28 citations · 85 across the 19 of their papers we have counts for
26 papers
Euler Cutting Planes for Fractional CVaR Programming
Pranay Seshadri, Hubert Dzieciol, Zhe Feng +1
We maximise expected reward per unit of marginal tail risk, a reward-to-CVaR ratio against a baseline. The standard Dinkelbach route re-solves a Rockafellar--Uryasev LP or QP with…
Spatial anomaly detection with optimal transport
Pranay Seshadri, Andrew B. Duncan, George Thorne +1
This manuscript outlines an automated anomaly detection framework for jet engines. It is tailored for identifying spatial anomalies in steady-state temperature measurements at vari…
Prior-informed Uncertainty Modelling with Bayesian Polynomial Approximations
Chun Yui Wong, Pranay Seshadri, Andrew B. Duncan +2
Orthogonal polynomial approximations form the foundation to a set of well-established methods for uncertainty quantification known as polynomial chaos. These approximations deliver…
Density reconstruction from schlieren images through Bayesian nonparametric models
Bryn Noel Ubald, Pranay Seshadri, Andrew Duncan
This study proposes a radically alternate approach for extracting quantitative information from schlieren images. The method uses a scaled, derivative enhanced Gaussian process mod…
Jarvis for Aeroengine Analytics: A Speech Enhanced Virtual Reality Demonstrator Based on Mining Knowledge Databases
Sławomir Konrad Tadeja, Krzysztof Kutt, Yupu Lu +3
In this paper, we present a Virtual Reality (VR) based environment where the engineer interacts with incoming data from a fleet of aeroengines. This data takes the form of 3D compu…
Polynomial Ridge Flowfield Estimation
Ashley Scillitoe, Pranay Seshadri, Chun Yui Wong +1
Computational fluid dynamics plays a key role in the design process across many industries. Recently, there has been increasing interest in data-driven methods, in order to exploit…
Automatic Borescope Damage Assessments for Gas Turbine Blades via Deep Learning
Chun Yui Wong, Pranay Seshadri, Geoffrey T. Parks
To maximise fuel economy, bladed components in aero-engines operate close to material limits. The severe operating environment leads to in-service damage on compressor and turbine…
Blade Envelopes Part II: Multiple Objectives and Inverse Design
Chun Yui Wong, Pranay Seshadri, Ashley Scillitoe +3
Blade envelopes offer a set of data-driven tolerance guidelines for manufactured components based on aerodynamic analysis. In Part I of this two-part paper, a workflow for the form…
Bayesian Assessments of Aeroengine Performance with Transfer Learning
Pranay Seshadri, Andrew Duncan, George Thorne +3
Aeroengine performance is determined by temperature and pressure profiles along various axial stations within an engine. Given limited sensor measurements both along and between ax…
Blade Envelopes Part I: Concept and Methodology
Chun Yui Wong, Pranay Seshadri, Ashley Scillitoe +2
Blades manufactured through flank and point milling will likely exhibit geometric variability. Gauging the aerodynamic repercussions of such variability, prior to manufacturing a c…
Bayesian Mass Averaging in Rigs and Engines
Pranay Seshadri, Andrew Duncan, George Thorne
This paper introduces the Bayesian mass average and details its computation. Owing to the complexity of flow in an engine and the limited instrumentation and the precision of the s…
Uncertainty Quantification for Data-driven Turbulence Modelling with Mondrian Forests
Ashley Scillitoe, Pranay Seshadri, Mark Girolami
Data-driven turbulence modelling approaches are gaining increasing interest from the CFD community. However, the introduction of a machine learning (ML) model introduces a new sour…
AeroVR: Immersive Visualization System for Aerospace Design
Slawomir Konrad Tadeja, Pranay Seshadri, Per Ola Kristensson
One of today's most propitious immersive technologies is virtual reality (VR). This term is colloquially associated with headsets that transport users to a bespoke, built-for-purpo…
Supporting Multi-point Fan Design with Dimension Reduction
Pranay Seshadri, Shaowu Yuchi, Shahrokh Shahpar +1
Motivated by the idea of turbomachinery active subspace performance maps, this paper studies dimension reduction in turbomachinery 3D CFD simulations. First, we show that these sub…
Spatial Flow-Field Approximation Using Few Thermodynamic Measurements Part I: Formulation and Area Averaging
Pranay Seshadri, Duncan Simpson, George Thorne +2
Our investigation raises an important question that is of relevance to the wider turbomachinery community: how do we estimate the spatial average of a flow quantity given finite (a…
Spatial Flow-Field Approximation Using Few Thermodynamic Measurements Part II: Uncertainty Assessments
Pranay Seshadri, Andrew Duncan, Duncan Simpson +2
In this second part of our two-part paper, we provide a detailed, frequentist framework for propagating uncertainties within our multivariate linear least squares model. This permi…
Extremum Sensitivity Analysis with Polynomial Monte Carlo Filtering
Chun Yui Wong, Pranay Seshadri, Geoffrey T. Parks
Global sensitivity analysis is a powerful set of ideas and heuristics for understanding the importance and interplay between uncertain parameters in a computational model. Such a m…
Embedded Ridge Approximations
Chun Yui Wong, Pranay Seshadri, Geoffrey Parks +1
Many quantities of interest (qois) arising from differential-equation-centric models can be resolved into functions of scalar fields. Examples of such qois include the lift over an…
Numerical Evaluation of Entropy Generation in Isolated Airfoils and Wells Turbines
Tiziano Ghisu, Francesco Cambuli, Pierpaolo Puddu +3
In recent years, a number of authors have studied entropy generation in Wells turbines. This is potentially a very interesting topic, as it can provide important insights into the…
Quadrature Strategies for Constructing Polynomial Approximations
Pranay Seshadri, Gianluca Iaccarino, Tiziano Ghisu
Finding suitable points for multivariate polynomial interpolation and approximation is a challenging task. Yet, despite this challenge, there has been tremendous research dedicated…
Dimension Reduction via Gaussian Ridge Functions
Pranay Seshadri, Shaowu Yuchi, Geoffrey T. Parks
Ridge functions have recently emerged as a powerful set of ideas for subspace-based dimension reduction. In this paper we begin by drawing parallels between ridge subspaces, suffic…
Kronecker Product Least Squares
Pranay Seshadri
In this rather brief note we present and discuss techniques for solving Kronecker matrix product least squares problems. Our main contribution is an iterative approach that uses th…
An Aerodynamic Analysis of a Robustly Redesigned Modern Aero-Engine Fan
Pranay Seshadri, Geoffrey Parks, Shahrokh Shahpar
This paper documents results from a recent computational study aimed at de-sensitizing fan stage aerodynamics---in a modern, high bypass ratio aero-engine---to the effects of rear-…
Effectively Subsampled Quadratures For Least Squares Polynomial Approximations
Pranay Seshadri, Akil Narayan, Sankaran Mahadevan
This paper proposes a new deterministic sampling strategy for constructing polynomial chaos approximations for expensive physics simulation models. The proposed approach, effective…