Steady-state Computational Fluid Dynamics Research Articles

Urban-Scale Computational Fluid Dynamics Simulations with Boundary Conditions from Similarity Theory and a Mesoscale Model

Mesoscale numerical weather prediction models usually provide information regarding environmental parameters near urban areas at a spatial resolution of the order of thousands or hundreds of meters, at best. If detailed information is required at the building scale, an urban-scale model is necessary. Proper definition of the boundary conditions for the urban-scale simulation is very demanding in terms of its compatibility with environmental conditions and numerical modeling. Here, steady-state computational fluid dynamics (CFD) microscale simulations of the wind and thermal environment are performed over an urban area of Kozani, Greece, using both the k-ε and k-ω SST turbulence models. For the boundary conditions, instead of interpolating vertical profiles from the mesoscale solution, which is obtained with the atmospheric pollution model (TAPM), a novel approach is proposed, relying on previously developed analytic expressions, based on the Monin Obuhkov similarity theory, and one-way coupling with minimal information from mesoscale indices (Vy = 10 m, Ty = 100 m, L*). The extra computational cost is negligible compared to direct interpolation from mesoscale data, and the methodology provides design phase flexibility, allowing for the representation of discrete urban-scale atmospheric conditions, as defined by the mesoscale indices. The results compared favorably with the common interpolation practice and with the following measurements obtained for the current study: SODAR for vertical profiles of wind speed and a meteorological temperature profiler for temperature. The significance of including the effects of diverse atmospheric conditions is manifested in the microscale simulations, through significant variations (~30%) in the critical building-related design parameters, such as the surface pressure distributions and local wind patterns.

Analytical Thermal Boundary Condition for Quasi-Transient Simulation of Internal Flow Experiments

Transient thermochromic liquid crystal (TLC) experiments can provide high-fidelity spatially resolved heat transfer data for complex geometries, particularly where infrared techniques cannot be applied. One challenge when applying transient methods to internal geometries is the local definition of the driving gas temperature. The transient nature of the streamwise driving gas temperature profile has led to comparisons with steady-state computational fluid dynamics being questioned. This paper explores simulating the temporal behavior of transient TLC experiments directly. A novel technique is developed to account for differences in the gas and solid time scales, where surface temperature is calculated at each spatial location analytically from the surface heat flux, using an impulse response method assuming one dimensional, semi-infinite conduction. Postprocessing of the simulated surface temperature history is performed using the same method as experimentally, allowing for direct comparison. This analytical thermal boundary condition (ATBC) is applied to simulate a transient TLC experiment of a stationary superscaled rib turbulated internal cooling passage in a gas turbine engine. Traditional steady-state simulations were also performed with constant temporal and spatial temperature boundary conditions. Results show that calculations using the new ATBC and traditional steady-state method give very similar Nusselt number distributions and mean values in relation to the experimental data, suggesting the larger discrepancy between simulations and the experiments is not the definition of the driving gas temperature. Analysis of transient variation of Nusselt number indicated brief highly localized maximum variations up to 40%, although this was not found to significantly affect the mean values, and passage-averaged values converged to within 0.5% of the final value within 0.2 s.

Detailed kinetic mechanism of devolatilization stage and CFD modeling of downdraft gasifiers using pelletized palm oil empty fruit bunches

Oil palm residues, such as palm oil empty fruit bunches (PEFBs), are typically abandoned due to high moisture and bulky. Pelletization and downdraft gasification constitute a promising solution for small-scale power and heat production. In this study, the two-dimensional, steady-state computational fluid dynamics (CFD) model of a modified Imbert downdraft gasifier consuming pelletized PEFBs is developed. The detailed kinetic mechanism of biomass devolatilization coupled with particle-scale transport equations is incorporated to enable accurate prediction of the pyrolysis zone in the gasifier. Pelletized-biomass-particles packed bed is simulated by using a porous media model with volumetric species-transport CFD model, which is validated by comparing the prediction of the species volume fractions at the gas outlet with published experimental data. Velocity and temperature profiles of the downdraft gasifier are revealed, along with tar evolution pathline. The effect of the equivalence ratio on the producer gas composition, tar concentration, and cold gas efficiency is investigated. The optimum equivalence ratio is found at 0.30 based on the tar concentration of 5 mg Nm−3 and the cold gas efficiency of 62%.

Customized 3D printed bioreactors for decellularization-High efficiency and quality on a budget.

Decellularization (DC) of biomaterials with bioreactors is widely used to produce scaffolds for tissue engineering. This study uses 3D printing to develop efficient but low-cost DC bioreactors. Two bioreactors were developed to decellularize pericardial patches and vascular grafts. Flow profiles and pressure distribution inside the bioreactors were optimized by steady-state computational fluid dynamics (CFD) analysis. Printing materials were evaluated by cytotoxicity assessment. Following evaluation, all parts of the bioreactors were 3D printed in a commercial fused deposition modeling printer. Samples of bovine pericardia and porcine aortae were decellularized using established protocols. An immersion and agitation setup was used as a control. With histological assessment, DNA quantification and biomechanical testing treatment effects were evaluated. CFD analysis of the pericardial bioreactor revealed even flow and pressure distribution in between all pericardia. The CFD analysis of the vessel bioreactor showed increased intraluminal flow rate and pressure compared to the vessel's outside. Cytotoxicity assessment of the used printing material revealed no adverse effect on the tissue. Complete DC was achieved for all samples using the 3D printed bioreactors while DAPI staining revealed residual cells in aortic vessels of the control group. Histological analysis showed no structural changes in the decellularized samples. Additionally, biomechanical properties exhibited no significant change compared to native samples. This study presents a novel approach to manufacturing highly efficient and low budget 3D printed bioreactors for the DC of biomaterials. When compared to standard protocols, the bioreactors offer a cost effective, fast, and reproducible approach, which vastly improves the DC results.

Prediction of Key Crop Growth Parameters in a Commercial Greenhouse Using CFD Simulation and Experimental Verification in a Pilot Study

Controlled crop growth parameters, such as average air velocity, air temperature, and relative humidity (RH), inside the greenhouse are necessary prerequisites for commercial greenhouse operation. Frequent overshoots of such parameters are noticed in the Middle East. Traditional heating ventilation and air-conditioning (HVAC) systems in such greenhouses use axial fans and evaporative cooling pads to control the temperature. Such systems fail to respond to the extreme heat load variations during the day. In this study, we present the design and implementation of a single span, commercial greenhouse using box type evaporative coolers (BTEC) as the backbone of the HVAC system. The HVAC system is run by a fully-automated real time feedback-based climate management system (CMS). A full-scale, steady state computational fluid dynamics (CFD) simulation of the greenhouse is carried out assuming peak summer outdoor conditions. A pilot study is conducted to experimentally monitor the environmental parameters in the greenhouse over a 20-h period. The recorded data confirm that the crop growth parameters lie within their required ranges, indicating a successful design and implementation phase of the commercial greenhouse on a pilot scale.

Numerical Analysis and Wind Tunnel Validation of Low-Temperature Ablators undergoing Shape Change

Ground testing of ablative materials aims at providing critical data on the material behavior under hypersonic reentry conditions. This is normally done in plasma wind tunnel facilities. However, non-negligible technical challenges are faced in order to duplicate the real flight conditions, such as inducing the recession of space-relevant ablative materials, which requires sufficiently high inflow total enthalpies, and/or reproducing the actual hypersonic flow velocity, which requires sufficiently high inflow Mach numbers. Often, ground facilities which are providing one requirement are lacking the other one and vice-versa. A possible solution is to use low-temperature ablators in continuous hypersonic blow-down tunnels, where aerodynamic and ablative tests with considerable shape change effects may be performed under reasonably low total temperature conditions and with affordable test durations. These substances are readily available, and they sublimate or ablate in a fashion that can be described fairly accurately by theory. This work has the objective to numerically characterize the shape change of such materials in hypersonic conditions, concurrently providing a validation against literature data and from a dedicated experimental ground test campaign. The numerical procedure relies on ad-hoc mesh generation/evolution strategies taking into account the material shape change, and is based on subsequent steady-state Computational Fluid Dynamics (CFD) computations coupled with a customizable gas-surface interaction wall boundary condition. Preliminary numerical simulations helped the design of the experiments to be carried out in the von Karman Institute (VKI) H-3 hypersonic wind tunnel, in particular for the identification of capsule geometry and size in order to maximize the shape change caused by ablation. Subsequently, camphor is identified as the most suitable low-temperature ablator to be used in the experimental campaign after a thorough analysis of its surface reaction thermodynamics and kinetics. Results from the CFD approach are first compared with a literature experimental test case and then with those of the previously designed experiments, featuring a camphor sub-scale capsule, underlying advantages and limits of the numerical procedure adopted. The obtained numerical and experimental results underline how it is possible to obtain a relevant shape change for relatively small exposure times by using low-temperature ablators in continuous hypersonic blow-down wind tunnels. Hence, results from this work can be used to support the design and sizing of the actual heat shield and the analysis of the capsule’s aerodynamics and stability, accounting for shape change effects, by establishing an appropriate similitude between in-flight and on-ground conditions.

Numerical prediction of structural damage due to pressure buildup in subsea oil and gas equipment

Pressure buildup/annular pressure buildup in subsea oil and gas equipment occurs primarily due to the thermal expansion of trapped liquids. With the advent of modern computers, it has become increasingly possible to numerically analyze such problems with commercial codes available in the market. The objective of the present study is to propose a methodology for numerical prediction of structural damage in subsea oil and gas equipment due to pressure buildup. A judicious combination of computational fluid dynamics (CFD) with structural finite element analysis code has been used to perform a sample numerical analysis that is truly representative of a wide class of problems encountered in subsea oil and gas applications. The mitigation of trapped pressure is one among the prime areas of concern in the subsea oil and gas industry. In the present study, CFD analysis is used to determine the maximum pressure buildup due to the thermal expansion of trapped liquids in small leak tight enclosed volumes with rigid walls and the pressure obtained is used as a boundary condition for the structural analysis. In a nutshell, the analysis has been split into three steps (1) a steady-state CFD analysis to determine the temperature distribution within the oil and gas equipment under consideration, (2) the temperature contours obtained from the steady-state analysis are imposed as a boundary condition for the transient analysis to calculate the trapped pressure in the small volumes of interest and finally and (3) a structural analysis is used to determine the damage to the oil and gas equipment. The methodology adapted is similar to a one-way coupled fluid structure interaction analysis, but provides the added advantage of a significant reduction in computational cost. In the present study, the proposed methodology has been extended to a subsea Christmas tree (XT) and the pressure buildup in the hydraulic lines has been calculated. The results obtained using the present technique has been compared with analytical solution. The proposed numerical technique can be applied to any subsea or surface oil and gas equipment where pressure buildup due to trapped volume is a major issue. The findings of this study can help for better understanding of pressure buildup in trapped volumes within subsea/surface oil and gas equipment. This study can be applied to predict the thermal expansion of trapped volumes in subsea XTs, manifolds, pipe line end manifolds (PLEM) and pipe line end termination (PLET) units.

Computational fluid dynamics analysis of buoyancy-aided turbulent mixed convection inside a heated vertical rectangular duct

Heat transfer in buoyancy-aided turbulent mixed convection inside a vertical rectangular duct with air was investigated through steady-state computational fluid dynamics (CFD) analysis with Reynolds-averaged Navier–Stokes turbulence models. Heat transfer can occur in the passive safety system of a nuclear reactor, which uses natural circulation as an initial driving force owing to its relatively low flow rate and strong heat flux condition. One example is the reactor cavity cooling system in a very high temperature gas-cooled nuclear reactor, whose high operating temperature enables high-efficiency power generation and hydrogen production. In buoyancy-aided turbulent mixed convection, heat transfer can deteriorate under specific conditions. Therefore, heat transfer must be analyzed because its deterioration can affect the performance of the safety system, which has an influence on the safety of the nuclear reactor. In this study, the results of a CFD analysis were compared with experimental results obtained from the riser heat transfer experimental facility, which is an experimental heat transfer facility with a 4.0 vertical rectangular duct test section. The CFD analyses were performed using a realizable k–ε model and a v2–f model, and the results were compared with the experimental results. It was confirmed that the results of the v2–f model exhibited good agreement with the experimental results. Based on this fact, four additional idealized cases were calculated using the v2–f model to investigate heat transfer deterioration in the turbulent mixed-convection regime. The calculation results revealed that the gradient of the velocity profile from the wall toward the center was reduced outside the near-wall region owing to buoyancy, which led to a reduction in the shear stress, turbulence generation, and heat transfer. In addition, the velocity gradient beyond the near-wall region reached a negative value above a certain buoyancy number, and turbulence generation and heat transfer started to recover. This analysis of heat transfer deterioration can provide insight into the construction of a heat-transfer coefficient correlation for buoyancy-aided turbulent mixed convection, and it will contribute to the development of heat transfer predictions and the evaluation of safety systems in nuclear reactors.

Geometrically induced wall shear stress variability in CFD-MRI coupled simulations of blood flow in the thoracic aortas

Aortic aneurysm is associated with aberrant blood flow and wall shear stress (WSS). This can be studied by coupling magnetic resonance imaging (MRI) with computational fluid dynamics (CFD). For patient-specific simulations, extra attention should be given to the variation in segmentation of the MRI data-set and its effect on WSS.We performed CFD simulations of blood flow in the aorta for ten different volunteers and provided corresponding WSS distributions. The aorta of each volunteer was segmented four times. The same inlet and outlet boundary conditions were applied for all segmentation variations of each volunteer. Steady-state CFD simulations were performed with inlet flow based on phase-contrast MRI during peak systole.We show that the commonly used comparison of mean and maximal values of WSS, based on CFD in the different segments of the thoracic aorta, yields good to excellent correlation (0.78–0.95) for rescan and moderate to excellent correlation (0.64–1.00) for intra- and interobserver reproducibility. However, the effect of geometrical variations is higher for the voxel-to-voxel comparison of WSS. With this analysis method, the correlation for different segments of the whole aorta is poor to moderate (0.43–0.66) for rescan and poor to good (0.48–0.73) for intra- and interobserver reproducibility.Therefore, we advise being critical about the CFD results based on the MRI segmentations to avoid possible misinterpretation. While the global values of WSS are similar for different modalities, the variation of results is high when considering the local distributions.

Distributed deep reinforcement learning for simulation control

Several applications in the scientific simulation of physical systems can be formulated as control/optimization problems. The computational models for such systems generally contain hyperparameters, which control solution fidelity and computational expense. The tuning of these parameters is non-trivial and the general approach is to manually ‘spot-check’ for good combinations. This is because optimal hyperparameter configuration search becomes intractable when the parameter space is large and when they may vary dynamically. To address this issue, we present a framework based on deep reinforcement learning (RL) to train a deep neural network agent that controls a model solve by varying parameters dynamically. First, we validate our RL framework for the problem of controlling chaos in chaotic systems by dynamically changing the parameters of the system. Subsequently, we illustrate the capabilities of our framework for accelerating the convergence of a steady-state computational fluid dynamics solver by automatically adjusting the relaxation factors of the discretized Navier–Stokes equations during run-time. The results indicate that the run-time control of the relaxation factors by the learned policy leads to a significant reduction in the number of iterations for convergence compared to the random selection of the relaxation factors. Our results point to potential benefits for learning adaptive hyperparameter learning strategies across different geometries and boundary conditions with implications for reduced computational campaign expenses 4 4Data and codes available at https://github.com/Romit-Maulik/PAR-RL..

Multi-objective optimization of PEM fuel cell by coupled significant variables recognition, surrogate models and a multi-objective genetic algorithm

This paper aims to present a fast and systematic optimization approach for proton exchange membrane fuel cell (PEMFC) by combining variance analysis, surrogate models and non-dominated sorting genetic algorithm (NSGA-II). First, a three-dimensional steady-state PEMFC computational fluid dynamics (CFD) model is developed as the base model for optimization. Second, six variables that have significant effect on PEMFC performance are selected from numerious common parameters using variance analysis, reducing the number of decision variables from 11 to 6. Then, three data-driven ensemble learning models are trained as surrogate models to accelerate the fitness values evaluation of the optimization algorithm. Finally, three PEMFC performance indexes, including power density, system efficiency and oxygen distribution uniformity on cathode catalyst layer are optimized simultaneously based on NSGA-II. Using the NSGA-II combined with surrogate models, a set of Pareto solutions is obtained in a short time. The results indicate that PEMFCs with optimized parameters perform better than the base model in terms of all three performance indexes, demonstrating the success of this approach in solving time-consuming multi-optimization problems. This study provides a fast and systematic approach for PEMFC multi-objective optimization and can be a guide for engineering applications.

Test Results for the Static and Rotordynamic Characteristics of a Long (L/D = 0.75) Smooth Seal in Two-Phase (Mainly Gas) Conditions With a 62-Bar Inlet Pressure

Abstract Recent multiphase-pump developments encountered several rotordynamic issues with smooth balance-piston seals, creating a need to better understand the performance of annular seals under multiphase-flow operation. This paper presents measurements of static and dynamic characteristics of a long smooth seal (L/D = 0.75, D = 114.686 mm, and Cr = 0.200 mm) operating under pure- and mainly air condition in which air is mixed with silicone oil (PSF-5cSt). Tests are performed at a supply pressure of 62.1 bars-g, three rotation speeds (5, 10, and 15 krpm), three pressure ratios (PRs) (0.6, 0.5, 0.4), for a range of inlet liquid volume fraction (LVFi) from 0% to 8%. The results are then compared to: (1) the previous test reported by Zhang et al. (2017, “Experimental Study of the Static and Dynamic Characteristics of a Long Smooth Seal with Two-Phase, Mainly-air Mixtures,” ASME J. Eng. Gas Turbines Power, 139(12), p. 122504) with similar testing condition but a different seal geometry (L/D = 0.65, D = 89.306 mm, and Cr = 0.188 mm) and (2) the predictions from a bulk-flow model developed by San Andrés (2012, “Rotordynamic Force Coefficients of Bubbly Mixture Annular Pressure Seals,” ASME J. Eng. Gas Turbines Power, 134(2), p. 022503). Results show a significant increase of direct dynamic stiffness KΩ as LVFi increases, especially at low PR. Test results reported by Zhang et al. (2017, “Experimental Study of the Static and Dynamic Characteristics of a Long Smooth Seal with Two-Phase, Mainly-air Mixtures,” ASME J. Eng. Gas Turbines Power, 139(12), p. 122504) has an opposite tendency of KΩ as an impact of increasing LVFi values. Concerning cross-coupled dynamic stiffness kΩ and cross-coupled damping c, the results from Zhang et al. (2017) and the present results agree to the effects of changing speed, PR, and LVFi under pure- and mainly air conditions. As LVFi increases, direct damping C increases while test results reported by Zhang et al. (2017, “Experimental Study of the Static and Dynamic Characteristics of a Long Smooth Seal with Two-Phase, Mainly-air Mixtures,” ASME J. Eng. Gas Turbines Power, 139(12), p. 122504) showed no significant increase. A steady-state computational fluid dynamics (CFD) result for a testing case suggests a significant difference happening inside the two seals (present seal and Zhang et al.'s (2017, “Experimental Study of the Static and Dynamic Characteristics of a Long Smooth Seal with Two-Phase, Mainly-air Mixtures,” ASME J. Eng. Gas Turbines Power, 139(12), p. 122504) seal). A full investigation in CFD is needed. Except for the direct dynamic stiffness and the impact of changing LVFi on the cross-coupled dynamic stiffness, the bulk-flow model of San Andrés (2012, “Rotordynamic Force Coefficients of Bubbly Mixture Annular Pressure Seals,” ASME J. Eng. Gas Turbines Power, 134(2), p. 022503) predicts decently the tendencies and magnitudes of the rotordynamic coefficients.

Enhancing Air Quality for Embedded Hospital Germicidal Lamps

The indoor air of a hospital is always full of bacteria and viruses due to patients with different diseases. These bacteria and viruses could be highly infectious to the people in the hospital irrespective of their health conditions, and could be hazardous to the patients, their care takers, and hospital staff. Thus, keeping a good hospital air quality is very essential to the operation of the hospital. This study aims at enhancing ventilation of the interior lighting of hospitals with germicidal capabilities. Air disinfection is accomplished by adding the specially designed disinfecting filters and fans to existing embedded lamps in the hospitals. The embedded lamp has a square shape of 601 mm in width and 112 mm in thickness. In the design stage, the air flow inside the embedded lamp with the added filters and fans was investigated by numerical simulation using a computational fluid dynamics (CFD) tool. Three designs, referred to as Types 1, 2, and 3, were evaluated using steady-state CFD flow simulations. The ventilation rate of the Type 1 design was about 251.9 CMH, and 348.3 CMH for the Type 2 design by increasing the fan outlet area. However, even though the ventilation was increased by 34%, the flow field of the Type 2 design was not uniform, resulting in flows being circulated around the side locations. Thus, the Type 3 design further treats this aspect by streamlining the outlet geometry and adding flow guiding vanes to reduce flow resistance and flow unsteadiness; the corresponding air ventilation rate reached 376.3 CMH. Hence, the Type 3 design was fabricated and tested. The test results confirm that the design not only has a higher ventilation rate but also operates under a smaller pressure drop, thus accomplishing the goal of providing good air quality in the hospital environment efficiently. Moreover, the associated flow noise is reduced by about 8 dBA. Hence, both an increase in the air ventilation rate and a reduction of noise are achieved simultaneously by the present method.

Design and analysis of a smart-attachment to jacket and helmet used by two-wheeler riders using Peltier-module

A two-wheeler ride without wearing a helmet is punishable offence in many countries and, it can be irritating to have it around your head owing to heat and sweat generated. People riding over long distances or in harsh-conditions, in addition to a helmet uses a jacket to prevent themselves from the weather. Controlling the temperature that a rider is exposed to is highly-essential for the safety, quality and the ability of the rider to enjoy rides. The smart-attachment to jackets and helmets is an equipment which is capable of imparting an enhanced riding experience by regulating the temperature around a rider’s head and body. The device makes use of the phenomenon of thermoelectric effect, i.e. the Peltier effect to control temperature around the head and the body. In this study a Peltier TEC1-12706 module is used in the design of the smart-attachment to helmets and jackets and the proposed system makes use of the ambient air for the heat transfer process. The ambient-air, when allowed to flow over the Peltier-module gets cooled and hence enables temperature regulation. The design and analysis of a mechanism to control temperature in helmets and jackets is proposed through this study and steady-state thermal analysis and Computational Fluid Dynamics (CFD) analysis are performed on the proposed model making use of commercially available Finite Element Analysis (FEA) software, namely ANSYS. The system developed through this study can be used as an attachment to existing helmets and jackets with minor modifications and is designed in such a way as to not interfere with crash-protection capability of the helmet/jacket and can be used under rainy conditions adding to the versatility of the product.

An orifice shape-based reduced order model of patient-specific mitral valve regurgitation

Mitral valve regurgitation (MR) is one of the most prevalent valvular heart diseases. Its quantitative assessment is challenging but crucial for treatment decisions. Using computational fluid dynamics (CFD), we developed a reduced order model (ROM) describing the relationship between MR flow rates, transvalvular pressure differences, and the size and shape of the regurgitant valve orifice. Due to its low computational cost, this ROM could easily be implemented into clinical workflows to support the assessment of MR. We reconstructed mitral valves of 43 patients from 3D transesophageal echocardiographic images and estimated the 3D anatomic regurgitant orifice areas using a shrink-wrap algorithm. The orifice shapes were quantified with three dimensionless shape parameters. Steady-state CFD simulations in the reconstructed mitral valves were performed to analyse the relationship between the regurgitant orifice geometry and the regurgitant hemodynamics. Based on the results, three ROMs with increasing complexity were defined, all of which revealed very good agreement with CFD results with a mean bias below 3% for the MR flow rate. Classifying orifices into two shape groups and assigning group-specific flow coefficients in the ROM reduced the limit of agreement predicting regurgitant volumes from 9.0 ml to 5.7 ml at a mean regurgitant volume of 57 ml.

Assessing cooling energy reduction potentials by retrofitting traditional cavity walls into passively ventilated cavity walls

A major roadblock in achieving substantial building energy reduction is the low performance of old buildings that account for a significant portion of the building energy consumption. Finding low-cost energy retrofit solutions that do not disrupt occupants’ daily life during the retrofitting is the key to successful building energy retrofit initiatives. In this paper, a novel and low-cost exterior wall retrofitting solution is introduced, and its performance in reducing space cooling load was quantitatively evaluated to demonstrate its feasibility and effectiveness. The primary goal of this paper is to provide a quantitative assessment of the cooling-energy savings potential by using the proposed new wall system. The intended retrofitting targets are the large amount of existing cavity-wall buildings located in hot climate regions. The quantification of the before-after heat-flux reduction was conducted through a 3-dimensional steady-state low turbulence computational fluid dynamics (CFD) model, which is validated by benchmarking its prediction against the published experimental case results. The outcomes of the investigation suggest that this simple low-cost solution has great potentials in reducing buildings’ summer cooling load in hot climate regions. The applicability of this solution is not limited to retrofitting existing buildings. New energy-efficient building designs can also adopt this solution in their envelope systems.

Validation of a Radial Compressor CFD Analysis

In this study, a radial compressor flow at a high speed is investigated by Computational Fluid Dynamics (CFD) methods. The radial compressor of interest consists of a rotor, diffuser, and exit guide vanes and has an operational rotational speed of 21789 rpm. The geometry of the compressor and its test results such as compression ratio and adiabatic efficiency are available in literature. After extensive mesh convergence tests, steady-state CFD analysis has been performed for compressible and turbulent flow using the ideal gas approach. The main motivation of the study is the determine the appropriate CFD approach and boundary conditions of the problem that will fit best to the measurements. The CFD analysis revealed that the maximum relative errors for the adiabatic efficiency and the pressure ratio were 3.6 % and 1.3 %, respectively.

Sensitivity analysis of proposed natural ventilation IEQ designs for archetypal open-plan office layouts in a temperate climate

ABSTRACT Designing naturally ventilated deep, open-plan offices could improve occupants’ thermal comfort and productivity and ensure energy reductions; however, this can be challenging when relying on façade only openings. This research examines the ventilation performance sensitivity of atria, innovative façade openings and interior layouts of open-plan offices, in order to identify optimal typologies. Different building typologies are developed through a combination of various atria designs and configurations, with the effective use of high-aspect-ratio (HAR) openings with a similar dimension to that of the floor-to-ceiling height, in either a mid-level vertical (MLV) or high-level horizontal (HLH) orientation. Steady-state computational fluid dynamics (CFD) simulations are performed to predict internal airflow and temperature distribution in a moderate climate and water-bath modelling (WBM) experiments to validate the computational models. Results showed that MLV provide superior cooling potential (up to 2.5°C reductions) and higher ventilations rates; despite, increasing thermal gradients. Unobstructed atria with a horizontal profile similar to that of the building footprint also performed well. Overall, façade opening design was shown to be the most influential design parameter. This research has presented guidance based on reliable results to better equip building designers and architects in the design of successful naturally ventilated deep, open-plan offices.

Stochastic assessment of aerodynamics within offshore wind farms based on machine-learning

Abstract Wind turbine flow field prediction is difficult as it requires computationally expensive computational fluid dynamics (CFD) models. The contribution of this paper is to propose and develop a method for stochastic analysis of an offshore wind farm using CFD and a non-intrusive stochastic expansion. The approach is developed through testing a range of machine-learning methods, evaluating dataset requirements and comparing the accuracy against site measurement data. The approach used is detailed and the results are compared with real measurements obtained from the existing wind farm to quantify the accuracy of the predictions. An existing offshore wind farm is modelled using a steady-state CFD solver at several deterministic input ranges and an approximation model is trained on the CFD results. The approximation models compared are Artificial Neural Networks, Gaussian Process, Radial Basis Function, Random Forest and Support Vector Regression. RBF achieves a mean absolute error relative to the CFD model of only 0.54% and the error of the SVR predictions relative to the real data, with scatter, was 12%, compared to 16% from Jensen. This approach has the potential to be used in more complex situations where an existing analytical method is either insufficient or unable to make a good prediction.

Disclosure of the internal transport phenomena in an air-cooled proton exchange membrane fuel cell—Part I: Model development and base case study

In this study, the internal transport phenomena and mechanism inside an air-cooled proton exchange membrane fuel cell (PEMFC) are investigated. It helps to understand the factors that affect the performance of an air-cooled PEMFC and optimize the design of Membrane Electrode Assembly (MEA) and the flow field. This series article contains two parts. In this paper, i.e., Part Ⅰ of this series, a three-dimensional, two-phase flow, non-isothermal, steady-state Computational Fluid Dynamics (CFD) model is established to investigate the liquid water generation mechanism and the species distributions inside an air-cooled PEMFC single cell with a Base Case flow field design. Dry hydrogen and ambient air (the relative humidity and the stoichiometry are 60% and 150 separately) are considered for the simulation and validation. It is found that the liquid water appears mostly inside the cathode electrode underneath the cathode rib. Inside the anode gas diffusion layer (GDL), the mass fraction of H2 underneath the cathode ribs is lower than that underneath the cathode channels, while the mass fraction of H2O shows the opposite. The distributions of O2 mass fraction and H2O mass fraction inside the cathode GDL have the same trend as those of H2 mass fraction and H2O mass fraction inside the anode GDL. The membrane water content is periodically distributed from channel to channel and its value underneath the cathode rib is much larger than that underneath the cathode channel. The current density distribution is affected by the distribution of water content, i.e., the part underneath the cathode rib shows a larger current density than that underneath the cathode channel.