Numerical analysis of transport phenomena for designing of ejector in PEM forklift system

A “credible” computational fluid dynamics (CFD) model has the potential to provide a meaningful evaluation of safety in medical devices. One major challenge in establishing “model credibility” is to determine the required degree of similarity between the model and experimental results for the model to be considered sufficiently validated. This study proposes a “threshold-based” validation approach that provides a well-defined acceptance criteria, which is a function of how close the simulation and experimental results are to the safety threshold, for establishing the model validity. The validation criteria developed following the threshold approach is not only a function of Comparison Error, E (which is the difference between experiments and simulations) but also takes in to account the risk to patient safety because of E. The method is applicable for scenarios in which a safety threshold can be clearly defined (e.g., the viscous shear-stress threshold for hemolysis in blood contacting devices). The applicability of the new validation approach was tested on the FDA nozzle geometry. The context of use (COU) was to evaluate if the instantaneous viscous shear stress in the nozzle geometry at Reynolds numbers (Re) of 3500 and 6500 was below the commonly accepted threshold for hemolysis. The CFD results (“S”) of velocity and viscous shear stress were compared with inter-laboratory experimental measurements (“D”). The uncertainties in the CFD and experimental results due to input parameter uncertainties were quantified following the ASME V&V 20 standard. The CFD models for both Re = 3500 and 6500 could not be sufficiently validated by performing a direct comparison between CFD and experimental results using the Student’s t-test. However, following the threshold-based approach, a Student’s t-test comparing |S-D| and |Threshold-S| showed that relative to the threshold, the CFD and experimental datasets for Re = 3500 were statistically similar and the model could be considered sufficiently validated for the COU. However, for Re = 6500, at certain locations where the shear stress is close the hemolysis threshold, the CFD model could not be considered sufficiently validated for the COU. Our analysis showed that the model could be sufficiently validated either by reducing the uncertainties in experiments, simulations, and the threshold or by increasing the sample size for the experiments and simulations. The threshold approach can be applied to all types of computational models and provides an objective way of determining model credibility and for evaluating medical 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.

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.

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.

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

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) 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.

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.

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 droplet drift during aerial spraying process of oilseed rape, which is induced by complex flow field including random lateral wind, is difficult to predict and suppress. In this study, the high-fidelity computational fluid dynamics (CFD) technique is employed to simulate the two-phase flow of droplets in the rotor flow field, and the influence of main operation parameters on spraying effect is investigated numerically. Furthermore, the mechanism of droplet deposition in various operation conditions is discussed according to the analysis of unsteady flow field characteristics. However, the simulation via CFD technique is time-consuming, and it is not suitable for multidisciplinary work and optimization design. To address such issue, a filter white Gaussian noise signal is used to mimic the random lateral wind, and the droplet drift distance is obtained numerically. Based on the input and output dataset of CFD, the recursive algorithm including nonlinear autoregressive exogenous model and surrogate-based recurrence framework and the deep learning method for time-series prediction called long short-term memory neural network are used to build the efficient reduced-order model, respectively. Numerical simulations show that the droplet drift distance can be predicted by measurable lateral wind speed via the reduced-order model approach, which agreed well with the results obtained via the CFD method. In addition, the reduced-order model could decrease computation cost by 6 orders of magnitude with an acceptable accuracy, which indicates that the proposed method could be used for the design of off-line closed-loop controller of a variable spraying system.

In Victoria, Australia, brown coal is utilised as a major source of energy for the power generation industry. Victorian and South Australian brown coals have a very high moisture content and therefore, the efficiencies of power generation in traditional pulverised fuel fired furnaces are low. Fluidised beds offer a number of advantages over conventional furnaces, leading to improvements in efficiency and environmental impact. A disadvantage with implementing fluidised bed technology is the issue of scale-up. Fluidised bed behaviour can alter significantly with changes in scale, because of their strong dependence on the bed hydrodynamics. Hence, there is a need to accurately model bed behaviour to ensure that the effect of changes in scale are well understood and will not become costly and time consuming. Computational Fluid Dynamics (CFD) techniques can be applied to fluidised bed systems to gain a better understanding of the hydrodynamic behaviour involved. In the past, numerical models have considered only single particle sizes due to the added complexity of interaction between particles of differing sizes and densities. Industrial fluidised beds typically contain more than one particle size and density, therefore there is a need to develop a numerical model which takes this into account. The aim of this thesis is to develop and validate CFD techniques for modelling the behaviour of a gas-solid fluidised bed containing more than one particle size and density. To provide validation data for the numerical model, physical experiments are undertaken on a small two-dimensional bubbling gas-solid fluidised bed. Mixing and segregation behaviour of different materials are investigated. The experiments demonstrate that whilst only a small proportion of the bed consists of different size/density particles, significant changes in bed behaviour are apparent. Changes in bubble rise velocity, bubble size and bubble shape are observed. A number of constitutive equations must be included in the numerical model, including relationships for the momentum transfer between various phases and solids pressure. Different combinations of these constitutive equations are investigated. A new equation for particle-particle interactions is derived and included in a CFD model. The CFD model is validated against both data in the literature and physical experiments. From the validation studies, an optimum equation set is identified. This optimum equation set produces numerical results that closely resemble experimental bed behaviour, thus bringing the goal of solving scale-up problems one step closer. The use of this type of CFD model will ultimately result in timely and cost effective solutions for both the power generation and chemical processing industries.

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.

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.

Sensitivity analysis of WRF-CFD-based downscaling methods for evaluation of urban pedestrian-level wind

Oil and gas wells are generally drilled with the intention of forming a filter cake on the wellbore walls to primarily reduce the large losses of drilling fluid into the surrounding formation. Unfortunately, formation conditions are frequently encountered that may result in unacceptable losses of drilling fluid into the surrounding formation despite the type of drilling fluid employed and filter cake created. It is extremely important to optimize filter cake thickness as very thick filter cake can cause stuck pipe and other drilling problems. The focus of this research is to use a computational fluid dynamics (CFD) technique to numerically simulate filter cake formation on the vertical wellbore wall at high-pressure (25,500 psi or 175.8 MPa) and temperature (170°C) conditions. Here, the drilling fluids were treated as a two-phase system of solid particulates suspended in a non-Newtonian fluid. Drilling process simulations were performed for drilling fluid with two particle sizes, 45- and 7- µm, under extreme drilling conditions of high pressure and temperature. The comparison of both scenarios clearly shows that the drilling fluid with larger particles (45 µm) forms thicker filter cake compared to drilling fluids with smaller particles (7 µm). We have further used FLUENT CFD code to successfully simulate filter cake formation on the wellbore wall at moderate pressure (2,000 psi or 13.8 MPa) and temperature (30°C) conditions with drilling fluid of 45 µm particles. The results for axisymmetric and planar wellbore show that the cake formed during extreme drilling processes is thicker than that formed for shallow drilling processes. Filter cake formed on the vertical wellbore wall is nonuniform for both extreme and shallow drilling process. Key words: Filter cake, two-phase flow, computational fluid dynamics (CFD), deep drilling.