CFD analysis of Pd-Ag membrane reactor performance during ethylbenzene dehydrogenation process

CFD modeling of liquid entrainment through vertical T-junction of fourth stage automatic depressurization system (ADS-4)

In handling Floating LNG storage and transportation, the rollover phenomena, referred to the spontaneous mixing of stratified LNG layers leading to increased LNG boil off rates, is one of the major safety concerns in LNG storage tanks. Stratification occurs when the LNG in the tank forms in different layers with different densities and temperatures. Heat leaks through the tank insulation leads to sudden mixing of these various density layers. This causes a sudden release of large amount of vapor and over pressurization of the tank leading to tank damage and failure. In FLNGs, the motion of the cargo can advance the boil off rates further. A Computational Fluid Dynamics (CFD) model is proposed to capture the rollover phenomenon and its impact on boil off rate under static LNG conditions. The CFD model is first validated against experimental data for density distribution and is subsequently used to conduct a series of CFD studies to evaluate the rollover in different operating pressure conditions inclusive of heat leakage through wall. The study involves a fully thermodynamics and phase change coupled multiphase model accounting for the presence of multi-component system and is used to predict the boil off rate during a rollover occurrence in a static storage tank. CFD analysis provides a comprehensive time dependent mixing behavior, inclusive of flow, density temperature distributions and mass transfer effects, of an LNG system under different conditions of feed rate, thermal gradients and storage pressure. In particular, with rollover event, the sudden change in density variations and boil off rates are captured. There were many accidents reported in the LNG plants due to rollover. Different methods exist to monitor and prevent the rollover such as equipment installation to promote mixing, avoiding long stoppage time etc. The proposed CFD model can model the rollover phenomenon accurately while being able to predict the feasibility and efficiency of various rollover prevention methods.

In the hydrogen production cycle the syngas stream coming out from reformers or coal gasification plants contains a large percentage of H2 (ca. 50%) and CO (ca 45%). In fact, it is systematically upgraded by a water gas shift reaction (WGS) in order to convert the CO present and, at the same time, to produce further hydrogen. Water gas shift is an exothermic thermodynamics limited reaction and the presence of products like H2 further depletes the CO conversion achievable. In traditional applications this upgrading stage is usually performed in two reaction stages: firstly, the syngas stream is fed to a reactor operated in a high temperature range (300–400 °C) to exploit the advantages offered by a fast kinetics; then, the outlet stream of the first reactor is fed, after cooling, in a low temperature stage, for the benefit of the thermodynamics. This final stream is, thus, fed to a separation unit to recover the hydrogen from the rest of the gaseous stream. In this work the upgrading of a syngas stream is experimentally investigated in a Pd-based membrane reactor (MR) operated in the medium/high temperature range (340–375 °C). The advantages on the MR performance offered by fast kinetics and permeation rate have been analyzed as a function of the feed pressure (up to 1100 kPa), feed molar ratio, and gas hourly space velocity (GHSV). The values of these variables used in the experiments are closer to those used in the industrial applications. The MR performance, compared with the ones of a traditional reactor (TR) operated in the same conditions, was evaluated also in terms of volume index which evidences the lower catalyst volume required by an MR for achieving the same conversion of a TR. Owing to the fast kinetics and permeation rate, the limit due to the presence of product (i.e., H2) in the feed stream added to that imposed by the thermodynamics were successfully overcome with the MR operated in the high temperature range. A CO conversion significantly higher than the thermodynamics upper limit of a TR was achieved, also at high values of GHSV and less than 30% of the reaction volume of a TR was required for achieving a conversion equal to 90% of the traditional reactor equilibrium conversion.

High-pitched noise generated by dental air turbine handpieces (ATHs) causes discomfort and anxiety, discouraging dental visits. Understanding the time-dependent noise generation mechanism associated with compressed airflow in ATHs is crucial for effective noise reduction. However, the direct investigation of airflow dynamics within ATHs is challenging. The transient-state modeling of computational fluid dynamics (CFD) simulations remains unexplored owing to the complexities of high rotational speeds and air compressibility. This study develops a novel CFD framework for transient (time-dependent) modeling under high-speed rotational conditions. Simulations were performed using a three-dimensional model reconstructed from a commercial ATH. Simulations were conducted at 320,000 rpm using a novel framework that combines the immersed boundary and building cube methods. A fine 0.025 mm mesh spacing near the ATH, combined with supercomputing resources, enabled the simulation of hundreds of millions of cells. The simulation results were validated using experimental noise measurements. The CFD simulation revealed transient airflow and aeroacoustic behavior inside and around the ATH that closely matched the prominent frequency peaks from the experimental data. This study is the first to simulate the transient airflow of ATHs. The proposed CFD model can accurately predict aeroacoustics, contributing to the future development of quieter and more efficient dental devices.

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.

Radial heat transport in a fixed-bed reactor made of metallic foam pellets: Experiment and particle-resolved computational fluid dynamics

An application of a Pd-based membrane in a multistage spherical styrene monomer production process for hydrogen extraction

A numerical investigation was performed to study the variation in axial and lateral velocity profiles occurring downstream of the inlet nozzle of a typical Westinghouse 17×17 PWR fuel assembly. A Computational Fluid Dynamic (CFD) model was developed with commercial CFD software. The model comprised the lower region of the fuel assembly, including: the Debris Filter Bottom Nozzle (DFBN), P-grid, Bottom Inconel grid, one and half grid span, as well as the lower core plate hole. The purpose of the study was to obtain insight into the flow redistribution resulting from the interaction of the jet arising from the lower core plate hole and the fuel assembly structure. In particular the axial and lateral velocities before and after the nozzle were studied. The results, axial and lateral velocity contours, streamlines and maximum axial and lateral velocity distributions at various elevations are presented and discussed in relation to the potential risk of high turbulent excitation over the rod and the resulting rod-to-grid fretting-wear damage. The CFD model results indicated that the large jet flows from the lower core plate are effectively dissipated by DFBN nozzle and the grids components of the fuel assembly. The breakup of the large jets in the DFBN and the lower grids helps to reduce the steep velocity gradients and thus the rod vibration and fretting-wear risk in the lower part of the fuel assembly. The presented CFD model is one step towards developing advanced tools that can be used to confirm and evaluate the effect of complex PWR structures on flow distribution. In the future the presented model could be integrated in a larger CFD model involving several fuel assemblies for evaluating the lateral velocities generated due to the non-uniform inlet conditions into the various fuel assemblies.

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.

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.

CO2 is the main anthropogenic greenhouse gas and its reduction plays a decisive role in reducing global climate change. As a CO2 elimination method, the present work is based on chemical absorption using aqueous ammonia as solvent. A CFD (computational fluid dynamics) model was developed to study CO2 capture in a single droplet. The objective was to identify the main mechanisms responsible for CO2 absorption, such as diffusion, solubility, convection, chemical dissociation, and evaporation. The proposed CFD model takes into consideration the fluid motion inside and outside the droplet. It was found that diffusion prevails over convection, especially for small droplets. Chemical reactions increase the absorption by up to 472.7% in comparison with physical absorption alone, and evaporation reduces the absorption up to 41.9% for the parameters studied in the present work.

The constant development of aero engines towards lighter but yet more compact designs, without decreasing their efficiency, has led to gradually increased demands of the lubrication systems, such as the bearing chambers of the aero engine. For this reason, it is of particular importance to increase our level of understanding of the flow field inside the bearing chambers in order to optimize its design and performance. The flow field in such cases is of a complicated nature since there is a strong interaction between air-flow and lubricant oil together with the geometrical configurations and the shaft rotational speed inside the bearing chamber. The behavior of this interaction must be investigated in order to understand the flow field development inside the aero engine bearing and, at a next step, optimize its performance in relation to the lubrication and heat transfer capabilities. Such an effort is presented in this work where an investigation of the air-flow field development inside the front bearing chamber of an aero engine is attempted. The front bearing chamber is divided in two separate smaller sections where the flow passes from the first section partially through the bearing and the holding structure, to the second one where the vent and the scavenge are placed. The investigation was performed with the combined use of experimental measurements and Computational Fluid Dynamics (CFD) modeling. The experimental measurements were carried out with the use of a Laser Doppler Anemometry (LDA) system in an experimental rig modeling the front bearing chamber of an aero engine for real operating conditions taking into account both air-flow and lubricant oil-flow and for a varying number of shaft rotating speeds. The CFD modeling was performed with the use of a commercial CFD package. The air-flow inside the bearing was modeled with the adoption of a porous medium assumption. The experimental measurements and the CFD computations presented similar flow patterns and satisfactory quantitative agreement. At the same time the effect of the important parameters such as the air and oil mass flow together with the shaft rotation speed and the effect of the chamber inside geometry were identified. These conclusions can be exploited in future attempts in combination with the developed CFD model, in order to optimize the efficiency of the lubricant and cooling system. The latter forms the main target of this work which is the development of a useful engineering tool capable of predicting the flow field inside the aero engine bearing so as to be used for optimization efforts.

Urban environmental problem became one of major issues during its urbanization processes. Environmental impacts are assessed during recent urban planning and development. Though the environmental impact assessment considers meteorological impact as a minor component, changes in wind environment during development can largely affect the distribution pattern of air temperature, humidity, and pollutants. Impact assessment of local wind is, therefore, a major element for impact assessment prior to any other meteorological impact assessment. Computational Fluid Dynamics (CFD) models are utilized in various fields such as in wind field assessment during a construction of a new building and in post analysis of a fire event over a mountain. CFD models require specially formatted input data and produce specific output files, which can be analyzed using special programs. CFD's huge requirement in computing power is another hurdle in practical use. In this study, a CFD model and related software processors were automated and integrated as a microscale wind environmental impact assessment system. A supercomputer system was used to reduce the running hours of the model. Input data processor ingests development plans in CAD or GIS formatted files and produces input data files for the CFD model. Output data processor produces various analytical graphs upon user requests. The system was used in assessing the impacts of a new building near an observatory on wind fields and showed the changes by the construction visually and quantitatively. The microscale wind assessment system will evolve, of course, incorporating new improvement of the models and processors. Nevertheless the framework suggested here can be utilized as a basic system for the assessment.

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.

In the present study, a Computational Fluid Dynamics (CFD) model was set up to analyse the dynamic behaviour of LNG (Liquefied Natural Gas) tanks adopted in heavy trucks refuelling stations in normal operating conditions or during process upsets. The CFD model was based on the Volume-Of-Fluid (VOF) method to simulate the transient behaviour of a multi-phase flow in a 100 m3 vertical cylindrical tank. The model first considered a fully insulated vessel, and subsequently it was modified to take into account possible damages of the insulation layer, this being a critical upset scenario. The CFD model allowed predicting the dynamic pressure build up in the damaged tank, thus obtaining key indications for the evaluation of the vessel mechanical resistance and set up of safety measures. The model also provided the prediction of vapor temperature with respect to time and external heat source, that is a key issue to assess the effectiveness of the thermal insulation.