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Related publications (9)

Automatic Parameterization for Aerodynamic Shape Optimization via Deep Geometric Learning

Pascal Fua, Zhen Wei

We propose two deep learning models that fully automate shape parameterization for aerodynamic shape optimization. Both models are optimized to parameterize via deep geometric learning to embed human prior knowledge into learned geometric patterns, elimina ...

2023

Surrogate modelling for seismic collapse risk assessment of steel moment resisting frames

Dimitrios Lignos, Andronikos Skiadopoulos, Nenad Bijelic

With the overall goal of reducing the numerical burden of uncertainty quantification involved in seismic risk assessments, this paper examines opportunities for assessment of seismic collapse capacity and risk using data-driven surrogates as a complement t ...

2023

A combined genetic algorithm and active learning approach to build and test surrogate models in Process Systems Engineering

François Maréchal, Julia Granacher

In Process Systems Engineering, computationally-demanding models are frequent and plentiful. Handling such complexity in an optimization framework in a fast and reliable way is essential, not only for generating meaningful solutions but also for providing ...

Pergamon-Elsevier Science Ltd2023

Robust design using multiobjective optimisation and artificial neural networks with application to a heat pump radial compressor

Jürg Alexander Schiffmann, Soheyl Massoudi, Cyril Picard

Although robustness is an important consideration to guarantee the performance of designs under deviation, systems are often engineered by evaluating their performance exclusively at nominal conditions. Robustness is sometimes evaluated a posteriori throug ...

2022

A Pareto Dominance Principle for Data-Driven Optimization

Daniel Kuhn, Tobias Sutter

We propose a statistically optimal approach to construct data-driven decisions for stochastic optimization problems. Fundamentally, a data-driven decision is simply a function that maps the available training data to a feasible action. It can always be exp ...

2024

Accurate and efficient interpretation of load-test data for asset-management

Sai Ganesh Sarvotham Pai

Increasing demand for new infrastructure and ageing of existing infrastructure has made management of infrastructure a key challenge of this century. Replacement of all ageing civil infrastructure is economically and environmentally unsustainable. Civil in ...

EPFL2019

The GBS code for tokamak scrape-off layer simulations

Paolo Ricci, Joaquim Loizu Cisquella, Trach-Minh Tran, Sébastien Jolliet, Federico David Halpern, Fabio Riva, Annamaria Mosetto, Christoph Wersal

We describe a new version of GBS, a 3D global, flux-driven plasma turbulence code to simulate the turbulent dynamics in the tokamak scrape-off layer (SOL), superseding the code presented by Ricci et al. (2012) [14]. The present work is driven by the object ...

Elsevier2016

Complementary Germanium Electron-Hole Bilayer Tunnel FET for Sub-0.5-V Operation

Mihai Adrian Ionescu, Luca De Michielis, Livio Lattanzio

In this paper we present a novel device, the Germanium Electron-Hole Bilayer Tunnel FET (Ge EHBTFET), which exploits carrier tunneling through a bias-induced electron-hole bilayer. The proposed architecture provides a quasi-ideal alignment between the tunn ...

Institute of Electrical and Electronics Engineers2012

AdS/QCD: the relevance of the geometry

Andrea Wulzer

We investigate the relevance of the metric and of the geometry in five-dimensional models of hadrons. Generically, the metric does not affect strongly the results and even flat space agrees reasonably well with the data. Nevertheless, we observe a preferen ...

Springer Nature2010