Yuri Bazilevs is the E. Paul Sorensen Chair in the School of Engineering at Brown University. He was previously a Full Professor and Vice Chair in the Structural Engineering (SE) Department, and an Adjunct Full Professor in the Mechanical and Aerospace Engineering (MAE) Department, in the Jacobs School of Engineering at UCSD. He joined UCSD as an Assistant Professor in July of 2008, was promoted to Associate Professor with tenure in July 2012, and, subsequently, to Full Professor in July 2014. Yuri completed his PhD and Postdoc training, in 2006 and 2008, respectively, at UT Austin's Institute for Computational Engineering and Sciences (ICES).
Statement
Over a decade ago, Computational Science has been identified as “the third pillar of scientific method”, alongside with theory and experimentation, which are considered to be the two original pillars of scientific discovery [1]. It is now safe to say that Computational Science and Engineering (CSE) has “come of age”, and today presents a thriving enterprise that involves the development and use of computational algorithms, and their implementation in the environment of High Performance Computing (HPC), to translate mathematical models of physical phenomena into computer models that ultimately attempt to predict the future. CSE has been successful in a broad and increasing list of scientific and technological developments in basic science, engineering, and medicine, and also presents an integral and ever growing part of many agencies research and development programs.
However, as CSE matured, the development of modeling and simulation methods for basic sciences has taken a different path from that of engineering applications. The development of modeling and simulation methods for scientific discovery is focused on elucidating new scientific phenomena in natural or man-made physical systems. In the case of continuum systems, such as solids or fluids, the term “modeling” is often understood as the development, from experimental or observation data, of the novel constitutive relations, such as, for example, interaction potentials, rate-dependent forms of plastic and damage laws, shock and eddy viscosities, etc. The issues of geometric complexity, realistic boundary conditions, topological changes in the problem domain due to fragmentation or contact, etc., are often secondary and thus seldom addressed. Conversely, modeling and simulation in support of engineering design is focused on complex-geometry methods and efficiency of the discretization approaches. The issues of realistic boundary conditions and problem-domain motion become the primary drivers of methods development, and the fundamental physics/mechanics is often traded for empirical models that best fit the computational framework developed for a given application. Models that are easily implemented and that are “inexpensive” to execute are often preferred, especially when a large number of analyses is needed to support design.
Nevertheless, the initially divergent paths that modeling and simulation developments have taken in the science and engineering fields are starting to merge. On the one hand, cutting-edge science is becoming increasingly interested in applications involving complex geometry and coupled mechanical phenomena. For example, analysis of metamaterials, which derive their favorable mechanical properties from a specific topological and geometric arrangement of their substructures, relies more and more heavily on complex-geometry discretization methods. Coupled phenomena, such as fluid-solid or fluid-structure interaction (FSI) [2], are essential for accurate modeling of biological cell structures or that of materials subjected to high-strain-rate air-blast loading. On the other hand, the low accuracy of empirical models, which are often employed outside their limited range of applicability, is nowadays seldom compatible with the precision demands of modern engineering. This is especially true in the defense sector. In recent years, in several engineering applications, empiricism is often traded for fundamental, first- principle-based scientific theories. For example, in the area of solids and structures the development of multiscale computational methods is now enabling accurate, efficient, and, most importantly, predictive modeling of structures comprised of complex materials, such as concrete or laminated fiber-reinforced composites. In the area of fluids, large-eddy simulation approaches based on the so-called variational multiscale methods, which make no assumptions about the problem geometry or flow regime, are starting to be routinely employed for engineering-scale aerodynamic and hydrodynamic analyses.
While HPC has played a tremendous role in raising the quality and fidelity of computational simulations in science and engineering, 10-15 years ago a new concept of the so-called Dynamic-Data-Driven Application Systems (DDDAS) [3] has emerged that further changed the way CSE is approached these days. DDDAS is a framework in which dynamic and/or static sensor and measurement data collected for a given physical system is used to dynamically update a simulation model of that system. Using measurement data, the model geometry, boundary conditions, forcing, material parameters, etc., may be updated to better represent physical reality. At the same time, the properly updated computational model is able to produce higher-fidelity outputs for the quantities of interest for which measurements are not available, and further steer data measurement through appropriate placement of sensors. As such, DDDAS is a framework in which measurement and simulation co-exist in a symbiotic environment, which further enhances the predictive power of simulation methods.
These convergent demands that science and engineering applications place on the modeling and simulation methods today create an opportunity to rethink how these methods are developed and employed in academia, industry, and research labs. In his reserch work, Yuri addresses these demands by developing a first-of-its-kind, unified, predictive modeling framework that incorporates first-principle-based approaches, enables new scientific discovery, and possesses the accuracy, robustness, and efficiency attributes necessary to support modern engineering analysis and design. The PI envisions taking Isogeometric Analysis (IGA) [4], of which he is one of the original developers, as the foundational methodology for the following reasons:
IGA was proposed in an effort to “bridge the gap” between Computer-Aided Design (CAD) and the Finite Element Method (FEM) routinely employed in Computer-Aided Engineering (CAE). As such, at its foundation, IGA, unlike other computational technology, has a strong link to CAD and, as a result, engineering design.
IGA is function-based computational methodology, which, like FEM, relies on the weak or variational statement of the boundary value problem. As such, IGA is compatible with FEM on several levels: a. Under certain assumptions on the discretization, IGA reduces to standard FEM; b. IGA may be “coupled” with FEM in a straightforward fashion, which is especially useful for multiphysics applications like FSI. This compatibility is important for integration of IGA into existing analysis frameworks, and essential for adoption by users interested in IGA for their applications.
For the discretization of the solution fields, IGA makes use of splines, which are piece- wise polynomial functions joined with higher-order continuity. For many problems, arising in both science and engineering, the higher-order nature of splines gives high per- degree-of-freedom accuracy necessary to resolve the spatially multiscale phenomena present in many physical systems. In addition, the increased continuity of the basis functions gives rise to superior robustness necessary for engineering applications. As such, IGA has this rare combination of accuracy and robustness, which is well suited for the proposed modeling and simulation framework that treats science and engineering applications in a unified manner.
The PI and his team are pursuing research and development of novel core and special computational methods, where IGA plays a central role as the key unifying concept for CSE. The methods development is driven by advanced applications coming from academia, industry, and national lab collaborations, thus making the corresponding partnerships an essential component of this effort.
References
[1] D.A. Reed et al., “Computational Science: Ensuring America's Competitiveness”, PITAC Report, Arlington, VA, 2005.
[2] Y. Bazilevs, K. Takizawa, and T.E. Tezduyar, “Computational Fluid-Structure Interaction: Methods and Applications”, Wiley 2013.
[3] F. Darema. Dynamic data driven applications systems: A new paradigm for application simulations and measurements. In proceedings of ICCS 2004 4th International Conference on Computational Science, pages 662–669, 2004.
[4] J.A. Cottrell, T.J.R. Hughes, and Y. Bazilevs, “Isogeometric Analysis. Toward Integration of CAD and FEA”, Wiley 2009.
Computational Modeling of Free-Surface Fluid-Object Interaction for Coastal hydraulic Applications; Sponsor: Army Research Office (ARO); Amount: $50,000; Dates: 07/01/2010-03/31/2011.
A Pipeline for Patient-Specific Cardiovascular Modeling: Imaging, Simulation and Visualization; Sponsor: UCSD Chancellor’s Grant; Amount: $60,000; Dates: 06/01/2009-05/31/2010.
A Pipeline for Patient-Specific Cardiovascular Modeling: Imaging, Simulation and Visualization; Sponsor: UCSD Chancellor’s Grant; Amount: $60,000; Dates: 06/01/2010-05/31/2011.
Los Alamos - UC San Diego Educational Collaboration - Phase VII – Computational Fluid-Structure Interaction Simulation of Wind Turbines; Sponsor: Los Alamos National Security, LLC; Amount: $40,295; Dates: 10/01/09 - 09/30/10.
Los Alamos - UC San Diego Educational Collaboration - Phase VIII – Computational Fluid-Structure Interaction Simulation of Wind Turbines; Sponsor: Los Alamos National Security, LLC; Amount: $53,725; Dates: 10/01/10 - 09/30/11.
Free-Surface Fluid-Object Interaction for the Large-Scale Computation of Ship Hydrodynamics Phenomena; Sponsor: Army Research Office (ARO); Amount: $244,447; Dates: 05/01/11 – 04/30/14.
CAREER: Fluid-Structure Interaction and High Performance Computing for Wind Energy Applications; Sponsor: National Science Foundation (NSF); Amount: $458,838; Dates: 05/01/11 – 04/30/16.
DDDAS: Computational Steering of Large-Scale Structural Systems Through Advanced Simulation, Optimization, and Structural Health Monitoring; Sponsor: Air Force Office of Scientific Research (AFOSR); Amount: $695,905; Dates: 01/01/12 – 12/31/15.
Los Alamos - UC San Diego Educational Collaboration - Phase IX – Isogeometric Methods for Lagrangian Hydrodynamics; Sponsor: Los Alamos National Security, LLC; Amount: $101,115; Dates: 09/01/11 – 10/31/12.
Applications of Quantum Computing in Aerospace Science and Engineering; Sponsor: Air Force Office of Scientific Research (AFOSR); Amount: $3,750,000 (Co-PI, my share $400,000); Dates: 09/01/11 – 08/31/16.
CDS&E: A Large-Scale Data Discovery Framework For Understanding Intermittent, Performance-Critical Phenomena In Simulations Of Off-Shore Wind Turbines; National Science Foundation (NSF); Amount: $500,000 (Co-PI, my share $170,000); Dates: 09/01/13 - 08/31/16.
Fluid—Structure Interaction Simulation of Gas Turbine Engines Using Isogeometric Analysis; Sponsor: Army Research Office (ARO); Amount: $440,000; Dates: 01/01/14 - 6/14/18.
Progressive Damage Modeling for Combined Impact and Compressive Residual Strength Prediction; Sponsor: NASA; Amount: $1,085,500 (Co-PI, my share $450,000): Dates: 10/01/15 – 9/30/19.
Multiscale DDDAS with Emphasis on Aerospace Structures and Application to Unmanned Aerial Vehicles; Sponsor: Air Force Office of Scientific Research (AFOSR); Amount: $736,000; Dates: 10/01/15 – 3/15/19.
Improving Particle-Grid Methods; Sponsor: Los Alamos National Security, LLC; Amount: $67,658; Dates: 4/1/17 – 12/1/17.
Improving Particle-Grid Methods; Sponsor: Los Alamos National Security, LLC; Amount: $75,000; Dates: 1/1/18 – 9/30/18.
LES and RANS Simulations of Estuarine Flows: Understanding and Parameterizing the Role of Langmuir Turbulence; National Science Foundation (NSF); Amount: $178,177; Dates: 08/15/18 - 07/31/2021.
PLENARY, SEMI-PLENARY AND NAMED LECTURES
Y. Bazilevs, “3D Simulation of Wind Turbine Rotors at Full Scale: Geometry Modeling, Aerodynamics and Fluid-Structure Interaction”, Plenary Lecture, Maths & Air 2010, Zaragoza, Spain, June 16-18 2010.
Y. Bazilevs, “Enabling Computational Technology for Offshore Wind Turbines”, Plenary Lecture at the IVth International Conference on Computational Methods in Marine Engineering (MARINE2011), Lisbon, Portugal, Sept. 28-30, 2011.
Y. Bazilevs, “Fluid—Structure Interaction Modeling for Offshore Wind Turbines”, Plenary Lecture at IXth Deep Sea Offshore Wind R&D Seminar (DeepWind2012), Trondheim, Norway, January 19-20, 2012.
Y. Bazilevs, “Fluid-Structure Interaction Simulation of Wind Turbines at Full Scale”, Plenary Lecture at Young Investigators Conference (YIC2012), Aveiro, Portugal, April 24-27, 2012.
Y. Bazilevs, “Computational fluid-structure interaction: Blood pumps, surface ships, and wind turbines”, Semi-Plenary Lecture, ACM 2013 – A Conference Celebrating the 70th Birthday of Thomas J.R. Hughes, San Diego, CA, February 24-27, 2013.
Y. Bazilevs, “Computational Fluid-Structure Interaction: From Blood Pumps to Wind Turbines”, Semi-Plenary Lecture at 12^{th} US National Congress on Computational Mechanics (USNCCM 2013), Raleigh, NC, July 22-25, 2013.
Y. Bazilevs, Warren Lecture, “Isogeometric Analysis and Fluid—Structure Interaction for Wind Turbines”, Department of Civil and Environmental Engineering, University of Minnesota, February 28, 2014.
Y. Bazilevs, “FSI Modeling and Simulation of Onshore and Offshore Wind Turbines at Full Scale”, Plenary Lecture at ParCFD 2014, Trondheim, Norway, May 20-22, 2014.
Y. Bazilevs, “Computational FSI: Methods Developed and Computations Performed”, Semi-Plenary Lecture at FEF 2015, Taipei, Taiwan, March 16-18, 2015.
Y. Bazilevs, “Computational Fluid-Structure Interaction with Applications”, Plenary Lecture at Coupled Problems 2015, Venice, Italy, May 18-20, 2015.
Y. Bazilevs, “IGA: Some New Fundamental Developments and Advanced Applications”, Plenary Lecture at IGA 2015, Trondheim, Norway, June 1-3, 2015.
Y. Bazilevs, “Robust Solution Strategies for Fluid-Structure Interaction Problems with Applications”, Plenary Lecture at Domain Decomposition 2015, Jeju Island, South Korea, July 6-10, 2015.
Y. Bazilevs, “Recent Advances in Isogeometric Analysis and Fluid-Structure Interaction”, Plenary Lecture at 28^{th} Nordic Seminar on Computational Mechanics, Tallinn, Estonia, October 22-23, 2015.
Y. Bazilevs, “Flexible Fluid-Structure Interaction Framework with Applications”, Semi-Plenary Lecture at FEF 2017, Rome, Italy, April 5-7, 2017.
Y. Bazilevs, “Flexible FSI: From Wind Turbines to Air Blast”, Plenary Lecture at International Conference on Advances in Computational Mechanics 2017, Phu Quoc Island, Vietnam, August 2-4, 2017.
Y. Bazilevs, “IGA as Enabling Technology for Engineering-Scale Simulations in Fluids, Solids, and FSI”, Plenary Lecture at IGA 2017, Pavia, Italy, September 11-13, 2017.
Y. Bazilevs, “IGA of Solids, Structures, and FSI: From Early Results to Recent Developments”, Plenary Lecture at Texas Applied Mathematics and Engineering Symposium (TAMES) 2017, Austin, TX, September 21-23, 2017.
Y. Bazilevs, “Recent Advances in IGA for FSI: Air-Blast FSI – Framework and Applications”, Semi-Plenary Lecture at ECCM - ECFD 2018 - 6th European Conference on Computational Mechanics (Solids, Structures and Coupled Problems) & 7th European Conference on Computational Fluid Dynamics, Glasgow, Scotland, June 11-15, 2018.
Y. Bazilevs, “Isogeometric Methods for Extreme-Event Simulation: Air-Blast FSI – Framework and Applications”, Semi-Plenary Lecture at WCCM 2018 – 13th World Congress on Computational Mechanics & 2nd Pan American Congress on Applied Mechanics, New York, New York, July 22-27, 2018.
Y. Bazilevs, “Isogeometric Methods for Extreme-Event Simulation: Air-Blast FSI – Framework and Applications”, Plenary Lecture at NewMech 2018, Providence, RI, September 29, 2018.
Year | Degree | Institution |
---|---|---|
2006 | PhD | University of Texas |
2001 | MS | Rensselaer Polytechnic Institute |
2000 | BS | Rensselaer Polytechnic Institute |
Postdoctoral Fellow and Lecturer | University of Texas at Austin, Institute for Computational Engineering and Sciences (ICES) | 2006-2008 | Austin, TX, USA |
Graduate Research Assistant | University of Texas at Austin, Computational Engineering and Science | 2002-2006 |
2018 Springer book titled “Frontiers in Computational Fluid-Structure Interaction and Flow Simulation: Research from Lead Investigators under Forty – 2018” dedicated to Y. Bazilevs and K. Takizawa in celebration of their 40^{th} birthday.
2018 Highly Cited Researcher – Engineering Category; Computer Science Category
2018 ASCE Walter L. Huber Civil Engineering Research Prize
2017 Highly Cited Researcher – Engineering Category; Computer Science Category
2016 Highly Cited Researcher – Engineering Category; Computer Science Category
2015 Highly Cited Researcher – Engineering Category; Computer Science Category
2015 USACM Fellow
2014 Highly Cited Researcher – Computer Science Category
2014 Warren Lecture, Civil and Environmental Engineering, University of Minnesota
2013 Adviser, Chancellor’s Dissertation Medal in Engineering for best PhD Thesis (M.-C. Hsu)
2012 ASME Applied Mechanics Division Thomas J.R. Hughes Young Investigator Award
2011 USACM Gallagher Young Investigator Award
2011 NSF CAREER Award
2010 IACM Young Investigator Award
2010 Hellman Fellowship, UCSD
2009 “Most Cited Author in 2005-2008” Award. Computer Methods in Applied Mechanics and Engineering, Journal published by Elsevier.
2007 Outstanding PhD Dissertation Nominee, UT-Austin.
2002 Michael A. Sadowsky Prize for Best MS Thesis in Mechanics, RPI.Name | Title |
---|---|
Ainsworth, Mark | Francis Wayland Professor of Applied Mathematics |
Bower, Allan | Professor of Engineering |
Gao, Huajian | Walter H. Annenberg Professor Emeritus of Engineering |
Goldsmith, Franklin | Assistant Professor of Engineering |
Guduru, Pradeep | Professor of Engineering |
ASME Applied Mechanics Division (ASME-AMD)
US Association for Computational Mechanics (USACM)
International Association for Computational Mechanics (IACM)
ASCE Engineering Mechanics Institute (ASCE-EMI)
ENGN2912N - Isogeometric Methods in Computational Mechanics
ENGN1300 - Structural Analysis
ENGN 1300 - Structural Analysis |
ENGN 2340 - Computational Methods in Structural Mechanics |
ENGN 2912N - Isogeometric Methods in Computational Mechanics |