Research

Our team undertakes research in the following areas.

bayesian inference

uncertainty quantification

polynomial chaos

dimension reduction

polynomial interpolation

surrogate-based optimisation

supervised machine learning

sensitivity analysis

active subspaces

matrix computations

numerical integration

design of experiment

transfer learning

manifold learning

linear algebra

Relevant papers may be found below.

Data-driven dimension reduction

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Title

Embedded ridge approximations

Authors

Chun Yui Wong, Pranay Seshadri, Geoffrey Parks, Mark Girolami

Essence

Constructing ridge approximations for vector-valued quantities, and scalar-valued functions that are integrals of vector-valued fields. For example, the lift, drag and pressure coefficients of an airfoil.

Journal

Computer Methods in Applied Mechanics

Year

2020

Resources

Paper | Preprint | Blog


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Title

Blade envelopes parts I & II

Authors

Chun Yui Wong, Pranay Seshadri, Ashley Scillitoe, Andrew Duncan, Geoffrey Parks

Essence

Interpreting the design of a blade (airfoil) as a Gaussian distribution with known mean (nominal) but unknown covariance. Estimating this covariance matrix by generating samples from the inactive subspace for loss in part I. In part II we extend the approach in part I to multiple objectives (flow capacity, loss and peak Isentropic Mach number) and demonstrating how this approach can be used for inverse design.

Journal

ASME Journal of Turbomachinery (under review)

Year

2020

Resources

Preprint I | Blog I | Preprint II | Blog II | Slides

Video


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Title

Design Space Exploration of Stagnation Temperature Probes via Dimension Reduction

Authors

Ashley Scillitoe, Bryn Noel Ubald, Pranay Seshadri, Shahrokh Shahpar

Essence

Using polynomial variable projection to explore the design space of a stagnation temperature probe representative of those used in gas-turbine aero engines. Dimension reducing subspaces are used to find more accurate designs with less sensitivity to manufacturing uncertainties.

Conference

ASME Turbo Expo

Year

2021

Resources

Paper | Blog | Code


Title

Turbomachinery active subspace performance maps

Authors

Pranay Seshadri, Shahrokh Shahpar, Paul Constantine, Geoffrey Parks, Mike Adams

Essence

On generating 2D contour plots of the entire 25D design space of a modern fan blade from a jet-engine.

Journal

ASME Journal of Turbomachinery

Year

2018

Resources

Preprint | Paper


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Title

Supporting multi-point fan design with dimension reduction

Authors

Pranay Seshadri, Shaowu Yuchi, Shahrokh Shahpar, Geoffrey Parks

Essence

Polynomial variable projection applied to three distinct fan blades at different operating conditions.

Journal

The Aeronautical Journal

Year

2018

Resources

Preprint | Paper

Numerical integration

Title

Effectively subsampled quadratures

Authors

Pranay Seshadri, Akil Narayan, Sankaran Mahadevan

Essence

Subsampling quadrature points from a tensorial grid via QR with column pivoting on a weighted Vandermonde-type matrix.

Journal

SIAM/ASA Journal on Uncertainty Quantification

Year

2017

Resources

Paper | Preprint


Title

Quadrature strategies for constructing polynomial approximations

Authors

Pranay Seshadri, Gianluca Iaccarino, Tiziano Ghisu

Essence

A review of recent approaches for identifying quadrature rules in hypercubes, followed by a template-type characterisation of how one arrive at new quadrature rules.

Journal

Uncertainty Modeling for Engineering Applications, Springer.

Year

2018

Resources

Paper | Preprint

Multi-fidelity parameter studies

Coming soon! But in the interim check out the slides below:

Title

Bayesian polynomial chaos

Resources

Slides

Uncertainty quantification and sensitivity analysis

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Title

Extremum sensitivity analysis with polynomial Monte Carlo filtering

Authors

Chun Yui Wong, Pranay Seshadri, Geoffrey Parks

Essence

Deriving Sobol’ indices for polynomial ridge approximations, and developing methods for extremeum sensitivity analysis using Monte Carlo filtering and correlated polynomial approximations.

Journal

Reliability Engineering and System Safety (under review)

Year

2019

Resources

Preprint | Blog


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Title

Sensitivity analysis of a coupled hydrodynamic-vegetation model using the effectively subsampled quadratures method

Authors

Tarandeep Kalra

Essence

The application of effectively subsampled quadratures for computing Sobol’ indices for a coupled hydrodynamic-vegetation model.

Journal

Geoscientific Model Development Discussions

Year

2019

Resources

Paper | Blog

Flow-field estimation

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Title

Polynomial ridge flowfield estimation

Authors

Ashley Scillitoe, Pranay Seshadri, Chun Yui Wong, Andrew Duncan

Essence

Flowfield estimation for a new geometry or boundary condition given a relevant training repository of the same test case.

Journal

Physics of Fluids (under review)

Year

2021

Resources

Preprint | App