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▶ Contacts
Boris Diskin [ E-mail ]
Hiroaki Nishikawa [ E-mail
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▶ Past Seminars
Season 8 (2018-2019)
Season 7 (2017-2018)
Season 6 (2016-2017)
Season 5 (2015-2016)
Season 4 (2014-2015)
Season 3 (2013-2014)
Season 2 (2012-2013)
Season 1 (2011-2012)
List of Speakers
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▶ NIA Researchers
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Boris Diskin, Ph.D.
Research Fellow, NIA
Adjoint-based optimization methods, Finite-volume discretizations, Multigrid methods on structured/unstructured grids
Web
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E-mail
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David Del Rey Fernández, Ph.D.
Postdoctoral Fellow, NIA
Robust high-order numerical methods for the solution of partial differential equations.
E-mail
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Prahladh S. Iyer Ph.D.
Postdoctoral Fellow, NIA
DNS/ LES of complex flows, transition to turbulence and turbulence modeling.
E-mail
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Heather Kline Ph.D.
Research Engieer, NIA
Adjoint-based design, transition to turbulence, and hypersonic air-breathing propulsion
E-mail
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Yi Liu, Ph.D.
Senior Research Scientist, NIA
high-order accurate methods, turbomachinery and rotorcraft applicaitons.
E-mail
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Asitav Mishra, Ph.D.
Research Engineer II, NIA
Adjoint-based multi-disciplinary fixed and rotary-wing analysis and design optimization, finite-element methods, and high-performance computing using heterogeneous GPU/CPU computing paradigms applied to CFD problems.
E-mail
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Hiroaki Nishikawa, Ph.D.
Associate Research Fellow, NIA
Discretization and convergence acceleration methods for unstructured grids
Web
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E-mail
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CFD Notes
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Juliette Pardue
PhD Student, ODU/NIA
Mesh generation, parallel algorithms, and computational geometry.
E-mail
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Pedro Paredes, Ph.D.
Research Engineer, NIA
Linear flow instability and control of complex flows and study of laminar-turbulent transition in compressible boundary layers
E-mail
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Balaji S. Venkatachari, Ph.D.
Sr. Research Engineer, NIA
Numerical algorithm development, Hypersonics, TPS modeling (continuum and multi-scale modeling), and CAA.
E-mail
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Ali Uzun, Ph.D.
Sr. Research Scientist, NIA
Computational fluid dynamics using high-order numerical methods, turbulence simulations, computational aeroacoustics and parallel computing.
E-mail
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▶ Faculties in Residence
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Bill Moore, Ph.D.
Professor in Residence, NIA
Atmospheric & Planetary Sciences,
Hampton University
Thermal Evolution of Planet and Satellite Inteiors, Dynamical Evolution of Planets and Satellites,
Coupled Atmosphere-Interior Modeling of Planets, What Makes a Planetary Body Habitable?
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E-mail
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James D. Baeder, Ph.D.
NIA Langley Professor
Aerospace Engineering,
University of Maryland
Computational Aerodynamics and Aeroacoustics
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Olivier A Bauchau, Ph.D.
NIA Langley Professor
Aerospace Engineering,
University of Maryland
Multibody Dynamics, Rotorcraft Aero-Mechanical Comprehensive Modeling, Structural Dynamics, and Composites Materials and Structures
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NIA CFD Seminar Schedule
Click here to view the full list of videos.
Click the camera icon below to go directly to the video for each seminar.
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124th NIA CFD Seminar:
03-06-2020
11:00am-noon (EDT)
NIA Room 137
 video
High-Performance Flow Visualization: Research, Development, and Application
Scientific visualization is an important application of computer graphics to scientific computing by providing deep insight into the pattern underlying large-scale data. Vector data visualization, or flow visualization, plays a crucial role in a wide variety of areas such as oceanographic- atmospheric modeling, computational fluid dynamics simulation, and electro-magnetic field analysis, to name only a few. It is unique for depicting directional information in addition to the spatial distribution and geometric structures that scalar data visualization, as a sibling, is intended to reveal. The last two decades have seen many geometry-based and texture-based algorithms for visualizing flows ranging from steady to unsteady and from 2D to 3D. As we seek the most effective representations for exploring surface and volume flows, there are signs of revisiting geometry-based methods with further improvement, from texture-based approaches, and resorting to parallel visualization.
This talk provides a high-level and sampling description of Dr. Liu's algorithmic research and system development along this path in high-performance flow visualization over the past 20+ years, involving AUFLIC (Accelerated Unsteady Flow Line Integral Convolution), VAUFLIC (Volume AUFLIC), ADVESS (ADVanced Evenly Spaced Streamline placement), IVDESS (Interactive View-Driven Evenly Spaced Streamline placement), his two-year industrial experience at Kitware, Inc. for participating in the development of two large-scale cross-platform open-source general-purpose visualization packages VTK and ParaView, as well as his recent work on Parallel Flow Visualization (via GPU, multi-threading, and MPI). Also demonstrated are three 'Active' systems / packages (irrelevant to any project) that he independently developed for interactive flow visualization, i.e., ActiveLIC (Line Integral Convolution), ActiveIBFV (Image-Based Flow Visualization), and ActiveFLOVE (FLOw Visualization Environment).
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Speaker Bio:
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Dr. Zhanping Liu is a tenure-track assistant professor with the department of Computational Modeling and Simulation Engineering at Old Dominion University. He was a USRA (Universities Space Research Association) faculty visitor of the division of NASA Advanced Supercomputing (NAS) at NASA Ames Research Center (May ~ July, 2014) and an FRPP (Faculty Research Participation Program) faculty visitor of the division of Mathematics and Computer Science (MCS) at Argonne National Lab (May ~ July, 2013) during his employment as a tenure-track assistant professor with the department of Computer Science at Kentucky State University (2011 ~ 2016). Much earlier, Dr. Liu was a research fellow of the Bio-medical Image Analysis Group of the School of Medicine at the University of Pennsylvania (2010 ~ 2011), a research staff member of the Scientific Computing and Visualization Group at Kitware, Inc. ("Leaders in Visualization Technology", 2008 ~ 2010), a research scientist of the Visualization Analysis and Imaging Lab (VAIL) of the High- Performance Computing Collaboratory (HPC2) at Mississippi State University (2001 ~ 2008), and a post- doctoral associate of the Micro-CT Image Reconstruction and Volume Visualization Lab of the College of Medicine at the University of Iowa (2000 ~ 2001). He received the PhD degree in Computer Science from Peking University (2000) and the BS degree in Mathematics from Nankai University (1992). His research interests consist in scientific visualization (particularly vector / flow data visualization), parallel visualization (via GPU, multi-threading, and MPI), and data analysis. Since 1997, Dr. Liu has been performing not only algorithmic research but also system development (using C/C++) in scientific visualization. He has independently developed 9 data visualization systems / packages (VF-VTK, RadVis, Triton-II-Flow, ActiveLIC, ActiveIBFV, ActiveFLOVE, SynVizer, cuVis, and TB-CLIC), without dependence on any third-party library / tool. He participated in the development of VTK, ParaView, and DOXIV. More information about his work and personal hobbies are available at www.zhanpingliu.org.
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123rd NIA CFD Seminar:
09-04-2019
11:00am-noon (EDT)
NIA Room 137
video
Hyperbolic Navier-Stokes Method Based on Reconstructed-Discontinuous-Galerkin or Reconstructed-Finite-Volume Formulation with Variational Reconstruction
The objective of the presented work is to develop an efficient, accurate and compact method for solving compressible Navier-Stokes (NS) equations by combining the hyperbolic Navier-Stokes (HNS) formulation and the reconstructed discontinuous Galerkin method (rDG), which includes the finite-volume (FV) and discontinuous Galerkin methods. A new HNS formulation is derived, so that an efficient high-order construction for compressible NS equations can be derived. The gradients of the primitive variables such as density, velocity and temperature are introduced as additional unknowns. The newly introduced gradients can be recycled to get a higher-order polynomial solution for these primitive variables. An even more accurate method is obtained when reconstruction is performed on these gradient variables. These reconstructed variables are also reused as higher-order derivatives of the primitive variables. In the presented work, a variational formulation is used for reconstruction. This variational reconstruction (VR) can be seen as an extension of the compact finite difference schemes to unstructured grids. The reconstructed variables are obtained by solving an extreme value problem, which minimizes the jumps at cell interfaces, and therefore maximizes the smoothness of the reconstructed polynomials. The spatial discretization is performed by multiplying the HNS system by a test function matrix. If the matrix is taken as a diagonal matrix, then the primitive variables and auxiliary variables are regarded as decoupled. This will generate a FV type formulation, which is denoted as HNS+rFV method. If the matrix is taken as the primitive variables and auxiliary variables are coupled, a Galerkin type formulation is obtained, which is denoted as HNS+rDG method. All the primitive variables, auxiliary variables and reconstructed variables are stored in a consistent way with the Taylor-basis DG counterpart. The fully implicit method is implemented for steady problems, while a third-order implicit Runge-Kutta (IRK), i.e., ESDIRK3 time marching method is implemented for unsteady flows. In these implicit methods, an automatic differentiation tool TAPENADE is used to obtain the resulting flux Jacobian matrices. The approximate system of linear equations arising from the Newton iteration is solved with two methods: symmetric gauss-seidel (SGS) and general minimum residual (GMRES) algorithm with lower-upper symmetric gauss-seidel (LU-SGS) preconditioning.
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Speaker Bio:
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Lingquan Li received the Bachelor's degree of Aerospace Engineering at Xi'an Jiaotong University, Xi'an, Shaanxi Province, China, in July 2011. She then attended the graduate school at Fudan University, Shanghai, China, in September 2013 and studied under the supervision of Dr. Aiming Yang. She received the Master's degree of Aerospace Engineering in July 2016. The author was then recruited by the Department of Mechanical and Aerospace Engineering at North Carolina State University (NCSU), Raleigh, North Carolina, USA, and studied in the doctoral program of Aerospace Engineering since August 2016. Her academic advisor is Dr. Hong Luo.
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122nd NIA CFD Seminar:
08-27-2019
11:00am-noon (EDT)
NIA Room 137
video
Uncertainty Quantification via Optimal Experimental Design and Bayesian Neural Networks for Aerospace Applications
Models and data are two pillars of scientific research: models make predictions, and data help calibrate existing models and develop new ones. In this talk, we focus on two important interactions between models and data: (1) optimal experimental design (OED) for identifying the most useful data, and (2) Bayesian neural networks (BNNs) - a class of data-driven models with quantified uncertainty-for accelerating expensive predictions.
First, we present the OED framework that systematically quantifies and maximizes the value of experiments. Indeed, some experiments can produce more useful data than others, and well-chosen experiments can lead to substantial savings. We describe a general mathematical framework that accommodates nonlinear and computationally intensive (e.g., ODE- and PDE-based) models. The formalism employs Bayesian statistics and an information-theoretic objective, and we develop tractable numerical methods with demonstrations on designing combustion kinetic experiments and sensor placement for contaminant source inversion.
Next, we introduce BNNs as data-driven surrogate models. The capability of rapid predictions
with quantified uncertainty makes them excellent tools for supporting real-time, high-consequence decision-making. In a proof-of-concept application on in-flight detection of rotorcraft blade icing, we build a BNN from a database of SU2 simulations to directly map noise signals to aerodynamic performance metrics, thus bypassing the expensive inverse problems. The BNN is able to produce a distribution of predictions instead of a single-value output, reflecting the quality and confidence of the machine learning model, and offering valuable information for pilot decision-making. Lastly, we present preliminary results on machine learning reconstruction of turbulent fluctuations for stochastic noise generation in RANS-based aeroacoustic simulations using SU2, where in particular we investigate a data-driven characterization of turbulence energy spectrum from LES computations.
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Speaker Bio:
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Dr. Xun Huan is an Assistant Professor of Mechanical Engineering at the University of Michigan-Ann Arbor, and affiliated faculty to the Michigan Institute for Computational Discovery & Engineering (MICDE), the Michigan Institute for Data Science (MIDAS), and the U-M Applied Physics Program. Dr. Huan received a Ph.D. in Computational Science and Engineering from MIT Department of Aeronautics and Astronautics, and was a postdoctoral researcher at Sandia National Laboratories in Livermore, California. His research broadly revolves around uncertainty quantification, machine learning, and numerical optimization, with a focus on aerospace and mechanical engineering applications. His current projects involve optimal experimental design for identifying and acquiring the most useful data, and methods for quantifying uncertainty and trust for machine learning models. Outside work, Dr. Huan is passionate about aviation and holds a private pilot certificate.
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121st NIA CFD Seminar:
08-21-2019
11:00am-noon (EDT)
NIA Room 137
video
Tangent and Adjoint Problems in Partially Converged Flows
As computers and algorithms have developed, the field of CFD has expanded to include a larger role for Aerodynamic/Multidisciplinary Shape Optimization and Adaptive Mesh Refinement. Both these applications solve first the primal problem (or the governing equations), and then the adjoint problem, derived off a zero residual condition, to obtain the objective sensitivities or output-based error estimate respectively. As the field of CFD has moved to more difficult problems: higher-order formulations, blunt geometries, or time-accurate simulations, convergence of the governing equations to a zero residual condition has become difficult or impractical to achieve. Despite these limitations, the use of the adjoint technique has continued unabated even in cases where the zero residual constraint has not been fulfilled. These systems are highly sensitive to the state at which they are linearized and can provide inaccurate sensitivity calculations or error estimations, negatively impacting design optimization and/or mesh refinement results. This work presents the derivation and application of the tangent and adjoint problems based off the linearization of the primal solver, which allows for sensitivity calculations and error estimates in partially converged flows.
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Speaker Bio:
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Emmett did his undergraduate work in aeronautical engineering at McGill University, where he worked as a research assistant for Prof. Siva Nadarajah in the McGill Computational Aerodynamics Group. He began his PhD at University of Wyoming supervised by Prof. Dimitri Mavriplis in the fall of 2015. In 2016, he was awarded a NASA Aeronautical Graduate Scholarship/Fellowship through the NASA ASTAR program. His research in mechanical engineering is focused on adjoint method development with an application towards MDO and AMR.
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120th NIA CFD Seminar:
08-15-2019
11:00am-noon (EDT)
NIA Room 137
video
Developing Data-Augmented Turbulence Models using Field Inversion and Machine Learning
Reynolds-Averaged Navier-Stokes (RANS) simulations have been the go-to choice among computational techniques for preliminary design and optimization of flow configurations, owing to their speed and computational cost-effectiveness; but, they suffer from significant inaccuracies when compared to their higher-fidelity counterparts which can be attributed to inadequacies in the turbulence models being used. Data-driven approaches seem to be a lucrative solution to address this problem. While the data available from experiments and high-fidelity simulations cannot be directly used to improve these models, the relationship between flow features and the intended augmentation can be inferred and captured in a functional form using Field Inversion and Machine Learning. The presentation discusses the mathematical setting, framework, variations and applications of the methodology with results for both simple and moderately complex problems, and, finally, generalization strategies being pursued to broaden the predictive applicability of this technique beyond the class of problems used for augmentation, along with related preliminary results.
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Speaker Bio:
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Vishal Srivastava received his B.Tech degree in Aerospace Engineering from the Indian Institute of Technology, Kanpur and is currently a Ph.D. Candidate in the Department of Aerospace Engineering at the University of Michigan, Ann Arbor. With Dr. Karthik Duraisamy as his advisor, he is studying data-driven techniques to improve turbulence modeling for use in predictive simulations.
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119th NIA CFD Seminar:
08-12-2019
11:00am-noon (EDT)
NIA Room 137
video
Solution Error Control Using Automated Mesh Interface Creation and Efficient Output-Based Adaptation Mechanics
As numerical simulations are applied to more complex and large-scale problems, solution verification becomes increasingly important in ensuring accuracy of the computed results. Although improvements in computer hardware have brought expensive simulations within reach, efficiency is still paramount, especially in the context of design optimization and uncertainty quantification. This work addresses both of these needs through contributions to solution-based adaptive algorithms, in which the discretization is modified through feedback of solution error estimates so as to improve the accuracy. In particular, new methods are developed for two discretizations relevant to Computational Fluid Dynamics: the Active Flux method and the discontinuous Galerkin method. For the Active Flux method, which is fully-discrete third-order discretization, both the discrete and continuous adjoint methods are derived and used to drive mesh (h) refinement and dynamic node movement, also known as r-adaptation. For the discontinuous Galerkin method, which is an arbitrary-order finite-element discretization, efficiency improvements are presented for computing and using error estimates derived from the discrete adjoint, and a new r-adaptation strategy is presented for unsteady problems. For both discretizations, error estimate efficacy and adaptive efficiency improvements are shown relative to other strategies. Additionally, an automated one-to-one non-conformal mesh interface creation process will be introduced. This automated non-conformal mesh interface creation process eliminates human setup error while reducing the case setup time by 50% on average, for practical industrial applications.
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Speaker Bio:
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In February 2018, Dr. Kaihua Ding obtained his Ph.D. in Aerospace Engineering from the University of Michigan-Ann Arbor, with the dissertation title, Efficient Output-Based Adaptation Mechanics for High-Order Computational Fluid Dynamics Methods. For the last one and a half years, Dr. Ding worked at ANSYS Fluent as a researcher and CAE software developer, inside Fluent solver team - the solver / dynamic mesh sub-team. His work has been released in ANSYS Fluent 19.5, which includes, but is not limited to, the new one-to-one non-conformal mesh interface functionality as well as the universal periodic pairing functionality.
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118th NIA CFD Seminar:
08-05-2019
11:00am-noon (EDT)
NIA Room 137
video
Distributed Vortex-Wave Interaction Arrays and Turbulent Shear Flows
High Reynolds number descriptions of nonlinear exact coherent structures in shear flows are discussed using a combination of asymptotic and numerical methods. Such states have been previously shown to describe: a) Bypass transition and b) Near wall streaks in developed and boundary layer turbulent shear flows.
Here we discuss the more general relevance of arrays of vortex-wave interactions to turbulent shear flows. The mean flow associated with such arrays is driven by the local interaction of waves, rolls and streaks and the slow dynamics of the interaction gives equations to determine the mean flow and the variation of the dominant energy carrying wavenumbers. The approach leads to evolution equations which can be viewed as explicit closure models related to turbulence modelling. The arrays predict many of the classical properties of turbulent shear flows such as uniform momentum
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Speaker Bio:
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Philip did his undergraduate and graduate work at Imperial College, London. His research in Applied Mathematics concentrates on nonlinear hydrodynamic stability theory, computational fluid dynamics, boundary layer control, convection, lubrication theory, chaotic fluid motion, geomorphology of rivers, coherent structures in high Reynolds number flows. In 2014, he became Head of School of Mathematics at Monash University, Melbourne, Australia. And prior to that appointment, he was Professor of Applied Mathematics at Imperial College as well as Head of Mathematics and Director of Institute of Mathematics and Director of LFC-UK during his time there.
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117th NIA CFD Seminar:
07-12-2019
11:00am-noon (EDT)
NIA Room 137
video
Drag and Noise Reduction of Flatback Trailing-edge Airfoils by Span-wise Wavy Trailing-edge Design
The flatback airfoil is a promising idea for future large wind turbine blade structure design; however, it causes notable drag increase and low frequency tonal noise due to the presence of span-wise coherent standing flow and Karman vortex shedding at the trailing edge. Current research proposes a span-wise wavy trailing edge design as a solution to the flatback airfoil drag and noise, and provides relevant CFD results. Proposed span-wise wavy trailing edge prevents the span-wise coherent standing flow and vortex shedding, results in a decrease of the tonal noise and pressure drag of the airfoil. A design parametric study for the span-wise wavy trailing edge is conducted, and followed by the isolated rotor simulation of the SNL100-meter blade. In the parametric study, the best aerodynamic span-wise wavy trailing edge design increases maximum 150% of lift/drag ratio, and reduces the tonal noise by 20-25dB(SPL), compared to the flatback airfoil. In the SNL100-meter rotor blade simulation, the span-wise wavy trailing edge results in 2.62% of turbine power generation, and 5-15dB(SPL) of tonal noise reduction. In the research, Delayed Detached Eddy Simulation is employed in HPC environment. In-house(at University of Maryland) developed N-S solvers, OVERTURNS(CPU-based) and GPURANS3D(GPGPU-based) are used for the computation.
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Speaker Bio:
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SeungJoon Yang is a recent granted(May 2019) PhD from University of Maryland. He had granted his B.S. and M.S. degree at the Korea Aerospace University, Goyang, South Korea. He is born and raised in South Korea, came and joined the CFD research group in the Alfred Gessow Rotor Craft Center at University of Maryland in 2013, after graduating from Korea Aerospace University. During his M.S program, his research mostly focused on the fuel injection/mixing system for the high-speed propulsion such as Gas-Turbine/Ramjet/Scramjet, approaching with CFD techniques, such as Multi-phase flow simulation(Liquid-Gas / Solid-Liquid-Gas), Large Eddy Simulation, Particle Tracking Simulation. At the University of Maryland, he joined the State of Maryland Wind Energy Research program, and focused on drag/noise reduction research for the future large wind turbine blade. His recent research is interested in turbulent modeling, blunt body aerodynamics, aero-acoustics, and GPU computation.
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116th NIA CFD Seminar:
05-22-2019
11:00am-noon (EDT)
NIA Room 137
video
In-Tunnel Simulation of the HL-CRM in the LaRC 14 x 22 ft. Wind Tunnel - Part II: Model-in-Tunnel Simulation Using TAU-DRSM
The presentation gives an overview about a first set of results of in-tunnel CFD simulations of the HL-CRM wing/body configuration in the LaRC 14 x 22 ft. wind tunnel, loosely linked to wind tunnel tests that have been conducted in late 2018. The simulations are carried out using DLR's TAU code in conjunction with a differential variant of the SSG/LRR Reynolds Stress turbulence model. To prepare for this study, different in-tunnel simulation approaches have been previously verified for the empty high speed leg of the 14 x 22 ft. wind tunnel against existing FUN3D and USM3D results (see
109th NIA CFD Seminar). The study compares results of the HL-CRM in landing configuration installed in the test section against free air computations for low speed high lift conditions. Main objectives are to assess the impact the semispan mounting and the wind tunnel walls on the aerodynamic characteristics of the configuration prior to the application of wind tunnel corrections, to investigate the fundamental aerodynamic interference phenomena involved, and to assess methodological issues involved in the simulation approach, such as grid topology and turbulence modeling.
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Speaker Bio:
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Ralf Rudnik is heading the transport aircraft department at DLR's Institute of Aerodynamics
and Flow Technology in Braunschweig since 2003. His scientific focus is on high lift aerodynamics,
engine/airframe integration, and CFD validation. Dr. Rudnik participated in numerous collaborative research
projects on aerodynamic validation and acted as a coordinator of the European high lift project EUROLIFT
and the German research project HINVA (High Lift Inflight Validation). In this context, he has been responsible
for dedicated stall tests with DLR's Airbus A320 ATRA flight test aircraft, carried out in close
collaboration with Airbus. He is currently engaged in research activities on STOL aircraft featuring circulation
control and over-the-wing mounted engines embedded in the German Coordinated Research Centre CRC
880 and in research and committee activities of the AIAA High Lift Prediction workshop.
Ralf Rudnik holds a diploma degree in aerospace engineering from the Technical University of
Braunschweig. He received a doctoral degree from the Technical University of Berlin. Since 2006 he
teaches configuration aerodynamics at the Technical University of Braunschweig. He is a visiting researcher
at NIA since September 2018.
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115th NIA CFD Seminar:
05-22-2019
11:00am-noon (EDT)
NIA Room 137
video
Experimental and Computational Investigations into Supersonic and Hypersonic Viscous Flows
In this talk we provide an overview of the various research activities in the broad area of compressible boundary layers and shock induced separated flows. In the first half, Venkat Narayanaswamy will present the ongoing research activities on shock boundary layer interactions. The focus will be the current investigations into the dominant flow interactions in different flow units spanning near-2D closed separation unit generated by compression ramp through open separation generated by a sharp fin. Particularly, this talk will focus on the sidewall interference effects on compression ramp interactions and will elucidate the mechanisms that drive the separated flow unsteadiness with increasing shock strength. A variety of measurement tools employed to provide a detailed understanding of the on-surface and off-surface flowfield structure will be presented.
In the second half of the talk, Pramod Subbareddy will discuss the recent works in his group. Three main topics to be discussed - (i) Wall-Modeled LES holds the promise of alleviating the high costs of simulating turbulent boundary layers. We will discuss our experience with various approaches to this problem, with focus on high speed flows. (ii) Modern stability analysis tools (resolvent/input-output analysis) have shown great potential for improving our understanding of several aspects of transition, as well as turbulent flow. We will present preliminary work on the development and usage of these methods. (iii) Designing low-dissipation methods for multi-species flow calculations presents numerical challenges since preserving scalar boundedness is often problematic (problems show up in the form of temperature overshoots, lack of mass conservation, etc). We will discuss an approach to tacking this problem.
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Speaker Bio:
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Dr. Venkat Narayanaswamy is an Associate Professor at Mechical and Aerospace Engineering Department of NCSU, where he has served the department since 2012. He directs a lab comprising eight graduate students and four undergraduate students focusing on high-speed aerodynamics/propulsion and energy related topics. Dr. Venkat Narayanaswamy received his doctoral degree from The University of Texas at Austin specializing in shock boundary interaction physics and plasma-based control. Subsequently, he pursued a postdoctoral fellowship at The University of Texas at Austin and RWTH Aachen, Germany, before joining NCSU. Dr. Narayanaswamy has authored over 25 journal publications and over 25 articles in peer-reviewed conferences. He is recognized with numerous research awards and honors including the AFOSR DURIP Award (2018), AFOSR Young Investigator Program Award (2016), Air Force Summer Faculty Fellowship (2016), and NC Space Grant New Investigator Award (2014).
Pramod Subbareddy is an Assistant Professor in the Mechanical and Aerospace Engineering department at North Carolina State University. He received his Ph.D. degree in Aerospace Engineering from the University of Minnesota in 2007 and his B.Tech degree in Aerospace Engineering from the Indian Institute of Technology, Madras, in 1999. He is a co-developer of the US3D computational fluid dynamics code, with a focus on its numerical and turbulence modeling aspects. His research interests lie in the general areas of turbulence modeling, numerical algorithms, flow stability and transition, and more recently, fluid-structure interactions.
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114th NIA CFD Seminar:
05-08-2019
11:00am-noon (EDT)
NIA Room 137
video
Toward Physically Exact RANS-LES
Accurate and feasible simulations of turbulent flow around aircraft suffer from two major problems. On the one hand, computationally very efficient pure Reynolds-averaged Navier-Stokes (RANS) methods fail to describe the main features of such flows because of their lacking ability to resolve turbulent flows. On the other hand, pure Large Eddy Simulation (LES) methods, which are capable of simulating resolved flow, are computationally way too expensive for wall-bounded turbulent flows. The development of solutions to these problems via the design of hybrid methods involving both RANS and LES elements takes place now over decades. About a thousand research papers following a huge variety of solution strategies are published every year now. The talk describes basic solution strategies in order to highlight conceptual questions. Previous applications of hybrid methods are described then by focusing on hill-type flows involving flow separation. These applications reveal the great potential of hybrid methods to accurately simulate separated flows at computational cost being a fraction of pure LES cost. The applications also reveal significant problems of usually applied methods. The final part of the talk focuses on the solution of some essential problems that were basically unaddressed so far, for example the question of how resolved and modeled turbulent motions can be kept in balance under changing resolution conditions. A theoretical solution to this question is presented for several well-known turbulence models. Initial applications show the potential of these news simulation methods.
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Speaker Bio:
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Dr. Stefan Heinz is Full Professor of Mathematics at the University of Wyoming. Dr. Heinz received his PhD in physics from the Heinrich-Hertz Institute in Berlin, Germany. Prior to joining the University of Wyoming, he held engineering faculty positions at TU Delft, Netherlands, and TU Munich, Germany. He has more than 25 years of research experience in the field of turbulence and turbulent combustion modeling and simulation. Dr. Heinz has published and presented his research through more than 200 international journal articles, conference publications, and invited presentations. He authored two textbooks on turbulence and stochastic processes. He has held visiting professor appointments at several universities and institutes. We won several teaching and research awards, he was honored as Adjunct Professor of Mechanical Engineering at the University of Wyoming. He is a fellow of the Hanse-Wissenschaftskolleg (Institute for Advanced Study, Delmenhorst) in Germany.
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113th NIA CFD Seminar:
04-26-2019
11:00am-noon (EDT)
NIA Room 137
video
Scramjet Ground Testing and Control Approaches
Modern numerical methods are playing an important role in the development and design of new scramjet concepts. However, in the same way it did for the Air Force X-51 and NASA X-43 programs, ground-based experimental testing is expected to form the core of near- and medium-term scramjet development. Ground-based experimental testing, however, does not enable a perfect simulation of flight conditions. The test medium is often not pure air, testing is usually subscale, and many boundary conditions, such as inflow velocity, temperature, density and Mach number, as well as wall temperatures, are not spatially or temporally matched. If scramjet performance and operation is to be fully understood and predicted, then the effects of these imperfect simulations must be quantified. This presentation will focus on some of the key test technique effects for a particular class of scramjet called a dual-mode scramjet. Specifically, the effect of test gas vitiation on combustion propagation and flameholding will be examined. Spatial and temporal non-uniformities in combustor thermal boundary conditions, including flow thermal non-equilibrium effects, will also be examined. With these concepts in mind, control approaches for dual-mode scramjet testing in wind tunnels will also be presented. Finally, given the potential application of scramjet propulsion to space access and the presenter's role in higher education, the presentation will conclude with a description of a stimulating way to improve the pedagogy of undergraduate spacecraft design instruction using high altitude balloon flight testing and cubesats.
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Speaker Bio:
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Dr. Christopher Goyne is an Associate Professor of Mechanical and Aerospace Engineering and the Director of the Aerospace Research Laboratory at the University of Virginia. Dr. Goyne obtained a Ph.D. and Bachelor of Engineering from the University of Queensland in Australia. He has 25 years of research experience in the fields of high-speed aerodynamics, diagnostic development, controls and scramjet ground and flight testing. Dr. Goyne has published and presented his research through 150 international journal articles, conference publications, patents, reports and invited presentations. He is an Associate Fellow of the American Institute of Aeronautics and Astronautics (AIAA) and, within this organization, is a past Chair of the Hypersonic Technology and Aerospace Planes Program Committee. Dr. Goyne is currently the Chair of the Virginia Space Grant Consortium Advisory Council and a member of the Small Sat Virginia Initiative Steering Committee. He is also an Associate Editor for the Shock Waves journal.
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112th NIA CFD Seminar:
04-24-2019
11:00am-noon (EDT)
NIA Room 137
video
Grid-Adaptation for Large Eddy Simulations
While grid-adaptation has reached a certain level of maturity in several areas of CFD, the application to turbulence-resolving simulations (most notably, LES) is still in its infancy. The chaotic and broadband nature of the dynamics in an LES leads to 2 major challenges. First, the grid affects both the numerical and modeling error in LES, compared to only the numerical error in non-broadband problems. As a result, the estimation of the local error production can not be purely mathematical but must also require physics-informed reasoning and assumptions. Secondly, the chaotic nature causes adjoints to diverge exponentially, which makes direct application of the adjoint-weighted residual method cumbersome. The talk will discuss 3 separate approaches to this problem that have been developed in the PI's group over the last couple of years, with applications to turbulent channel flow and the flow over a backward-facing step. Outstanding issues and ongoing/future work will be discussed, with some emphasis on the ongoing/planned work under the current NRA-funded project to merge wall-modeled LES with algorithms for grid-adaptation and adaptively finding the optimal thickness of the wall-modeled layer.
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Speaker Bio:
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Johan Larsson is an Associate Professor at the University of Maryland where he works on multiple problems
in the field of computational turbulence including wall-modeling for large eddy simulation,
grid-adaptation for turbulence-resolving simulations, high-speed turbulent flows, and
uncertainty quantification for turbulence problems.
He earned his PhD at the University of Waterloo, Canada, in 2006, and then worked at the
Center for Turbulence Research at Stanford University as a postdoctoral fellow and
Research Associate for 6 years before joining the University of Maryland in 2012.
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111th NIA CFD Seminar:
04-11-2019
11:00am-noon (EDT)
NIA Room 137
video
Numerical investigation of noise sources and noise mitigation strategies for Ultra High Bypass Ratio engines
The development of Ultra High Bypass Ratio (UHBR) engines, to reduce both fuel consumption and noise pollution, is creating new challenges for the aeroacoustics community. UHBR are characterized by larger fan diameter, lower rotational speed of the fan and lower jet core velocity. Consequence is that jet noise is decreasing while other sources of noise, such as jet installation noise and rotor/stator interaction noise, become dominant. At the same time, well-established noise mitigation technologies such as acoustic liners are challenged to accommodate the lower rotational velocity of the fan. In this talk, an overview of the Computational Aeroacoustics research in this field carried out at TU Delft, aiming at identifying the physical mechanisms and developing physics-based noise reduction strategies, will be presented.
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Speaker Bio:
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Francesco Avallone is Assistant Professor at the AWEP Department, Wind Energy Section, at Delft University of Technology. He received both his MSc and PhD degrees from the University of Naples Federico II. His PhD focused on non-intrusive techniques for boundary layer transition in hypersonic flows. In 2015, he joined Delft University of Technology as PostDoc in Aeroacoustics. During this period, he worked on turbulent boundary layer trailing edge noise mitigation with innovative trailing edge serrations. Since July 2017, he is Assistant Professor. His research interests are airfoil self-noise, acoustic liners and jet installation noise. For his research he uses both experimental and computational techniques.
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110th NIA CFD Seminar:
03-19-2019
11:00am-noon (EDT)
NIA Room 137
video
Integrated Field Inversion and Machine Learning With Embedded Neural Network Training
A new approach is presented towards the end of developing data-augmented models. The goal is to effectively reduce model form errors in a Reynolds Averaged Navier-Stokes setting. Since the information required for model improvement is not directly available in higher fidelity simulation or experimental data, model augmentations have to be extracted from the data using the solution of inverse problems. Existing data-driven turbulence modeling approaches either ignore the inference step - in which case, learning is applied directly on the data - or separate the inference and learning steps. In the proposed approach, the learning step is integrated into the field inversion process. This integrated approach ensures that the process generates learnable model discrepancy, and thus results in a consistent machine learned model that can be embedded in a predictive setting. Additionally, a new layered approach is proposed to train neural networks, demonstrating the promise to greatly reduce training time. In this presentation I will present two methods of integrated learning during field inversion, and will discuss recent results on both a simple model problem and RANS applications using the Stanford University Unstructured (SU2) code.
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Speaker Bio:
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Jon Holland completed his undergraduate work at the University of Notre Dame, and is currently an Aerospace Engineering Ph.D. Candidate at the University of Maryland, College Park. With advisors Dr. James Baeder at University of Maryland and Dr. Karthik Duraisamy at University of Michigan Jon has been studying methods for augmenting physics based simulations with data.
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109th NIA CFD Seminar:
03-14-2019
2pm-3pm (EDT)
NIA Room 137
video
In-Tunnel CFD Simulation of the HL-CRM in the LaRC 14 x 22 ft Wind Tunnel - Part I: Empty Tunnel Simulation Approaches and Verification Using TAU-DRSM
The presentation summarizes preparatory studies for envisaged in-tunnel simulations of the HL-CRM in the LaRC 14 x 22 ft. wind tunnel. Corresponding tests have been conducted in late 2018. DLR's in-tunnel simulation approach based on RANS computations is outlined and verified against existing empty tunnel computations of the 14 x22 ft wind tunnel carried out using FUN3D and USM3D. Based on this verification, different numerical approaches for the computation of the so-called high speed leg of the tunnel are compared. In this context, modification of the inlet and the diffuser are presented. Finally, a grid refinement study for the flow in the empty high speed leg is presented in order to highlight impacts of grid resolution on flow features in the rectangular duct. The studies are carried out using DLR's TAU code in conjunction with a differential variant of the SSG/LRR Reynolds Stress turbulence model.
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Speaker Bio:
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Prof. Dr. Ralf Rudnik is from DLR, German Aerospace Center at the Institute of Aerodynamics and Flow Technology in Braunschweig, Germany, holds a Diploma in Aerospace Engineering from the Technical University Braunschweig and a PhD in Aerodynamics from the Technical University of Berlin. Since 2003, he is Head of the Transport Aircraft Branch at the Institute of Aerodynamics and Flow Technology, and External professor of the Technical University of Baunschweig (lecturer for configuration aerodynamics). His research fields are high lift aerodynamics engine/airframe integration, CFD and turbulence model validation. Since 2009, he is a member of the Organizing Committee of the AIAA High Lift Prediction Workshops.
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108th NIA CFD Seminar:
10-01-2018
11:00am-noon (EDT)
NIA Room 137
video
Overset mesh and related technology in scFLOW
scFLOW is a commercial CFD code developed by Software Cradle since 2016. I introduced the overset mesh technology of SC/Tetra at NIA seminar in 2014. scFLOW is a successor product of SC/Tetra. scFLOW is based on a cell-centered discretization while SC/Tetra is based on a node-centered discretization. Unstructured polyhedral cells can be used for a computational mesh, and both pressure-based and density-based FVM solvers have been implemented for incompressible and compressible flows. Overset mesh technology is introduced aiming to analyze a flow around objects with complex motions. Hole-cutting process is realized using alternating digital tree (ADT) data structure and inclusion determination based on the X-rays algorithm. scFLOW's overset mesh technology can be coupled with physical functions such as free surface analysis, 6-DOF mechanism analysis and flow-structure interaction (FSI) analysis. The density-based scheme coupled with the overset mesh technology is especially effective for analyzing a moving object in a high-Mach number compressible flow. Numerical results of basic verification and engineering application are shown in this presentation.
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Speaker Bio:
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Tomohiro Irie is a group leader of Software Engineering Department at Software Cradle Co., Ltd. in charge scFlow solver development.
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107th NIA CFD Seminar:
09-27-2018
11:00am-noon (EDT)
NIA Room 101
video
Solutions of Boundary Value and Periodic Problems for Flexible Multibody Dynamics Systems
Traditionally, the solution of flexible multibody dynamics problems is obtained via time marching. Many problems, however, are formulated as boundary value or periodic problems. The dynamic response of flexible multibody systems will be investigated via the finite element method, within the framework of the motion formalism, which leads to governing equations presenting low-order nonlinearities. Boundary value and periodic problems require global interpolation schemes that approximate the unknown motion fields over the system's entire period of response. The classical interpolation schemes developed for linear fields cannot be used for the nonlinear configuration manifolds, such as SO(3) or SE(3), that are used to describe the kinematics of multibody systems. Furthermore, the configuration and velocity fields are related through nonlinear kinematic compatibility equations.
It seems natural to implement the collocation version of the Fourier spectral method to determine periodic solutions of flexible multibody systems. Clearly, special procedures must be developed to adapt the Fourier spectral approach to flexible multibody systems. Assembly of the linearized governing equations at all the grid points leads to the governing equations of the spectral method. Numerical examples illustrate the performance of the proposed approach.
For periodic and boundary value problems, an approach based on the assembly of time- discretized elements provides an alternative approach to the problem. While it does not achieve the exponential convergence of Fourier spectral methods, it is computationally effective. The classical time integration schemes used in structural and multibody dynamics, such as the generalized-&alpha schemes, are not suitable for this approach. Time-discontinuous Galerkin schemes will be shown to be well suited for the solution of such problems.
The development of rigorous motion interpolation schemes also leads to interesting schemes for the spatial discretization of beam and shells. Spectral beam elements will be presented that are far simpler to implement than their counterparts based on the shape function used in classical finite element methods.
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presentation file (pdf)
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Olivier A. Bauchau |
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Speaker Bio:
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Dr. Bauchau earned his B.S. degree in engineering at the Université de Ličge, Belgium, and M.S. and Ph.D. degrees from the Massachusetts Institute of Technology. He has been a faculty member of the Department of Mechanical Engineering, Aeronautical Engineering, and Mechanics at the Rensselaer Polytechnic Institute in Troy, New York (1983-1995), a faculty member of the Daniel Guggenheim School of Aerospace Engineering of the Georgia Institute of Technology in Atlanta, Georgia (1995-2010), a faculty member of the University of Michigan Shanghai Jiao Tong University Joint institute in Shanghai, China (2010-2015). He is now Igor Sikorsky Professor of Rotorcraft and Langley Professor at the Department of Aerospace Engineering at the University of Maryland.
His fields of expertise include finite element methods for structural and multibody dynamics, rotorcraft and wind turbine comprehensive analysis, and flexible multibody dynamics. He is a Fellow of the American Society of Mechanical Engineers, a Technical Fellow of the American Helicopter Society, and a Fellow of the American Institute of Aeronautics and Astronautics. His book entitled "Flexible Multibody Dynamics" has won the 2012 Textbook Excellence Award from the Text and Academic Authors Association. He is the 2015 recipient of the ASME d'Alembert award for lifelong contributions to the field of multibody system dynamics.
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106th NIA CFD Seminar:
09-24-2018
11:00am-noon (EDT)
NIA Room 141
video
DNS of Roughness-Induced Transition in the Boundary Layer of a Hypersonic Spherical Forebody
The laminar-turbulent transition of the boundary layer on spherical forebodies at hypersonic speeds is a fundamental and yet not fully understood problem. Laminar-turbulent transition significantly impacts on skin friction and heat-transfer rates at the wall and, thus, its understanding is related to reliability and costs of re-entry vehicles.
Numerous experimental investigations have been conducted on capsule models with roughness in the last decades. However, further numerical investigations based on new computational methods are still needed. Compared to stability analysis (e.g. linear stability theory and parabolized stability equations), Direct Numerical Simulations allow for a more complete insight into non-linear instability mechanisms. Furthermore, as wind-tunnel experiments at realistic re-entry conditions matching all relevant dimensionless parameters, including the Damköhler number, are extremely difficult to realize, numerical simulations represent an important and often non-substitutable investigation tool.
In this talk, I will present the instability mechanisms in the boundary layer of a capsule-like geometry in the presence of a patch of (pseudo-)random distributed roughness. A set of different simulations are conducted for freestream conditions matching both wind-tunnel (Ma=6) and realistic re-entry (Ma=20) scenarios. In the case of re-entry conditions, the gradual inclusion of chemical and thermal non-equilibrium in the gas modeling will show the influence of the high temperature on the stability properties of the reacting boundary layer in the roughness wake.
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Speaker Bio:
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Antonio Di Giovanni is a PhD student at the Technical University of Munich, Germany. His research includes stability investigations on high-enthalpy hypersonic boundary layers. Current research projects comprehend studies of roughness-induced transition on capsule geometries and Görtler instabilities under consideration of non-equilibrium effects.
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105th NIA CFD Seminar:
09-18-2018
11:00am-noon (EDT)
NIA Room 137
video
Three-Dimensional Prism-Dominant Mesh Generation for Viscous Flows Around Surface Slope Discontinuities
The NASA CFD Vision 2030 Study has identified mesh generation to be a significant bottleneck in the CFD pipeline. Human intervention is often required due to a lack of robustness and automation while generating the mesh. An automated approach to generating unstructured three-dimensional, prism-dominant meshes for viscous flows is presented. Meshes comprised of prisms are advantageous because they yield a more accurate solution and have fewer elements than their purely-tetrahedral mesh counterpart. An extrusion-based approach using multiple normals is used where anisotropic prisms are formed from the surface mesh facets and blend prisms are used to fill the cavities between multiple normals. Multiple normals are needed at a node to satisfy the visibility requirement for all incident surface facets. These multiple normals arise at regions of the surface mesh where there are convex discontinuities in the slope of the surface across edges. Nodes where blend region meshes must be formed are classified using an exhaustive enumeration scheme based on the number of convex edges and concave edges that are incident upon the node. Templates are presented to robustly mesh all the enumerated types of blend regions that occur at ridges, cusps, and corner nodes, including non-Lipschitz nodes. Intersections are detected in the boundary layer using an efficient spatial partitioning tree and are treated using Laplacian smoothing of the normal vectors or by reducing the total height of the boundary layer in the identified regions. The remainder of the volume is then tetrahedralized with an isotropic Delaunay mesh generator.
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Speaker Bio:
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Juliette Pardue is a Ph.D. candidate in Computer Science at Old Dominion University under Dr. Andrey Chernikov and Dr. Nikos Chrisochoides. She is part of the Center for Real Time Computing, National Institute of Aerospace, and NASA Langley. Her research interests include mesh generation, parallel algorithms, computational fluid dynamics, and computational geometry. She has been published in the International Meshing Roundtable, the International Conference on Parallel Processing where her paper won the best paper award, the Virginia Modeling, Analysis, and Simulation Center Capstone Conference, and AIAA's Aviation Fluid Dynamics Conference. The first revision of her 2D distributed-memory parallel mesh generation work and code are currently under review by ACM's Transactions on Mathematical Software.
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104th NIA CFD Seminar:
08-22-2018
11:00am-noon (EDT)
NIA Room 141
video
Sensitivity analysis of flexible multibody systems with application to rotor dynamics
The combination of analysis and optimization methods in mechanical engineering, also known as design optimization, has great potential in product development. In turn, robust sensitivity analyses that provide reliable and efficient objective function gradients play a key role in design optimization. This paper presents a discrete adjoint method for the sensitivity analysis of flexible mechanical systems. The ultimate goal is to be able to relate the physical properties of beam cross-sections to the dynamic behavior of the system, which is key to design realistic flexible elements. The underlying flexible multibody formulation is one that supports large-amplitude motion, beams with sophisticated composite cross-sections, and kinematic joints. A summary of the kinematic and dynamic foundations of the forward equations is presented first. Then, a discrete adjoint method, along with meaningful examples and validation, is presented. The method has proven to provide accurate and reliable sensitivities.
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Speaker Bio:
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Alfonso Callejo graduated in Industrial Engineering from the University of Navarra in 2008 and obtained a Master's Degree in Mechanical Engineering from the Technical University of Madrid in 2010. He obtained a Ph.D. in Mechanical Engineering at the University Institute for Automobile Research in 2013, entitled "Dynamic Response Optimization of Vehicles through Efficient Multibody Formulations and Automatic Differentiation Techniques". During his Ph.D., he conducted research at the Motion Research Group of the University of Waterloo. In 2013 he joined the National Institute for Aviation Research at Wichita State University. From 2014 to 2016 he was a Postdoctoral Fellow at McGill University's Centre for Intelligent Machines. Dr. Callejo is currently an Asst. Research Scientist at the University of Maryland. His research interests are in the areas of Efficient Multibody Formulations, Flexible Multibody Systems and Sensitivity Analysis.
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103rd NIA CFD Seminar:
07-24-2018
11:00am-noon (EDT)
NIA Room 137
video
Study of High-Speed Transition due to Roughness Elements
Transitional hypersonic boundary layers due to diamond-shaped and cylindrical roughness elements (passive tripping) are studied using direct numerical simulations (DNS). A low Reynolds number experiment, consisting of an array of diamond-shaped roughness elements (Semper & Bowersox 2017), and a high Reynolds number experiment, consisting of an array of cylindrical roughness elements (Williams et al. 2018), are used to validate our simulations. Three dynamically prominent flow structures are consistently observed in both arrays as well as in their respective isolated roughness configurations. These flow structures are the upstream vortex system, the shock system, and the shear layers and the counter-rotating streamwise vortices from the wake of the roughness elements. Analysis of the power spectral density (PSD) reveals the dominant source of instability due to the diamond-shaped roughness elements as a coupled system of the shear layers and the counter-rotating streamwise vortices irrespective of spanwise roughness-spacing (isolated roughness and roughness-array). However, the dominant source of instability due to the cylindrical roughness elements is observed to be the upstream vortex system irrespective of spanwise roughness-spacing. Therefore, the shape of a roughness element plays an important role in the instability mechanism. Furthermore, dynamic mode decomposition (DMD) of three-dimensional snapshots of pressure fluctuations unveil globally dominant modes consistent with the PSD analysis in all the roughness configurations.
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Speaker Bio:
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Prakash Shrestha is a doctoral candidate in the Department of Aerospace Engineering and Mechanics at University of Minnesota-Twin Cities. Currently, he is working at National Institute of Aerospace (NIA) as a summer visiting student with Scott Berry, NASA Langley Research Center (LaRC), in high-speed transition due to wall-injectors. His research interests include boundary-layer stability, transition to turbulence, modal analysis, complex grid-generation, supersonics, and hypersonics.
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102nd NIA CFD Seminar:
06-20-2018
11:00am-noon (EDT)
NIA Room 137
video
A GPU Accelerated Adjoint Solver for Shape Optimization
A graphics processing units (GPUs) accelerated adjoint-based optimization platform is proposed in this paper. Significant speed up gains and strong linear scalability of an existing in-house developed three-dimensional structured GPU Reynolds Averaged Navier-Stokes solver is presented first. As a first step towards the proposed GPU adjoint solver, a two-dimensional structured adjoint Euler solver is developed. The adjoint solver is further utilized to set up an airfoil shape optimization framework in Python and demonstrated for an airfoil shape optimization inverse problem. The two-dimensional adjoint Euler solver is extended to incorporate GPU acceleration using Compute Unified Device Architecture (CUDA) kernels and named ADjoint-GARfield (ADGAR). The adjoint optimization platform, ADGAR, is verified to a high accuracy of 14 significant digits with the serial adjoint Euler solver. Diagonalized Alternate Direction Implicit (DADI) iterative implicit schemes for both the forward and adjoint formulations are implemented and accelerated using CUDA kernels. The GPU accelerated structured code is finally successfully utilized to perform several airfoil shape optimizations for inverse design problems. Significant speedup up to 20x is observed using ADGAR for computations on a single GPU over a single CPU core.
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Speaker Bio:
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Asitav Mishra is an Assistant Research Scientist in the Department of Aerospace Engineering at the University of Maryland as well as at the NIA since Oct 2017. His earlier research experiences include post-doctoral scholar positions at the University of Michigan (2015-2017) and the University of Wyoming (2012-2015) following his Ph.D in Aerospace Engineering from the University of Maryland in 2012. His research interests include adjoint based coupled multi-disciplinary fixed and rotary-wing design optimization, vortex wake-lifting surface interactions as well as performance predictions in rotary wing flows, and high performance computing using heterogenous GPU/CPU computing paradigms applied to CFD problems.
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