizontal cylinders, are shown and discussed.

Computational Fluid Dynamic Modeling of Urethral Strictures

Wind tunnel and CFD study of dust dispersion from pesticide-treated maize seed

A Fourier-based methodology without numerical diffusion for conducting dye simulations and particle residence time calculations

This paper reports the development of a computational fluid dynamics (CFD) model of a spark ignition (SI) engine and the application of the engine model into an undergraduate internal combustion (IC) course. This two-dimensional (2D) four-stroke SI engine model simulates the combustion of the fuel, heptane, in the engine cylinder based on realistic boundary conditions. The development of the model helps engineering students better understand the combined effects of chemical reactions, species transport, flow patterns and temperature distributions in the SI engine. This model has been applied in a practical session in an undergraduate engineering course since 2012. To the best knowledge of the authors, this is the first time that CFD engine models are used as a hands-on tool in IC engine courses. Feedback from students is quite positive.

This paper presents the first simulation model of a tilting pad journal bearing (TPJB) using three-dimensional (3D) computational fluid dynamics (CFD), including multiphase flow, thermal-fluid, transitional turbulence, and thermal deformation of the shaft and pads employing two-way fluid–structure interaction (FSI). Part I presents a modeling method for the static performance. The model includes flow between pads BP, which eliminates the use of an uncertain, mixing coefficient (MC) in Reynold's equation approaches. The CFD model is benchmarked with Reynold's model with a 3D thermal-film, when the CFD model boundary conditions are consistent with the Reynolds boundary conditions. The Reynolds model employs an oversimplified MC representation of the three-dimensional mixing effect of the BP flow and heat transfer, and it also employs simplifying assumptions for the flow and heat transfer within the thin film between the journal and bearing. This manufactured comparison shows good agreement between the CFD and Reynold's equation models. The CFD model is generalized by removing these fictitious boundary conditions on pad inlets and outlets and instead models the flow and temperature between pads. The results show that Reynold's model MC approach can lead to significant differences with the CFD model including detailed flow and thermal modeling between pads. Thus, the CFD approach provides increased reliability of predictions. The paper provides an instructive methodology including detailed steps for properly applying CFD to tilt pad bearing modeling. Parts I and II focus on predicting static and dynamic response characteristic responses, respectively.

<div class="htmlview paragraph">Development of Caterpillar Fuel Systems' MEUI-B injector has involved application of Computational Fluid Dynamics (CFD) in order to improve performance of the high pressure spill valve. Initial performance bench testing with concept stage experimental injectors indicated that the chamber pressure was decaying at an unacceptably slow rate, and the valve demonstrated erratic behavior at some operating conditions. The slow pressure decay and inconsistent spill valve motion were believed to be caused by flow forces generated during the low lift portion of the spill valve opening event. This theory was pursued by utilizing CFD to design two valves for testing in the next phase of the injector development cycle: A baseline geometry, similar to the original concept injector valve, and a new design incorporating localized seat geometry changes for inducing flow force assisted valve opening. Bench test performance data clearly shows that the modified design significantly improves the spill valve opening event and subsequent chamber pressure decay rate. This paper documents the CFD analysis which led to the development of the new MEUI-B high pressure spill valve design.</div>

Bubbly flow behavior simulation in two-phase chemical reactors such bubble column type reactors is widely employed for chemical industry purposes. The computational fluid dynamics (CFD) approach has been employed by engineers and researchers for modeling these types of chemical reactors. In spite of the CFD robustness for simulating transport phenomena and chemical reactions in these reactors, this approach has been known as expensive for modeling such turbulent complex flows. Artificial intelligence (AI) algorithm of the adaptive network-based fuzzy inference system (ANFIS) are largely understood and utilized for the CFD approach optimization. In this hybrid approach, the CFD findings are learned by AI algorithms like ANFIS to save computational time and expenses. Once the pattern of the CFD results have been captured by the AI model, this hybrid model can be then used for process simulation and optimization. As such, there is no need for further simulations of new conditions. The objective of this paper is to obviate the need for expensive CFD computations for two-phase flows in chemical reactors via coupling CFD data to an AI algorithm, i.e., differential evolution based fuzzy inference system (DEFIS). To do so, air velocity as the output and the values of the x, and y coordinates, water velocity, and time step as the inputs are inputted the AI model for learning the flow pattern. The effects of cross over as the DE parameter and also the number of inputs on the best intelligence are investigated. Indeed, DEFIS correlates the air velocity to the nodes coordinates, time, and liquid velocity and then after the CFD modeling could be replaced with the simple correlation. For the first time, a comparison is made between the ANFIS and the DEFIS performances in terms of the prediction capability of the gas (air) velocity. The results released that both ANFIS and DEFIS could accurately predict the CFD pattern. The prediction times of both methods were obtained to be equal. However, the learning time of the DEFIS was fourfold of ANFIS.

The application of computational fluid dynamics(CFD) in the food industry such as drying, thermal sterilization, mixing, refrigeration and humidification of cold storage was reviewed. The results from previous studies have shown that CFD was a powerful numerical tool that is applied to model fluid flow situations and aid in the optimal design of engineering equipment and food process. With the development of computer technology, it is conceivable that CFD will continue to provide more explanations for physical modeling of fluid flow and process system design for the food industry.