Bio
I am the Robert Bosch Chair and a professor in the Mechanical Engineering Department (https://me.stanford.edu).
I received my PhD in Italy from the Politecnico di Bari in 2005 and have worked for several years at the Center for Turbulence Research (NASA Ames & Stanford) before joining the faculty at Stanford in 2007. Since 2014 I am the Director of the PSAAP Center at Stanford, funded by the US Department of Energy: a $20M research Center focused on multiphysics simulations, uncertainty quantification and exascale computing (http://exascale.stanford.edu).
In 2010, I received the Presidential Early Career Award for Scientists and Engineers (PECASE) award from President Obama. in the last couple of years, I received best paper awards from AIAA, ASME IMECE and Turbo Expo Conferences.
Over the years, my interests in research and teaching have touched many topics, but always revolved around the use of computing and data to solve problems in energy, biomedicine, aerodynamics, propulsion, design.
Academic Appointments
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Professor, Mechanical Engineering
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Member, Bio-X
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Affiliate, Precourt Institute for Energy
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Affiliate, Stanford Woods Institute for the Environment
Administrative Appointments
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Chair, Mechanical Engineering Department (2024 - Present)
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Senior Visiting Member, Institute for Advanced Studies, HKUST (Hong Kong) (2023 - 2023)
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Visiting Fellow, University of Melbourne (Australia) (2022 - 2023)
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Visiting Professor, Universita' di Napoli (Italy) (2022 - 2023)
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Director, ICME Institute for Computational and Mathematical Engineering (2018 - 2024)
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Visiting Professor, Ecole Centrale Paris (2016 - 2016)
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Director, Exascale Computing Engineering Center - PSAAP II (2014 - Present)
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Visiting Professor, Technical University of Munich (2011 - 2011)
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Director, TFSA Thermal and Fluid Sciences Industrial Affiliates Program (2010 - 2018)
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Professor, Mechanical Engineering Department, Stanford (2007 - Present)
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Postdoctoral Fellow, Mechanical Engineering Department, Stanford (2005 - 2007)
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Research Engineer, CTR, Center for Turbulence Research (1998 - 2005)
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Research Scientist, CIRA, Italian Center for Aerospace Research (1993 - 1998)
Honors & Awards
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Fellow of the American Physical Society (elected), APS (2019)
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TUM Ambassador, Technical University of Munich (2018)
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ASME IMECE Best Paper Award, ASME (2017)
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Jefferson Goblet Award, Best Paper, AIAA (2017)
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Turbo Expo Best Paper Award, ASME (2016)
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William R. and Inez Kerr Bell Faculty Scholar, Stanford University (2014)
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Gold Medal Honoring Italians Abroad, City of Piano di Sorrento (Italy) (2013)
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Associate Fellow of the American Institute of Aeronautics and Astronautics, AIAA (2011)
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Presidential Early Career Award for Scientists and Engineers, The White House & US Department of Energy (2010)
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Humboldt Fellowship, Humboldt Research Fellowship Program (2009)
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Terman Fellow, Stanford University (2007)
Boards, Advisory Committees, Professional Organizations
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Guest Editor, International Journal of Uncertainty Quantification (2019 - Present)
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Associate Editor, Computers and Fluids (2018 - Present)
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Associate Editor, Flow, Turbulence & Combustion (2015 - Present)
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Associate Editor, Journal of Computational Physics (2014 - Present)
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Co-Chair, APS Division of Fluid Dynamics Conference (2014 - 2014)
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AdCom, Advisory Committee to the Chair, Mechanical Engineer Department, Stanford (2013 - 2018)
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Associate Editor, ASME Applied Mechanics Review (2013 - 2017)
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General Chair (elected), AIAA XVI Non-Deterministic Approaches (2013 - 2013)
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Technical Chair (elected), AIAA XV Non-Deterministic Approaches (2013 - 2013)
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Associate Fellow, AIAA (2012 - Present)
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Member, SIAM, ASME, AIAA, APS (2010 - Present)
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Non-Deterministic Approaches Technical Committee, AIAA (2010 - Present)
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Member of the Board of Directors, Cascade Technologies Inc (2000 - Present)
Professional Education
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PhD, Politecnico di Bari, Italy, Mechanical Engineering (2005)
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MS, University di Napoli, Italy, Aeronautical Engineering (1993)
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BS, University di Napoli, Italy, Aeronautical Engineering (1992)
Patents
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ES Shaqfeh, G Iaccarino, P Shah. "United States Patent App. 15/435,112 Methods and Systems for Simulating Nanoparticle Flux", Leland Stanford Junior University, Sep 14, 2017
Current Research and Scholarly Interests
Computing and data for energy, health and engineering
Challenges in energy sciences, green technology, transportation, and in general, engineering design and prototyping are routinely tackled using numerical simulations and physical testing. Computations barely feasible two decades ago on the largest available supercomputers, have now become routine using turnkey commercial software running on a laptop. Demands on the analysis of new engineering systems are becoming more complex and multidisciplinary in nature, but exascale-ready computers are on the horizon. What will be the next frontier? Can we channel this enormous power into an increased ability to simulate and, ultimately, to predict, design and control? In my opinion two roadblocks loom ahead: the development of credible models for increasingly complex multi-disciplinary engineering applications and the design of algorithms and computational strategies to cope with real-world uncertainty.
My research objective is to pursue concerted innovations in physical modeling, numerical analysis, data fusion, probabilistic methods, optimization and scientific computing to fundamentally change our present approach to engineering simulations relevant to broad areas of fluid mechanics, transport phenomena and energy systems. The key realization is that computational engineering has largely ignored natural variability, lack of knowledge and randomness, targeting an idealized deterministic world. Embracing stochastic scientific computing and data/algorithms fusion will enable us to minimize the impact of uncertainties by designing control and optimization strategies that are robust and adaptive. This goal can only be accomplished by developing innovative computational algorithms and new, physics-based models that explicitly represent the effect of limited knowledge on the quantity of interest.
Multidisciplinary Teaching
I consider the classical boundaries between disciplines outdated and counterproductive in seeking innovative solutions to real-world problems. The design of wind turbines, biomedical devices, jet engines, electronic units, and almost every other engineering system requires the analysis of their flow, thermal, and structural characteristics to ensure optimal performance and safety. The continuing growth of computer power and the emergence of general-purpose engineering software has fostered the use of computational analysis as a complement to experimental testing in multiphysics settings. Virtual prototyping is a staple of modern engineering practice! I have designed a new undergraduate course as an introduction to Computational Engineering, covering theory and practice across multidisciplanary applications. The emphasis is on geometry modeling, mesh generation, solution strategy and post-processing for diverse applications. Using classical flow/thermal/structural problems, the course develops the essential concepts of Verification and Validation for engineering simulations, providing the basis for assessing the accuracy of the results.
Projects
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PSAAP Project, Stanford
PSAAP Stands for Predictive Science Academic Alliance Program; this is a large research project funded by the US Department of Energy and the National Nuclear Security Administration (https://exascale.stanford.edu/)
Location
Stanford
2024-25 Courses
- Computational Engineering
ME 123 (Aut) - Computational Methods in Fluid Mechanics
CME 369, ME 469 (Spr) -
Independent Studies (15)
- Curricular Practical Training
CME 390 (Aut, Win, Spr, Sum) - Engineering Problems
ME 391 (Aut, Win, Spr, Sum) - Engineering Problems and Experimental Investigation
ME 191 (Aut, Win, Spr, Sum) - Experimental Investigation of Engineering Problems
ME 392 (Aut, Win, Spr, Sum) - Honors Research
ME 191H (Aut, Win, Spr, Sum) - Master's Directed Research
ME 393 (Aut, Win, Spr, Sum) - Master's Directed Research: Writing the Report
ME 393W (Aut, Win, Spr, Sum) - Master's Research
CME 291 (Aut, Win, Spr, Sum) - Ph.D. Research
CME 400 (Aut, Win, Spr, Sum) - Ph.D. Research Rotation
CME 391 (Aut, Win, Spr, Sum) - Ph.D. Research Rotation
ME 398 (Aut, Win, Spr, Sum) - Ph.D. Teaching Experience
ME 491 (Aut, Win, Spr) - Practical Training
ME 199A (Win, Spr) - Practical Training
ME 299A (Aut, Win, Spr, Sum) - Practical Training
ME 299B (Aut, Win, Spr, Sum)
- Curricular Practical Training
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Prior Year Courses
2023-24 Courses
- Computational Engineering
ME 123 (Spr) - First Year Seminar Series
CME 300 (Aut) - Linear Algebra with Application to Engineering Computations
CME 200, ME 300A (Aut)
2022-23 Courses
- First Year Seminar Series
CME 300 (Aut)
2021-22 Courses
- Computational Engineering
ME 123 (Aut) - Computational Methods in Fluid Mechanics
CME 369, ME 469 (Spr) - Departmental Seminar
CME 500 (Win) - First Year Seminar Series
CME 300 (Aut) - ICME QUALIFYING EXAMS WORKSHOP
CME 300Q (Spr)
- Computational Engineering
Stanford Advisees
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Doctoral Dissertation Reader (AC)
Brian Munguía, Christopher Williams, Andy Wu -
Orals Chair
Saied Mahdian -
Doctoral Dissertation Advisor (AC)
Mark Benjamin -
Doctoral Dissertation Co-Advisor (AC)
NEELANJAN AKULI, Chloe Choi, Albo Voci -
Master's Program Advisor
Jeffrey Gu, Jiubo Huang, Daniel Paul Kunin -
Doctoral (Program)
Izabel Aguiar, Ayya Alieva, Henry Collis, Leah Collis, Shaun Datta, Tiffany Fan, Devansh Jalota, Nikita Kozak, Trevor Maxfield, Caleb Redshaw, Joshua Rozner, Jimmy Smith, Xun Tang, David Zhang -
Postdoctoral Research Mentor
Tony Zahtila
All Publications
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A physics-informed machine learning model for the prediction of drop breakup in two-phase flows
INTERNATIONAL JOURNAL OF MULTIPHASE FLOW
2024; 180
View details for DOI 10.1016/j.ijmultiphaseflow.2024.104934
View details for Web of Science ID 001294056600001
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Computational Study of Laser-Induced Modes of Ignition in a Coflow Combustor
FLOW TURBULENCE AND COMBUSTION
2024
View details for DOI 10.1007/s10494-024-00575-x
View details for Web of Science ID 001293501700001
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Laser-induced indirect ignition of non-premixed turbulent shear layers
COMBUSTION AND FLAME
2024; 264
View details for DOI 10.1016/j.combustflame.2024.113426
View details for Web of Science ID 001222690000001
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Uncertainty quantification in autoencoders predictions: Applications in aerodynamics
JOURNAL OF COMPUTATIONAL PHYSICS
2024; 506
View details for DOI 10.1016/j.jcp.2024.112951
View details for Web of Science ID 001219680700001
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Large-scale in-silico analysis of CSF dynamics within the subarachnoid space of the optic nerve.
Fluids and barriers of the CNS
2024; 21 (1): 20
Abstract
Impaired cerebrospinal fluid (CSF) dynamics is involved in the pathophysiology of neurodegenerative diseases of the central nervous system and the optic nerve (ON), including Alzheimer's and Parkinson's disease, as well as frontotemporal dementia. The smallness and intricate architecture of the optic nerve subarachnoid space (ONSAS) hamper accurate measurements of CSF dynamics in this space, and effects of geometrical changes due to pathophysiological processes remain unclear. The aim of this study is to investigate CSF dynamics and its response to structural alterations of the ONSAS, from first principles, with supercomputers.Large-scale in-silico investigations were performed by means of computational fluid dynamics (CFD) analysis. High-order direct numerical simulations (DNS) have been carried out on ONSAS geometry at a resolution of 1.625 μm/pixel. Morphological changes on the ONSAS microstructure have been examined in relation to CSF pressure gradient (CSFPG) and wall strain rate, a quantitative proxy for mass transfer of solutes.A physiological flow speed of 0.5 mm/s is achieved by imposing a hydrostatic pressure gradient of 0.37-0.67 Pa/mm across the ONSAS structure. At constant volumetric rate, the relationship between pressure gradient and CSF-accessible volume is well captured by an exponential curve. The ONSAS microstructure exhibits superior mass transfer compared to other geometrical shapes considered. An ONSAS featuring no microstructure displays a threefold smaller surface area, and a 17-fold decrease in mass transfer rate. Moreover, ONSAS trabeculae seem key players in mass transfer.The present analysis suggests that a pressure drop of 0.1-0.2 mmHg over 4 cm is sufficient to steadily drive CSF through the entire subarachnoid space. Despite low hydraulic resistance, great heterogeneity in flow speeds puts certain areas of the ONSAS at risk of stagnation. Alterations of the ONSAS architecture aimed at mimicking pathological conditions highlight direct relationships between CSF volume and drainage capability. Compared to the morphological manipulations considered herein, the original ONSAS architecture seems optimized towards providing maximum mass transfer across a wide range of pressure gradients and volumetric rates, with emphasis on trabecular structures. This might shed light on pathophysiological processes leading to damage associated with insufficient CSF flow in patients with optic nerve compartment syndrome.
View details for DOI 10.1186/s12987-024-00518-8
View details for PubMedID 38419077
View details for PubMedCentralID PMC10900650
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Toward accelerated data-driven Rayleigh-Bénard convection simulations.
The European physical journal. E, Soft matter
2023; 46 (7): 64
Abstract
A hybrid data-driven/finite volume method for 2D and 3D thermal convective flows is introduced. The approach relies on a single-step loss, convolutional neural network that is active only in the near-wall region of the flow. We demonstrate that the method significantly reduces errors in the prediction of the heat flux over the long-time horizon and increases pointwise accuracy in coarse simulations, when compared to direct computations on the same grids with and without a traditional subgrid model. We trace the success of our machine learning model to the choice of the training procedure, incorporating both the temporal flow development and distributional bias.
View details for DOI 10.1140/epje/s10189-023-00302-w
View details for PubMedID 37505317
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Neural networks for large eddy simulations of wall-bounded turbulence: numerical experiments and challenges.
The European physical journal. E, Soft matter
2023; 46 (7): 55
Abstract
We examine the application of neural network-based methods to improve the accuracy of large eddy simulations of incompressible turbulent flows. The networks are trained to learn a mapping between flow features and the subgrid scales, and applied locally and instantaneously-in the same way as traditional physics-based subgrid closures. Models that use only the local resolved strain rate are poorly correlated with the actual subgrid forces obtained from filtering direct numerical simulation data. We see that highly accurate models in a priori testing are inaccurate in forward calculations, owing to the preponderance of numerical errors in implicitly filtered large eddy simulations. A network that accounts for the discretization errors is trained and found to be unstable in a posteriori testing. We identify a number of challenges that the approach faces, including a distribution shift that affects networks that fail to account for numerical errors.
View details for DOI 10.1140/epje/s10189-023-00314-6
View details for PubMedID 37458832
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Differentiable Control for Adaptive Wake Steering
IEEE. 2023: 165-170
View details for Web of Science ID 001027160300022
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SIMULTANEOUS IDENTIFICATION AND DENOISING OF DYNAMICAL SYSTEMS
SIAM JOURNAL ON SCIENTIFIC COMPUTING
2023; 45 (4): A1413-A1437
View details for DOI 10.1137/22M1486303
View details for Web of Science ID 001036538600001
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Machine Learning to Predict Aerodynamic Stall
INTERNATIONAL JOURNAL OF COMPUTATIONAL FLUID DYNAMICS
2022; 36 (7): 641-654
View details for DOI 10.1080/10618562.2023.2171021
View details for Web of Science ID 000933273100008
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Spinning-enabled wireless amphibious origami millirobot.
Nature communications
2022; 13 (1): 3118
Abstract
Wireless millimeter-scale origami robots have recently been explored with great potential for biomedical applications. Existing millimeter-scale origami devices usually require separate geometrical components for locomotion and functions. Additionally, none of them can achieve both on-ground and in-water locomotion. Here we report a magnetically actuated amphibious origami millirobot that integrates capabilities of spinning-enabled multimodal locomotion, delivery of liquid medicine, and cargo transportation with wireless operation. This millirobot takes full advantage of the geometrical features and folding/unfolding capability of Kresling origami, a triangulated hollow cylinder, to fulfill multifunction: its geometrical features are exploited for generating omnidirectional locomotion in various working environments through rolling, flipping, and spinning-induced propulsion; the folding/unfolding is utilized as a pumping mechanism for controlled delivery of liquid medicine; furthermore, the spinning motion provides a sucking mechanism for targeted solid cargo transportation. We anticipate the amphibious origami millirobots can potentially serve as minimally invasive devices for biomedical diagnoses and treatments.
View details for DOI 10.1038/s41467-022-30802-w
View details for PubMedID 35701405
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Task-parallel in situ temporal compression of large-scale computational fluid dynamics data
INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS
2022
View details for DOI 10.1177/10943420221085000
View details for Web of Science ID 000786636800001
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When Are Allowables Conservative?
AIAA JOURNAL
2021; 59 (5): 1760-1772
View details for DOI 10.2514/1.J059578
View details for Web of Science ID 000647156500020
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Extending bluff-and-fix estimates for polynomial chaos expansions
JOURNAL OF COMPUTATIONAL SCIENCE
2021; 50
View details for Web of Science ID 000697573900007
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Learning to differentiate
JOURNAL OF COMPUTATIONAL PHYSICS
2021; 424
View details for DOI 10.1016/j.jcp.2020.109873
View details for Web of Science ID 000588203600029
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Extending bluff-and-fix estimates for polynomial chaos expansions
Journal of Computational Science
2021; 50: 101287
View details for DOI 10.1016/j.jocs.2020.101287
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Pass-efficient methods for compression of high-dimensional turbulent flow data
JOURNAL OF COMPUTATIONAL PHYSICS
2020; 423
View details for DOI 10.1016/j.jcp.2020.109704
View details for Web of Science ID 000588199000039
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A benchmark for particle-laden turbulent duct flow: A joint computational and experimental study
INTERNATIONAL JOURNAL OF MULTIPHASE FLOW
2020; 132
View details for DOI 10.1016/j.ijmultiphaseflow.2020.103410
View details for Web of Science ID 000601063300006
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Design exploration and optimization under uncertainty
PHYSICS OF FLUIDS
2020; 32 (8)
View details for DOI 10.1063/5.0020858
View details for Web of Science ID 000563493800001
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Uncertainty quantification of combustion noise by generalized polynomial chaos and state-space models
COMBUSTION AND FLAME
2020; 217: 113–30
View details for DOI 10.1016/j.combustflame.2020.03.010
View details for Web of Science ID 000537624000013
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Data-driven dimensional analysis of heat transfer in irradiated particle-laden turbulent flow
INTERNATIONAL JOURNAL OF MULTIPHASE FLOW
2020; 125
View details for DOI 10.1016/j.ijmultiphaseflow.2019.103198
View details for Web of Science ID 000525874000017
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Bi-fidelity approximation for uncertainty quantification and sensitivity analysis of irradiated particle-laden turbulence
JOURNAL OF COMPUTATIONAL PHYSICS
2020; 402
View details for DOI 10.1016/j.jcp.2019.108996
View details for Web of Science ID 000503387600012
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MULTILEVEL MONTE CARLO SAMPLING ON HETEROGENEOUS COMPUTER ARCHITECTURES
INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION
2020; 10 (6): 575–94
View details for DOI 10.1615/Int.J.UncertaintyQuantification.2020033179
View details for Web of Science ID 000599583800005
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FOREWORD: SPECIAL ISSUE ON MULTILEVEL-MULTIFIDELITY APPROACHES FOR UNCERTAINTY QUANTIFICATION
INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION
2020; 10 (6): V-IX
View details for DOI 10.1615/Int.J.UncertaintyQuantification.v10.i6.10
View details for Web of Science ID 000599583800001
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MULTIFIDELITY MODELING OF IRRADIATED PARTICLE-LADEN TURBULENCE SUBJECT TO UNCERTAINTY
INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION
2020; 10 (6): 499–514
View details for DOI 10.1615/Int.J.UncertaintyQuantification.2020032236
View details for Web of Science ID 000599583800002
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Single-point structure tensors in turbulent channel flows with smooth and wavy walls
PHYSICS OF FLUIDS
2019; 31 (12)
View details for DOI 10.1063/1.5130629
View details for Web of Science ID 000505722900001
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Fast Precision Margin with the First-Order Reliability Method
AMER INST AERONAUTICS ASTRONAUTICS. 2019: 5042–53
View details for DOI 10.2514/1.J058345
View details for Web of Science ID 000501328200035
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Simulation of microparticle inhalation in rhesus monkey airways
PHYSICAL REVIEW FLUIDS
2019; 4 (8)
View details for DOI 10.1103/PhysRevFluids.4.083101
View details for Web of Science ID 000480243600001
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Cutting the double loop: Theory and algorithms for reliability-based design optimization with parametric uncertainty
INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING
2019; 118 (12): 718–40
View details for DOI 10.1002/nme.6035
View details for Web of Science ID 000467449900002
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Eigensensitivity analysis of subgrid-scale stresses in large-eddy simulation of a turbulent axisymmetric jet
INTERNATIONAL JOURNAL OF HEAT AND FLUID FLOW
2019; 77: 314–35
View details for DOI 10.1016/j.ijheatfluidflow.2019.04.014
View details for Web of Science ID 000471084900025
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Eigenvector perturbation methodology for uncertainty quantification of turbulence models
PHYSICAL REVIEW FLUIDS
2019; 4 (4)
View details for DOI 10.1103/PhysRevFluids.4.044603
View details for Web of Science ID 000463909300001
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Uncertainty Estimation Module for Turbulence Model Predictions in SU2
AIAA JOURNAL
2019; 57 (3): 1066–77
View details for DOI 10.2514/1.J057187
View details for Web of Science ID 000459609400016
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Estimating uncertainty in homogeneous turbulence evolution due to coarse-graining
PHYSICS OF FLUIDS
2019; 31 (2)
View details for DOI 10.1063/1.5080460
View details for Web of Science ID 000460093800072
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Quadrature Strategies for Constructing Polynomial Approximations
SPRINGER INTERNATIONAL PUBLISHING AG. 2019: 1–25
View details for DOI 10.1007/978-3-030-04870-9_1
View details for Web of Science ID 000505478300001
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Lurking Variable Detection via Dimensional Analysis
SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION
2019; 7 (1): 232–59
View details for DOI 10.1137/17M1155508
View details for Web of Science ID 000462645400010
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Turbulence Modeling in the Age of Data
ANNUAL REVIEW OF FLUID MECHANICS, VOL 51
2019; 51: 357–77
View details for DOI 10.1146/annurev-fluid-010518-040547
View details for Web of Science ID 000456389200014
- An Alternative Formulation for Design Under Uncertainty Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences Springer. 2019
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Immersed-finite-element method for deformable particle suspensions in viscous and viscoelastic media
PHYSICAL REVIEW E
2018; 98 (6)
View details for DOI 10.1103/PhysRevE.98.063316
View details for Web of Science ID 000454635700007
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Hierarchy of models for electrostatic comb-drive actuators in electrolytes
JOURNAL OF MICROMECHANICS AND MICROENGINEERING
2018; 28 (12)
View details for DOI 10.1088/1361-6439/aae9bb
View details for Web of Science ID 000450253500002
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Effects of particle polydispersity on radiative heat transfer in particle-laden turbulent flows
INTERNATIONAL JOURNAL OF MULTIPHASE FLOW
2018; 104: 42–59
View details for DOI 10.1016/j.ijmultiphaseflow.2018.03.011
View details for Web of Science ID 000432643700005
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Data-Free and Data-Driven RANS Predictions with Quantified Uncertainty
FLOW TURBULENCE AND COMBUSTION
2018; 100 (3): 593–616
View details for DOI 10.1007/s10494-017-9870-6
View details for Web of Science ID 000426863700001
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A Framework for Characterizing Structural Uncertainty in Large-Eddy Simulation Closures
FLOW TURBULENCE AND COMBUSTION
2018; 100 (2): 341–63
View details for DOI 10.1007/s10494-017-9844-8
View details for Web of Science ID 000424665400002
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DEMONSTRATING THE POTENTIAL OF A NOVEL MODEL TO IMPROVE OPEN-LOOP CONTROL OF ELECTROSTATIC COMB-DRIVE ACTUATORS IN ELECTROLYTES
AMER SOC MECHANICAL ENGINEERS. 2018
View details for Web of Science ID 000428486500022
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Suspension flow through an asymmetric T-junction
Journal of Fluid Mechanics
2018; 844
View details for DOI 10.1017/jfm.2018.183
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Application of QMU to the design of a nuclear waste storage tank
NUCLEAR ENGINEERING AND DESIGN
2017; 324: 379–89
View details for DOI 10.1016/j.nucengdes.2017.09.016
View details for Web of Science ID 000414699200033
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Uncertainty Estimation for Reynolds-Averaged Navier-Stokes Predictions of High-Speed Aircraft Nozzle Jets
AIAA JOURNAL
2017; 55 (11): 3999–4004
View details for DOI 10.2514/1.J056059
View details for Web of Science ID 000413944800033
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Growth of viscoelastic wings and the reduction of particle mobility in a viscoelastic shear flow
PHYSICAL REVIEW FLUIDS
2017; 2 (10)
View details for DOI 10.1103/PhysRevFluids.2.103302
View details for Web of Science ID 000413739100002
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Study of the flow unsteadiness in the human airway using large eddy simulation
PHYSICAL REVIEW FLUIDS
2017; 2 (8)
View details for DOI 10.1103/PhysRevFluids.2.083101
View details for Web of Science ID 000407447900001
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A low-rank control variate for multilevel Monte Carlo simulation of high-dimensional uncertain systems
JOURNAL OF COMPUTATIONAL PHYSICS
2017; 341: 121-139
View details for DOI 10.1016/j.jcp.2017.03.060
View details for Web of Science ID 000402211300008
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Fully resolved viscoelastic particulate simulations using unstructured grids
JOURNAL OF COMPUTATIONAL PHYSICS
2017; 338: 313-338
View details for DOI 10.1016/j.jcp.2017.02.068
View details for Web of Science ID 000400037800015
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Polynomial chaos assessment of design tolerances for vortex-induced vibrations of two cylinders in tandem
AI EDAM-ARTIFICIAL INTELLIGENCE FOR ENGINEERING DESIGN ANALYSIS AND MANUFACTURING
2017; 31 (2): 185-198
View details for DOI 10.1017/S0890060417000075
View details for Web of Science ID 000400957900006
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Efficient control variates for uncertainty quantification of radiation transport
JOURNAL OF QUANTITATIVE SPECTROSCOPY & RADIATIVE TRANSFER
2017; 189: 398-406
View details for DOI 10.1016/j.jqsrt.2016.12.033
View details for Web of Science ID 000394060900040
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Eigenspace perturbations for uncertainty estimation of single-point turbulence closures
PHYSICAL REVIEW FLUIDS
2017; 2 (2)
View details for DOI 10.1103/PhysRevFluids.2.024605
View details for Web of Science ID 000396067700002
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A generalized multi-resolution expansion for uncertainty propagation with application to cardiovascular modeling
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
2017; 314: 196-221
Abstract
Computational models are used in a variety of fields to improve our understanding of complex physical phenomena. Recently, the realism of model predictions has been greatly enhanced by transitioning from deterministic to stochastic frameworks, where the effects of the intrinsic variability in parameters, loads, constitutive properties, model geometry and other quantities can be more naturally included. A general stochastic system may be characterized by a large number of arbitrarily distributed and correlated random inputs, and a limited support response with sharp gradients or event discontinuities. This motivates continued research into novel adaptive algorithms for uncertainty propagation, particularly those handling high dimensional, arbitrarily distributed random inputs and non-smooth stochastic responses. In this work, we generalize a previously proposed multi-resolution approach to uncertainty propagation to develop a method that improves computational efficiency, can handle arbitrarily distributed random inputs and non-smooth stochastic responses, and naturally facilitates adaptivity, i.e., the expansion coefficients encode information on solution refinement. Our approach relies on partitioning the stochastic space into elements that are subdivided along a single dimension, or, in other words, progressive refinements exhibiting a binary tree representation. We also show how these binary refinements are particularly effective in avoiding the exponential increase in the multi-resolution basis cardinality and significantly reduce the regression complexity for moderate to high dimensional random inputs. The performance of the approach is demonstrated through previously proposed uncertainty propagation benchmarks and stochastic multi-scale finite element simulations in cardiovascular flow.
View details for DOI 10.1016/j.cma.2016.09.024
View details for Web of Science ID 000392782900012
View details for PubMedCentralID PMC5568857
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Vortex-induced rotations of a rigid square cylinder at low Reynolds numbers
JOURNAL OF FLUID MECHANICS
2017; 813: 482-507
View details for DOI 10.1017/jfm.2016.77
View details for Web of Science ID 000394376400024
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LEAST SQUARES APPROXIMATION OF POLYNOMIAL CHAOS EXPANSIONS WITH OPTIMIZED GRID POINTS
SIAM JOURNAL ON SCIENTIFIC COMPUTING
2017; 39 (5): A1991-A2019
View details for DOI 10.1137/15M1028303
View details for Web of Science ID 000415797300063
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PHYSICAL REVIEW FLUIDS
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AIAA JOURNAL
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Polynomial Chaos Methods for Hyperbolic Partial Differential Equations Numerical Techniques for Fluid Dynamics Problems in the Presence of Uncertainties Introduction
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View details for DOI 10.1007/978-3-319-10714-1_1
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2015: 23-29
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Numerical Solution of Hyperbolic Problems
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2015: 31-44
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Nonlinear Transport Under Uncertainty
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2015: 81-109
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View details for Web of Science ID 000372656800007
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2015: 47-80
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JOURNAL OF FLUID MECHANICS
2014; 755
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Nonlinear instability of a supersonic boundary layer with two-dimensional roughness
JOURNAL OF FLUID MECHANICS
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PHYSICS OF FLUIDS
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JOURNAL OF COMPUTATIONAL PHYSICS
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JOURNAL OF FLUIDS ENGINEERING-TRANSACTIONS OF THE ASME
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Local shear and mass transfer on individual coral colonies: Computations in unidirectional and wave-driven flows
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JOURNAL OF COMPUTATIONAL PHYSICS
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2014; 759
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JOURNAL OF COMPUTATIONAL PHYSICS
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7th International Symposium on Turbulence Heat and Mass Transfer (THMT)
ELSEVIER SCIENCE INC. 2013: 137–148
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COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
2013; 263: 42-55
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View details for Web of Science ID 000319952900007
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RELIABILITY ENGINEERING & SYSTEM SAFETY
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PHYSICS OF FLUIDS
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Simplex stochastic collocation with ENO-type stencil selection for robust uncertainty quantification
JOURNAL OF COMPUTATIONAL PHYSICS
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Chemical kinetic uncertainty quantification for Large Eddy Simulation of turbulent nonpremixed combustion
PROCEEDINGS OF THE COMBUSTION INSTITUTE
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View details for Web of Science ID 000313125400133
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Essentially Non-oscillatory Stencil Selection and Subcell Resolution in Uncertainty Quantification
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View details for Web of Science ID 000332623300008
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2013; 30 (8): 1054-1085
View details for DOI 10.1108/EC-05-2012-0110
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A sparse multiresolution stochastic approximation for uncertainty quantification
8th International Conference on Scientific Computing and Applications
AMER MATHEMATICAL SOC. 2013: 295–303
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View details for Web of Science ID 000319240200031
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JOURNAL OF FLUIDS ENGINEERING-TRANSACTIONS OF THE ASME
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View details for Web of Science ID 000314761300001
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AIAA JOURNAL
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JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS
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View details for Web of Science ID 000306881900013
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JOURNAL OF FLUIDS ENGINEERING-TRANSACTIONS OF THE ASME
2012; 134 (6)
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View details for Web of Science ID 000305267600001
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Risk Assessment of Scramjet Unstart Using Adjoint-Based Sampling Methods
AIAA JOURNAL
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View details for Web of Science ID 000301204700007
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JOURNAL OF FLUID MECHANICS
2012; 693: 297-318
View details for DOI 10.1017/jfm.2011.531
View details for Web of Science ID 000300022300012
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An Aerodynamic Investigation of an Isolated Stationary Formula 1 Wheel Assembly
JOURNAL OF FLUIDS ENGINEERING-TRANSACTIONS OF THE ASME
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View details for Web of Science ID 000302599000002
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Automotive Flow and Acoustic Predictions using Large Eddy Simulations
INTERNATIONAL JOURNAL OF FLUID MECHANICS RESEARCH
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FORWARD AND BACKWARD UNCERTAINTY PROPAGATION FOR DISCONTINUOUS SYSTEM RESPONSE USING THE PADE-LEGENDRE METHOD
INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION
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ASME Fluids Engineering Division Summer Meeting (FEDSM)
AMER SOC MECHANICAL ENGINEERS. 2012: 1–8
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SIMPLEX STOCHASTIC COLLOCATION WITH RANDOM SAMPLING AND EXTRAPOLATION FOR NONHYPERCUBE PROBABILITY SPACES
SIAM JOURNAL ON SCIENTIFIC COMPUTING
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Backward uncertainty propagation method in flow problems: Application to the prediction of rarefaction shock waves
COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING
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INTERNATIONAL JOURNAL OF HEAT AND FLUID FLOW
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JOURNAL OF FLUIDS ENGINEERING-TRANSACTIONS OF THE ASME
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RELIABILITY ENGINEERING & SYSTEM SAFETY
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View details for Web of Science ID 000293107900014
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A high-order numerical method to study hypersonic boundary-layer instability including high-temperature gas effects
PHYSICS OF FLUIDS
2011; 23 (8)
View details for DOI 10.1063/1.3614526
View details for Web of Science ID 000294483500027
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16th International Workshop on Numerical Methods for Non-Newtonian Flows
ELSEVIER SCIENCE BV. 2011: 554–65
View details for DOI 10.1016/j.jnnfm.2011.02.005
View details for Web of Science ID 000291286700004
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A FACTORIZATION OF THE SPECTRAL GALERKIN SYSTEM FOR PARAMETERIZED MATRIX EQUATIONS: DERIVATION AND APPLICATIONS
SIAM JOURNAL ON SCIENTIFIC COMPUTING
2011; 33 (5): 2995-3009
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A numerical study of scalar dispersion downstream of a wall-mounted cube using direct simulations and algebraic flux models
INTERNATIONAL JOURNAL OF HEAT AND FLUID FLOW
2010; 31 (5): 805-819
View details for DOI 10.1016/j.ijheatfluidflow.2010.05.006
View details for Web of Science ID 000281918600008
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JOURNAL OF COMPUTATIONAL PHYSICS
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View details for Web of Science ID 000277944400001
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JOURNAL OF FLUID MECHANICS
2010; 651: 415-442
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Disturbance evolution in a Mach 4.8 boundary layer with two-dimensional roughness-induced separation and shock
JOURNAL OF FLUID MECHANICS
2010; 648: 435-469
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Reynolds-averaged modeling of polymer drag reduction in turbulent flows
JOURNAL OF NON-NEWTONIAN FLUID MECHANICS
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View details for Web of Science ID 000276285000006
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ACTA MATHEMATICA SCIENTIA
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2010; 31 (5): 2681-2699
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Efficiency of Shock Capturing Schemes for Burgers' Equation with Boundary Uncertainty
SPRINGER-VERLAG BERLIN. 2010: 737-745
View details for DOI 10.1007/978-3-642-11795-4_79
View details for Web of Science ID 000395207900079
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Linear and non-linear disturbance evolution in a compressible boundary-layer with localized roughness
7th IUTAM Symposium on Laminar-Turbulent Transition
SPRINGER. 2010: 271–276
View details for DOI 10.1007/978-90-481-3723-7_43
View details for Web of Science ID 000277097200043
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SIAM JOURNAL ON NUMERICAL ANALYSIS
2010; 47 (6): 4073-4097
View details for DOI 10.1137/080741574
View details for Web of Science ID 000277836100003
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Stable Boundary Treatment for the Wave Equation on Second-Order Form
JOURNAL OF SCIENTIFIC COMPUTING
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View details for DOI 10.1007/s10915-009-9305-1
View details for Web of Science ID 000271272300003
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Numerical analysis of the Burgers' equation in the presence of uncertainty
JOURNAL OF COMPUTATIONAL PHYSICS
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View details for DOI 10.1016/j.jcp.2009.08.012
View details for Web of Science ID 000271342600011
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INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN ENGINEERING
2009; 80 (6-7): 868-880
View details for DOI 10.1002/nme.2564
View details for Web of Science ID 000271559400010
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Pade-Legendre approximants for uncertainty analysis with discontinuous response surfaces
JOURNAL OF COMPUTATIONAL PHYSICS
2009; 228 (19): 7159-7180
View details for DOI 10.1016/j.jcp.2009.06.024
View details for Web of Science ID 000269582300003
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JOURNAL OF COMPUTATIONAL PHYSICS
2009; 228 (18): 6753-6772
View details for DOI 10.1016/j.jcp.2009.05.036
View details for Web of Science ID 000269375000007
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JOURNAL OF COMPUTATIONAL PHYSICS
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View details for Web of Science ID 000268898200028
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A least-squares approximation of partial differential equations with high-dimensional random inputs
JOURNAL OF COMPUTATIONAL PHYSICS
2009; 228 (12): 4332-4345
View details for DOI 10.1016/j.jcp.2009.03.006
View details for Web of Science ID 000266506400004
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Accurate Immersed-Boundary Reconstructions for Viscous Flow Simulations
AIAA JOURNAL
2009; 47 (7): 1750-1760
View details for DOI 10.2514/1.42187
View details for Web of Science ID 000267676100017
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DNS of buoyancy-dominated turbulent flows on a bluff body using the immersed boundary method
JOURNAL OF COMPUTATIONAL PHYSICS
2009; 228 (9): 3189-3208
View details for DOI 10.1016/j.jcp.2008.12.037
View details for Web of Science ID 000265059100003
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Numerical simulation of scalar dispersion downstream of a square obstacle using gradient-transport type models
ATMOSPHERIC ENVIRONMENT
2009; 43 (16): 2518-2531
View details for DOI 10.1016/j.atmosenv.2009.02.044
View details for Web of Science ID 000266273300002
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A hybrid method for unsteady inviscid fluid flow
COMPUTERS & FLUIDS
2009; 38 (4): 875-882
View details for DOI 10.1016/j.compfluid.2008.09.010
View details for Web of Science ID 000264305000014
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Computational aspects of scalar dispersion modeling and simulation in complex flows
Conference on Scientific Computation in Physics
SOC ITALIANA FISICA. 2009: 257–60
View details for DOI 10.1393/ncc/i2009-10405-9
View details for Web of Science ID 000273305000052
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LES prediction of wall-pressure fluctuations and noise of a low-speed airfoil
INTERNATIONAL JOURNAL OF AEROACOUSTICS
2009; 8 (3): 177-197
View details for Web of Science ID 000280098800001
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Numerical simulation of scalar dispersion in separated flows using algebraic flux models
6th International Symposium on Turbulence, Heat and Mass Transfer
BEGELL HOUSE, INC. 2009: 413–416
View details for Web of Science ID 000312877800087
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MINIMAL REPETITION DYNAMIC CHECKPOINTING ALGORITHM FOR UNSTEADY ADJOINT CALCULATION
SIAM JOURNAL ON SCIENTIFIC COMPUTING
2009; 31 (4): 2549-2567
View details for DOI 10.1137/080727890
View details for Web of Science ID 000268859500007
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Stable and accurate wave-propagation in discontinuous media
JOURNAL OF COMPUTATIONAL PHYSICS
2008; 227 (19): 8753-8767
View details for DOI 10.1016/j.jcp.2008.06.023
View details for Web of Science ID 000259753700017
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An immersed boundary method for compressible flows using local grid refinement
JOURNAL OF COMPUTATIONAL PHYSICS
2007; 225 (2): 2098-2117
View details for DOI 10.1016/j.jcp.2007.03.008
View details for Web of Science ID 000255304500045
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LES on Cartesian grids with anisotropic refinement
Symposium on Complex Effects in Large Eddy Simulation
SPRINGER. 2007: 219-?
View details for Web of Science ID 000244562300016
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Towards time-stable and accurate LES on unstructured grids
Symposium on Complex Effects in Large Eddy Simulation
SPRINGER. 2007: 235-?
View details for Web of Science ID 000244562300017
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Complex effects in large eddy simulations
Symposium on Complex Effects in Large Eddy Simulation
SPRINGER. 2007: 1-?
View details for Web of Science ID 000244562300001
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Towards rapid analysis of turbulent flows in complex internal passages
6th International Symposium on Engineering Turbulence Modelling and Measurements (ETMM6)
SPRINGER. 2006: 27–39
View details for DOI 10.1007/s10494-006-9035-5
View details for Web of Science ID 000241258600003
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Natural and forced conjugate heat transfer in complex geometries on Cartesian adapted grids
JOURNAL OF FLUIDS ENGINEERING-TRANSACTIONS OF THE ASME
2006; 128 (4): 838-846
View details for DOI 10.1115/1.2201625
View details for Web of Science ID 000239418300021
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Large-eddy simulation of reacting turbulent flows in complex geometries
4th ASME/JSME Joint Fluids Engineering Conference
ASME. 2006: 374–81
View details for DOI 10.1115/1.2179098
View details for Web of Science ID 000237675800005
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Computational study on the internal layer in a diffuser
JOURNAL OF FLUID MECHANICS
2006; 550: 391-412
View details for DOI 10.1017/S0022112005008116
View details for Web of Science ID 000236195700020
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Near-wall behavior of RANS turbulence models and implications for wall functions
JOURNAL OF COMPUTATIONAL PHYSICS
2005; 204 (1): 265-291
View details for DOI 10.1016/j.jcp.2004.10.018
View details for Web of Science ID 000227733600013
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Immersed boundary methods
ANNUAL REVIEW OF FLUID MECHANICS
2005; 37: 239-261
View details for DOI 10.1146/annurev.fluid.37.061903.175743
View details for Web of Science ID 000226822300011
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Rapid techniques for measuring and modeling turbulent flows in complex geometries
6th International Symposium on Engineering Turbulence Modelling and Measurements (ETMM6)
ELSEVIER SCIENCE BV. 2005: 3–16
View details for Web of Science ID 000233989100001
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Numerical simulation of the flow around a circular cylinder at high Reynolds numbers
5th International Symposium on Engineering Turbulence Modelling and Measurements
ELSEVIER SCIENCE INC. 2003: 463–69
View details for DOI 10.1016/S0142-727X(03)00061-4
View details for Web of Science ID 000183511800006
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Reynolds averaged simulation of unsteady separated flow
INTERNATIONAL JOURNAL OF HEAT AND FLUID FLOW
2003; 24 (2): 147-156
View details for DOI 10.1016/S0142-727X(02)00210-2
View details for Web of Science ID 000181820200001
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Large eddy simulation of a road vehicle with drag-reduction devices
AIAA JOURNAL
2002; 40 (12): 2447-2455
View details for Web of Science ID 000179662000009
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Reynolds averaged simulation of flow and heat transfer in ribbed ducts
INTERNATIONAL JOURNAL OF HEAT AND FLUID FLOW
2002; 23 (6): 750-757
View details for Web of Science ID 000179180700003
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An approach to local refinement of structured grids
JOURNAL OF COMPUTATIONAL PHYSICS
2002; 181 (2): 639-653
View details for DOI 10.1006/jcph.2002.7147
View details for Web of Science ID 000178141700013
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Conjugate heat transfer predictions in two-dimensional ribbed passages
2nd International Symposium on Advances in Computational Heat Transfer
ELSEVIER SCIENCE INC. 2002: 340–45
View details for Web of Science ID 000176299600013
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Numerical simulation of the flow around a circular cylinder at high Reynolds number
5th International Symposium on Engineering Turbulence Modelling and Measurements
ELSEVIER SCIENCE BV. 2002: 657–665
View details for Web of Science ID 000178612700062
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Predictions of a turbulent separated flow using commercial CFD codes
JOURNAL OF FLUIDS ENGINEERING-TRANSACTIONS OF THE ASME
2001; 123 (4): 819-828
View details for Web of Science ID 000173027000011
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Heat transfer predictions in ribbed ducts and cavities
2nd International Symposium on Advances in Computational Heat Transfer
BEGELL HOUSE, INC. 2001: 607–614
View details for Web of Science ID 000172068000065