Selection Of Turbulence Model Research Articles

Enhancing climate control and management in arid conditions: A numerical study on the impact of roof pitch angle on greenhouse climates

This paper presents a comprehensive investigation of the impact of the roof pitch angle on the microclimate in greenhouses, particularly in arid regions. The research combines experimental datasets with numerical modeling. The numerical model aims to assess the collective effects on the internal environment involving crops, soil, polyethylene, and air. Validation of numerical outcomes is conducted through a comparison with experimental data, with a specific focus on the temperature and velocity profiles derived from a greenhouse prototype. The study incorporates numerical model optimization, encompassing a turbulence model selection and a grid independence analysis, to ensure the reliability of the numerical model. The numerical results demonstrate that the roof pitch angle significantly affects the distributions of the interior temperature, the velocity fields, the Discrete Ordinates (DO) irradiation, and the static pressure. To accurately capture such variations, robust correlations were established. In addition, a comparative analysis of the crop height (Hc) impact was carried out demonstrating the direct effect of the height on both velocity and temperature profiles. In fact, at a Hc of 1m, the temperature reaches T = 321.5K, whereas for Hc = 0.5m, the temperature does not exceed T = 318K. This finding holds significant implications for the greenhouse design and the agricultural operations, advancing our understanding of the intricate dynamics that govern the microclimate within greenhouses, especially in arid regions. The findings of this work provide valuable insights into the impact of the roof pitch as well as the crop height on greenhouse climates and underscores the importance of precise modeling and control for successful agricultural management.

Numerical Analysis of Altered Parallel Flow Heat Exchanger with Promoted Geometry at Multifarious Baffle Prolongs

This study investigated the influence of BFFSP on the thermohydraulic performance of a SATHEC(s) using a novel computational approach. The novelty lies in the detailed exploration of the interplay between BFFSP, MFRT, and key performance parameters. Unlike prior studies, which often focus on a limited range of operating conditions, this work employs a comprehensive parametric analysis encompassing two BFFSPs (95 mm and 125 mm) and four MFRTs (0.1, 0.3, 0.5, and 0.7 kg/h). This extensive analysis provides a deeper understanding of the trade-off between the HTRFR enhancement and PDP associated with the BFFSP across a wider range of operating conditions. This investigation leverages the power of computational fluid dynamics (CFD) simulations for high-fidelity analysis. ANSYS Fluent, a widely recognized commercial CFD software package, was used as a computational platform. A three-dimensional steady-state model of HEXR geometry was established. The cold fluid was modeled as water, and the hot fluid was modeled as water. The selection of appropriate turbulence models is crucial for accurate flow simulations within the complex geometry of HEXR. This study incorporates a well-established two-equation turbulence model to effectively capture turbulent flow behavior. The governing equations for mass, momentum, and energy conservation were solved numerically within the CFD framework. Convergence criteria were meticulously established to ensure the accuracy and reliability of the simulation results. BFFs are crucial components in HEXRs as they promote fluid mixing and turbulence on the HTRFR surface, thereby enhancing HTRFR. This study explores the interplay between BFFSP and HTRFR effectiveness. It is hypothesized that a larger BFFSP (125 mm) might lead to a higher HTC owing to the increased fluid mixing. However, the potential drawbacks of the increased PDP due to the flow restriction also need to be considered. The PDP across the HEXR is a critical parameter that affects pumping costs and overall system yield. This study investigates the impact of BFFSP on the PDP. It is expected that a larger BFFSP (125 mm) will result in a higher PDP, owing to the increased resistance to fluid flow. Here, we aim to quantify the trade-off between enhanced HTRFR and increased PDP associated with different BFFSPs. The optimal design of an HEXR seeks a balance between achieving a high HTRFR rate and minimizing pressure losses. HTRPD, a metric combining both HTC and PDP, was employed to evaluate the thermohydraulic performance. We hypothesized that a specific BFFSP might offer a superior HTRPD, indicating an optimal balance between HTRFR effectiveness and PDP for the investigated HEXR geometry and operating conditions. CFD simulations were conducted using ANSYS Fluent to analyze the effects of BFFSP and MFRT on the HTC, PDP, and HTRPD. The simulations employed a commercially available HEXR geometry with water as the cold and hot fluid. The results are presented and discussed to elucidate the relationships between the BFFSP, MFRT, and key performance parameters of the HEXR. This study provides valuable insights into the influence of BFFSP on the thermohydraulic performance of HEXRs. The findings can aid in optimizing the HEXR design by identifying the BFFSP that offers the best compromise between HTRFR enhancement and PDP for specific operating conditions. The results contribute to the knowledge base of HEXR design and optimization, potentially leading to improved yield in various industrial applications. The results indicate that a larger BFFSP (125 mm) leads to higher outlet temperatures but also results in a higher PDP compared to the 95 mm design. Conversely, the 95 mm BFFSP exhibits a lower PDP but achieves a lower HTC. In terms of thermohydraulic performance, as indicated by HTRPD, the 95 mm BFFSP with the lowest MFRT (0.1 kg/h) achieved the highest value, surpassing the 125 mm design by 19.81%. This suggests that a 95 mm BFFSP offers a better trade-off between HTRFR effectiveness and pressure loss, potentially improving the overall HEXR performance.

The Lagrangian Atmospheric Radionuclide Transport Model (ARTM) – sensitivity studies and evaluation using airborne measurements of power plant emissions

Abstract. The Atmospheric Radionuclide Transport Model (ARTM) operates at the meso-γ scale and simulates the dispersion of radionuclides originating from nuclear facilities under routine operation within the planetary boundary layer. This study presents the extension and validation of this Lagrangian particle dispersion model and consists of three parts: (i) a sensitivity study that aims to assess the impact of key input parameters on the simulation results, (ii) the evaluation of the mixing properties of five different turbulence models using the well-mixed criterion, and (iii) a comparison of model results to airborne observations of carbon dioxide (CO2) emissions from a power plant and the evaluation of related uncertainties. In the sensitivity study, we analyse the effects of the stability class, roughness length, zero-plane displacement factor, and source height on the three-dimensional plume extent as well as the distance between the source and maximum concentration at the ground. The results show that the stability class is the most sensitive input parameter as expected. The five turbulence models are the default turbulence models of ARTM 2.8.0 and ARTM 3.0.0, one alternative built-in turbulence model of ARTM, and two further turbulence models implemented for this study. The well-mixed condition tests showed that all five turbulence models are able to preserve an initially well-mixed atmospheric boundary layer reasonably well. The models deviate only 6 % from the expected uniform concentration below 80 % of the mixing layer height, except for the default turbulence model of ARTM 3.0.0 with deviations of up to 18 %. CO2 observations along a flight path in the vicinity of the lignite power plant Bełchatów, Poland, measured by the Deutsches Zentrum für Luft- und Raumfahrt (DLR) Cessna aircraft during the Carbon Dioxide and Methane Mission (CoMet) campaign in 2018 allowed for evaluation of model performance for the different turbulence models under unstable boundary layer conditions. All simulated mixing ratios are of the same order of magnitude as the airborne in situ data. An extensive uncertainty analysis using probability distribution functions, statistical tests, and direct spatio-temporal comparisons of measurements and model results help to quantify the model uncertainties. With the default turbulence setups of ARTM versions 2.8.0 and 3.0.0, the plume widths are underestimated by up to 50 %, resulting in a strong overestimation of the maximum plume CO2 mixing ratios. The comparison of the three alternative turbulence models shows good agreement of the peak plume CO2 concentrations, the CO2 distribution within the plumes, and the plume width, with a 30 % deviation in the peak CO2 concentration and a less than 25 % deviation in the measured CO2 plume width. Uncertainties in the simulations may arise from the different spatial and temporal resolutions of simulations and measurements in addition to the turbulence parametrisation and boundary conditions. The results of this work may help to improve the accurate representation of real plumes in very unstable atmospheric conditions through the selection of distinct turbulence models. Further comparisons at different stability regimes are required for a final assessment of model uncertainties.

Modeling Environmental Conditions in Poultry Production: Computational Fluid Dynamics Approach

In recent years, computational fluid dynamics (CFD) has become increasingly important and has proven to be an effective method for assessing environmental conditions in poultry houses. CFD offers simplicity, efficiency, and rapidity in assessing and optimizing poultry house environments, thereby fueling greater interest in its application. This article aims to facilitate researchers in their search for relevant CFD studies in poultry housing environmental conditions by providing an in-depth review of the latest advancements in this field. It has been found that CFD has been widely employed to study and analyze various aspects of poultry house ventilation and air quality under the following five main headings: inlet and fan configuration, ventilation system design, air temperature–humidity distribution, airflow distribution, and particle matter and gas emission. The most commonly used turbulence models in poultry buildings are the standard k-ε, renormalization group (RNG) k-ε, and realizable k-ε models. Additionally, this article presents key solutions with a summary and visualization of fundamental approaches employed in addressing path planning problems within the CFD process. Furthermore, potential challenges, such as data acquisition, validation, computational resource requirements, meshing, and the selection of a proper turbulence model, are discussed, and avenues for future research (the integration of machine learning, building information modeling, and feedback control systems with CFD) are explored.

Space-dependent turbulence model aggregation using machine learning

Computational models of fluid flows based on the Reynolds-Averaged Navier–Stokes (RANS) equations supplemented with a turbulence model are the gold standard in engineering applications. A plethora of turbulence models and related variants exist, none of which are fully reliable outside the range of flow configurations for which they were calibrated. Thus, the choice of a suitable turbulence closure largely relies on subjective expert judgement and engineering know-how. In this article, we propose a data-driven methodology for combining the solutions of a set of competing turbulence models. The individual model predictions are linearly combined for providing an ensemble solution accompanied by estimates of predictive uncertainty due to the turbulence model choice. First, for a set of training flow configurations we assign high weights to component models in the regions where they perform best, and vice versa, based on a measure of distance between high-fidelity data and individual model predictions. The model weights are then mapped into a space of features, representative of the local flow physics, and regressed using a Random Forests (RF) algorithm. Finally, the RF regressor is used to infer spatial distributions of the model weights for unseen configurations. Predictions of new cases are constructed as a convex linear combination of the underlying models solutions, while the between-model variance provides information about regions of high model uncertainty. The method is demonstrated for a class of flows through the compressor cascade NACA65 V103 at Re≃3×105. The results show that the aggregated solution outperforms the accuracy of individual models for the quantity used to inform the RF regressor, and performs well for other quantities well-correlated with the previous one. The estimated uncertainty intervals are generally consistent with the target high-fidelity data. The present approach then represents a viable methodology for a more objective selection and combination of alternative turbulence models in configurations of interest for engineering practice.

The NOx-O3 photochemical reactive air pollutant dispersion around an isolated building—the role of turbulence model and building aspect ratio

The NOx-O3 photochemical reactive air pollutant dispersion around an isolated building bears significant scientific and engineering implications. The present work extends the investigation to the role of turbulence models and building aspect ratio, providing valuable insights for future numerical investigations and building complex design. Validated against wind tunnel experiments, a serial Computational Fluid Dynamics (CFD) investigation was conducted with physiochemical coupling, including one large eddy simulation with near-wall resolution (LES-NWR) and three Reynolds-averaged Navier-Stokes (RANS) viscosity models (i.e., standard k-ε model (STK), renormalization group k-ε model (RNG), realizable k-ε model (RLZ)). The numerical models were assessed regarding the predictive capability of the mean pollutant concentration and velocity fields. Results show that the areas of high NO concentration are generally indifferent to the selection of turbulence models. Elsewhere, the RLZ provides the most comparable results to the LES-NWR, whereas the RNG and STK underestimate the reverse flow in the building wake and produce subpar predictions at the roof. The RNG also yields the weakest prediction by overestimating the lateral separation bubbles’ influence. Furthermore, changing the aspect ratio has negligible effects on the stream and spanwise dispersion of the highly concentrated pollutant. However, the building width plays a more decisive role in constraining the streamwise dispersion than the building height. Doubling the building length also slows down the shrinkage of recirculation, leading to a steep deduction in the streamwise dispersion along the building height.

Research on Rotation/Curvature Correction Method of SA Turbulence Model for Numerical Simulation of Axial Compressor

The strong rotation effect exists in the flow of compressors, but it is rarely considered in the common turbulence models used in numerical simulation. In addition, when the widely used turbulence model is applied to the numerical simulation of compressor flow, it often needs to be modified. In order to evaluate the applicability of various turbulence model modification methods in axial compressor flow simulation, and explore suitable modification methods. Based on the numerical simulation software ASPAC for axial flow compressor developed by our research group, three turbulence model rotation/curvature correction methods were implemented based on SA turbulence model and applied to the flow simulation of Rotor 37. The results show that the modified models mainly affect the flow separation of the rotor suction surface. Specifically, the SA-Helicity model improves the prediction accuracy of the separation flow in the compressor. The total temperature and pressure calculated by SA-R and SA-RC models are on the small side. In this study, the applicability of rotation/curvature correction method of various SA turbulence models in compressor flow simulation is evaluated in detail based on transonic compressor, which provides a basis for the selection of turbulence models and the research of turbulence model and correction methods adapted to compressor simulations.

Numerical Validation of Low Reynolds Number Airfoil for Uav

Low Reynolds flow continues to get researchers attention for its relevance in a number of areas including the flight regimes of Micro Air Vehicle (MAV). The Laminar Separation Bubble (LSB) which is largely responsible for the non-linear aerodynamic characteristics have been studied both numerically and experimentally. In this work, a high fidelity computation was carried out to study LSB as well as the dependence of aerodynamic characteristics on a symmetrical thick airfoil at low Reynolds numbers. Flow structure in the bubble is clearly brought out with the appropriate selection of turbulence model in the solver. Also, the extent of LSB was well predicted by transition SST turbulence model in the solver. A novel approach has been made to obtain the location and length of LSB using the values of wall shear stress and the results are encouraging. Also, a comparative analysis of flow transition and surface pressure distribution was made by four different turbulence models and the results are discussed.

Numerical Study of the Flow Characteristics of Downburst-like Wind over the 3D Hill Using Different Turbulence Models

With the rapid development of computational fluid dynamics (CFD) technology, it has been widely used to study the wind field characteristics of downbursts in mountainous areas. However, there is little guidance on the selection of different turbulence models for simulating downburst wind fields over hills using CFD, and few comparative studies have been conducted. This paper used nine turbulence models to simulate the wind field of a downburst over a 3D quadratic ideal hill. The simulated values of average and transient winds were compared with wind tunnel test data, and the flow characteristics at different moments under a downburst were analyzed. The flow characteristics in the wake region of the downburst over the hill are also quantitatively analyzed using the proper orthogonal decomposition (POD) method. The results show that approximately 85% of the results from the LES and REA models fall within a 30% error range, so the large eddy simulation (LES) model and the realizable k-ε model (REA) are more accurate in simulating the mean wind field, and the transient wind field simulated by the LES model is also in good agreement with the experimental data. In addition, this paper reveals the evolution mechanism of the transient wind field structure over a hill model under a downburst and finds that the first-order mode obtained by POD may be related to the acceleration effect on the hilltop.

Validation of computational fluid dynamics simulations for determining pressure loss coefficients of ventilation components

Ventilation systems include a variety of components for which necessary pressure loss data is often unavailable. Computational fluid dynamics simulations could substitute for expensive measurements, but validation simulations with suitable data are crucial to assess model uncertainties. Existing CFD validation studies either did not focus specifically on pressure losses, only covered few components, or did not include recent developments in turbulence modelling. In the present work, 33 bends, 4 gates and 2 tees were simulated using a consistent approach. Computational fluid dynamics simulations were validated with published data: rectangular high-edge and wide-edge bends from the experimental dataset of Sprenger, gates and diverging tees from the SMACMA guide. The considered flows cover important basic flow phenomena: deflection, splitting and flow separation. The 39 components were simulated with three turbulence models at 14 Reynolds numbers. The simulations predicted pressure loss coefficients accurately for various components. Cases with strong flow separation regions were most challenging. The model prediction uncertainty was assessed by carrying out simulations with three selected turbulence models. As in the experimental data from Sprenger, the simulations showed a distinct dependence of pressure loss coefficients on the Reynolds number for bends. In contrast, for abrupt deflections and flow separation at sharp edges, the Reynolds number dependency was minor. Technical pressure loss data of ductwork components is needed for the dimensioning, optimisation, and energy assessment of ventilation systems. The present validation study assesses the present state of the art of CFD simulations to determine pressure loss coefficients and the resulting prediction uncertainties.

Numerical Investigations on Effect of Inflow Parameters on Development of Secondary Flow Field for Linear Low-Pressure Turbine Cascade

Abstract Endwall flows contribute the most crucial role in loss generation for axial flow turbine and compressor blades. These losses lead to modifying the blade loading and overall performance in terms of stable operating range. The present study aimed to determine the endwall flow streams in a low-speed low-pressure linear turbine cascade vane using a numerical approach. The study includes two sections. The first section includes an attempt to understand different secondary flow streams available at the endwall. The location of the horseshoe vortex and subsequent vortex patterns are identified in the section. The selection of a suitable turbulence model among shear stress transport (SST) k–ω and SST γ–θ to identify endwall flow streams is studied prior to the section. The steady-state numerical study is performed using Reynolds Averaged Navier–Stokes equations closed by the SST γ–θ turbulence model. The computational results are validated with experimental results available in the literature and are found to be in good agreement. The study is extended for different inflow conditions in a later section. The second section includes the effect of flow incidence and turbulence intensity on the endwall secondary flow field. Four different inflow incidences are considered for the study. The inlet turbulence intensities are varied by 1% and 10% for each case. The results revealed different secondary flow patterns at an endwall and found the change in behavior with inflow conditions. SST γ–θ turbulence model with lower turbulence intensity is more suitable to identify such flow behavior.

Assessment of turbulent heat flux models for URANS simulations of turbulent buoyant flows in ROCOM tests

Turbulent mixing in buoyant flows is an essential mechanism involved in many scenarios related to nuclear safety in nuclear power plants. Comprehensive understanding and accurate predictions of turbulent buoyant flows in the reactor are of crucial importance, due to the function of mitigating the potential detrimental consequences during postulated accidents. The present study uses URANS methodology to investigate the buoyancy-influenced flows in the reactor pressure vessel under the main steam line break accident scenarios. With a particular focus on the influence of turbulent heat flux closure models, various combinations of two turbulence models and three turbulent heat flux models are utilized for the numerical simulations of three ROCOM tests which have different characteristic features in terms of the flow rate and fluid density difference between loops. The simulation results are compared with experimental measurements of the so-called mixing scalar in the downcomer and at the core inlet. The study shows that the anisotropic turbulent heat flux models are able to improve the accuracy of the predictions under conditions of strong buoyancy whilst in the weak buoyancy case, a major role is played by the selected turbulence models with essentially a negligible influence of the turbulent heat flux closure models.

Mesh and turbulence model sensitivity analyses of computational fluid dynamic simulations of a 37M CANDU fuel bundle

Mesh and turbulence model sensitivity analyses have been performed on computational fluid dynamics simulations executed with Hydra and ANSYS Fluent for a single CANadian Deuterium Uranium (CANDU) 37M nuclear fuel bundle placed within a standard pressure tube. The goal of this work was to perform a methodical analysis to objectively determine an appropriate mesh and to gauge the sensitivity of different turbulence models for CANDU subchannel flow under isothermal conditions. The boundary conditions and material properties are representative of normal operating conditions in a high-powered channel of the Darlington Nuclear Generating Station. Four meshes were generated with ANSYS Workbench Meshing, ranging from 22 to 84 million cells, and analyzed here to determine an appropriate level of mesh resolution and quality. Five turbulence models were compared in the turbulence model sensitivity analysis: standard k−ε, RNG k−ε, realizable k−ε, SST k−ω, and the Reynolds Stress Model. The intent of this work was to gain confidence in mesh generation and turbulence model selection of a single bundle to inform the decision making of subsequent investigations of an entire fuel channel containing a string of twelve bundles.

Impact of Turbulence Models and Objective Function on Three-Dimensional Robust Aerodynamic Optimization

The objective of this paper was to investigate the impact of two commonly used turbulence models in Reynolds-averaged Navier–Stokes simulations (Spalart–Allmaras and Menter’s shear stress transport models) on the three-dimensional optimum wing design obtained with the gradient-based deterministic and robust aerodynamic shape optimization in transonic, viscous, turbulent flow. In particular, the main contribution of this study to aerodynamic design area is to evaluate the impact of turbulence models and different weight distributions in the multi-objective function (equal, mean biased, and variance biased) on the computational cost, optimal shape, and its performance under Mach-number uncertainty obtained with robust optimization. The results of the study show that the effect of weight distribution in the objective function is more significant than the effect of turbulence model on the final shape obtained with robust design at lower off-design Mach numbers. Robust design tends to mitigate the impact of the turbulence model selection on the optimum shape and performance over the uncertain Mach-number range, whereas the choice of the turbulence model becomes significant at off-design conditions for the optimal shapes obtained with deterministic design. This study also demonstrates the effectiveness of using stochastic expansions in robust aerodynamic shape optimization of three-dimensional wings.

CFD-PBM Coupled modeling of bubble size distribution in a swirling-flow nanobubble generator

Swirling-flow nanobubble generator is an efficient hydrodynamic cavitation method that can continuously produce enormous quantities of bulk nanobubbles. However, the development of hydrodynamic models of nanobubble generation remains challenging and is rarely found in the literature due to the associated modeling complexity. In this work, a hydrodynamic model was developed to predict bubble size distribution in a swirling-flow type nanobubble generator using a combination of computational fluid dynamics (CFD) and population balance method (PBM). The proposed model was evaluated by considering several combinations of bubble coalescence, breakage, and turbulence models. The results show that the combination of the turbulence coalescence and Luo breakage models predicted better than any other model combination. The selection of appropriate turbulence models could improve the modeling accuracy. The standard k-Ω model provided better predictions than other turbulence models for high flow rates, while the standard k-ε model was more appropriate for low flow rates. The bubble number density was successfully predicted for a 30 min generation time. The turbulence dissipation rate influenced the bubble number density and mass transfer, and the results of simulation considering this relation corresponded to the experimental results. Therefore, the coupled CFD-PBM model can aid in the design of nanobubble generators using virtual prototypes and reduce the development costs required for broader applications.

Influence of turbulence models on the dynamic response of a semi-submersible floating offshore wind platform

With the aim of evaluating the effects of the selection of the wind turbulence model on the dynamic response of a semi-submersible floater supporting the DTU 10 MW RWT, we ran aero-hydro-servo-elastic simulations employing the OASIS code developed at IHCantabria. For each of the 4 sea states selected, apart from the reference case with only wave loads, we analysed 30 different realizations with coupled wind and wave loads for each of the 7 full-field turbulent winds generated by the turbulence simulator TurbSim: Kaimal and von Kármán spectral models with three different turbulence classes each and the API turbulence model.From the resulting platform motions and mooring line dynamics, it can be concluded that the selection of the wind turbulence model is not trivial. At U0=5.83 m/s, the obtained results show a high dependence on the turbulence class. However, as the wind speed increases and the wind turbine achieves the rated speed, the impact of the turbulence intensity is drastically reduced, and the design tension is dominated by the thrust force and thus by the vertical wind speed profile. The highest design tension of the windward mooring lines is obtained with the API model at U0=8.75 m/s (at least 357 Tm).

An improved air entrainment model for stepped spillways

This work considers the application of the air entrainment model developed in [P. Lopes et al. Int. J. Nonlin. Sci. Num., vol. 18, pp. 559-574, 2017] to simulation of flows in stepped spillways. Four Froude numbers are considered for the flow, with parameters selected to match available experimental data. An extensive simulation campaign led to the identification of several deficiencies in the model, most importantly, its strong grid dependence. An improvement to the interface detection algorithm used in the model is proposed, and simulations reveal improved robustness with respect to the grid density. Furthermore, two criteria for predicting the inception point of air entrainment are tested, based on energy balance and boundary layer state, respectively. The boundary layer-based approach is recommended due to superior accuracy and robustness with respect to turbulence model selection.

A review on Pitot tube icing in aeronautics: Research- design and characterization – future trends

The correct measurement of airspeed is a crucial task since a lot of algorithms for the autopilot are based on it and even human pilots depend completely on this reading to take corrective and non-corrective actions to control the aircraft. This work presents a detailed review concerning an important aspect of aeronautical safety, i.e., Pitot tube (PT) icing. The topics covered include first the risks present in flight, relating meteorological conditions, and antecedents of air accidents related to the icing of the PT. Then, the principles of operation of the PT, its conventional design, how such design is currently regulated, as well as unique guidance for experimentation of PT. Also discussed are the principal modelling considerations for the numerical analysis of PTs including the proper selection of geometry, governing equations, turbulence models, and boundary conditions for the simulation of different flight circumstances. This guidance for both experimental and numerical analysis is enriched with a well-selected state the art research. Finally, a summary of the most recent advances and future trends is offered. The outcomes of this review exhibit several interesting ideas showing promising results, such as microwave heating of the pitot surroundings, phase change materials that delay ice formation, and even mechanical internal arrangement of bulkheads to prevent the ice to travel through the throat of the probe. The combined research efforts on novel safety measures and new designs for aeronautical PT represent a remarkable potential to improve flight security.

Improved natural convection heat transfer correlations for reactor cavity cooling systems of high-temperature gas-cooled reactors: From computational fluid dynamics to Pronghorn

The reactor cavity cooling system (RCCS) is a common reactor safety system in high-temperature gas-cooled Reactors (HTGR) that removes heat from the reactor pressure vessel (RPV) by radiation (∼80%) and natural convection (∼20%). For the simulation of accident scenarios of HTGRs, intermediate fidelity and system codes models must be employed to limit the models’ execution time. While an accurate quantification of the radiative heat transfer is available in these models, the quantification of natural convection must rely on correlations of questionable accuracy for the Nusselt number. Commonly used correlations are based in experiments performed at low Rayleigh numbers and/or using isothermal walls in simplified geometries. This work improves on the accuracy of natural convection heat transfer correlations to support HTGR designs.These correlations include both local and average Nusselt numbers as a function of the global Rayleigh number, the local Rayleigh number, and the temperature profile at the hot wall of the RCCS. In the absence of dedicated experiments and the difficulty of performing high-fidelity simulations at realistic Rayleigh numbers, the data to fit the correlations are generated with computational fluid dynamics (CFD) using Reynolds Averaged Navier-Stokes (RANS) models. First, a careful selection of the RANS turbulence model is performed by comparing the results obtained with different RANS turbulence models against high-fidelity simulations of natural convection at Ra 1×1011 in a rectangular cavity. Next, the selected model is used to perform simulations of an HTGR cavity at different high Rayleigh numbers ∈[6.1×1011,2.9×1013] to encompass several HTGR designs, assuming an isothermal RPV wall. The results obtained are used to fit a correlation for the average and space-varying Nusselt number as a function of the global and local Rayleigh numbers via a sparsity-promoting, least-squares method. The selected RANS model is then used to perform simulations of a PBMR-400 (Pebble Bed Modular Reactor) HTGR cavity with the temperature profiles at the RPV wall obtained during a PLOFC (Pressurized loss of forced cooling) transient. We use the results obtained to fit a temperature-dependent correction to the space-varying Nusselt number with the sparsity-promoting, least-squares method. The results obtained in this work enable system-level codes, such as Pronghorn, to perform higher-fidelity simulations of the heat exchange process in the RCCS while still maintaining a low computational cost.

Selection of turbulence model in ventilation modeling for blind stopes

The authors present the results of mathematical modeling of working area ventilation in a blond stope using the methods of computational aerodynamic and different turbulence models. The analytical model is verified by comparing the model and in situ data.