scholarly journals Simulation of turbulent effective wakes for propellers in off-design conditions by a correction factor approach

2021 ◽  
Author(s):  
Antonio Sánchez-Caja ◽  
Jussi Martio ◽  
Ville M. Viitanen ◽  
Timo Siikonen
Keyword(s):  
Viscous Flow ◽  
Potential Flow ◽  
Computational Cost ◽  
Propeller Shaft ◽  
Wide Range ◽  
Flow Phenomena ◽  
Yaw Angle ◽  
Effective Wake ◽  
Pod Propulsor ◽  
Inclined Flow

AbstractThis paper presents a procedure for the estimation of propeller effective wakes in oblique flows. It shows how a recently developed method for controlling coupling errors can be applied to analyze propellers operating in off-design conditions. The approach allows the use of fast potential flow methods for the representation of the propeller in the context of viscous flow solvers and works accurately for a wide range of advance numbers and incidence angles with a minimum computational cost. The new method makes it possible to disclose flow phenomena on the effective wake that were hidden in conventional approaches of effective wake simulation. Different application cases are analyzed, such as a propeller-shaft configuration in inclined flow, a pod propulsor in an oblique inflow, and a ship hull advancing at a yaw angle. A dipole-like distortion on the effective wake is unmasked for a uniform flow incident to a propeller mounted on an inclined shaft. The flow component perpendicular to the axis is found to be responsible for the distortion. The effect of the direction of propeller rotation on the effective wake is illustrated for a single-shaft ship moving at a yaw angle. In particular, keel vortices are either attracted to or repelled from the propeller disk depending on the sign of the yaw angle or alternatively on that of the propeller rotation.

A Robust Implementation of a Reynolds Stress Model for Turbomachinery Applications in a Coupled Solver Environment

2020 ◽  
Author(s):  
David Roos Launchbury ◽  
Luca Mangani ◽  
Ernesto Casartelli ◽  
Francesco Del Citto
Keyword(s):  
Reynolds Stress ◽  
Turbulence Modeling ◽  
Computational Cost ◽  
Reynolds Stress Model ◽  
Tip Vortex ◽  
Stability And Convergence ◽  
Stress Model ◽  
Robust Implementation ◽  
Flow Phenomena ◽  
The Stability

Abstract In the industrial simulation of flow phenomena, turbulence modeling is of prime importance. Due to their low computational cost, Reynolds-averaged methods (RANS) are predominantly used for this purpose. However, eddy viscosity RANS models are often unable to adequately capture important flow physics, specifically when strongly anisotropic turbulence and vortex structures are present. In such cases the more costly 7-equation Reynolds stress models often lead to significantly better results. Unfortunately, these models are not widely used in the industry. The reason for this is not mainly the increased computational cost, but the stability and convergence issues such models usually exhibit. In this paper we present a robust implementation of a Reynolds stress model that is solved in a coupled manner, increasing stability and convergence speed significantly compared to segregated implementations. In addition, the decoupling of the velocity and Reynolds stress fields is addressed for the coupled equation formulation. A special wall function is presented that conserves the anisotropic properties of the model near the walls on coarser meshes. The presented Reynolds stress model is validated on a series of semi-academic test cases and then applied to two industrially relevant situations, namely the tip vortex of a NACA0012 profile and the Aachen Radiver radial compressor case.

A Hybrid Viscous/Potential Flow Method for the Prediction of the Performance of Podded and Ducted Propellers

2009 ◽  
Author(s):  
Spyros A. Kinnas ◽  
Shu-Hao Chang ◽  
Yi-Hsiang Yu ◽  
Lei He
Keyword(s):  
Viscous Flow ◽  
Lattice Method ◽  
Viscous Potential Flow ◽  
Flow Solver ◽  
Vortex Lattice Method ◽  
Ducted Propeller ◽  
Hybrid Numerical Method ◽  
Convergence Study ◽  
Effective Wake ◽  
Ducted Propellers

This paper presents the analysis of the performance for podded and ducted propellers using a hybrid numerical method, which couples a vortex lattice method (MPUF-3A) for the unsteady analysis of propellers and a viscous flow solver (NS-3X or FLUENT) for the prediction of the viscous flow around propulsors and the drag force on the pod and duct surfaces. The time averaged propeller force distributions are considered as source terms (body force) in the momentum equations of NS-3X and FLUENT. The effects of viscosity on the effective wake and on the performance of the propeller blade, as well as on the predicted pod and duct forces, are assessed. The convergence study of circulation distributions with number of lattices is reported in the ducted propeller case. Finally, the prediction of the performance for podded propellers (both single pull-type and twin-type) and ducted propellers from the present method is validated against existing experimental data.

scholarly journals The Open Global Glacier Model (OGGM) v1.0

2018 ◽  
Author(s):  
Fabien Maussion ◽  
Anton Butenko ◽  
Julia Eis ◽  
Kévin Fourteau ◽  
Alexander H. Jarosch ◽  
...  
Keyword(s):  
Mass Balance ◽  
Open Source ◽  
Sea Level ◽  
Computational Cost ◽  
Balance Model ◽  
Climate Data ◽  
Estimation Model ◽  
Model Framework ◽  
Validation Data ◽  
Wide Range

Abstract. Despite of their importance for sea-level rise, seasonal water availability, and as source of geohazards, mountain glaciers are one of the few remaining sub-systems of the global climate system for which no globally applicable, open source, community-driven model exists. Here we present the Open Global Glacier Model (OGGM, http://www.oggm.org), developed to provide a modular and open source numerical model framework for simulating past and future change of any glacier in the world. The modelling chain comprises data downloading tools (glacier outlines, topography, climate, validation data), a preprocessing module, a mass-balance model, a distributed ice thickness estimation model, and an ice flow model. The monthly mass-balance is obtained from gridded climate data and a temperature index melt model. To our knowledge, OGGM is the first global model explicitly simulating glacier dynamics: the model relies on the shallow ice approximation to compute the depth-integrated flux of ice along multiple connected flowlines. In this paper, we describe and illustrate each processing step by applying the model to a selection of glaciers before running global simulations under idealized climate forcings. Even without an in-depth calibration, the model shows a very realistic behaviour. We are able to reproduce earlier estimates of global glacier volume by varying the ice dynamical parameters within a range of plausible values. At the same time, the increased complexity of OGGM compared to other prevalent global glacier models comes at a reasonable computational cost: several dozens of glaciers can be simulated on a personal computer, while global simulations realized in a supercomputing environment take up to a few hours per century. Thanks to the modular framework, modules of various complexity can be added to the codebase, allowing to run new kinds of model intercomparisons in a controlled environment. Future developments will add new physical processes to the model as well as tools to calibrate the model in a more comprehensive way. OGGM spans a wide range of applications, from ice-climate interaction studies at millenial time scales to estimates of the contribution of glaciers to past and future sea-level change. It has the potential to become a self-sustained, community driven model for global and regional glacier evolution.

scholarly journals A Mobile Sensing System for UrbanPM2.5Monitoring with Adaptive Resolution

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Hongjie Guo ◽  
Guojun Dai ◽  
Jin Fan ◽  
Yifan Wu ◽  
Fangyao Shen ◽  
...  
Keyword(s):  
Air Quality ◽  
Meteorological Data ◽  
Computational Cost ◽  
Estimation Method ◽  
Mobile Sensing ◽  
Prototype System ◽  
Adaptive Grids ◽  
Sensing System ◽  
Adaptive Resolution ◽  
Wide Range

This paper develops a mobile sensing system, the first system used in adaptive resolution urban air quality monitoring. In this system, we employ several taxis as sensor carries to collect originalPM2.5data and collect a variety of datasets, including meteorological data, traffic status data, and geographical data in the city. This paper also presents a novel method AG-PCEM (Adaptive Grid-Probabilistic Concentration Estimation Method) to infer thePM2.5concentration for undetected grids using dynamic adaptive grids. We gradually collect the measurements throughout a year using a prototype system in Xiasha District of Hangzhou City, China. Experimental data has verified that the proposed system can achieve good performance in terms of computational cost and accuracy. The computational cost of AG-PCEM is reduced by about 40.2% compared with a static grid method PCEM under the condition of reaching the close accuracy, and the accuracy of AG-PCEM is far superior as widely used artificial neural network (ANN) and Gaussian process (GP), enhanced by 38.8% and 14.6%, respectively. The system can be expanded to wide-range air quality monitor by adjusting the initial grid resolution, and our findings can tell citizens actual air quality and help official management find pollution sources.

scholarly journals ORCHIDEE-ROUTING: A new river routing scheme using a high resolution hydrological database

2018 ◽  
Author(s):  
Trung Nguyen-Quang ◽  
Jan Polcher ◽  
Agnès Ducharne ◽  
Thomas Arsouze ◽  
Xudong Zhou ◽  
...  
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
River Flow ◽  
Anthropogenic Impacts ◽  
Computational Cost ◽  
Land Surface Model ◽  
Surface Model ◽  
Routing Scheme ◽  
Wide Range ◽  
River Routing

Abstract. This study presents a revised river routing scheme (RRS) for the Organising Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) land surface model. The revision is carried out to benefit from the high resolution topography provided the Hydrological data and maps based on SHuttle Elevation Derivatives at multiple Scales (HydroSHEDS), processed to a resolution of approximately 1 kilometer. The RRS scheme of the ORCHIDEE uses a unit-to-unit routing concept which allows to preserve as much of the hydrological information of the HydroSHEDS as the user requires. The evaluation focuses on 12 rivers of contrasted size and climate which contribute freshwater to the Mediterranean Sea. First, the numerical aspect of the new RRS is investigated, to identify the practical configuration offering the best trade-off between computational cost and simulation quality for ensuing validations. Second, the performance of the revised scheme is evaluated against observations at both monthly and daily timescales. The new RRS captures satisfactorily the seasonal variability of river discharges, although important biases come from the water budget simulated by the ORCHIDEE model. The results highlight that realistic streamflow simulations require accurate precipitation forcing data and a precise river catchment description over a wide range of scales, as permitted by the new RRS. Detailed analyses at the daily timescale show promising performances of this high resolution RRS for replicating river flow variation at various frequencies. Eventually, this RRS is well adapted for further developments in the ORCHIDEE land surface model to assess anthropogenic impacts on river processes (e.g. damming for irrigation operation).

scholarly journals Local flow assessment of the Japan Bulk Carrier using different turbulence models

2021 ◽  
Vol 1182 (1) ◽  
pp. 012004
Author(s):  
A Bekhit ◽  
F Popescu
Keyword(s):  
Experimental Data ◽  
Viscous Flow ◽  
Turbulence Models ◽  
Wake Flow ◽  
Design Stage ◽  
Bulk Carrier ◽  
Local Flow ◽  
Special Investigation ◽  
Ship Wake ◽  
Effective Wake

Abstract Ship resistance and powering represent the most important aspects in the initial design stage of the ship. Based on their estimation the basic milestone for selecting the main engine and the propulsion system is established. The majority of ships in the international fleet nowadays rely on the screw propeller working in the wake zone behind the ship. The wake flow of the ship has a direct impact on the propeller performance and the propulsion efficiency. Accurate prediction of the nominal and effective wake is crucially important to provide a proper understanding of the flow where the propeller will perform. From this point of view, the wake flow of the Capesize Japan Bulk Carrier (JBC) is assessed using a viscous flow Computational Fluid Dynamics (CFD) method. Numerical simulations are performed to predict the nominal and effective wake of the ship by making use of the viscous flow solver ISIS_CFD of the FINETM/Marine software provided by NUMECA. The solver is based on the finite volume method to build the spatial discretization of the transport equation to resolve the Reynolds-Averaged Navier-Stokes (RANS) equations. Closure to turbulence is achieved using different turbulence models in order to investigate their accuracy in predicting the complex wake flow of the ship. Two-phase flow approach is used to model the air-water interface where the Volume of Fluid method is implemented to capture the free-surface. The results for both nominal and effective wake are assessed against the experimental data provided by the National Maritime Research Institute (NMRI) and Yokohama National University in Japan that were presented in the seventh Workshop on CFD in ship hydrodynamics (Tokyo2015). The results validation showed a reasonable agreement compared to the experimental data for both nominal and effective wake. As it was expected, some turbulence models showed to be more accurate in predicting ship wake, especially the Shear Stress Transport (K-ω SST) and Explicit Algebraic Reynolds Stress (EASM) Models. A special investigation of the flow vortices is also taken into consideration.

scholarly journals A new entropy-variable-based discretization method for minimum entropy moment approximations of linear kinetic equations

2021 ◽  
Author(s):  
Tobias Leibner ◽  
Mario Ohlberger
Keyword(s):  
Optimization Problems ◽  
Hessian Matrix ◽  
Computational Cost ◽  
Kinetic Equations ◽  
New Method ◽  
Minimum Entropy ◽  
Reduced Basis ◽  
Simple Task ◽  
Wide Range ◽  
The Moment

In this contribution we derive and analyze a new numerical method for kinetic equations based on a variable transformation of the moment approximation. Classical minimum-entropy moment closures are a class of reduced models for kinetic equations that conserve many of the fundamental physical properties of solutions. However, their practical use is limited by their high computational cost, as an optimization problem has to be solved for every cell in the space-time grid. In addition, implementation of numerical solvers for these models is hampered by the fact that the optimization problems are only well-defined if the moment vectors stay within the realizable set. For the same reason, further reducing these models by, e.g., reduced-basis methods is not a simple task. Our new method overcomes these disadvantages of classical approaches. The transformation is performed on the semi-discretized level which makes them applicable to a wide range of kinetic schemes and replaces the nonlinear optimization problems by inversion of the positive-definite Hessian matrix. As a result, the new scheme gets rid of the realizability-related problems. Moreover, a discrete entropy law can be enforced by modifying the time stepping scheme. Our numerical experiments demonstrate that our new method is often several times faster than the standard optimization-based scheme.

scholarly journals A hierarchical Bayesian framework for force field selection in molecular dynamics simulations

2016 ◽  
Vol 374 (2060) ◽  
pp. 20150032 ◽  
Author(s):  
S. Wu ◽  
P. Angelikopoulos ◽  
C. Papadimitriou ◽  
R. Moser ◽  
P. Koumoutsakos
Keyword(s):  
Experimental Data ◽  
Molecular Dynamics ◽  
Force Field ◽  
Computational Cost ◽  
Md Simulations ◽  
Bayesian Framework ◽  
Underlying Structure ◽  
Hierarchical Bayesian ◽  
Wide Range ◽  
Selection Of

We present a hierarchical Bayesian framework for the selection of force fields in molecular dynamics (MD) simulations. The framework associates the variability of the optimal parameters of the MD potentials under different environmental conditions with the corresponding variability in experimental data. The high computational cost associated with the hierarchical Bayesian framework is reduced by orders of magnitude through a parallelized Transitional Markov Chain Monte Carlo method combined with the Laplace Asymptotic Approximation. The suitability of the hierarchical approach is demonstrated by performing MD simulations with prescribed parameters to obtain data for transport coefficients under different conditions, which are then used to infer and evaluate the parameters of the MD model. We demonstrate the selection of MD models based on experimental data and verify that the hierarchical model can accurately quantify the uncertainty across experiments; improve the posterior probability density function estimation of the parameters, thus, improve predictions on future experiments; identify the most plausible force field to describe the underlying structure of a given dataset. The framework and associated software are applicable to a wide range of nanoscale simulations associated with experimental data with a hierarchical structure.

Highly Efficient and Accurate Gas-Alkane Binary Mixture Interfacial Tension Equations for a Broad Range of Temperatures, Pressures, and Compositions

SPE Journal ◽  
2021 ◽  
pp. 1-19
Author(s):  
Yingnan Wang ◽  
Nadia Shardt ◽  
Janet A. W. Elliott ◽  
Zhehui Jin
Keyword(s):  
Experimental Data ◽  
Binary Mixture ◽  
Interfacial Tension ◽  
Binary Mixtures ◽  
Oil Recovery ◽  
Computational Cost ◽  
Petroleum Engineering ◽  
Pure Species ◽  
Highly Efficient ◽  
Wide Range

Summary Gas-alkane interfacial tension (IFT) is an important parameter in the enhanced oil recovery (EOR) process. Thus, it is imperative to obtain an accurate gas-alkane mixture IFT for both chemical and petroleum engineering applications. Various empirical correlations have been developed in the past several decades. Although these models are often easy to implement, their accuracy is inconsistent over a wide range of temperatures, pressures, and compositions. Although statistical mechanics-based models and molecular simulations can accurately predict gas-alkane IFT, they usually come with an extensive computational cost. The Shardt-Elliott (SE) model is a highly accurate IFT model that for subcritical fluids is analytic in terms of temperature T and composition x. In applications, it is desirable to obtain IFT in terms of temperature T and pressure P, which requires time-consuming flash calculations, and for mixtures that contain a gas component greater than its pure species critical point, additional critical composition calculations are required. In this work, the SE model is combined with a machine learning (ML) approach to obtain highly efficient and highly accurate gas-alkane binary mixture IFT equations directly in terms of temperature, pressure, and alkane molar weights. The SE model is used to build an IFT database (more than 36,000 points) for ML training to obtain IFT equations. The ML-based IFT equations are evaluated in comparison with the available experimental data (888 points) and with the SE model, as well as with the less accurate parachor model. Overall, the ML-based IFT equations show excellent agreement with experimental data for gas-alkane binary mixtures over a wide range of T and P, and they outperform the widely used parachor model. The developed highly efficient and highly accurate IFT functions can serve as a basis for modeling gas-alkane binary mixtures for a broad range of T, P, and x.

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