Computational fluid dynamics simulation and parametric study of coal gasification in a circulating fluidized bed reactor

CFD modeling of heat transfer and hydrodynamics in a draft tube conical spouted bed reactor under pyrolysis conditions: Impact of wall boundary condition

Effects of fluidization velocity on solid stack volume in a bubbling fluidized-bed with nozzle-type distributor

Parametric study of particles homogenization in cold-flow riser reactors

While designing the power requirements of a ship, the most important factor to be considered is the ship resistance, or the sea drag forces acting on the ship. It is important to have an estimate of the ship resistance while designing the propulsion system since the power required to overcome the sea drag forces contribute to ‘losses’ in the propulsion system. There are three main methods to calculate ship resistance: Statistical methods like the Holtrop-Mennen (HM) method, numerical analysis or CFD (Computational Fluid Dynamics) simulations, and model testing, i.e. scaled model tests in towing tanks. At the start of the design stage, when only basic ship parameters are available, only statistical models like the HM method can be used. Numerical analysis/ CFD simulations and model tests can be performed only when the complete 3D design of the ship is completed. The present paper aims at predicting the calm water ship resistance using CFD simulations, using the Flow-3D software package. A case study of a roll-on/roll-off passenger (RoPax) ferry was investigated. Ship resistance was calculated at various ship speeds. Since the mesh affects the results in any CFD simulation, multiple meshes were used to check the mesh sensitivity. The results from the simulations were compared with the estimate from the HM method. The results from simulations agreed well with the HM method for low ship speeds. The difference in the results was considerably high compared to the HM method for higher ship speeds. The capability of Flow-3D to perform ship resistance analysis was demonstrated.

Extension of the chemical percolation devolatilization model for predicting formation of tar compounds as soot precursor in coal gasification

Computational fluid dynamics and experimental study of the hydrodynamics of a gas–solid tapered fluidized bed

High energy consumption in fluidized bed dryers (FBDs) remains a critical challenge for tea processing, largely due to poor fluidization quality of sticky, irregular, and non-uniform tea particles. To address this issue, this study investigated the potential of horizontal-axis rotary agitators to improve the hydrodynamics of a gas-solid FBD and reduce energy losses. Computational fluid dynamics (CFD) simulations were performed using the two-fluid model combined with the kinetic theory of granular flow (TFM-KTGF), focusing on key parameters including pressure drop, standard deviation of pressure drop, solid volume fraction distribution, and granular temperature. Some configurations were analyzed: a bed without an agitator, and beds equipped with rotary agitators of varying blade numbers (three and five) and diameters (200 mm and 300 mm) at different rotational speeds. The results demonstrated that introducing a horizontal-axis rotary agitator significantly improves fluidization. The largest rotary domain (five blades, 300 mm diameter) achieved the lowest pressure drop of 315,135 Pa at 6.28 rad/s, while also promoting more uniform solid distribution and increasing granular temperature up to 2.5 × 10⁻ 3 J/kg. The agitator enhanced particle circulation, expanded lean regions within the bed, and reduced dense packing, leading to improved gas-solid contact and reduced resistance to airflow. Furthermore, increasing the agitator speed decreased pressure drop and its standard deviation, while increasing the granular temperature, confirming the beneficial effect of enhanced stirring energy. This study highlights the effectiveness of horizontal-axis rotary agitators in enhancing the hydrodynamic performance of FBDs, offering a promising approach to improve energy efficiency and drying uniformity in tea production. The insights presented here can guide future design and optimization of industrial-scale dryers handling cohesive, irregular particles.

3D CFD simulation of a circulating fluidized bed with on-line adjustment of mechanical valve

In dense gas–solid fluidized beds the heat transfer to immersed objects is strongly coupled to the hydrodynamic behavior. The objective of this study is to experimentally and numerically assess the heat transfer coefficient around a horizontal tube in a Geldart B bubbling fluidized bed and derive a numerical-correlative approach for predicting the angular dependent heat transfer coefficient. The considered system consists of corundum as the solid bed material and air as the fluidization gas, entering the cylindrical geometry through a Tuyere nozzle distributor. Experimental data are obtained from a pilot scale test-rig with different tubular heat transfer probes and evaluated in a comprehensive uncertainty analysis. The resulting magnitude and angle dependent variations of the heat transfer coefficient at different superficial gas velocities are compared to three dimensional numerical simulations. The applied CFD model of the fluidized bed treats both gas and powder as Eulerian phases. The size distribution of the particles is described by two granular phases with corresponding mean diameters and a sphericity factor to account for their non-spherical shape. The fluid–solid interactions in this Multi Fluid Model are considered by incorporating the Kinetic Theory of Granular Flow and a sphericity-adapted drag model. The hydrodynamics at the tube surface, e.g. solid volume fraction, gas and particle velocities, are used for a novel numerical-correlative calculation of the angle dependent heat transfer coefficient between the bed material and the immersed tube. Special focus is set on depicting the particle contact time at the tube surface appropriately. The numerical results show the correct tendency of an increasing heat transfer coefficient with rising gas velocity and are partially in good agreement with the experimental observations.

Bench test and computational fluid dynamics (CFD ) simulation of the air pump loss on the 380 hydraulic retarder are completed in this paper . It turns out that the CFD simulation has nice reliability from the contrast of the air pump loss between the test and the simulation . And on this foundation , CFD simulation of two kinds of retarders with different turbulent structures is done . The contrast of the results of the simulation give the effects of different turbulent structures on cutting down the are pump loss .

Optimization methods have been widely applied to the aerodynamic design of gas turbine blades. While applying optimization to high-fidelity computational fluid dynamics (CFD) simulations has proven capable of improving engineering design performance, a challenge has been overcoming the prolonged run-time due to the computationally expensive CFD runs. Reduced-order models and, more recently, machine learning methods have been increasingly used in gas turbine studies to predict performance metrics and operational characteristics, model turbulence, and optimize designs. The application of machine learning methods allows for utilizing existing knowledge and datasets from different sources, such as previous experiments, CFD, low-fidelity simulations, 1D or system-level studies. The present study investigates inserting a machine learning model that utilizes such data into a high-fidelity CFD driven optimization process, and hence effectively reduces the number of required evaluations of the CFD model. Artificial Neural Network (ANN) models were trained on data from over three thousand two-dimensional (2D) CFD analyses of turbine blade cross-sections. The trained ANN models were then used as surrogates in a nested optimization process alongside a full three-dimensional Navier–Stokes CFD simulation. The much lower evaluation cost of the ANN model allows for tens of thousands of design evaluations to guide the search of the best blade profiles to be used in the more expensive, high-fidelity CFD runs, improving the progress of the optimization while reducing the required computation time. It is estimated that the current workflow achieves a five-fold reduction in computational time in comparison to an optimization process that is based on three-dimensional (3D) CFD simulations alone. The methodology is demonstrated on the NASA/General Electric Energy Efficient Engine (E3) high pressure turbine blade and found Pareto front designs with improved blade efficiency and power over the baseline. Quantitative analysis of the optimization data reveals that some design parameters in the present study are more influential than others, such as the lean angle and tip scaling factor. Examining the optimized designs also provides insight into the physics, showing that the optimized designs have a lower amount of pressure drop near the trailing edge, but have an earlier onset of pressure drop on the suction side surface when compared to the baseline design, contributing to the observed improvements in efficiency and power.

Modification of kinetic theory of granular flow for frictional spheres, part II: Model validation

Today, many wells in heterogeneous carbonate reservoirs throughout the Middle East and Caspian Sea area are being completed with long intervals and complex completion equipment, such as limited entry liners and inflow control devices (ICDs). Accurate modeling and understanding of fluid placement during a stimulation operation through such long complex completions can be quite challenging. In this paper, an integrated approach of modeling, experiments and computational fluid dynamics (CFD) simulations will be presented. A computational tool based on a transient one-dimensional (1D) approach has been developed in-house to model stimulation through such completions. In order to validate the 1D approach for reliable fluid displacement predictions, annulus fluid displacement experiments in perforated liners supported by CFD simulations have been conducted. The experimental setup consists of an outer Lucite pipe representing the well-bore geometry and an inner aluminum pipe with multiple perforations of variable diameter. The setup mimics the real field application in a 1:1 scale with respect to the pipe and perforation diameters while the test section is limited to 27 ft. The experimental procedure is as follows: fluid is pumped into the annulus through the perforations until the annulus is completely filled,the fluid tank is switched "on-the-fly" to the tank with the displacing fluid resulting in the displacement of the annulus fluid by the displacing fluid through the perforations. The experiments and the CFD simulations indicate that even with a single open perforation inside the 27-ft test section, the three-dimensional (3D) flow field around the perforation rapidly transitions to uniform annular flow within a few feet uniformly displacing the annulus fluid. The model also provides insight into various well injection processes in sandstone and carbonate formation, such as scale squeezes, solvent treatments, and HF acid treatments. Introduction The length of production and injection intervals in a single well continues to increase in order to contact more reservoir rock with a single wellbore penetration and improve project economics. Multiple, thick stacked reservoirs are accessed by vertical and deviated wells while thinner reservoirs are being exploited with longer and longer horizontal wells1–3. To keep up with drilling capability, completion technology has advanced considerably in the past few years. Horizontal wells are "compartmentalized" using mechanical and/or swellable packers. Within a given compartment, injection and production can be controlled by use of inflow control devices (ICDs), limited entry (LE) liners, and/or sliding sleeves. The liners also make it easier to enter the completion interval with logging tools, wire line, and coiled tubing. While various tools are available to evaluate long-term, steady-state production and injection into such wells, modeling of short-term, transient injection into such completions is very challenging due to the long lateral lengths, limited entry points from the liner to each compartment, and the presence of an open annulus with occasional packer isolations. This is especially important for long wells in carbonate formations as all wells require acid stimulation upon initial completion, and occasionally throughout the well life.

A normally-open thermally-actuated microvalve was designed (using microfabrication/soft-lithography techniques involving 3D Printed molds), assembled and tested. The motivation of the research work is to develop an array of microvalves for precise delivery of water to individual plants in a field (with the goal of developing smart irrigation systems for high value cash-crops in the agricultural sector). It is currently impossible to control application of irrigation-water at the level of a single plant. If such a capability were practically available on farms, the result would be a step change in precision agriculture, such that the output of every plant in a farm field could be optimized (i.e., food-water-energy nexus in sustainability applications). The aim of this study is to develop and test a microfluidic system (consisting of a microvalve array) that could be controlled, capillary by capillary, to deliver the needed amount of water to individual plants in a large field. Two types of test fluids were leveraged for thermo-hydraulic actuation of the microvalves developed in this study: (a) Design-I: using air, and (b) Design-II: using Phase Change Material (PCM). The PCM used in this study is PureTemp29. The proposed approach enabled a simple and cheap design for microvalves that can be manufactured easily and are robust to weather conditions (e.g., when exposed to the elements in orchards and open fields). Other advantages include: safe and reliable operation; low power consumption; can tolerate anomalous pressure loads/fluctuations; simple actuation; affords easy control schemes; is amenable for remote control; provides long-term reliability (life-cycle duration estimated to be 3∼5 years); can be mass produced and is low maintenance (possibly requiring no maintenance over the life time of operation). The microvalve consists of two layers: a flow layer and a control layer. The control layer is heated from below and contains a microfluidic chamber with a flexible polymeric thin-membrane (200 microns in thickness) on top. The device is microfabricated from Poly-Di-Methyl-Siloxane (PDMS) using soft lithography techniques (using a 3D Printed mold). The control chamber contains either air (thermo-pneumatic actuation) or PCM (thermo-hydraulic actuation involving repeated melting/freezing of PCM). The flow layer contains the flow channel (inlet and outlet ports, horizontal section and valve seat). The experimental results from testing the efficacy of the two types of micro-valves show a 60% reduction (for thermo-pneumatic actuation using air) and 40% reduction (for thermo-hydraulic actuation using PCM) in water flow rates for similar actuation conditions (i.e., heater temperature values). PCM design is expected to consume less power (lower OPEX) for long-term actuation but may have slower actuation speed and have higher manufacturing costs (CAPEX). Air actuation design is expected to consume more power (higher OPEX) for longer-term operation but may have faster actuation speeds and lower manufacturing costs (CAPEX). Computational Fluid Dynamics (CFD) simulations were performed to investigate the effect of flowing water (in the microfluidic channel) on the average absolute pressure and temperature of air in the actuation chamber. The CFD simulations were performed using a commercial tool (Ansys™ 2019R1®). The results from the CFD simulations are presented in this study.

The removal of toxic gases leaking during excavation in infrastructure projects is crucial for both human health and environmental protection. In this process, Computational Fluid Dynamics (CFD) simulations are highly valuable for modeling and analyzing complex physical processes associated with the transport and dispersion of gases. During infrastructure projects in geothermal regions, various gases may leak from underground sources. These gases may include toxic and/or flammable substances such as hydrogen sulfide (H₂S), carbon dioxide (CO₂), and methane (CH₄). Designing an effective ventilation system is essential for the removal of toxic gases through ventilation. CFD simulations can be utilized to evaluate the design and performance of ventilation systems. Modeling gas leaks from sources encountered during excavation using CFD simulations can help understand how gases move throughout infrastructure projects and their environmental impacts. CFD simulations can assist in optimizing factors such as the placement of ventilation systems, duct design, air flow rates, and filtration efficiency. This optimization ensures the effective removal of toxic gases and minimizes environmental impacts. CFD simulations can also be used to assess the efficiency and safety of ventilation systems designed for the mitigation of toxic gases. Additionally, simulating the operation of ventilation systems during potential emergency situations can help in evaluating associated risks.