Convective Overshooting in Extreme Horizontal-branch Stars Using MESA with the k-omega Model*

To explore overshoot mixing beyond the convective core in core helium-burning stars, we use the k−ω model, which is incorporated into the Modules of Experiments in Stellar Astrophysics to investigate overshoot mixing in the evolution of subdwarf B (sdB) stars. Our results show that the development of the convective core can be divided into three stages. The mass of the convective core increases monotonically when the radiative temperature gradient, ∇rad, monotonically decreases outwardly, and overshoot mixing presents an exponential decay similar to Herwig. The splitting of the convective core occurs repeatedly when the minimum value of ∇rad near the convective boundary is smaller than the adiabatic temperature gradient, ∇ad. The mass at the outer boundary of the convective shell M sc can exceed 0.2 M ⊙ after the central helium abundance drops to about Y c ≈ 0.45. It is close to the convective core masses derived by asteroseismology for younger models (0.22 to ∼0.28 M ⊙). In the final stage, “core breathing pulses” occurred two or three times. Helium was injected into the convective core by overshoot mixing and increased the lifetime of sdB stars. The mass of the mixed region M mixed can rise to 0.303 M ⊙ by the end. The oxygen content in the central core of our g-mode sdB models is about 80% by mass. The high amounts of oxygen deduced from asteroseismology may be evidence supporting the existence of core breathing pulses.

Creep Parameters Determination by Omega Model to Norton Bailey Law by Regression Analysis for Austenitic Steel SS-304

In the material’s creep failure analysis, the difficulty of assessing the applied thermo-mechanical boundary conditions makes it critically important. Numerous creep laws have been established over the years to predict the creep deformation, damage evolution and rupture of the materials subjected to creep phenomena. The omega model developed by the American Petroleum Institute and Material Properties Council is one of the most commonly used creep material models for numerical analysis over the years. It is good in defining the fitness of mechanical equipment for service engineering evaluation to ensure the reliable service life of the equipment. The Omega model, however, is not readily accessible and specifically incorporated for creep evaluation in FEA software codes and creep data is always scarce for the complete analysis. Therefore, extrapolation of creep behavior was performed by fitting various types of creep models with a limited amount of creep data and then simulating them, beyond the available data points. In conjunction with the Norton Bailey model, based on API-579/ASME FFS-1 standards, a curve fitting technique was employed called regression analysis. From the MPC project omega model, different creep strain rates were obtained based on material, stress and temperature-dependent data. In addition, as the strain rates increased exponentially with the increase in stresses, regression analysis was used for predicting creep parameters, that can curve fit the data into the embedded Norton Bailey model. The uncertainties in extrapolations and material constants has highlighted to necessitate conservative safety factors for design requirement. In this case study, FEA creep assessment was performed on the material SS-304 dog bone specimen, considered as a material coupon to predict time-dependent plastic deformation along with creep behavior at elevated temperatures and under constant stresses. The results indicated that the specimen underwent secondary creep deformation for most of the period.

Towards a Computational Fluid Dynamics-Based Fuzzy Logic Controller of the Optimum Windcatcher Internal Design for Efficient Natural Ventilation in Buildings

Recently, increased attention has been given to the coupling of computational fluid dynamics (CFD) with the fuzzy logic control system for obtaining the optimum prediction of many complex engineering problems. The data provided to the fuzzy system can be obtained from the accurate computational fluid dynamics of such engineering problems. Windcatcher performance to achieve thermal comfort conditions in buildings, especially in hot climate regions, is considered as one such complex problem. Windcatchers can be used as natural ventilation and passive cooling systems in arid and windy regions in Saudi Arabia. Such systems can be considered as the optimum solution for energy-saving and obtaining thermal comfort in residential buildings in such regions. In the present paper, three-dimensional numerical simulations for a newly-developed windcatcher model have been performed using ANSYS FLUENT-14 software. The adopted numerical algorithm is first validated against previous experimental measurements for pressure coefficient distribution. Different turbulence models have been firstly applied in the numerical simulations, namely, standard k-epsilon model (1st and 2nd order), standard Wilcox k-omega model (1st and 2nd order), and SST k-omega model. In order to assess the accuracy of each turbulence model in obtaining the performance of the proposed model of the windcatcher system, it is found that the second order k-epsilon turbulence model gave the best results when compared with the previous experimental measurements. A new windcatcher internal design is proposed to enhance the ventilation performance. The fluid dynamics characteristics of the proposed model are presented, and the ventilation performance of the present model is estimated. The numerical velocity profiles showed good agreement with the experimental measurements for the turbulence model. The obtained results have shown that the second order k-epsilon turbulence can predict the different important parameters of the windcatcher model. Moreover, the coupling algorithm of CFD and the fuzzy system for obtaining the optimum operating parameters of the windcatcher design are described.

Investigation on particulate matter and gas motion processes in the advanced multi-channel cyclone-separator with secondary gas inlets

Research into gas flow motion as a transported phase and pollutant – particulate matter (PM) is of crucial importance, their changes in particular areas of the object require knowledge of improving the apparatus. A cyclone is considered one of the most popular devices due to the new modified multi-channel design that involves combined separation and filtration phenomena. The findings of an accurate numerical model provide an opportunity to verify long-term experimental studies. In addition, it is possible to determine the impact of the designed principal elements of the structure comprising secondary gas inlets, inner slits and the convex bottom on gas and PM motion through verification conducting experimental research. The study focuses on simulating the upgraded cyclone using the SST k-omega model. The research has been conducted under the specified gas flow conditions such as high temperature and relative humidity (aggressive) gas and presents the results of the physical model to compare with. To achieve greater computational accuracy, a digital model of the cyclone made of specific volumetric elements has been developed thus expanding the grid and stepping to form the boundary zone. As a result, numerical simulation results differ by no more than 12.8% compared to the experimental studies results.

COMPARISON OF STANDARD k-epsilon AND SST k-omega TURBULENCE MODEL FOR BREASTSHOT WATERWHEEL SIMULATION

Currently, Computational Fluid Dynamics (CFD) was utilized to predict the performance, geometry optimization or physical phenomena of a breastshot waterwheel. The CFD method requires the turbulent model to predict the turbulent flow. However, until now there is special attention on the effective turbulent model used in the analysis of breastshot waterwheel. This study is to identify the suitable turbulence model for a breatshot waterwheel. The two turbulence models investigated are: standard k-epsilon model and shear stress transport (SST) k-omega. Pressure based and one degrees of freedom (one-DoF) feature was used in this case with 75 Nm, 150 Nm, 225 Nm and 300 Nm as preloads. Based on the results, the standard k-epsilon model gave similar result with the SST k-omega model. Therefore, the simulation for breastshot waterwheel will be efficient if using the standard k-epsilon model because it requires lower computational power than the SST k-omega model. However, to study about physical phenomenon, the SST k-omega model is recommend.

Parameterization of Vegetation Scattering Albedo in the Tau-Omega Model for Soil Moisture Retrieval on Croplands

An accurate radiative transfer model (RTM) is essential for the retrieval of soil moisture (SM) from microwave remote sensing data, such as the passive microwave measurements from the Soil Moisture Active Passive (SMAP) mission. This mission delivers soil moisture products based upon L-band brightness temperature data, via retrieval algorithms for surface and root-zone soil moisture, the latter is retrieved using data assimilation and model support. We found that the RTM based on the tau-omega (τ-ω) model can suffer from significant errors over croplands in the simulation of brightness temperature (Tb) (in average between −9.4K and +12.0K for single channel algorithm (SCA); −8K and +9.7K for dual-channel algorithm (DCA)) if the vegetation scattering albedo (omega) is set constant and temporal variations are not considered. In order to reduce this uncertainty, we propose a time-varying parameterization of omega for the widely established zeroth order radiative transfer τ-ω model. The main assumption is that omega can be expressed by a functional relationship between vegetation optical depth (tau) and the Green Vegetation Fraction (GVF). Assuming allometry in the tau-omega relationship, a power-law function was established and it is supported by correlating measurements of tau and GVF. With this relationship, both tau and omega increase during the development of vegetation. The application of the proposed time-varying vegetation scattering albedo results in a consistent improvement for the unbiased root mean square error of 16% for SCA and 15% for DCA. The reduction for positive and negative biases was 45% and 5% for SCA and 26% and 12% for DCA, respectively. This indicates that vegetation dynamics within croplands are better represented by a time-varying single scattering albedo. Based on these results, we anticipate that the time-varying omega within the tau-omega model will help to mitigate potential estimation errors in the current SMAP soil moisture products (SCA and DCA). Furthermore, the improved tau-omega model might serve as a more accurate observation operator for SMAP data assimilation in weather and climate prediction model.

Fluctuation identities for Omega-killed spectrally negative Markov additive processes and dividend problem

In this paper, we solve exit problems for a one-sided Markov additive process (MAP) which is exponentially killed with a bivariate killing intensity $\omega(\cdot,\cdot)$ dependent on the present level of the process and the current state of the environment. Moreover, we analyze the respective resolvents. All identities are expressed in terms of new generalizations of classical scale matrices for MAPs. We also remark on a number of applications of the obtained identities to (controlled) insurance risk processes. In particular, we show that our results can be applied to the Omega model, where bankruptcy takes place at rate $\omega(\cdot,\cdot)$ when the surplus process becomes negative. Finally, we consider Markov-modulated Brownian motion (MMBM) as a special case and present analytical and numerical results for a particular choice of piecewise intensity function $\omega(\cdot,\cdot)$ .