Computational fluid dynamics modeling of abutment scour under steady current using the level set method

A three dimensional Computational Fluid Dynamics (CFD) model solving Reynolds-averaged Navier-Stokes (RANS) equations with k-ε turbulence model has been developed based on OpenFoam to investigate a tidal turbine performance. The CFD model is validated by comparing the simulation results with the performance characteristic data. Simulation results match the measured data with discrepancies less than 5.4%. The well validated model is then adopted to predict the turbine performance with a current heading angle of 30 degree. The simulated turbine power coefficient and flow field details from OpenFoam are compared with those obtained from commercial software ANSYS FLUENT for verification. The two simulated results match each other with a difference of only 3%. Simulated results indicate that the turbine power output drops significantly when the tidal turbine operates with a current heading angle of 30 degree. The performance loss due to a misalignment between the current and the turbine axis is analyzed with the aim to identify main causes and provide recommendations to tidal turbine operation.

The effects of an apartment complex on flow and pollutant dispersion in an urban area are numerically investigated using a computational fluid dynamics (CFD) model. The CFD model is based on the Reynolds-averaged Navier-Stokes equations and includes the renormalization group k- turbulence model. The geographic information system (GIS) data is used as an input data of the CFD model. Eight numerical simulations are carried out for different inflow directions and, for each inflow direction, the effects of an apartment complex are investigated, comparing the characteristics of flow and dispersion before and after construction of the apartment complex in detail. The observation data of automatic weather system (AWS) is analyzed. The windrose analysis shows that the wind speed and direction after the construction of the complex are quite different from those before the construction. The construction of the apartment complex resulted in the decrease in wind speed at the downwind region. It is also shown that the wind speed increased partially inside the apartment complex due to the channeling effect to satisfy the mass continuity. On the whole, the wind speed decreased at the downwind region due to the drag effect by the apartment complex. As a result, the passive pollutant concentration increased (decreased) near the downwind region of (within) the apartment complex compared with that before the construction.

Pulverized coal fired combustion is a major contributor to global emissions of nitric oxide (NO). Release of NO into the atmosphere causes toxic NO, reduction of ozone, formation of smog, and reduced visibility. Computational fluid dynamic (CFD) modelling of NO emissions from pulverized coal fired boilers offers several benefits including optimisation of boiler operating conditions to minimize NO emissions and development of low NO technology. Formation of NO within a pulverized coal fired boiler is a complex process, yet simple mechanisms are used to approximate the formation process. CFD modelling of NO formation requires prediction of the 1. nitrogen release rate from coal during devolatilization and char combustion, 2. possibly the type of nitrogen compound released during devolatilization and char combustion, 3. gas phase conversion of nitrogen compounds to NO (including possible NO reduction mechanisms), 4. contributions of thermal and prompt NO, and 5. conversion of char nitrogen to NO. This thesis assessed currently used models for processes 1-5 for accuracy and reliability in simple systems and CFD modelling. Models for processes 1-5 were improved, if required. CFD models currently assume the rate of nitrogen release equals a times the carbon release rate, where a equals 1. Laboratory and utility boiler measurements showed that a varies between 0.8 and 1.2. The sensitivity of a to NO emissions should be tested in CFD models for a variety of cases. If NO emissions are sensitive to a, a value of 1.07 is recommended for utility boilers as estimated from utility boiler measurements. The type of nitrogen compound released during devolatilization and char combustion may affect the reaction kinetics converting nitrogen compounds to NO. Previous laboratory measurements concluded that HCN and NH3 are the major nitrogen compounds released during devolatilization. The most likely compound released during char combustion is NO. The conversion of HCN and NH3 to NO was found to vary in fuel-rich conditions at temperatures between 1200 K and 2000 K. Therefore a NO prediction model should include conversion of HCN and NH3 to NO. Currently used global kinetic mechanisms were found to inadequately predict NO formation. Commonly used thermal NO mechanisms significantly over-predict NO formation at temperatures greater than 2200 K and long residence times. This trend is not critical in coal-fired systems because maximum temperatures are less than 2000 K. The de Soete mechanism is commonly used to predict the conversion of HCN to NO. This mechanism was found to under-predict NO formation at temperatures less than 1700 K. The de Soete mechanism was adjusted to improve predictions at low temperatures. An investigation into the use of reduced reaction mechanisms found it was not theoretically possible to reduce a comprehensive reaction mechanism to the extent it could be incorporated into a CFD model, and solve within the same simulation time as a CFD model using global kinetics. An empirical equation was developed that fits the profile of NO formation and HCN destruction. The equations fit NO and HCN profiles across a wide range of conditions. Values of NO and HCN at conditions other than the simulated ones are calculated by interpolation. This mechanism offers an alternative approach to prediction of NO formation by global kinetic mechanisms. Currently available char nitrogen to NO equations are simple, and do not consider parameters such as char size, temperature and char surface area. Empirical equations were developed to calculate the conversion of char nitrogen to NO given the char size, temperature, O2 concentration, NO concentration, char surface area and intrinsic reactivity. The accuracy and reliability of NO predictions determined by CFD models was assessed by comparison of model predictions and utility boiler measurements. CFD models were assessed by four criteria including how accurately NO emissions were predicted, how accurately NO profiles and profiles of species important to NO formation within the burner region were predicted, how accurately temperature and O2 concentrations were predicted and how accurately the model predicted trends in NO emissions as combustion conditions changed. The CFD model investigated, Furnace, could not satisfy the set criteria and therefore modelling results should be interpreted carefully.n

The work described here concentrates on under-expanded, axisym-metric turbulent jets issuing into quiescent conditions. Under-expanded turbulent jets are applicable to most aircraft propulsion applications that use convergent nozzles. Experimental studies used laser doppler velocimetry (LDV) and pitot probe measurements along the jet centreline. These measurements were made for two nozzle pressure ratios (2·5 and 4·0) and at various streamwise positions up to 10 nozzle diameters downstream of the nozzle exit plane. A computational fluid dynamics (CFD) model was developed using the Fluent code and utilised the RNG K-ε two-equation turbulence model. A mesh resolution of approximately one hundredth of nozzle exit diameter was found to be sufficient to establish a mesh independent solution.Comparison of the jet centreline axial velocity (LDV data) and pressure ratio (pitot probe data) showed good agreement with the CFD model. The correct number of shock cells had been predicted and the shock strength agreed well between the experiments and numerical model. The CFD model was, however, found to over-predict the shock cell length resulting in a longer supersonic core. There was some evidence, based on analysis of the LDV measurements that indicates the presence of swirl and jet unsteadiness, which could contribute to a shortening of the shock cell length. These effects were not modelled in the CFD. Correlation between the LDV and pitot probe measurements was generally good, however, there was some evidence that probe interference may have caused the premature decay of the jet. Overall, this work has indicated the good agreement between a CFD simulation using the RNG k-ε turbulence model and experimental data when applied to the prediction of the flowfield generated by under-expanded turbulent jets. The suitability of the LDV technique to jet flows with velocities up to 500ms-1has also been demonstrated.

Computational fluid dynamics (CFD) model has been widely used for prototyping data centers. Evolving it to high-fidelity {\em digital twin} is desirable for the management and operations of large-scale data centers. Manually calibrating CFD model parameters to achieve twin-class fidelity by specially trained domain expert is tedious and labor-intensive. To reduce manual efforts, existing automatic calibration approaches developed for various computational models apply heuristics to search model configurations within an empirically defined parameter bound. However, in the context of CFD, each search step requires long-lasting CFD model's iterated solving, rendering these approaches impractical with increased model complexity. This paper presents Kalibre, a knowledge-based neural surrogate approach that performs CFD model calibration by iterating four key steps of i) training a neural surrogate model based on CFD-generated data, ii) finding the optimal parameters at the moment through neural surrogate retraining based on sensor-measured data, iii) configuring the found parameters back to the CFD model, and iv) validating the CFD model using sensor-measured data as the ground truth. Thus, the parameter search is offloaded to the neural surrogate which is ultra-faster than CFD model's iterated solving. To speed up the convergence of Kalibre, we integrate prior knowledge of the twinned data center's thermophysics into the neural surrogate design to improve its learning efficiency. With about five hours computation on a 32-core processor, Kalibre achieves mean absolute errors (MAEs) of $0.81^o$C and $0.75^o$C in calibrating two CFD models for two production data halls hosting thousands of servers each while requires fewer CFD solving processes than existing baseline approaches.

Computational fluid dynamics (CFD) modelling and optimum gap size of a compact steam methane reforming (SMR) reactor

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

Computational fluid dynamics (CFD) models are powerful computational tools to simulate urban-landscape scale atmospheric dispersion events. They are proven to be very useful for security management and emergency response. Essential inputs to CFD models include landscape characteristics, which are often captured by various GIS data layers. While it is logical to couple GIS and CFD models to take advantage of available GIS data and the visualization and cartographic rendering capabilities of GIS, the integration of the two tools have been minimal. In this paper, we took the first step to evaluate the use of GIS data in CFD modeling. Specifically, we explore how efficient is to use GIS data in CFD models and how sensitive the CFD results are to different GIS data formats. Using campus topography and building data, and the FEFLO-URBAN CFD model, we performed atmospheric release simulations using topographic data in contour and raster formats. We found that using raster format was quite efficient and contour data required significant effort. Though the simulation outputs from the two data formats were not identical, their overall outcomes were similar and did not post alarming discrepancies. We concluded that using GIS data have tremendous potential for CFD modeling.

At present, fossil-fuel power plants supply the majority of the world’s demand of electric energy. The environmental and health threats from anthropogenic emissions of greenhouse gases (GHG) of these power plants have been considered as one of the main reasons for global climate change. In order to make the existing fossil fuel energy sources more environmentally friendly, a new generation of advanced power plant with increased output and environmental performance is required to be built. Oxy-fuel combustion technique can potentially provide significant opportunities for near-zero emissions from the existing and new-build power plants by capturing and storing the carbon dioxide emissions from burning fossil fuels and biomass. To obtain a better understanding of the overall oxy-fuel combustion process, it is important to investigate the effects of oxy-fuel-fired conditions on the combustion characteristics and heat transfer performance as innovations in the energy used. As a first step in developing and validating a computational tool to numerically model combustion of gaseous fuel, a computational fluid dynamics (CFD) modelling study has been carried out involving propane combustion with associated chemical reactions, radiative heat transfer, and turbulence. Three different combustion environments that were adopted experimentally in a 100 kW drop tube firing unit, were examined. One air-fired (reference case) and two oxy-fuel-fired cases (21 vol.% O2 for one combustion case (OF21) and 27 vol.% O2 for the other combustion case (OF27)) were investigated. The irreversible singlestep and reversible multi-step reaction mechanisms were considered. The results obtained with the multi-step chemistry mechanism showed improved agreement, particularly in the flame zone. The unburnt fuel in air-fired and OF27 cases was less than that of the OF21 case due to the low oxygen concentration used in the latter combustion case. As a second step of this research program, a comprehensive CFD modelling study was undertaken by integrating the combustion of pulverized dry lignite in several combustion environments. Four different cases were investigated: an air-fired and three different oxy-fuel combustion environments (25 % vol. O2 concentration (OF25), 27 % vol. O2 concentration (OF27), and 29 % vol. O2 concentration (OF29) were considered. The available experimental results from a lab-scale 100 kW firing lignite unit (Chalmers’ furnace) were selected for the validation of these simulations. The findings showed reasonable agreement with the qualitative and quantitative measurements of temperature distribution profiles and species concentration profiles at the most intense combustion locations inside the furnace. Through the use of Computational Fluid Dynamics (CFD), it is concluded that the resident time, stoichiometry, and recycled flue gas rates are relevant parameters to optimize the design of oxy-fuel furnaces. Under the same oxy-fuel combustion conditions as above, the appropriate mathematical models with the related kinetics parameters were implemented. The purpose was to accurately calculate the temperature distributions, species concentrations (O2, CO2, CO, H2O, and H2), NOx emission concentrations, and the radiation heat transfer. In this step of the modelling investigation, the multi-step chemical reaction mechanisms were conducted on the gas-phase and solid-phase of the coal reaction in one-, two-, and three-step reaction schemes. The predicted results showed a reasonably good agreement against the measured data for all the combustion cases, but in the three-step scheme the results were highly improved, particularly in the flame envelope zone. In the final step of the investigation, a computational fluid dynamics (CFD) modelling study has been developed to investigate Victorian brown coal combustion in a 550 MW utility boiler under air-fired and three oxy-fuel-fired scenarios. User-defined functions (UDFs) were written and incorporated into the CFD code in order to calculate the following mathematical models: the PC devolatilization, char burnout, multi-step chemical reactions, mass and heat transfer, carbon in fly-ash, and NOx formation/destruction. A level of confidence of the CFD model was achieved by validating four different parameters of the conventional combustion case. The numerical results of OF29 combustion condition were considerably similar to the reference firing results in terms of gas temperature levels and radiative heat transfer relative to the OF25 and OF27 combustion cases. In addition, a significant increase in the CO2 concentrations and a noticeable decrease in the NOx formation were observed under all oxy-fuel combustion scenarios. This study of oxy-fuel combustion in a large-scale tangentially-fired boiler is important prior to its implementation in real-life.

The modelling of complex free surface flows over weirs and in the vicinity of bridge piers is presented in a numerical model emulating open channel flow based on the Reynolds Averaged Navier-Stokes (RANS) equations. The importance of handling the turbulence at the free surface in the case of different flow regimes using an immiscible two-phase RANS Computational Fluid Dynamics (CFD) model is demonstrated. The free surface restricts the length scales of turbulence and this is generally not accounted for in standard two-equation turbulence modelling approaches. With the two-phase flow approach, large-velocity gradients across the free surface due to the large difference in the density of the fluids can lead to over-production of turbulence. In this paper, turbulence at the free surface is restricted with an additional boundary condition for the turbulent dissipation. The resulting difference in the free surface features and the consequences for the solution of the flow problem is discussed for different flow conditions. The numerical results for the free surface and stream-wise velocity gradients are compared to experimental data to show that turbulence damping at the free surface provides a better representation of the flow features in all the flow regimes and especially in cases with rapidly varying flow conditions.

Chronic rhinosinusitis with nasal polyposis (CRSwNP) is among the most common causes of olfactory loss, potentially mediated by inflammatory sensorineural loss and/or by conductive obstruction of airflow to the olfactory receptor sites. Dupilumab is a monoclonal antibody treatment for severe, inadequately controlled CRSwNP, which often results in significant olfactory improvement compared to placebo.1, 2 Yet the mechanism by which it improves olfaction remains unsettled. Previous studies have implicated the role of interleukin 13 (IL-13) in inducing damage to olfactory epithelium, suggesting a possible sensorineural anti-inflammatory mechanism.3-5 Studies have also shown a significant reduction in polyp burden after dupilumab, suggesting there may be a conductive component, although this mechanism has not been quantitatively confirmed.5 The goal of this study is to use computational fluid dynamic modeling (CFD) to examine the potential conductive mechanism of how dupilumab may alleviate olfactory loss in patients with CRSwNP. Three-dimensional (3D) computational fluid dynamic (CFD) models were constructed using a previously described method6 based on cone beam computed tomography (CT) scans (3D Accuitomo 170; J. Morita USA, Inc.) of one CRSwNP patient (a 33-year-old female) who did not improve symptomatically after multiple surgeries but did with dupilumab (22-item Sino-Nasal Outcome Test [SNOT-22] baseline: 84; 7 weeks postsurgery: 74; 11 months post-dupilumab: 24). Airflow patterns and velocity changes throughout the nasal airway were simulated under restful quasi-steady (15-Pa pressure drop between the nostrils and the nasal pharynx) using CFD software (ANSYS Fluent 19.2; Ansys, Inc., Canonsburg, PA) at the following time points: (1) baseline, where the patient had been experiencing sinus symptoms for 8 years after unsuccessful treatment with budesonide and azelastine nasal sprays, and multiple sinus surgeries at an external hospital; (2) 7 weeks after revision comprehensive sinus surgery in October 2018; and (3) 11 months after starting dupilumab in December 2020, when her symptoms remitted after surgery and a trial of benralizumab was ineffective at symptomatic relief. The numerical method and meshing protocol applied in this study have been previously validated against experimental measurements.6 The baseline CT showed a completely obstructed nasal airway and sinuses, and CFD simulations showed that no air would pass through the nasal airway or the olfactory region, corroborating the patient's symptom of complete anosmia. Postsurgery, CFD modeling demonstrated an improvement in patency of the olfactory cleft, with 0.5% of the total airflow passing through the olfactory region (pink/purple region in Figure 1). This percentage of olfactory flow distribution is further increased to 26.4%, or a 51.8-fold increase post-dupilumab. There was minimal change (∼1%) in overall nasal resistance between the last two time points (postsurgery: 0.0486 Pa/ml/s; post-dupilumab: 0.0480 Pa/ml/s). The non-obstructed olfactory surface area increased from 0.411 cm2 (postsurgery) to 8.525 cm2 (post-dupilumab), or a 20.7-fold increase. This improvement in patent olfactory area and airflow corresponded to a significant improvement in smell identification score (postsurgery: 16 to post-dupilumab: 35). Postsurgery, most airflow occurs in high velocity between the inferior and middle turbinates (Figure 2A,B), whereas a minimal amount, if any, reaches the superior turbinate and olfactory cleft in the model (Figure 1A,B). Post-dupilumab, airflow is more well-distributed throughout the entire nasal cavity, with significantly more velocity of airflow superior to the middle turbinate (Figure 1C,D), suggesting a potential conductive mechanism by which dupilumab aids in olfactory improvement. The patient's Nasal Obstruction Symptom Evaluation (NOSE) score had already improved significantly after surgery (baseline: 80 to postsurgery: 35), with a small additional benefit after starting dupilumab (35 to 30). This trend corresponds well with CFD simulation findings that surgery and dupilumab are likely both efficacious in relieving nasal obstruction (∼1% difference in nasal resistance), whereas dupilumab has a further effect of increasing relative airflow to the olfactory region. Limitations of this study include its design as a case report and its retrospective nature, which limit generalizability. The study also relies on preexisting CT scans that did not necessarily capture optimal time points. However, this study highlights an interesting finding that dupilumab may offer greater relief of congestion specifically in the olfactory region, which may inspire future, more well-powered prospective studies on this topic. The mechanism by which dupilumab improves olfaction in patients with CRSwNP may involve the reduction of regional nasal obstruction in the olfactory cleft, thereby allowing more odorants to reach the olfactory epithelium, in addition to the potential sensorineural recovery described in the literature. The authors have no conflicts of interest to disclose. NIH NIDCD R01 DC013626 and R21 DC017530 to Kai Zhao.

Physical controls on mixing and transport within rising submarine hydrothermal plumes: A numerical simulation study

The maritime sector aims to achieve short and medium-term sustainability targets through the conversion of Internal Combustion Engines to methanol operation. For small to medium sized engines, Port Fuel Injection (PFI) is the most viable injection method to achieve this conversion. However, the knowledge of the behaviour of methanol in combustion engines, particularly its spray characteristics under PFI conditions, is limited. To better understand liquid methanol sprays, this paper studies the injection of methanol in marine PFI conditions through Computational Fluid Dynamics (CFD) modelling. The CFD models use the Lagrangian-Eulerian (LE) coupling method within the Reynolds Averaged Navier Stokes (RANS) turbulence framework. Numerical results were validated using dedicated methanol experiments from the literature for both high and low injection pressures. Subsequently, this predictive CFD framework was used in a number of different injection pressures with scaled injection quantities that represent marine applications. Moreover, we demonstrated that high injection pressure improves atomisation and, thus, evaporation prior to wall impingement. This work strongly contributes to our understanding of marine PFI methanol engines by modelling fuel quantities relevant for ship applications. Our approach can be implemented in full engine simulations to solve evaporation challenges often found in small-bore methanol marine engines.

Waves induced by ship movement might be harmful for the habitat in the littoral zone of rivers due to the temporally increasing bed shear stress, the high-energy breaking waves and the consequently related detachment of benthic animals. In order to understand the complex hydrodynamic phenomena resulting from littoral waves, we present the testing of a novel methodology that incorporates field observations and numerical tools. The study is performed at a section of the Danube River in Hungary and analyzes the influence of different ship types. The field methods consist of parallel acoustic measurements (using Acoustic Doppler Velocimetry (ADV)) conducted at the riverbed and Large Scale Particle Image Velocimetry (LSPIV) of the water surface. ADV measurements provided near-bed flow velocities based on which the wave induced currents and local bed shear stress could be estimated. The LSPIV was able to quantify the dynamics of the breaking waves along the bank. Furthermore, computational fluid dynamics (CFD) modeling was successfully applied to simulate the propagation and the breaking of littoral waves. The used techniques complement each other well and their joint application provides an adequate tool to support the improvement of riverine habitats.

Background The Fontan operation has significantly improved long-term outcomes for patients with single-ventricle physiology, serving as a definitive palliative procedure. To optimise postoperative haemodynamics, early extubation is routinely performed following the Fontan operation. However, the theoretical rationale and underlying physiological mechanisms of its impact remain poorly understood. Purpose This study aims to elucidate the haemodynamic mechanisms underlying the Fontan circulation by developing serial patient-specific Fontan computational fluid dynamics (CFD) models. Furthermore, it evaluates the impact of extubation following the Fontan operation by comparing various haemodynamic parameters derived from these patient-specific CFD models. Methods Four patients with single-ventricle physiology (one female and three males, median body weight: 10.4 kg, range: 9.2-10.6kg) who underwent the Fontan operation were included in this study. A 0–1-dimensional lumped parameter Fontan circulation CFD model was derived from previous models and adapted using patient-specific data, including radial artery pressure waveforms, central venous pressure (CVP), lactate levels, and oxygen saturation. Patient-specific Fontan circulation CFD models were reconstructed at four time points before and after extubation in each patient by minimising the differences between the actual and standard Fontan circulation CFD waveforms and CVP values, using the gradient descent method. The following haemodynamic parameters were evaluated: Cardiac output (CO) per minute; End-systolic elastance (Ees) relative to arterial elastance (Ees/Ea); Ejection fraction (EF); Stroke work (SW) to pressure-volume area (PVA) ratio (SW/PVA). Results Between pre- and post-extubation, central venous pressure (CVP) decreased from 12.4 ± 1.4 mmHg to 9.5 ± 0.4 mmHg, while arterial oxygen saturation increased from 95.1 ± 1.4% to 99.5 ± 0.4% (measured data). Cardiac output (CO) increased by 35.4%, from 3.1 ± 0.1 L·min⁻¹·m⁻² to 4.2 ± 0.2 L·min⁻¹·m⁻², and the mean pulmonary artery (PA) flow rate increased by 40.7%, from 22.6 ± 1.1 mL·s⁻¹ to 31.8 ± 1.5 mL·s⁻¹ (derived from the patient-specific Fontan CFD models). Among the three patients who were extubated within 5 to 15 hours after admission to the paediatric intensive care unit (PICU)—excluding one patient who was extubated later (40 hours after PICU admission)—Ees/Ea decreased by 23.5% (range: 22–37%), while SW/PVA increased by 14.7% (range: 12–28%). Conclusion A series of patient-specific Fontan CFD models demonstrated that extubation led to a reduction in CVP and an increase in oxygen saturation, as well as improved cardiac output and pulmonary flow. These findings suggest that negative airway pressure plays a crucial role in optimising Fontan circulation, particularly in the postoperative period, by contributing to haemodynamic stabilisation.Variables pre/post-extubation Cardiac function pre/post-extubation