An efficient setup for freestream turbulence on transition prediction over aerospace configurations

Halila, Gustavo Luiz Olichevis; Bigarella, E. D. V.; Antunes, Alexandre P.; Azevedo, João Luiz F.

doi:10.1016/j.ast.2018.08.013

Cited by 15 publications

(2 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Ma et al [201] discussed the solutions to deal with fluid structure interactions (FSI) since FSI was so many factors such as a vibration at hypersonic inlet and deflections of wings and rotors; computational fluid dynamics (CFD) and the finite volume method CFD were used to analyze FSI [202]. To predict the transition of freestream turbulence in different aerospace configurations, Halila et al [203] identified a number of inflow turbulence variables and investigate their impact on drag forces in a cruise condition of jetliner aircrafts. Bemmami and David [204] proposed a model-based method to deal with the complexity of modern systems, the performance of system was verified by simulation.…”

Section: Big Space Data Analysismentioning

confidence: 99%

The State of the Art of Information Integration in Space Applications

Yung

et al. 2022

IEEE Access

View full text Add to dashboard Cite

This paper aims to present a comprehensive survey on information integration (II) in space informatics. With an ever-increasing scale and dynamics of complex space systems, II has become essential in dealing with the complexity, changes, dynamics, and uncertainties of space systems. The applications of space II (SII) require addressing some distinctive functional requirements (FRs) of heterogeneity, networking, communication, security, latency, and resilience; while limited works are available to examine recent advances of SII thoroughly. This survey helps to gain the understanding of the state of the art of SII in sense that (1) technical drivers for SII are discussed and classified; (2) existing works in space system development are analyzed in terms of their contributions to space economy, divisions, activities, and missions; (3) enabling space information technologies are explored at aspects of sensing, communication, networking, data analysis, and system integration; (4) the importance of first-time right (FTR) for implementation of a space system is emphasized, the limitations of digital twin (DT-I) as technological enablers are discussed, and a concept digital-triad (DT-II) is introduced as an information platform to overcome these limitations with a list of fundamental design principles; (5) the research challenges and opportunities are discussed to promote SII and advance space informatics in future.INDEX TERMS Information integration (II), space informatics, digital triad (DT-II), internet of digital-triad things (IoDTT), first-time right (FTR), space information integration (SII). FIGURE 2. Technical drivers of II applications.

show abstract

Section: Big Space Data Analysismentioning

confidence: 99%

The State of the Art of Information Integration in Space Applications

Yung

et al. 2022

IEEE Access

View full text Add to dashboard Cite

show abstract

“…The far field boundary condition for k and ω is computed based on 0.5% turbulence intensity and ν t /ν = 50. According to Halila et al [35], this setup is effective to reproduce turbulence transition for the kOmegaSSTLM model. We use the same design variable and constraint setup as shown in Table 3 except that we consider only the nominal flight condition C L =0.75.…”

Section: Aerodynamic Shape Optimization With Turbulence Transitionmentioning

confidence: 99%

An Object-oriented Framework for Rapid Discrete Adjoint Development using OpenFOAM

Mader

Martins

et al. 2019

AIAA Scitech 2019 Forum

View full text Add to dashboard Cite

The adjoint method is an efficient approach for computing derivatives because its computational cost is independent of the number of design variables. Using the derivatives computed from the adjoint method, a gradient-based optimization can handle complex design problems such as full-scale aircraft. Despite the above advantages, implementing the adjoint method for a partial differential equation based primal solver is a time-consuming task. To lower the barrier for adjoint implementations, we propose an object-oriented framework to rapidly develop the discrete adjoint method based on OpenFOAM; an open-source, multiphysics package that contains more than 80 primal solvers involving a wide range of disciplines such as aerodynamics, hydrodynamics, heat transfer, structures, combustion, and multiphase flow. The proposed framework provides high-level interfaces that allow us to implement the adjoint method for any existing steady-state OpenFOAM primal solvers by adding or modifying only O(100) lines of source code. In this paper we introduce the overall structure of the proposed adjoint framework and detail the adjoint development process by starting with a simple scalar transport equation and then extending the development to the Navier-Stokes equations. So far, we have implemented adjoint methods for five primal solvers and four turbulence models. We observe excellent adjoint scalability with up to O(10) million cells and O(1000) CPU cores, and the maximal error in the adjoint derivatives is less than 0.1%. To further demonstrate the benefit of having the flexibility to rapidly develop the adjoint method for different solvers and turbulence models, we showcase three successful aerodynamic shape optimizations that cover incompressible, compressible, full turbulence, and transitional turbulence conditions. Our proposed adjoint framework has the potential of becoming a useful tool to handle high-fidelity multidisciplinary design optimization problems for general engineering systems such as aircraft, cars, ships, and turbomachinery.

show abstract