U of T ENGINEERING

University of Toronto Institute for Aerospace Studies

Aerospace Computational Engineering Lab

Publications

To request an accessible list of publications, please contact communications@utias.utoronto.ca.

Journal Papers

  1. AH Razavi and M Yano. Registration-based nonlinear model reduction of parametrized aerodynamics problems with applications to transonic Euler and RANS flows. Journal of Computational Physics, 521:113576, 2025. paper | doi:10.1016/j.jcp.2024.113576
  2. M Ebrahimi and M Yano. A hyperreduced reduced basis element method for reduced-order modeling of component-based nonlinear systems. Computer Methods in Applied Mechanics and Engineering, 431:117254, 2024. paper | doi:10.1016/j.cma.2024.117254
  3. E Parish, M Yano, I Tezaur, and T Iliescu. Residual-based stabilized reduced-order models of the transient convection-diffusion-reaction equation obtained through discrete and continuous projection. Archives of Computational Methods in Engineering. Accepted. 2024. paper | doi:10.1007/s11831-024-10197-1
  4. C Audouze, A Klein, A Butscher, N Morris, PB Nair, and M Yano. Robust level-set-based topology optimization under uncertainties using anchored ANOVA Petrov-Galerkin method. SIAM/ASA Journal on Uncertainty Quantification, 11(3): 877-905, 2023. paper | doi:10.1137/22M1524722
  5. G Lu, AM Steinberg, and M Yano. A sparse optical flow inspired method for 3D velocimetry. Experiments in Fluids, 64:66, 2023. doi:10.1007/s00348-023-03593-z
  6. AF Ilersich, KA Schau, JC Oefelein, AM Steinberg, and M Yano. Augmenting covariance estimation for ensemble-based data assimilation in multiple-query scenarios. Combustion Theory and Modelling, 26(6):1041-1070, 2022. paper | doi:10.1080/13647830.2022.2105259
  7. G Donoghue and M Yano. A multi-fidelity ensemble Kalman filter with hyperreduced reduced-order models. Computer Methods in Applied Mechanics and Engineering, 398:115282, 2022. paper | doi:10.1016/j.cma.2022.115282
  8. E Du and M Yano. Efficient hyperreduction of high-order discontinuous Galerkin methods: element-wise and point-wise reduced quadrature formulations. Journal of Computational Physics, 466:111399, 2022. paper | doi:10.1016/j.jcp.2022.111399
  9. A Klein, PB Nair, and M Yano. A priori error analysis of shape derivatives of linear functionals in structural topology optimization. Computational Methods in Applied Mechanics and Engineering, 395:114991, 2022. paper | doi:10.1016/j.cma.2022.114991
  10. M Sleeman and M Yano. Goal-oriented model reduction for parametrized time-dependent nonlinear partial differential equations. Computational Methods in Applied Mechanics and Engineering, 388:114206, 2022. paper | doi:10.1016/j.cma.2021.114206
  11. K Kumashiro, AM Steinberg, and M Yano. A functional error analysis of differential optical flow methods. Experiments in Fluids, 62:159, 2021. paper | doi:10.1007/s00348-021-03244-1
  12. M Yano, T Huang, and MJ Zahr. A globally convergent method to accelerate topology optimization using on-the-fly model reduction. Computational Methods in Applied Mechanics and Engineering, 375:113635, 2021. paper | doi:10.1016/j.cma.2020.113635
  13. G Donoghue and M Yano. Spatio-stochastic adaptive discontinuous Galerkin methods. Computational Methods in Applied Mechanics and Engineering, 374:113570, 2021. paper | doi:10.1016/j.cma.2020.113570
  14. M Yano. Goal-oriented model reduction of parametrized nonlinear PDEs; application to aerodynamics. International Journal for Numerical Methods in Engineering, 121:5200-5226, 2020. paper | doi:10.1002/nme.6395
  15. M Yano. Discontinuous Galerkin reduced basis empirical quadrature procedure for model reduction of parametrized nonlinear conservation laws. Advances in Computational Mathematics, 45:2287-2320, 2019. paper | doi:10.1007/s10444-019-09710-z
  16. M Yano and AT Patera. An LP empirical quadrature procedure for reduced basis treatment of parametrized nonlinear PDEs. Computational Methods in Applied Mechanics and Engineering, 344:1104-1123, 2019. paper | doi:10.1016/j.cma.2018.02.028
  17. D Getty, H Li, M Yano, C Gao, and AE Hosoi. Luck and the law: quantifying chance in fantasy sports and other contests. SIAM Review, 60:869–887, 2018. paper | doi:10.1137/16M1102094
  18. M Yano. A reduced basis method for coercive equations with an exact solution certificate and spatio-parameter adaptivity: energy-norm and output error bounds, SIAM Journal on Scientific Computing, 40(1):A388-A420, 2018. paper | doi:10.1137/16M1071341
  19. T Taddei, JD Penn, M Yano, and AT Patera. Simulation-based classification; a model-order reduction approach for structural health monitoring. Archives of Computational Methods in Engineering, 25(1): 23-45, 2018. paper | doi:10.1007/s11831-016-9185-0
  20. AT Patera and M Yano. An LP empirical quadrature procedure for parametrized functions. Comptes Rendus Mathematique, 355(11):1161-1167, 2017. paper | doi:10.1016/j.crma.2017.10.020
  21. M Yano. A minimum-residual mixed reduced basis method: Exact residual certification and simultaneous finite-element reduced-basis refinement. Mathematical Modelling and Numerical Analysis, 50:163-185, 2016. paper | doi:10.1051/m2an/2015039
  22. Y Maday, O Mula, AT Patera, and M Yano. The generalized Empirical Interpolation Method: stability theory on Hilbert spaces with an application to the Stokes equation. Computational Methods in Applied Mechanics and Engineering, 287:310-334, 2015. paper | doi:10.1016/j.cma.2015.01.018
  23. M Yano. A reduced basis method with exact-solution certificates for steady symmetric coercive equations. Computational Methods in Applied Mechanics and Engineering, 287:290-309, 2015. paper | doi:10.1016/j.cma.2015.01.003
  24. Y Maday, AT Patera, JD Penn, and M Yano. A parametrized-background data-weak approach to variational data assimilation: Formulation, analysis, and application to acoustics. International Journal for Numerical Methods in Engineering, 102(5):933-965, 2015. paper | doi:10.1002/nme.4747
  25. M Yano. A space-time Petrov-Galerkin certified reduced basis method: Application to the Boussinesq equations. SIAM Journal on Scientific Computing, 36(1):A232-A266, 2014. paper | doi:10.1137/120903300
  26. M Yano, AT Patera, and K Urban. A space-time certified reduced basis method for Burgers' equation. Mathematical Models and Methods in Applied Sciences, 24:1903, 2014. paper | doi:10.1142/S0218202514500110
  27. M Yano, JD Penn, and AT Patera. A model-data weak formulation for simultaneous estimation of state and bias. Comptes Rendus Mathematique, 351(23-24):937-941, 2013. paper | doi:10.1016/j.crma.2013.10.034
  28. M Yano and AT Patera. A space-time variational approach to hydrodynamic stability theory. Proceedings of the Royal Society A, 469(2155): Article Number 20130036, 2013. paper | doi:/10.1098/rspa.2013.0036
  29. M Yano and DL Darmofal. An optimization framework for anisotropic simplex mesh adaptation. Journal of Computational Physics, 231:7626-7649, 2012. paper | doi:10.1016/j.jcp.2012.06.040
  30. M Yano and DL Darmofal. BDDC preconditioning for high-order Galerkin least-squares method using inexact solvers. Computational Methods in Applied Mechanics and Engineering, 199:2958-2969, 2010. doi:10.1016/j.cma.2010.06.006
  31. M Yano and MLR Walker. Generalized theory of annularly-bounded helicon waves. Physics of Plasmas, 14, 033510:1-7, 2007. doi:10.1063/1.2716663
  32. M Yano and MLR Walker. Plasma ionization by annularly-bounded helicon waves. Physics of Plasmas, 13, 063501:1-5, 2006. doi:10.1063/1.2207125

Book Chapters

  1. M Yano. Model reduction in computational aerodynamics. In P Benner, S Grivet-Talocia, A Quarteroni, G Rozza, WHA Schilders, and LM Silveira (Eds.), Model Order Reduction, Volume 3, Chapter 6, 2020. paper | doi:10.1515/9783110499001-006 | book
  2. M Yano. A reduced basis method with an exact solution certificate and spatio-parameter adaptivity: application to linear elasticity. In P Benner, M Ohlberger, A Patera, G Rozza, and K Urban (Eds.), Model Reduction of Parametrized Systems, Chapter 4, 55-76, 2017. paper | doi:10.1007/978-3-319-58786-8_4 | book

Conference Papers

  1. G Lu, A Fereidooni, A Grewal, and M Yano. Adaptive Gaussian process surrogate models for efficient uncertainty quantification of flutter boundary. AIAA SciTech 2025, January 2025. paper
  2. AH Razavi and M Yano. Nonlinear model reduction for rapid and reliable CFD: application to transonic RANS flows. CSME/CFD2024, May 2024. paper
  3. B Gibson and M Yano. Accelerated nonlinear-PDE-constrained optimization by reduced order modelling. ECCOMAS Congress, June 2022. paper | doi:10.23967/eccomas.2022.035
  4. AF Ilersich, K Schau, JC Oefelein, AM Steinberg, and M Yano. Reducing the cost of ensemble-based data assimilation in multiple-query scenarios through covariance augmentation. AIAA-2021-3632, AIAA Propulsion and Energy, August 2021. paper | doi:10.2514/6.2021-3632
  5. E Du, M Sleeman, and M Yano. Adaptive discontinuous-Galerkin reduced-basis reduced-quadrature method for many-query CFD problems. AIAA-2021-2716, AIAA Aviation 2021, August 2021. paper | doi:10.2514/6.2021-2716
  6. K Kumashiro, A Steinberg, and M Yano. High spatial resolution 3d fluid velocimetry by tomographic particle flow velocimetry. AIAA-2019-0269, AIAA Scitech 2019 Forum, January 2019. paper | doi:10.2514/6.2019-0269
  7. Y Maday, AT Patera, JD Penn, and M Yano. PBDW state estimation: noisy observations; configuration-adaptive background spaces; physical interpretations. Proceedings SMAI CANUM 2014, Carry-le-Rouet, France, in ESAIM: Proceedings and Surveys, 50:144-168, 2015. paper | doi:10.1051/proc/201550008
  8. DL Darmofal, SR Allmaras, M Yano, and J Kudo. An adaptive, higher-order discontinuous Galerkin finite element method for aerodynamics. AIAA-2013-2871, 21st AIAA Computational Fluid Dynamics Conference, June 2013. paper | doi:10.2514/6.2013-2871
  9. M Yano and DL Darmofal. Anisotropic simplex mesh adaptation by metric optimization for higher-order DG discretizations of 3D compressible flows. 10th World Congress on Computational Mechanics, July 2012. paper | doi:10.5151/meceng-wccm2012-18538
  10. M Yano and DL Darmofal. An optimization framework for anisotropic simplex mesh adaptation: application to aerodynamic flows. AIAA-2012-0079, 50th AIAA Aerospace Sciences Meeting, January 2012. paper | doi:10.2514/6.2012-79
  11. M Yano, JM Modisette and DL Darmofal. The importance of mesh adaptation for high-order discretizations of aerodynamic flows. AIAA-2011-3852, 20th AIAA Computational Fluid Dynamics Conference, June 2011. paper | doi:10.2514/6.2011-3852
  12. J Andren, H Gao, M Yano, DL Darmofal, C Ollivier-Gooch, and ZJ Wang. A comparison of higher-order methods for a set of canonical aerodynamics applications. AIAA-2011-3230, 20th AIAA Computational Fluid Dynamics Conference, June 2011. paper | doi:10.2514/6.2011-3230
  13. M Yano and DL Darmofal. Massively parallel solver for the high-order Galerkin least-squares method. AIAA-2009-4135, 19th AIAA Computational Fluid Dynamics Conference, June 2009. paper | doi:10.2514/6.2009-4135
  14. S D Howe, N Barra, J Bess, E Colvin, P Cummings, B Cunningham, M Christ, R Johnson, R O'Brien, J Perkins, K Supak, M Yano. Using a nuclear rocket to support a lunar outpost: is it cost effective? Proceedings of the Space Nuclear Conference, American Nuclear Society, June 2007.
  15. M Yano, D Palmer, L Williams, and MLR Walker. Design and operation of an annular helicon plasma source. AIAA-2007-5309, 43rd AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit, July 2007. paper | doi:10.2514/6.2007-5309

Technical Reports

  1. M Yano and DL Darmofal. ProjectX results (C1.1 bump; C1.2 Ringleb; C1.3 NACA0012; C1.4 flat plate; C2.2 RAE2822; C3.1 MDA high-lift). 1st International Workshop on High-Order CFD Methods, January 2012.
  2. M Yano and DL Darmofal. On dual-weighted residual error estimates for p-dependent discretizations. MIT Aerospace Computational Design Laboratory Technical Report, ACDL TR-11-1, 2011.

Dissertations

  1. M Yano. An Optimization Framework for Adaptive Higher-Order Discretizations of Partial Differential Equations on Anisotropic Simplex Meshes. Doctoral thesis, Massachusetts Institute of Technology, Aeronautics and Astronautics, May 2012.
  2. M Yano. Massively Parallel Solver for the High-Order Galerkin Least-Squares Method. Masters thesis, Massachusetts Institute of Technology, Computational for Design and Optimization, May 2009.

Textbook

  1. M Yano, JD Penn, G Konidaris and AT Patera. Math, Numerics, & Programming for Mechanical Engineers, V 1.2, September, 2012. (OpenCourseWare)

Old publication page: https://arrow.utias.utoronto.ca/~myano/publications

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