Numerical Resolution of Compressor Corner Separation Problem

2021 ◽  
Author(s):  
Wei Sun ◽  
Zhong-Nan Wang ◽  
Liping Xu
Author(s):  
Wei Sun ◽  
Zhong-Nan Wang ◽  
Liping Xu

Abstract Corner separation is a common flow phenomenon within compressors that can significantly affect the compressor performance. The RANS turbulence closures, commonly used in the industrial CFD simulations, often struggle to predict corner separation with reasonable accuracy. In this paper, the results of two RANS-based modelling approaches are presented for the corner separation within a high-loaded Prescribed Velocity Distribution (PVD) compressor cascade. The flow characteristics are studied to facilitate understanding the causes of varying performance of RANS models. It is observed that mixing plays a crucial role in accurately predicting the type, location, and size of flow separation. The source terms that control the turbulence mixing in SA and SST models are identified, based on physical analyses. Both RANS models are modified to better model the mixing process. Based on the modified SST model, an improved RANS-LES blending function has been proposed for a hybrid RANS-LES model. This new blending function ensures reliable shielding of attached boundary layers by the RANS portion of the hybrid model. Finally, to gain further understanding of the endwall flow physics, the turbulence characteristics of the resolved corner separation flow are studied, in terms of the large-scale unsteadiness and loss generation mechanisms.


2020 ◽  
Vol 501 (2) ◽  
pp. 1803-1822
Author(s):  
Seunghwan Lim ◽  
Douglas Scott ◽  
Arif Babul ◽  
David J Barnes ◽  
Scott T Kay ◽  
...  

ABSTRACT As progenitors of the most massive objects, protoclusters are key to tracing the evolution and star formation history of the Universe, and are responsible for ${\gtrsim }\, 20$ per cent of the cosmic star formation at $z\, {\gt }\, 2$. Using a combination of state-of-the-art hydrodynamical simulations and empirical models, we show that current galaxy formation models do not produce enough star formation in protoclusters to match observations. We find that the star formation rates (SFRs) predicted from the models are an order of magnitude lower than what is seen in observations, despite the relatively good agreement found for their mass-accretion histories, specifically that they lie on an evolutionary path to become Coma-like clusters at $z\, {\simeq }\, 0$. Using a well-studied protocluster core at $z\, {=}\, 4.3$ as a test case, we find that star formation efficiency of protocluster galaxies is higher than predicted by the models. We show that a large part of the discrepancy can be attributed to a dependence of SFR on the numerical resolution of the simulations, with a roughly factor of 3 drop in SFR when the spatial resolution decreases by a factor of 4. We also present predictions up to $z\, {\simeq }\, 7$. Compared to lower redshifts, we find that centrals (the most massive member galaxies) are more distinct from the other galaxies, while protocluster galaxies are less distinct from field galaxies. All these results suggest that, as a rare and extreme population at high z, protoclusters can help constrain galaxy formation models tuned to match the average population at $z\, {\simeq }\, 0$.


Vibration ◽  
2020 ◽  
Vol 4 (1) ◽  
pp. 49-63
Author(s):  
Waad Subber ◽  
Sayan Ghosh ◽  
Piyush Pandita ◽  
Yiming Zhang ◽  
Liping Wang

Industrial dynamical systems often exhibit multi-scale responses due to material heterogeneity and complex operation conditions. The smallest length-scale of the systems dynamics controls the numerical resolution required to resolve the embedded physics. In practice however, high numerical resolution is only required in a confined region of the domain where fast dynamics or localized material variability is exhibited, whereas a coarser discretization can be sufficient in the rest majority of the domain. Partitioning the complex dynamical system into smaller easier-to-solve problems based on the localized dynamics and material variability can reduce the overall computational cost. The region of interest can be specified based on the localized features of the solution, user interest, and correlation length of the material properties. For problems where a region of interest is not evident, Bayesian inference can provide a feasible solution. In this work, we employ a Bayesian framework to update the prior knowledge of the localized region of interest using measurements of the system response. Once, the region of interest is identified, the localized uncertainty is propagate forward through the computational domain. We demonstrate our framework using numerical experiments on a three-dimensional elastodynamic problem.


Mathematics ◽  
2021 ◽  
Vol 9 (16) ◽  
pp. 1835
Author(s):  
Antonio Barrera ◽  
Patricia Román-Román ◽  
Francisco Torres-Ruiz

A joint and unified vision of stochastic diffusion models associated with the family of hyperbolastic curves is presented. The motivation behind this approach stems from the fact that all hyperbolastic curves verify a linear differential equation of the Malthusian type. By virtue of this, and by adding a multiplicative noise to said ordinary differential equation, a diffusion process may be associated with each curve whose mean function is said curve. The inference in the resulting processes is presented jointly, as well as the strategies developed to obtain the initial solutions necessary for the numerical resolution of the system of equations resulting from the application of the maximum likelihood method. The common perspective presented is especially useful for the implementation of the necessary procedures for fitting the models to real data. Some examples based on simulated data support the suitability of the development described in the present paper.


2021 ◽  
Vol 504 (2) ◽  
pp. 2325-2345
Author(s):  
Emanuel Sillero ◽  
Patricia B Tissera ◽  
Diego G Lambas ◽  
Stefano Bovino ◽  
Dominik R Schleicher ◽  
...  

ABSTRACT We present p-gadget3-k, an updated version of gadget-3, that incorporates the chemistry package krome. p-gadget3-k follows the hydrodynamical and chemical evolution of cosmic structures, incorporating the chemistry and cooling of H2 and metal cooling in non-equilibrium. We performed different runs of the same ICs to assess the impact of various physical parameters and prescriptions, namely gas metallicity, molecular hydrogen formation on dust, star formation recipes including or not H2 dependence, and the effects of numerical resolution. We find that the characteristics of the simulated systems, both globally and at kpc-scales, are in good agreement with several observable properties of molecular gas in star-forming galaxies. The surface density profiles of star formation rate (SFR) and H2 are found to vary with the clumping factor and resolution. In agreement with previous results, the chemical enrichment of the gas component is found to be a key ingredient to model the formation and distribution of H2 as a function of gas density and temperature. A star formation algorithm that takes into account the H2 fraction together with a treatment for the local stellar radiation field improves the agreement with observed H2 abundances over a wide range of gas densities and with the molecular Kennicutt–Schmidt law, implying a more realistic modelling of the star formation process.


Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3897
Author(s):  
Miguel Ángel González-Cagigal ◽  
Juan Carlos del-Pino-López ◽  
Alfonso Bachiller-Soler ◽  
Pedro Cruz-Romero ◽  
José Antonio Rosendo-Macías

This paper presents a procedure for the derivation of an equivalent thermal network-based model applied to three-core armored submarine cables. The heat losses of the different metallic cable parts are represented as a function of the corresponding temperatures and the conductor current, using a curve-fitting technique. The model was applied to two cables with different filler designs, supposed to be equipped with distributed temperature sensing (DTS) and the optical fiber location in the equivalent circuit was adjusted so that the conductor temperature could be accurately estimated using the sensor measurements. The accuracy of the proposed model was tested for both stationary and dynamic loading conditions, with the corresponding simulations carried out using a hybrid 2D-thermal/3D-electromagnetic model and the finite element method for the numerical resolution. Mean relative errors between 1 and 3% were obtained using an actual current profile. The presented procedure can be used by cable manufacturers or by utilities to properly evaluate the cable thermal situation.


Electronics ◽  
2018 ◽  
Vol 7 (10) ◽  
pp. 219 ◽  
Author(s):  
Alberto Sanchez ◽  
Elías Todorovich ◽  
Angel de Castro

As the performance of digital devices is improving, Hardware-In-the-Loop (HIL) techniques are being increasingly used. HIL systems are frequently implemented using FPGAs (Field Programmable Gate Array) as they allow faster calculations and therefore smaller simulation steps. As the simulation step is reduced, the incremental values for the state variables are reduced proportionally, increasing the difference between the current value of the state variable and its increments. This difference can lead to numerical resolution issues when both magnitudes cannot be stored simultaneously in the state variable. FPGA-based HIL systems generally use 32-bit floating-point due to hardware and timing restrictions but they may suffer from these resolution problems. This paper explores the limits of 32-bit floating-point arithmetics in the context of hardware-in-the-loop systems, and how a larger format can be used to avoid resolution problems. The consequences in terms of hardware resources and running frequency are also explored. Although the conclusions reached in this work can be applied to any digital device, they can be directly used in the field of FPGAs, where the designer can easily use custom floating-point arithmetics.


2013 ◽  
Vol 43 (9) ◽  
pp. 1862-1879 ◽  
Author(s):  
Leonel Romero ◽  
Yusuke Uchiyama ◽  
J. Carter Ohlmann ◽  
James C. McWilliams ◽  
David A. Siegel

Abstract Knowledge of horizontal relative dispersion in nearshore oceans is important for many applications including the transport and fate of pollutants and the dynamics of nearshore ecosystems. Two-particle dispersion statistics are calculated from millions of synthetic particle trajectories from high-resolution numerical simulations of the Southern California Bight. The model horizontal resolution of 250 m allows the investigation of the two-particle dispersion, with an initial pair separation of 500 m. The relative dispersion is characterized with respect to the coastal geometry, bathymetry, eddy kinetic energy, and the relative magnitudes of strain and vorticity. Dispersion is dominated by the submesoscale, not by tides. In general, headlands are more energetic and dispersive than bays. Relative diffusivity estimates are smaller and more anisotropic close to shore. Farther from shore, the relative diffusivity increases and becomes less anisotropic, approaching isotropy ~10 km from the coast. The degree of anisotropy of the relative diffusivity is qualitatively consistent with that for eddy kinetic energy. The total relative diffusivity as a function of pair separation distance R is on average proportional to R5/4. Additional Lagrangian experiments at higher horizontal numerical resolution confirmed the robustness of these results. Structures of large vorticity are preferably elongated and aligned with the coastline nearshore, which may limit cross-shelf dispersion. The results provide useful information for the design of subgrid-scale mixing parameterizations as well as quantifying the transport and dispersal of dissolved pollutants and biological propagules.


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