MICDE catalyst grant leads to new NSF funding to study cascade “ecohydromics” in the Amazonian headwater system

By | Feature, News, Research

The Amazon Basin cycles more water through streamflow and evaporation than any other contiguous forest in the world, and transpiration by trees is a critical part of this cycle. Understanding how plant roots, stems, and leaves interact with soil water to regulate forest transpiration across landscapes is a critical knowledge gap, especially as climate changes. Professor Valeriy Ivanov, from the Department of Civil and Environmental Engineering at U-M, is the lead investigator in a newly NSF funded project that links diverse disciplines – plant ecophysiology, ecology, and hydrology – and will build a unique modeling framework to characterize landscape variation in physiological and hydrological processes in the Amazon Basin. The framework will integrate a wide array of field observations with detailed watershed modeling for hypothesis testing. The team includes Tyeen Taylor, research fellow also from the Civil and Environmental Engineering Department at U-M, and many collaborators in the U.S. at the University of Arizona, University of West Virginia, University of Nebraska, as well as Brazilian researchers at the Federal University of Eastern Para, and Federal University of Amazonas, National Institute for Amazonian Research, and Eastern Amazon Agricultural Agency. Detailed, physical models of ecophysiology and above- and below-ground hydrology will be informed by observations of leaf physiology, tree morphological traits, soil moisture, groundwater, and streamflow. Data and models will be integrated employing novel tools in probabilistic learning and uncertainty quantification. The computational framework tools to be used in this project were developed in part with the support from MICDE Catalyst grant program for the 2018 project “Urban Flood Modeling at “Human Action” Scale: Harnessing the Power of Reduced-Order Approaches and Uncertainty Quantification” led by Prof. Ivanov. 

Given (a) a mechanistic model M (e.g., a stomatal conductance model), (b) one can treat its inputs 𝛏 (e.g., parameters) as random variables. These inputs are sampled and model simulations are carried out. Using (c) PCEs, we construct a surrogate model that best approximates the model output – left-hand-side of (c). The surrogate is then evaluated with Monte Carlo simulations and used for (d) parameter inference. (d.1) is the flow of outputs from the surrogate model into a likelihood function L (D | 𝛏) to compare the surrogate model output and observed data D. This inference produces the posterior distribution for 𝛏. This pdf can then be sent back to the surrogate in (d.2) to reduce the uncertainty in the inputs and to obtain pdf for a quantity of interest (e).

“The reduced-ordered modeling approach developed during the MICDE Catalyst grant project is a key element of the new project,” said Prof. Ivanov, “the MICDE seed funding has allowed us to build a general framework that is applicable to a wide range of computational applications in earth-system science, and thus made our project proposal more competitive”.

The MICDE Catalyst Grants program funds projects that have the potential to catalyze and reorient the directions of their research fields by developing and harnessing powerful paradigms of computational science. This new NSF project is an example of the reach of the program.

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We welcome 20 students to the 2021-22 class of MICDE graduate fellows

By | Feature, News

MICDE is proud to announce the recipients of the 2021 MICDE graduate fellowships. The fellows’ research projects involve the use and advancement of scientific computing techniques and practices. “This year, MICDE awarded fellowships in a wide array of disciplines ranging from chemistry to biostatistics and interdisciplinary mathematics to applied physics,” said Krishna Garikipati, MICDE director and professor of mechanical engineering and mathematics. “Engineering is also well represented with fellows focused on disciplines such as aerospace, biomedical, civil and environmental, climate and space, industrial and operations, materials science, mechanical, and naval architecture and marine engineering.”

For the past seven years, MICDE has awarded fellowships to over 135 graduate students from our large community of computational scientists. “I am so excited and honored to be a part of the MICDE Fellowship program. My research interest is in an interdisciplinary field between healthcare and data science. This fellowship symbolizes my core value for career development as a data scientist in healthcare,” said 2021 MICDE Fellowship recipient Hyeon Joo, Ph.D. pre-candidate in health infrastructure and learning systems and scientific computing. The MICDE graduate student top-off fellowship provides students with a stipend to use for supplies, technology, and other materials that will further their graduate education and research. Among other things, awards have helped many to travel to conferences and meetings around the world to share the rich and diverse research in computational science being carried out at U-M.

Yifu An, Climate and Space Sciences Engineering
Andre Antoine, Applied Physics
Shreyas Bhat, Industrial and Operations Engineering
Erin Burrell, Mechanical Engineering and Scientific Computing
Alanah Cardenas-O’Toole, Climate and Space Sciences Engineering
Brian Chen, Applied and Interdisciplinary Mathematics
Xinyu Fei, Industrial and Operations Engineering and Scientific Computing
Nicholas Galioto, Aerospace Engineering
Vishwas Goel, Materials Science and Engineering and Scientific Computing
Min-Chun Han, Civil and Environmental Engineering
Dalia Hassan, Chemistry and Scientific Computing
Alexander Hrabski, Naval Architecture and Marine Engineering and Scientific Computing
Javiera Jilberto Vallejos, Biomedical Engineering and Scientific Computing
Hyeon Joo, Learning Health Sciences and Scientific Computing
Timothy Jugovic, Chemistry and Scientific Computing
Ismael Mendoza, Physics and Scientific Computing
Aagnik (Nick) Pant, Applied Physics and Scientific Computing
Hardik Patil, Civil and Environmental Engineering
Amanda Wang, Materials Science and Engineering
Wenbo Wu, Biostatistics and Scientific Computing

Learn more about the fellows and the MICDE Fellowship program

Postdoc Position in Mechanical/Biomedical Engineering at the University of Michigan

By | News, SC2 jobs

Job Description:

Example of an image-based geometric model of a human aorta, discretized using an unstructured linear tetrahedral mesh.

Prof. Jesse Capecelatro in the Department of Mechanical Engineering and Prof. Alberto Figueroa of Biomedical Engineering are currently seeking a post-doctoral scholar for a one-year position.

The project aims at developing a numerical framework to simulate a large number of particles within the human body, from deformable red blood cells within arteries to better understand stroke, to rigid calcite particles in the ear canal responsible for vertigo. This will be performed within the CRIMSON (CardiovasculaR Integrated Modeling and SimulatiON) software environment, a Fortran-based finite element solver that simulates fluid flow in patient-specific geometries on unstructured grids.

Required Qualifications:

  • PhD in Engineering or a related field (e.g., Physics, Mathematics, or Computer Science)
  • Experience in Scientific Computing (proficiency in MPI and Fortran/C)
  • Interest in biological fluid dynamics and multiphase flow.

How to Apply:

If you are interested in this position, please email your curriculum vitae and at
least two references to Jesse Capecelatro (jcaps@umich.edu).