Performance analysis and design optimization of a novel Trombe wall system using CFD and response surface method

In this study, an investigation was made of the performance of a Trombe wall of classical structure used together with a heat store. Most Trombe walls are able to supply the heating needs of a space to which they are connected without the need for extra heating at times when the sun is shining. However, the heat obtained from the Trombe wall can be in excess of needs at such times, and measures must be taken to provide ventilation to the heated space. It is thought that the heat energy can be used more efficiently and productively by storing the excess heat outside the building and using it inside the building when there is no sunlight. To this purpose, a tank full of water and marble was built as a heat store as an alternative to the general Trombe wall design, and an attempt was made to minimise heat losses by burying it in the ground. It was concluded that in place of a traditional Trombe wall system using a massive wall heat store, a heat store could be constructed in a different position and with different materials. The Trombe wall system which was developed and tested met up to 30% of the energy needed for heating and cooling the building, and reduced the architectural and static disadvantages of Trombe wall systems. As a result of the study, it was seen that where a standard reinforced concrete wall could supply heat to the inside for 7 hours and 12 minutes, the figure for a wall made of paraffin wax was 8 hours and 55 minutes. In the same study, the heat storage thickness of a reinforced concrete wall was calculated as 20 cm, while that of a paraffin wax wall was calculated as 5 cm.

An urban living lab monitoring and post occupancy evaluation for a Trombe wall proof of concept

Development and experimental validation of a CFD model for PCM in a vertical triplex tube heat exchanger

Performance study of a phase change material Trombe wall system in summer in hot and humid area of China

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.

Thermal and electrical behavior of built-middle photovoltaic integrated Trombe wall: Experimental and numerical study

Influence of inlet structure on thermal stratification in a heat storage tank with PCMs: CFD and experimental study

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.

Passive cooling is a strategy that achieves thermal comfort inside buildings at minimum cost. The Trombe wall is one of the passive design techniques that contribute to reducing energy consumption in buildings. This research aims to improve the cooling performance of the Trombe wall through integrating the wall with a phase change material (PCM), i.e. paraffin wax, and a solar chimney (SC). A test room was built in the new city of Beni-Suef, Egypt, to evaluate the performance of the modified Trombe wall, which is integrated with a PCM and a SC. The indoor air temperature of the test room was measured during the summer of 2023 and compared for three different cases: (a) a traditional wall integrated with a PCM, (b) a Trombe wall integrated with a PCM and a SC and (c) a Trombe wall that is insulated at the indoor side and integrated with a PCM and a SC. The results showed that the lowest temperature difference between the indoor and outdoor temperatures in case (a) was –5.5°C, (b) was –6°C, however in case (c) the difference was reduced to –9.6°C. Also, the period in which the room temperature was lower than the outside temperature, which is named as the cold period, in case (a) and (b) were 9 h and 10 h, respectively, while in case (c) is 11 h. The results showed that insulating the Trombe wall internally and integrating it with a PCM and a SC increases the cold period and improves the thermal comfort of buildings in the summer season.

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

This paper investigates the simulation, response surface modeling, and optimization of the metalorganic chemical vapor deposition (MOCVD) process for the deposition of gallium nitride (GaN). Trimethylgallium (TMGa) and ammonia (NH3) are the precursors carried by hydrogen into the rotating-disk reactor. The deposition rate of GaN film and its uniformity form the focus of this study. Computational fluid dynamics (CFD) model simulates the deposition of the GaN film. CFD model is employed to identify two design variables, inlet velocity and inlet precursor concentration ratio, which significantly affect the deposition rate and uniformity of GaN film. Compromise response surface method (CRSM) is used to generate response surfaces for average deposition rate and uniformity. These response surfaces are used to generate the Pareto front for the conflicting objectives of optimal rate of average deposition and uniformity. Pareto front captures the trade-off between deposition rate and uniformity of the GaN film. It is observed that for the whole range of design variables, there are numerous options to get stable uniformity levels than deposition rate. The optimal inlet velocity and precursor concentration for different objective functions considered tend to be near the upper bounds.

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.

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.

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.

Film thickness uniformity is an important index to measure the quality of a deposited layer in selective epitaxial growth (SEG) of silicon using the chemical vapor deposition (CVD) process. The uniformity of a thin film is related to many parameters, such as rotation speed of a wafer, total flow rate, species concentration, susceptor temperature, and operating pressure. Therefore, it is very important to address the problem of coupling multiple parameters and solve the optimization in a computationally efficient manner. In this work, response surface methodology (RSM) is used to analyze the complex coupling effects of different operating parameters on silicon deposition uniformity. Based on the computational fluid dynamics (CFD) model, an accurate RSM model is obtained to predict non-uniformity with different parameters, including temperature, pressure, rotation speed of a wafer, and mole fraction of dichlorosilane (DCS). Analysis of variance (ANOVA) is conducted to determine the statistical significance of each factor in an empirical equation for the expected response. The results of ANOVA analysis indicate the goodness of fit of the regression model. The optimum combination of operating parameters of the problem considered in this study is a susceptor temperature of 1122.2 K, wafer rotation speed of 23.72 rpm, operating pressure of 112 Torr, and DCS mole fraction of 0.01186. The validation tests and optimum solution show that the results are in good agreement with those from the CFD model, and the maximum deviation between the computational solution and predicted values is 2.93%.