Michael Ortiz - US grants

In recent years researchers have come to believe that in spite of the continued advances in integrated circuit technology, there will be an upper limit to the speed of sequential processors, i.e. computers that process one instruction at a time. An alternate strategy to increase computational speed is to use parallel processing, the use of simultaneous processing of separate streams of data. Thus a most promising line of research would be the development of algorithms for multiprocessors. This equipment grant will provide partial support for the purchase of a 32-node hypercube system by an established group of engineers working in computational mechanics. They have extensive experience with sequential computations but now wish to explore parallel systems. The institutional support is adequate, I recommend support.

Research will be conducted into the inelastic deformation and failure of ceramics in a combined theoretical and experimental investigation. The research will address improved understanding of the development of microcrack structures and corresponding reduction in stiffness of materials. Constitutive equations will be developed for the evolution of damage due to microcrack initiation, growth, and coalescence. Sub- microsecond duration plane-wave experiments will be conducted to verify the theoretical models. The impacted ceramics specimens will be recovered and examined after impact to characterize the development of microcracks. An improved understanding of microcrack development in ceramics and the subsequent effect on stiffness will be applicable to a wide variety of strength/stiffness problems in ceramics.

This grant is for the partial support of an international (IUTAM) symposium on computational mechanics of materials to be held during June 15-18, 1993 at Brown University, Providence Rhode Island, U.S.A. The symposium will allow the presentation of state-of-the-art research findings in the area of computational mechanics of materials to the most outstanding and active workers in that emerging field from academe, government laboratories and industry. This field differs in scope from other branches of computational mechanics by placing a heavy emphasis on micromechanics and material characterization and design. It also utilizes methodologies not employed in other segments of computational mechanics.

9413819 Karniadakis A research group at Brown University, working on aspects of high performance architectures for computational science, will use ARI funds to purchase a state-of-the-art parallel computer for researches involved in: (1) Parallel Algorithims Paradigms; (2) Parallel Methods for Hyperbolic Problems; (3) Parallel Methods for Incompressible Flows.

Integrated Design, Modeling, and Simulation

At the highest level, the process of engineering design is: given a desired functionality, synthesize, refine, and describe a device which robustly exhibits the desired function. To build computational environments which support the designer and engineer in this task --- as the complexity of engineering continues to grow --- requires new, integrated modeling, simulation, visualization, and design environments. To be truly predictive they must be mathematically well-founded, scale gracefully to large problem sizes, and reliably model physical behavior across a wide range of scales. The research team represents computer science, mathematics, mechanical engineering, control and dynamical systems, and engineering design, to develop wholly new representations and algorithms, capable of addressing these issues in concert. The core integrating principle they employ is the mathematics of "multiresolution," i.e., descriptions at different levels of resolution, for geometry, numerical solvers, mechanics, and conceptual design. The technical approach is based on the use of subdivision geometry, coupled with thin shell equation dynamics. Integrating automatic model reduction techniques --- encompassing geometry, topology, and mechanics --- based on rigorous mathematics and dynamics principles allows them to accurately and efficiently model the behavior of complex assemblies across a wide range of physical scales from microscopic to gross behavior. Fluidly and accurately moving across many physical scales makes these representations and algorithms highly suitable for engineering design. Coupling them with set-based design methods allows designers and engineers to rapidly explore large design spaces.

The objective of the proposed research is to significantly advance modeling, simulation, and design environments as needed in, for example, the aircraft and automobile industries (among many others). Current industry practice is based on separately developed, often incompatible computational modules for geometric modeling, physical simulation, and analysis. With the increasing complexity of modern engineering, this approach incurs ever larger overhead and ultimately yields results whose physical accuracy is questionable. Reconsidering the mathematical, physical, and computer science foundations of such systems from scratch, employing an integrated team of researchers and students, can radically advance the state of the art in engineering design. Cross fertilization among the team members is already yielding a new approach to simulating the behavior of thin sheets of metal, removing a long standing problem in mechanics simulation, with the potential to revolutionize the use of computer simulations in this area. To ensure the relevance of their work to real industrial practice the researchers are collaborating closely with aircraft industry and vendors of computer modeling applications. Postdoctoral scholars, graduate students and undergraduates are integrated into this crossdisciplinary program. A new generation of researchers and practitioners is being educated who are equally at ease with questions of mathematics, computer science, and mechanical engineering.

Funding for this activity will be provided by the Division of Mathematical Sciences, the MPS Office of Multidisciplinary Activities, and by DARPA.

9813850 Ortiz The symposium brings together prominent members of the community with expertise in computational mechanics to review the current needs, trends, and opportunities pertaining to the testing and verification of large-scale advanced simulation codes. Recommendations are made on testing techniques, algorithm analysis, benchmark problems and other useful avenues for assessing the fidelity and performance of computational mechanics codes. ***

This award was made on a collaborative proposal submitted to the Division of Materials Research under the Information Technology Research solicitation NSF-04-012. The Division of Materials Research, the Chemistry Division, and the Division of Computing and Communications Foundations fund this award. The other proposals in this multidisciplinary collaborative are 0427188 and 0427540 and involve investigators at Caltech and Purdue. Research activities covered by this award fall under the National Priority Area, "Advances in Science and Engineering," and the Technical Focus Area, "Innovation in Computational Modeling or Simulation in Research." This award supports computational research and algorithm development with the aim of developing new modeling tools for materials failure and with the further aim of applying these tools to advance the understanding of stress corrosion cracking. This award also supports related educational activities some of which involve underrepresented groups.

The PIs aim to develop a scalable parallel and distributed computational framework consisting of methods, algorithms, and integrated data handling and visualization tools for: 1) an accurate quantum mechanical-level (QM) description; 2) reactive force fields (ReaxFF) to describe chemical reactions and polarization; 3) molecular dynamics (MD) simulations to extract atomistic mechanisms of SCC; 4) accelerated dynamics for long-time behavior to obtain parameters directly comparable to experiments; and 5) "atomistically informed" continuum models to reach macroscopic length and time scales. Automated model transitioning by novel techniques will be employed to embed higher fidelity simulations inside coarser simulations only when and where they are required, while controlled error propagation will ensure the overall accuracy of the results. The PIs plan to use this hierarchical multiscale computational framework to study stress corrosion cracking (SCC) of aluminum, iron, and nickel-aluminum superalloys in gaseous and aqueous environments. These materials are used widely in industrial applications and their performance and lifetime are often severely limited by stress corrosion in environments containing oxygen and water. Simulations will be used to extract an atomic-level understanding of the basic mechanisms underlying SCC. The PIs plan to investigate SCC inhibition by ceramic coatings (e.g., alumina and silicon carbide), self-assembled monolayers (e.g., oleic imidazolines), and by microorganisms (e.g., Shewanella oneidensis strain MR-1).

The PIs will deliver software tools having broad applicability across scientific disciplines and industry. This award supports annual computational science workshops for undergraduate students and faculty mentors from underrepresented groups. Workshops will be organized to foster close interactions between underrepresented minority graduate students at US institutions and postdoctoral level counterparts from Latin American institutions. Undergraduate students will be involved in the research through summer research experiences; at least half are expected to be from underrepresented groups. The PIs will also assist minority institutions in developing computational science curricula, and mentor early-career faculty from minority institutions and EPSCoR states.

This award also supports education. Elements of the PIs' education program include: 1) a unique graduate course jointly taught by USC and Caltech faculty emphasizing hands-on experience in hierarchical multiscale material simulations; 2) a dual-degree program at USC offering graduate students the opportunity to obtain a PhD in the physical sciences or engineering and an MS in computer science with specialization in high performance computing and simulations; and 3) summer research experiences for undergraduate students involving a total immersion course in computational science followed by research in simulation, parallel algorithms and visualization.
%%%
This award was made on a collaborative proposal submitted to the Division of Materials Research under the Information Technology Research solicitation NSF-04-012. The Division of Materials Research, the Chemistry Division, and the Division of Computing and Communications Foundations fund this award. The other proposals in this multidisciplinary collaborative are 0427177 and 0427540 and involve investigators at Caltech and Purdue. Research activities covered by this award fall under the National Priority Area, "Advances in Science and Engineering," and the Technical Focus Area, "Innovation in Computational Modeling or Simulation in Research." This award supports computational research and algorithm development with the aim of developing new modeling tools for materials failure and with the further aim of applying these tools to advance the understanding of stress corrosion cracking. This award also supports related educational activities some of which involve underrepresented groups.

Stress corrosion cracking (SCC) is a complex technological and economic problem involving premature and catastrophic failure of materials due to an insidious combination of mechanical stresses and chemically aggressive environments. Safe and reliable operation of structural systems are endangered by uncertainties in SCC, the reduction of which could have enormous economic impact. The PIs plan to develop computational tools that contain essential physics across a wide range of length and time scales to achieve an atomic-level mechanistic understanding of SCC. Because of the large number of atoms and complex physical and chemical processes, these tools will be able to manage distributed computing resources and focus them on SCC simulation.

The PIs plan to use these tools to study SCC of aluminum, iron, and nickel-aluminum superalloys in gaseous and aqueous environments. These materials are used widely in industrial applications and their performance and lifetime are often severely limited by stress corrosion in environments containing oxygen and water. Simulations will be used to understand the basic mechanisms underlying SCC. The PIs plan to investigate how various coatings and microorganisms inhibit SSC.

This award also supports education. Elements of the PIs' education program include: 1) a graduate course jointly taught by USC and Caltech faculty emphasizing hands-on experience in hierarchical multiscale material simulations; 2) a dual-degree program at USC offering graduate students the opportunity to obtain a PhD in the physical sciences or engineering and an MS in computer science with specialization in high performance computing and simulations; and 3) summer research experiences for undergraduate students.

The PIs will deliver software tools having broad applicability across scientific disciplines and industry. This award supports annual computational science workshops for undergraduate students and faculty mentors from underrepresented groups. Workshops will be organized to foster close interactions between underrepresented minority graduate students at US institutions and postdoctoral level counterparts from Latin American institutions. Undergraduate students from underrepresented groups will be involved in the research. In addition, the PIs will assist minority institutions in developing computational science curricula, and mentor early-career faculty from minority institutions and EPSCoR states.
***

Many contemporary problems in new advanced materials relate to variation in length, time scales, and variations inherent in their fabrication and function. Resolution of these problems requires predictive theories for these complex systems that in turn require advances in mathematics. In this PIRE project an international network of prominent mathematicians from four U.S. institutions, five European institutions, and a multinational industrial partner, will build on decades of collaboration and training at the interface of mathematics and materials sciences that have yielded many achievements at the forefront of sophisticated new mathematics and simulation methods. The project will focus on four principal research areas: 1. Pattern formation from energy minimization, 2. Challenges in atomistic to continuum modelling and computing, 3. Prediction of hysteresis (systems that have "memory" such that effects of stimuli are temporally delayed), and 4. Pattern dynamics and development of material microstructure.

U.S. and European students will benefit from internationalized education and research training within a PIRE framework promotes new patterns in research collaboration and education that includes cultural dimensions. Advanced graduate courses will be developed and shared across the network providing a truly internationalized curriculum and universal access to the best materials-relevant mathematics topics. U.S. graduate students and postdoctoral fellows will be immersed in intensive multi-advisor mentoring models strengthening their interdisciplinary and global research skills. Interested graduate students will be able to partake in an international industrial research internship. In addition, annual workshops and summer schools will extend the research to a much wider community of students and postdoctoral fellows outside the project.

This award will help to internationalize US institutions by linking them in a vibrant international network of applied mathematicians who integrate research relevant to materials science with a coherent program for training the next generation of globally-engaged scientific leaders in fast-developing areas of mathematics. The complementary strengths and expertise of the team will push the frontiers of applied analysis and clear the pathway for new applications in materials research. The U.S. will gain expertise and strength in the field of calculus of variations, essential to the first principal research area, through its base at two of the European research centers. Working with European partners will help unify and extend U.S. expertise in the modelling, computation, and analysis on problems arising in materials science. Advances in pattern dynamics research at several nodes of the network have revealed new modelling and analysis opportunities with the potential to be leveraged by this award.

Collaborators on this PIRE project include four U.S. institutions: Carnegie Mellon University (PA), California Institute of Technology, New York University, and University of Minnesota; five European institutions: University of Antwerp (Belgium), University of Bonn (Germany), Max Planck Institute for Mathematics in the Sciences (Germany), International School for Advanced Studies (SISSA)(Italy), and University of Oxford (UK); and an industrial partner: Robert Bosch GmbH (Germany and USA).

This project is supported by NSF's Office of International Science and Engineering and the Division of Mathematical Sciences.

In a number of areas of application, the behavior of systems depends sensitively on properties that pertain to the atomistic scale, i.e., the angstrom and femtosecond scales. However, often the properties and behaviors of interest are macroscopic and take place on the scale of centimeters to meters, and are characterized by slow evolution on the scale of minutes to years. No computationally-tractable atomistically-based models appear to be as yet available to study such slow phenomena over time scales of the order of minutes to years and in macroscopic samples while maintaining a strictly atomistic description of the material. This project addresses this chronic gap in predictive science. This approach offers unprecedented capability for the study of device-level properties mediated by slow, coupled, thermal-mechanical-chemical processes at the atomistic scale. Thus, beyond this application to Li-ion batteries, this methodology may be expected to have far-reaching impact as an enabling tool in applications requiring the careful accounting of atomic-level processes simultaneously with the elucidation of macroscopic properties over long time scales, e.g., stability of alloys and irradiated materials, electromigration in interconnects, corrosion and environmentally-assisted cracking, among others. The empirical atomic-level kinetic models, variational meanfield approximation schemes, variational time-discretization algorithms and spatial coarse-graining schemes developed under the project will be implemented into a verified and validated high-performance computing solver, the Extended Quasicontinuum (XQC) solver, for broad dissemination in the community.

This work is concerned with the further development and implementation of a novel multiscale analysis methodology. It combines elements of non-equilibrium statistical mechanics and kinetic and approximation theory. This approach offers unprecedented capability for the study of the long-term macroscopic behavior of complex multi-species atomistic systems mediated by slow, coupled, thermal-mechanical-chemical processes at atomistic scales. Application of the novel methodology to the investigation of silicon lithiation, both in bulk and in nanowires (SiNW) is considered. The potential use of silicon as a high energy-density anode material in Li-ion based batteries is hampered by the extensive mechanical degradation that occurs during lithiation. The current global market size for such storage, just for vehicle applications, is estimated at $1.5 billion, and is expected to grow to by more than 3,000% by the end of the decade. The ability to simulate silicon lithiation predictively at the device level and over large numbers of charge/discharge cycles is expected to enable the identification and assessment of novel nano-engineered materials for Li battery applications.

Project Abstract One of the major goals of the BRAIN initiative is to develop technologies capable of interfacing with specific neural circuits in the human brain. Ultrasonic neuromodulation (UNM) is among the most significant new technologies being developed for this purpose because it has the potential to non-invasively modulate neural activity in deep-brain regions with millimeter spatial precision. This unique capability would complement existing neuromodulation and imaging techniques in basic and clinical applications. However, despite a surge of interest in UNM, the lack of knowledge about its mechanisms and recent findings of off-target sensory effects accompanying direct neuromodulation pose significant challenges to the use of this technology in human neuroscience. In particular, while most groups working on UNM are racing ahead with device development and applications, we have uncovered a major issue with this technology that must be addressed before it can be used reliably by the neuroscience community: at the ultrasonic parameters used in most UNM studies, ultrasound causes not only direct neuromodulation of the targeted region, but also strong activation of auditory cortical circuits. This significantly confounds the interpretation of UNM-evoked electrical and motor responses seen in animal models, our understanding of efficacious doses and parameters, and most importantly, potential applications in humans. To overcome this issue, we will (1) establish an understanding of the mechanisms and parameters of both direct and indirect effects of ultrasound on neural circuits, (2) identify parameters for maximizing direct modulation, and (3) develop sham stimuli enabling properly controlled use of UNM as a tool for human neuroscience. To tackle these problems, we have assembled a multidisciplinary team of scientists and engineers with expertise in tissue mechanics, acoustics, biophysics, systems neuroscience, and human psychophysics who will use unique experimental approaches ranging from computational models to specially-developed transgenic rodents and human volunteers. If successful, this project will help resolve a key issue preventing focused ultrasound from serving as a reliable, interpretable modality for non-invasive neuromodulation, and lay the groundwork for the development of optimized devices and appropriate controls for widespread use of UNM in the study of brain circuits.