Chun Y. Seow
Department of Pathology and Laboratory Medicine, University of British Columbia

Chun Seow is a professor in the Department of Pathology and Laboratory Medicine at the University of British Columbia in Canada. He obtained his B.Sc. in mechanical engineering and a Ph.D. in muscle physiology from the University of Manitoba, and undertook his postdoctoral training at the University of Chicago.

Seow specializes in smooth and skeletal muscle cell biology/tissue physiology. His current research focus is on the mechanical function, ultrastructure, and biochemistry of airway smooth muscle, in health and disease. His other interests include skeletal muscle mechanics, ATPase cycle associated with the crossbridge cycle, energetics of muscle contraction, and mathematical modeling of muscle function. In his research career, he has received numerous national awards, including the Medical Research Council of Canada Fellowship, Canadian Institutes of Health Research (CIHR) New Investigator, and CIHR/BC Lung Association Investigator. His research has been continuously funded by CIHR since the start of his independent research career at UBC in 1996. He has published extensively in the area of muscle mechanics and structure, and provided editorials for journals such as Nature, American Journal of Physiology, and European Respiratory Journal. He has organized several international conferences and chaired numerous symposia. He is recognized as one of the leaders in muscle research.

Abstract
Hollow organs, such as stomach, bladder, blood vessel, and airway, are lined with a layer of smooth muscle that, through contraction and relaxation, controls organ functions such as emptying of bladder, peristalsis of gastrointestinal tracks, and maintenance of blood pressure. Smooth muscle is different from striated (i.e., cardiac and skeletal) muscles in terms of mechanical property and subcellular structure. The significance of these differences and some underlying mechanisms have only been revealed recently. The most striking difference between smooth and striated muscles is the structural malleability and functional adaptability of the former; this perhaps has evolved from the need of smooth muscle to generate force over a large length range due to the large changes in volume of hollow organs. The traditional reliance on striated muscle model to explain smooth muscle behavior is now questioned, and a model of structural plasticity for smooth muscle is emerging.

Rohan Abeyaratne
Massachusetts Institute of Technology

Rohan Abeyaratne is the Quentin Berg Professor of Mechanical Engineering at MIT and the director of the Singapore-MIT Alliance for Research and Technology (SMART). SMART is MIT's first, and to-date only, research centre outside the United States. It is also MIT's largest international program.

Prior to this, Abeyaratne was the head of the Department of Mechanical Engineering at MIT from 2001 to 2008 and its associate department head from 1996 to 2001. He has held visiting faculty positions at the California Institute of Technology, University of Cambridge, University of Minnesota and the National University of Singapore. Abeyaratne is a Fellow of ASME and a Fellow of the American Academy of Mechanics. He has served on the editorial boards of four international journals, and is a member of the scientific advisory boards of several universities. Furthermore, he recently completed serving a two-year term as president of the American Academy of Mechanics.

Professor Abeyaratne's research interest is in the field of theoretical mechanics where he is particularly known for his work on the dynamics of phase transitions. He has published extensively, including two books, the "Evolution of Phase Transitions" and "The Mechanics of Elastic Solids: Volume 1." Abeyaratne holds a MacVicar Fellowship, MIT's highest award for education. He received his B.Sc. in mechanical Eengineering from the University of Ceylon (1975), and his M.Sc. (1976) as well as Ph.D (1979) degrees from the California Institute of Technology.

Abstract
"Multiscale analysis" is an important and active field of research in mechanics. For example, one class of problems being studied involves deducing the macroscopic response of a body from knowing its microscopic response. Another involves using a macroscale analysis over part of a body, a microscale analysis over the remainder of the body, and then having these two analyses mesh together. Such problems are often considered in settings that involve quite complicated physics.

Yoichiro Matsumoto
University of Tokyo

In 1977, Yoichiro Matsumoto received his Doctor of Engineering from the Department of Mechanical Engineering, Graduate School, at the University of Tokyo where he became a lecturer of Mechanical Engineering.

In 1978, he became associate professor of Mechanical Engineering, and in 1992, was named professor of Mechanical Engineering

Abstract
The next-generation supercomputer of 10 Peta flops is now under development as a national project in Japan. Not only the hardware development but also the software development is highly expected, and the software development for the human body simulator is assigned as a grand challenge program for the effective use of the supercomputer. In this program, the multiscale and multiphysics natures of the living matter are emphasized. Under this concept, we are developing the multiscale simulator for a living human body. In this talk, the current stage of the project is briefly introduced. Then, our strategy for using medical images of a living human and some of the numerical methods we are developing for organ and body scale phenomena are explained. The future direction of our research and development is also mentioned.

Isaac Elishakoff
Florida Atlantic University

Issac Elishakoff serves as a Distinguished Research Professor at Florida Atlantic University. Prior to joining FAU, he was a professor of aeronautical engineering at the Technion-Israel Institute of Technology. He has had numerous appointments around the world, including Eminent Scholarship at the University of Beijing of Aeronautics and Astronautics, P.R. China; Distinguished Professorship at the University of Palermo, Italy; Inaugural Koiter Chair Professorship at the Delft University of Technology, Netherlands; Inaugural Freimann Chair as well as Massman Chair Professorships at the University of Notre Dame, USA, and Fellowship of the Japan Society for Promotion of Science (twice) at the University of Tokyo and University of Kyoto, respectively. He is the author or co-author of over 380 scientific papers and 22 books published by leading scientific publishers. His most recent book, entitled Optimization and Anti-Optimization of Structures under Uncertainty (with Professor Makoto Ohsaki of Kyoto University), was published by the Imperial College Press in 2010.

Abstract
This study deals with ocean energy-based research. In this regard, it should be mentioned that engineering decisions concerning the performance of structures that are either existing or are under development must be made in the presence of uncertainties. The remaining capacity of corroded structures provides a striking example of different aspects of uncertainty. These include an unknown or partially known extent of damage, and variability in loading and uncertain reserve of structural capacity, depending on the mode of failure. In this project, methods are proposed to be developed to compute the component reliability of corrosion-damaged members. Ocean structures are subjected to corrosion due to environmental exposure. As a result, the carrying capacity and hence the level of safety and reliability of these structures diminishes with time due to accumulation of corrosion damage (for example, the section loss). The level of uncertainty about the structural performance increases due to inherent uncertainty of the deterioration process. The rate of corrosion is often nonuniform and difficult to predict. The imposed loads and resistance of the structures are treated in this work as random variables. These parameters are themselves functions of several basic random variables, such as material properties, section dimensions, etc. Since the applied load and resistance are random, along with the rate and location of corrosion, the reduction in safety of corrosion-damaged structures can be expressed in terms of reliability. The experimental data associated with corrosion are usually analyzed using the probabilistic methods. However, using purely probabilistic methods alone does not provide realistic assessment of the structural reliability since not all uncertain variables are random. Hence, methods are developed to enclose the data inside either a hyper-rectangle or hyper-ellipsoid. Then one is looking for the lower and upper bounds of structural reliability under corrosion damage. Special emphasis will be placed on recent advances in the stochastic linearization technique.

Catherine Roome, Ed Hurd, Greg Paddon, Ab van Poortvliet
BC Safety Authority

Catherine Roome is chief operating officer for the BC Safety Authority (BCSA)-a risk management company with 280 employees that is committed to public safety, and is a 2007 and 2010 Canadian Top 100 Employer, 2007 & 2008 British Columbia Top 50 Employer, and Top 25 Family Friendly Employers in Canada for 2010.

The BCSA administers the safety regulations for boilers, electrical and gas installations, ski lifts, amusement rides, elevators and escalators, commuter rail, and industrial railways. If it has wires, pressure, or moving parts, then we want to make sure it is safe to work and play around.

An electrical engineer, Roome was vice president, engineering, when she joined the BCSA in 2005, and as chief operating officer she received Business in Vancouver's "Influential Women in Business" award in 2008. In 2009, she received the Distinguished Alumni Award from the Faculty of Engineering at the University of Victoria. She is Chair of Actsafe, an agency providing health and safety services to the motion picture and performing arts sectors.

Roome believes passionately that our generation's responsibility is to bring forward new ideas. Her leadership style is to "encourage that unique brilliance and potential that exists in everyone." She has a fairly unhealthy drive for results, is working on letting go of control, and is a perpetual optimist.

Abstract
A safety management plan is a document developed and maintained by an operating company that describes safety management practices and accountabilities at a facility. This document includes hazard identification and a risk control plan. The BC Safety Authority began work with the Province of British Columbia in 2009 toward enabling the use of Safety Management Plans as a regulatory methodology in the Safety Standards Act. Safety Management Plans would not replace current regulations-which would continue to be in place and develop-but would instead serve as an alternative path for achieving safety goals. The BC boiler and pressure vessel sector is the first area to be considered for its applicability, and this approach is intended to recognize technological advancements and the international market situation.

Balakumar Balachandran
University of Maryland

Balakumar Balachandran received his B.Tech. (naval architecture) from the Indian Institute of Technology, Madras, India; M.S. (aerospace engineering) from Virginia Tech, Blacksburg, VA; and Ph.D. (engineering mechanics) from Virginia Tech. Currently, he is a professor of mechanical engineering at the University of Maryland, where has been since 1993. His research interests include nonlinear phenomena, dynamics and vibrations, and control, and his recent efforts have focused on taking advantage of nonlinear phenomena for the benefit of a system.

The publications that he has authored/co-authored include over 50 journal publications, a Wiley textbook entitled Applied Nonlinear Dynamics: Analytical, Computational, and Experimental Methods (1995, 2006), a Thomson/Cengage textbook entitled Vibrations (2004, 2009), and a co-edited Springer book entitled Delay Differential Equations: Recent Advances and New Directions (2009). He serves on the editorial board of the Journal of Vibration and Control, is a deputy editor of the AIAA Journal, and is an associate editor of the ASME Journal of Computational and Nonlinear Dynamics. Balachandran is a Fellow of ASME, an Associate Fellow of AIAA, and a member of AAM, ASA, Sigma Xi, and SPIE. He served as the Chair of the ASME Applied Mechanics Division Technical Committee on Dynamics and Control of Structures and Systems from 2005 to 2007, and he currently serves as the Chair of the ASME Design Engineering Division Technical Committee on Multi-Body Systems and Nonlinear Dynamics.

Abstract
In typical tapping mode, atomic force microscopy (AFM) operations, the base excited microscale cantilever undergoes long-range attractive and short-range repulsive forces as it approaches the surface. Due to the strong nonlinearity of the tip-sample interaction forces, a variety of nonlinear phenomena has been observed. A special situation arises when the cantilever tip impacts the sample surface with zero speed (namely, grazing impacts). A better understanding of this dynamics can be useful for identifying contact in tapping mode AFM operations and, in particular, for characterization of soft biomaterials. To further the understanding of near-grazing dynamics in this context, experimental and analytical-numerical efforts have been pursued with macro- and microscale systems.

Avram Bar-Cohen
Director, TherPES Laboratory, Department of Mechanical Engineering, University of Maryland

Avram Bar-Cohen is an internationally recognized leader in thermal science and technology, an Honorary member of ASME, and Fellow of IEEE, as well as Distinguished University Professor and Department Chair since 2001 at the University of Maryland. His publications, lectures, short courses, and research outcomes, as well as professional service in ASME and IEEE, have helped to create the scientific foundation for the thermal management of electronic components and systems and pioneered techniques for energy-efficient sustainable design of manufactured products. His current research focuses on on-chip thermoelectric and two-phase microchannel coolers for high heat flux electronic components, thermal control of solid-state lighting systems, and polymer-fiber composite heat exchangers for seawater applications. Bar-Cohen was the general chair for the 2010 International Heat Transfer Conference in Washington DC and is currently the President of the Assembly of International Heat Transfer Conferences.

In addition to Honorary membership in ASME, Bar-Cohen's honors include the Luikov Medal from the International Center for Heat and Mass Transfer in Turkey (2008), ASME's Heat Transfer Memorial Award (1999), Curriculum Innovation Award (1999), Edwin F. Church Medal (1994) and Worcester Reed Warner Medal (2000), and the Electronic and Electrical Packaging Division's Outstanding Contribution Award (1994) as well as the InterPack Achievement Award (2007). Bar-Cohen was the founding chair of the IEEE Intersociety Conference on Thermal Management in Electronic Equipment (ITHERM) in 1988 and was recognized with the IEEE CPMT Society's Outstanding Sustained Technical Contributions Award (2002), the ASME/IEEE ITHERM Achievement Award (1998) and the THERMI Award from the IEEE/Semi-Therm Conference (1997).

Bar-Cohen has co-authored Design and Analysis of Heat Sinks (Wiley, 1995) and Thermal Analysis and Control of Electronic Equipment (McGraw-Hill, 1983), and has co-edited 14 books in this field. He has authored/co-authored some 329 journal papers, refereed proceedings papers, and chapters in books; has delivered 65 keynote, plenary and invited lectures at major technical conferences and institutions, and he holds eight U.S. and three Japanese patents. He has advised to completion 60 master's and Ph.D. students at the University of Maryland, the University of Minnesota and the Ben Gurion University, Beer Sheva, Israel, where he began his academic career in 1972.

From 1998 to 2001 he directed the University of Minnesota Center for the Development of Technological Leadership and held the Sweatt Chair in Technological Leadership. Increasing needs for miniaturization, functional density, and reliability, combined with the relative inefficiency of energy conversion devices, continue to drive the requirements for advanced thermal management of electronic and photonic systems. Significant progress has occurred in the past decade in TIMs, heat sinks, and liquid microchannel coolers, but these technologies are reaching their asymptotes. The thermal packaging community is however blessed with "gamechanging" opportunities in on-chip cooling, transient and periodic thermal diffusion, evaporative and ebullient processes, embedded thermal transport, and system-level energy optimization. The exploration, characterization, and modeling of the thermal packaging modalities that address these opportunities can be expected to lead to transformative changes in the performance of advanced electronic and photonic systems.

Massoud Kaviany
University of Michigan

Massoid Kaviany has been with the University of Michigan since 1986, teaching and doing research in the area of heat transfer physics. He is an ASME Fellow (1992) and chair of the Committee on Theory and Fundamental Research in Heat Transfer (1995-1998). He received the Heat Transfer Memorial Award (Science) in 2002 and the Harry Potter Gold Medal (Science of Thermodynamics) in 2010.

Abstract
Low phonon conductivity continues to be essential in high thermoelectric figure-of-merit (ZeT) materials, including skutterudites. We show that compound phase-transition phonon scattering can dominate phonon conductivity kp. We predict the phase diagram of Bax(CoSb3)4 with cluster expansion and Monte Carlo simulations, and find several stable compounds of Ba ordering over the intrinsic voids. The ordering at x = 0.25 is stable up to 350 K, while ordering at x = 0.5 is stable up to 750 K, with substantial concentration and temperature intervals of two-phase regions. We predict kp with molecular dynamics and the Green-Kubo autocorrelation decay, in good agreement with experiments, showing a minimum conductivity at x = 0.38 caused by the existence of two phases. We will discuss potential for higher ZeT using multiple fillers.

Gang Chen, Q. Hao, Y. Chalopin, T.F. Luo, Y. Nuo, Z.T. Tian, K. Esfarjani
Massachusetts Institute of Technology

Gang Chen is currently the Carl Richard Soderberg Professor of Power Engineering at the Massachusetts Institute of Technology. He obtained his Ph.D. degree from UC Berkeley in 1993, working under then Chancellor Chang-Lin Tien. He was a faculty member at Duke University (1993-1997), University of California at Los Angeles (1997-2001), before joining MIT in 2001. He is a recipient of the NSF Young Investigator Award, the ASME Heat Transfer Memorial Award, and the R&D100 Award. He is a member of the U.S. National Academy of Engineering, a Guggenheim Fellow, and an ASME Fellow. He has published extensively in the area of nanoscale energy transport and conversion and nanoscale heat transfer. He is the director of Solid-State Solar-Thermal Energy Conversion Center funded by the US DOE's Energy Frontier Research Centers program.

Abstract
Phonon transport in nanostructures is of great interest to many applications, such as thermoelectric energy conversion and microelectronic and photonic device thermal management. Characteristic lengths of nanostructures used for these applications are often smaller or comparable to phonon mean free path in the materials, leading to significant size and interface effects. In thermoelectrics, nanostructures are used to reduce phonon heat conduction for higher energy conversion efficiency. In microelectronic and photonic devices, nanostructures used for controlling electron and photon transport often lead to poor heat conduction characteristics of the devices. Despite the wellknown phenomena, modeling phonon transport in nanostructures has been difficult because many fundamental parameters, such as phonon mean free path and phonon interface scattering characteristics, are not known. This talk will discuss recent progress toward multiscale simulation of phonon transport in nanostructures. Molecular dynamics simulations are used to extract basic phonon properties, such as mean free path and interfacial scattering characteristics, which are used as inputs for Monte Carlo simulation or the Boltzmann equation to understand phonon transport in nanostructured materials and devices. Applications to thermoelectric and thermal interface materials will be discussed.

Ajing Cao, Feng Gao, Jianmin Qu
Department of Civil & Environmental Engineering, Department of Mechanical Engineering, Northwestern University

Jianmin Qu, the Walter P. Murphy Professor in the McCormick School of Engineering and Applied Science at Northwestern University, received his M.S. and Ph.D. from Northwestern in theoretical and applied mechanics in 1984 and 1987, respectively. Before joining the Northwestern University faculty in 2009, he was on the faculty of the School of Mechanical Engineering at Georgia Institute of Technology from 1989 to 2009. Qu's research focuses on several areas of theoretical and applied mechanics, including micromechanics of composites, interfacial fracture and adhesion, fatigue and creep damage in solder alloys, thermomechanical reliability of microelectronic packaging, defects and transport in ionic solids with applications to solid oxide fuel cells, and ultrasonic nondestructive evaluation of advanced engineering materials. He has authored/co-authored two books, 10 book chapters and over 120 referred journal papers in these areas.

Abstract
Because of their excellent electrical and thermal conductivity, carbon nanotubes (CNTs) are increasingly used in microelectronic devices as either electrical interconnects or thermal interface materials. A key technical issue in such applications is the junction resistance between a CNT and its interface materials. Although doable, experimental measurements of such interfacial electrical and thermal resistance are extremely difficult. Atomistic level simulations offer an alternative tool to study the electrical and thermal transport behavior at such junctions. In this talk, we present some recent results on CNT/Si and CNT/Cu interfaces based on the first principles calculations and molecular dynamic simulations.

Adam Z. Weber
Lawrence Berkeley National Laboratory

Adam Weber holds a B.S. and M.S. from Tufts University, the latter under the guidance of Professor Maria Flytzani-Stephanopoulos. He earned his Ph.D. at the University of California, Berkeley, in chemical engineering under the guidance of John Newman. His dissertation work focused on the fundamental investigation and mathematical modeling of water management in polymer-electrolyte fuel cells. Weber continued his study of water and thermal management in polymer-electrolyte fuel cells at Lawrence Berkeley National Laboratory, where he is now a staff scientist. He has authored over 20 peer-reviewed articles on fuel cells, developed many widely used models for fuel cells and their components, and has been invited to present his work at various international and national meetings, including the Gordon Research Conference on Fuel Cells, the Special Invitation Session at FC Expo 2007, a Marie Curie training course in nanostructured materials and membrane modeling and simulation, and a plenary lecture at the Proton Exchange Membrane Fuel Cells 6 Symposium. He has also been the recipient of a number of prestigious awards, including a Fulbright Scholarship to Australia and the 2008 Oronzio and Niccolò De Nora Foundation Prize on Applied Electrochemistry of the International Society of Electrochemistry. Weber is also on the Editorial Board of the Journal of Applied Electrochemistry.

Abstract
Understanding and optimizing transport phenomena in fuel cells is critical to improving their performance and durability. Although performance today is adequate, cost is not, and improved performance could enable reduced stack and cell costs. Due to the difficulties of probing the inner workings of polymer-electrolyte fuel cells during operation, mathematical modeling has been used to understand and optimize their behavior. In this talk, the main transport phenomena and their modeling will be reviewed. Of particular interest is understanding multiphase flow in fuel cell transport layers as well as the functioning of reaction agglomerates in fuel cell catalyst layers. In this talk, both issues will be examined with a focus on relevant experimental data, modeling methodology, and impact of simulation results. For multiphase flow, an approach that utilizes capillary pressure versus liquid saturation will be discussed. This experimental technique is used within our laboratory and believed to be a good measure of GDL wettability and gas-liquid interactions. To utilize this data, a model that uses contact-angle and pore-size distributions will be presented. Simulation and experimental results will elucidate the impact of microporous layers and the importance of phase-change induced flow on fuel-cell water management. For the catalyst-layer reaction modeling, a model will be presented that accounts specifically for reaction, heat transfer, and mass transport with an agglomerate composed of platinum supported on carbon, ionomer, and micropores. Such an activity is aimed at examining and testing the impact of the typical assumptions of first-order reaction rate, isothermal, and isopotential operation.

These assumptions are often made to make the mathematics more tractable, but one does not expect them to hold in reality a priori. In addition, an interfacial film of ionomer that covers the agglomerates and its impact will also be discussed.

Mamoru Ishii
Purdue University

Mamoru Ishii is a Walter H. Zinn Distinguished Professor of Nuclear Engineering at Purdue University. He also serves as the director of the Institute of Thermal-hydraulics established by the U.S. Nuclear Regulatory Commission. He obtained his B.S. from Yokohama National University in 1966, M.S. from New York University in 1968, and Ph.D. from Georgia Institute of Technology in 1971, all in mechanical engineering. His field of specialization is two-phase flow, nuclear thermal-hydraulics, and reactor safety. He received a number of scientific awards, including the ASME Heat Transfer Memorial Award. He had more than 180 journal papers and several books published.

Abstract
An accurate prediction of three-dimensional two-phase flow behaviors, either under a steady state or transient condition, is becoming increasingly important for the analysis of complicated industrial systems, such as a nuclear reactor coolant system. For such systems, the most practical two-phase flow model that has sufficient details yet is simple enough to obtain transient solutions is the well-known two-fluid model. However, the most difficult challenge is how to model the geometrical structure of the interface between phases in the averaged fields. In general, for the 3D two-fluid model, two types of constitutive relations should be developed. These are the bulk fluid transfer mechanisms related to stress and heat flux and the interfacial transfer between phases.

The former has an equivalent in the single-phase flow analysis, such as the turbulent flow models; however, the interfacial transfer constitutive relations are unique to two-phase flow. The interfacial transfer is strongly affected by the geometry of the interfacial structure and its motion, and therefore, the dynamic modeling of the interfacial structure is essential to the two-fluid analysis. For this purpose, the concept of the interfacial area transport equation has been proposed and developed into a sufficiently general and reliable model. This approach introduces two interfacial area transport equations in addition to the conservation equations of the two-fluid model. Therefore, in this approach the geometry of the interface is predicted by two variables that are the interfacial area concentration of a small bubble group and a large bubble group, such as slug or churn-turbulent bubbles. The fundamental formulation of this two-fluid model and interfacial area transport equation are discussed in detail. Some of the benchmark results using the CFX two-fluid CFD code with these modifications are presented. The results indicate that the introduction of the interfacial area transport can make a quantum improvement in the two-fluid model by eliminating the difficulty of describing the local interfacial structure in three-dimensional flow.

Chao-Yang Wang, Gang Luo
Pennsylvania State University

Chao-Yang Wang is Distinguished Professor of Mechanical, Chemical, and Materials Science and Engineering at the Pennsylvania State University. He has been the founding director of the Electrochemical Engine Center (ECEC) since 1997. Wang received the NSF CAREER award and premier research award from the Penn State Engineering Society, and has been a senior technical advisor to the United Nations Development Program (UNDP) and a delegate to Indo-U.S. and Canada-US fuel cell workshops. A fellow of ASME, Dr. Wang serves on the editorial board of several journals and book series. He holds 16 U.S. and international patents and has had nine book chapters and reviews as well as over 150 journal articles published. He has over 6000 SCI citations and an H-index of 44. His research interests cover the transport, materials, and manufacturing aspects of batteries and fuel cells.

Abstract
A general purpose battery modeling framework, termed as computational battery dynamics (CBD), will be presented. This multiscale framework incorporates a pore-level model, a cell-level model, and a stack model. The coupled thermal-electrochemical cell model not only predicts the electrochemical behavior but also the thermally induced change in electrochemistry. Implemented by a general computational fluid dynamics (CFD) technique, the cell model is not limited to one dimension. All these features, such as multidimension, multiscale, and thermal-electrochemical coupling, are essential for predicting the behavior of advanced battery systems used in electric vehicles (EVs) and hybrid vehicles (HEVs). For example, temperature uniformity is one of the most important aspects of design of automotive batteries. Nonuniform temperature distributions cause SOC balancing issues and may lead to shorter battery life. This becomes more severe for automotive battery packs, since they typically consist of hundreds of series-connected cells. To maximize pack energy and lifetime, more uniform temperature distribution and the cell balance must be maintained. We shall show that from a single cell to battery pack design, CBD is a powerful method for understanding mechanisms affecting performance of battery systems and for shortening design cycles.

Ann Marie Sastry, J.H. Seo, G. Less, M. Park, X.C. Zhang, M.D. Chung, H. Park
University of Michigan

Abstract
Simulation of Li-ion batteries, resolving statistical variation in the agglomerates that comprise active materials, is urgently required for optimization of automotive and wireless power systems. Modeling of Li-ion batteries is a challenging problem due to the presence of two special characteristics of the electrochemical system: multiphysics processes and disparate length and time scales.

The length scales in Li-ion batteries can range from particles at the micrometer length scale to the whole cell at the millimeter scale; when atomistic simulations are included the continuum decreases to the nanometer scale where lattice structures are modeled. The time scale in batteries spans from seconds to hours, electrochemical reactions occur in seconds, Li-ion diffusion occurs in minutes, and full cell cycling can take hours, depending on the charge/discharge rate. In these multiple scales, battery systems require multiphysics solutions involving transport of ions and electrons, electrochemical reactions at the solid-electrolyte interface, heat transfer, and intercalationinduced stress generation. For these physicochemical processes, the corresponding governing equations are coupled with nonlinear electrochemical kinetics. Multiphysics/multiscale modeling of such a complex system is difficult and numerically expensive, however, once perfected, will allow both understanding of the physicochemical processes of battery electrochemistries and the optimization of battery performance.

In our work, we utilize a stochastic approach in constructing model materials so that transport and mechanical properties can be studied from microscale to cell scale. We also present results of coupled multiphysics simulations for rational design of cells and materials.

N.R. Aluru
University of Illinois at Urbana-Champaign

N.R. Aluru received his B.E. degree with honors and distinction from the Birla Institute of Technology and Science (BITS), Pilani, India, in 1989, M.S. degree from Rensselaer Polytechnic Institute, Troy, NY, in 1991, and Ph.D. degree from Stanford University, Stanford, CA, in 1995. He is currently a Richard W. Kritzer Professor in the Department of Mechanical Science and Engineering at the University of Illinois at Urbana-Champaign (UIUC). He is also affiliated with the Beckman Institute for Advanced Science and Technology, the Department of Electrical and Computer Engineering, and the Bioengineering Department at UIUC. He was a postdoctoral associate at the Massachusetts Institute of Technology (MIT), Cambridge, from 1995 to 1997. In 1998, he joined the University of Illinois at Urbana-Champaign (UIUC) as an Assistant Professor.

Aluru received the NSF CAREER award in 1999, the NCSA faculty fellowship in 1999 and 2006, the 2001 CMES Distinguished Young Author Award, the Xerox Award for Faculty

Research in 2002, the ASME Gustus L. Larson Memorial Award in 2006, and the USACM Gallagher Young Investigator Award in 2007. He was named a Willett Faculty Scholar by the College of Engineering at UIUC for the period 2002-2008 and received the University Scholar Award in 2010. He is a subject editor of the IEEE/ASME Journal of Microelectromechanica Systems, served as the associate editor of IEEE Transactions in Circuits and Systems II for 2004-2005, and currently serves on the Editorial Board of a number of other journals.

Abstract
In this talk, we will present a data-driven stochastic collocation approach to include the effect of uncertain design parameters during complex multiphysics simulation of microsystems. The proposed framework comprises two key steps: first, probabilistic characterization of the input uncertain parameters based on available experimental information, and second, propagation of these uncertainties through the predictive model to relevant quantities of interest. The uncertain input parameters are modeled as independent random variables, for which the distributions are estimated based on available experimental observations, using a nonparametric diffusion mixing-based estimator. The diffusion-based estimator derives from the analogy between the kernel density estimation (KDE) procedure and the heat dissipation equation, and constructs density estimates that are smooth and asymptotically consistent. The diffusion model allows for the incorporation of the prior density and leads to an improved density estimate, in comparison to the standard KDE approach, as demonstrated through several numerical examples. Following the characterization step, the uncertainties are propagated to the output-dependent variables using the stochastic collocation approach, based on sparse grid interpolation. The stochastic multiphysics framework is used to study the effect of variations in Young's modulus, induced as a result of variations in manufacturing process parameters or heterogeneous measurements on the performance of a microswitch.

Van P. Carey
University of California at Berkeley

Van Carey is professor of mechanical engineering and holds the A. Richard Newton Chair in Engineering at the University of California at Berkeley. He is widely recognized for his research on near-interface microscale phenomena, transport in liquid-vapor systems, and computational modeling and simulation of energy conversion and transport processes. Since joining the Berkeley faculty in 1982, Carey's research has spanned a variety of applications areas, including high heat flux cooling of electronics, heat transfer in porous burners, data center energy efficiency, energy sustainability of information processing, fuel cell thermal management, building and vehicle air conditioning, forging and casting of aluminum, phase-change thermal energy storage, Rankine cycle power for manned space missions, heat pipes for aerospace applications, advanced concentrating solar absorber designs, and turbomachinery technologies for green energy conversion applications. His recent research has focused on multiscale heat, mass, and momentum transfer processes in renewable energy technologies. Carey is the author or co-author of over 180 technical publications and holds three patents. Two of his publications are advanced textbooks: Liquid-Vapor Phase Change Phenomena (Taylor and Francis, 2nd edition, 2007) and Statistical Thermodynamics and Microscale Thermophysics (Cambridge University Press, 1999).

Carey is a Fellow of the ASME and the American Association for the Advancement of Science. In recognition of his accomplishments in research and education, he received the 2004 ASME James Harry Potter Gold Medal for eminent achievement in the science of thermodynamics and the 2007 Heat Transfer Memorial Award for Science from the American Society of Mechanical Engineers.

Abstract
This paper explores the theoretical and computational challenges associated with modeling of flow, momentum transport, and energy-conversion processes in disk rotor drag turbine expanders. This category of expander devices, also known as Tesla turbines, has distinct advantages for Rankine power generation using low-temperature heat from a renewable source, such as solar, waste heat, or geothermal steam or hot water. Specifically, the nozzle and rotor designs and the overall expander can be simple to manufacture, low cost, and durable, making this type of expander an attractive option in green energy technology applications where low maintenance costs and rapid capital investment payback are important qualities. To achieve efficient energy conversion performance of rotor disk drag expanders requires that the nozzle efficiently converts flow exergy to fluid kinetic energy, and the rotor be designed to efficiently convert fluid angular momentum to shaft torque and power. To achieve these goals, modeling and analysis tools must provide the designer with a means to predict the performance of these components that accurately represents the physics and can be effectively used to illuminate the parametric trends in performance. Two categories of modeling are examined in this paper: (1) computational fluid dynamics (CFD) modeling and (2) more idealized one- and twodimensional analysis frameworks. The advantages and disadvantages of these two approaches are examined here for the specific flows of interest in this type of expander design. CFD modeling is shown to provide a more detailed prediction of three-dimensional effects in the turbine, which can be important in accurate prediction of efficiency loss mechanisms in the complex rotating flow in the narrow gap between rotor disks. However, CFD models require significant time for setup and execution, making extensive exploration of parametric effects on performance difficult. Although they provide a less rigorous treatment of the physics, one- and two-dimensional models of flow, momentum transport, and energy conversion can be structured to provide a clearer prediction of the effect of design parameters on performance. The implications of model predictions for optimal design of disk rotor expanders for green energy applications are discussed in detail.

Charles Farrar
Los Alamos National Laboratory

Chuck Farrar received a Ph.D. in civil engineering from the University of New Mexico in 1988. He has 27 years experience at Los Alamos National Laboratory, where he is currently the Engineering Institute Leader. His research interests focus on developing integrated hardware and software solutions to structural health monitoring problems. He is currently working jointly with engineering faculty at University of California, San Diego to develop the Los Alamos/UCSD Engineering Institute with a research focus on multidisciplinary projects that integrate advanced predictive modeling, novel sensing systems, and new approaches to information technology. In 2007, he was elected a Fellow of the American Society of Mechanical Engineers.

Abstract
Damage identification is carried out in conjunction with five closely related disciplines that include structural health monitoring (SHM), condition monitoring (CM), nondestructive evaluation (NDE), statistical process control (SPC), and damage prognosis (DP). Typically, SHM is associated with online, autonomous global damage identification in structural systems. CM is analogous to SHM but addresses damage identification in rotating and reciprocating machinery. NDE is usually carried out offline in a local manner with some prior knowledge of the damage location. SPC is process based rather than structure based and uses a variety of sensors to monitor changes in a process, one cause of which can result from structural damage. However, many of the statistical monitoring tools developed for SPC have been adapted to SHM and CM applications. Once damage has been detected, DP is used to predict the remaining useful life of a system. There are no distinct boundaries between these various disciplines, and in reality, many damage detection strategies will make use of some combination of these disciplines. This presentation will discuss various aspects of the damage identification process with particular emphasis on applications to clean energy infrastructure. New software (SHMTools) and hardware (WID-3 active, wireless sensor nodes) tools that have been developed at Los Alamos National Laboratory's Engineering Institute will be demonstrated and discussed in terms of their application to wind turbines. The talk will conclude with a summary of challenges for transitioning this research to practice.

Martin Pilch, Ph.D.
PMP Manager, Thermal and Fluid Processes Department, Sandia National Laboratories

Martin Pilch earned his B.S. in mechanical engineering from the Newark College of Engineering 1974.

He went on to earn his M.S. in nuclear engineering (1976) and his Ph.D. in nuclear engineering (1981) from the University of Virginia. Pilch currently is manager of the Thermal and Fluid Processes department and a Safety and Security focus area manager for the Advanced Simulation and Computing (ASC) Program at Sandia National Laboratories. He plays a key coordinating role for the laboratory for the development, demonstration, and deployment of methodologies for quantifying margins and uncertainties (QMU) that support risk-informed decisions affecting the stockpile of U.S. nuclear weapons. Pilch spent the first 19 years of his career developing and validating models for severe accident issues associated with the operation of nuclear power plants. During this time, he participated in and led major activities using a risk-informed approach, which integrated modeling and experiments in a probabilistic framework, for addressing and resolving safety issues that arose as a consequence of the accident at Three Mile Island. Pilch previously managed, for six years, the V&V subelement of the ASC Program at Sandia and was a line manager of the Validation and Uncertainty Quantification Department in the Engineering Sciences Center. As the V&V Program Manager, Pilch managed an R&D and applications portfolio with a goal of establishing credibility and quantifying uncertainties in the use of high-end modeling and simulation for nuclear weapon issues.

Abstract
Prediction is defined in the American Heritage Dictionary as follows: "To state, tell about, or make known in advance, especially on the basis of special knowledge." What special knowledge do we demand of modeling and simulation to assert that we have a predictive capability for high consequence applications? The "special knowledge" question can be answered in two dimensions: the process and rigor by which modeling and simulation is executed and assessment results for the specific application. Here we focus on the process and rigor dimension and address predictive capability in terms of six attributes: (1) geometric and representational fidelity, (2) physics and material model fidelity, (3) code verification, (4) solution verification, (5) validation, and (6) uncertainty quantification. This presentation will demonstrate through mini-tutorials, simple examples, and numerous case studies how each attribute creates opportunities for errors, biases, or uncertainties to enter into simulation results. The demonstrations will motivate a set of practices that minimize the risk in using modeling and simulation for high-consequence applications while defining important research directions. It is recognized that there are cultural, technical, infrastructure, and resource barriers that prevent analysts from performing all analyses at the highest levels of rigor. Consequently, the audience for this talk is (1) analysts, so they can know what is expected of them, (2) decision makers, so they can know what to expect from modeling and simulation, and (3) the R&D community, so they can address the technical and infrastructure issues that prevent analysts from executing analyses in a practical, timely, and quality manner. Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy under Contract No. DE-AC04-94AL85000.