Center for Design Optimization (CDO)

Dan Tortorelli

Dan Tortorelli has served as the Director for the Center of Design Optimization since its inception in 2016. He is also the George B. Grim Professor Emeritus of Mechanical Sciences and Engineering at the University of Illinois at Urbana-Champaign, a title earned upon retirement after a 26-year career on their faculty. His interdisciplinary team at LLNL develops software to optimize systems with respect to their structural, thermal, transport, fluidic, etc. performances. The software combines nonlinear programming and machine learning algorithms, finite element simulation, and high performance computing strategies.

Hernan Villanueva

Hernan Villanueva is an experienced engineer specializing in the practical application of computational optimization in physical and engineered systems. With his expertise in gradient-based shape and topology optimization frameworks, finite element and immersed boundary methods, reduced order models, and geometric modeling, he innovatively applies his knowledge to address complex engineering problems and pursues solutions with academic rigor and practical applicability.

Hernan completed a bachelor’s degree in mechanical engineering at the University of Kansas and earned both a master’s and Ph.D. in mechanical engineering at the University of Colorado, Boulder. His Ph.D. research at the Center for Aerospace Structures led to significant advancements in level set methods and the eXtended Finite Element Method (XFEM). This work laid the groundwork for the design of multi-material engineering systems, making lasting contributions to the field of shape and topology optimization with immersed boundary techniques. Hernan's scholarly contributions, published extensively in esteemed academic journals, have notably advanced the field of computational mechanics and topology optimization.

At LLNL, he continues his work on shape and topology optimization frameworks. He is instrumental in bridging the gap between design and manufacturing, developing tools that outperform existing commercial solutions in converting designs into 3D printing instructions. His innovative work on shape optimization with reduced order models for lattice structures has been featured in conferences, offering a novel approach to modeling complex metal mounts composed of intricate unit cell structures.

Kenny Swartz

Kenny Swartz is a computational optimization engineer in LLNL’s Computational Engineering Division. His current research includes topology optimization, shape optimization, design for additive manufacturing, and neural network-based surrogate model optimization. He is closely involved with the development of the Livermore Design Optimization (LiDO) software library.

Kenny received his bachelor’s, master’s, and Ph.D. in mechanical engineering from the University of Illinois at Urbana-Champaign, specializing in design optimization of micro-architected materials. He began his engineering experience as undergraduate research assistant developing computational fluid dynamics simulations of the continuous steel casting process. He gained industry experience through internships at Rolls-Royce Corp. and Caterpillar, Inc. before returning to academia to focus on x-ray diffraction measurements of residual stress in manufactured parts.

After working as an intern for two summers at LLNL, he spent the last two years of his graduate studies working with LLNL through the Graduate Research Scholars Program and then joined the Lab as a full-time staff member in 2022.

Jorge-Luis Barrera Cruz

Dr. Jorge-Luis Barrera Cruz is a research scientist specializing in the efficient translation of continuum theory of multi-physics models into large-scale object-oriented finite element and gradient-based shape and topology optimization computational frameworks. With a solid background in design optimization, finite element analysis, computational structural mechanics, and multiphysics modeling, Jorge-Luis strives to optimize the performance of engineering systems and materials through advanced optimization techniques. His research contributions aim to advance scientific knowledge in automating design optimization processes and hold promising practical applications across various industries.

Jorge-Luis began his academic journey by completing a bachelor’s degree in mechanical engineering at ESPOL in Ecuador, then a master's degree in mechanical engineering from The Ohio State University. Driven by a desire to explore design automation, he pursued a Ph.D. in aerospace engineering sciences from the University of Colorado, Boulder and conducted pioneering research on level set topology optimization using the eXtended Finite Element Method (XFEM), making significant contributions to the field.

Jorge-Luis actively engages in conferences and collaborates with leading experts to foster knowledge exchange, promote collaboration, and drive progress in the fields of systematic design optimization methods and nonlinear analysis of sentient materials. He is also deeply committed to mentoring and nurturing the next generation of scientists and engineers.

Anders Petersson

Anders Petersson is a computational mathematician in the Center for Applied Scientific Computing (CASC) at LLNL, where he currently leads projects on quantum optimal control and characterization. Anders' research lies at the cross-section of numerical methods for wave propagation, high performance computing, optimization and optimal control. His research is performed in close collaboration with physicists specializing in quantum information sciences. Anders previously lead the development of the exascale computing code SW4 for large scale seismic wave propagation, under the Serpentine Wave Propagation Project.

Hanyu Li

Dr. Hanyu Li is a postdoctoral researcher in LLNL’s Computational Engineering Division. Hanyu received his bachelor’s and master’s degrees in petroleum engineering from Texas A&M University and his Ph.D. in petroleum and geosystems engineering from the University of Texas at Austin. He joined the Lab in 2022.

Tom Epperly

Tom Epperly joined the Center for Applied Scientific Computing (CASC) in March 2000 as a computer scientist. His research focuses on developing software frameworks and standards for large-scale computational modeling of physical systems. He earned a B.S. in Chemical Engineering from Carnegie Mellon University and a Ph.D. in Chemical Engineering from the University of Wisconsin. Following his doctoral studies, Tom completed a post-doctoral year at the Centre for Process Systems Engineering at Imperial College in London, England. He later worked at Aspen Technology, Inc., where he contributed to the development of a software framework for optimizing process flowsheet simulations.

Since joining LLNL Tom has worked on numerous projects centered on software architecture for high-performance simulation and optimization of physical systems. As the Components Project Leader, he served as one of the lead architects of Babel, a high-performance language interoperability tool. He also played a key role in the FACETS project, which developed a parallel framework for integrated modeling of the core, edge, and wall regions of ITER-scale Tokamak fusion reactors. He also contributed data management components to the Carbon Capture Simulation Initiative (CCSI). Additionally, Tom served as lead architect for the NIF & Photon Sciences' Virtual Beamline application, re-engineering a Java-based application into C++ with MPI parallelism and prototyping on GPU-based hardware.

Most recently, Tom has taken on the role of CS architect for LiDO, the Livermore Design Optimization library. LiDO is a powerful tool designed to address a variety of engineering design challenges using mathematical optimization techniques from nonlinear programming and physics-based models built on partial differential equations. It enables users to construct large, complex mathematical models and define quantities of interest by combining operators that address specific aspects of the design problem.

Thomas Roy

Dr. Thomas Roy is a staff scientist in LLNL's Computational Engineering Division. His research interests mostly relate to the numerical solution of differential equations. His current research focuses on solvers and topology optimization for electrochemical applications, including batteries and CO2 reduction. His broader interests include high performance computing, scalable solvers, continuous optimization, and mathematical modelling. He received his bachelor's and master's degrees in mathematics from the University of Ottawa and his Ph.D. in mathematics from the University of Oxford.