Publications related to Multimodel Structural Performance Monitoring

Comparison of data interpretation methodologies for geotechnical back analysis

Rigorous back analysis plays a major role in providing information to engineers for better decision-making. Most research on this topic has focused on optimization techniques. Comparative studies of data interpretation methodologies have seldom been report ...

2019

Using Regularized Linear-Regression Surrogate Models for Accurate Probabilistic Structural Identification

Ian Smith, Sai Ganesh Sarvotham Pai

Model-based data interpretation has the potential to increase knowledge of structural behavior and support asset management. Models are usually conservative and contain many parameters and sources of systematic uncertainty, which need to be taken into acco ...

2019

Using Regularized Linear-Regression Surrogate Models for Accurate Probabilistic Structural Identification

Ian Smith, Sai Ganesh Sarvotham Pai

Model-based data interpretation has the potential to increase knowledge of structural behavior and support asset management. Models are usually conservative and contain many parameters and sources of systematic uncertainty, which need to be taken into acco ...

AMER SOC CIVIL ENGINEERS2019

Efficient Learning from Comparisons

Lucas Maystre

Humans are comparison machines: comparing and choosing an item among a set of alternatives (such as objects or concepts) is arguably one of the most natural ways for us to express our preferences and opinions. In many applications, the analysis of data con ...

EPFL2018

Evaluating predictive performance of sensor configurations in wind studies around buildings

Ian Smith, Maria Papadopoulou

A great challenge associated with urban growth is to design for energy efficient and healthy built environments. Exploiting the potential for natural ventilation in buildings might improve pedestrian comfort and lower cooling loads, particularly in warm an ...

Elsevier2016

Stream temperature modeling in mountainous environments

Aurélien Gallice

Stream temperature is one of the key variables affecting the habitat suitability of numerous aquatic species. Over the past decades, research efforts on this topic have concentrated on low-land rivers of North-America, whereas mountainous environments have ...

EPFL2016

Robust system identification and model predictions in the presence of systematic uncertainty

Ian Smith, Romain Pasquier

Model-based data-interpretation techniques are increasingly used to improve the knowledge of complex system behavior. Physics-based models that are identified using measurement data are generally used for extrapolation to predict system behavior under othe ...

Elsevier2015

Stream temperature prediction in ungauged basins: review of recent approaches and description of a new physics-derived statistical model

Michael Lehning, Marc Parlange, Bettina Schaefli, Aurélien Gallice

The development of stream temperature regression models at regional scales has regained some popularity over the past years. These models are used to predict stream temperature in ungauged catchments to assess the impact of human activities or climate chan ...

European Geosciences Union2015

Sparsistency of $\ell_1$-Regularized $M$-Estimators

Volkan Cevher, Jonathan Mark Scarlett, Yen-Huan Li

We consider the model selection consistency or sparsistency of a broad set of

\ell_1

-regularized

M

-estimators for linear and non-linear statistical models in a unified fashion. For this purpose, we propose the local structured smoothness condition (LSS ...

2015

Reducing the uncertainty on the structural behaviour of existing structures through data interpretation

Ian Smith, Pierino Lestuzzi, Yves Sylvain Gilles Reuland

This paper presents a methodology for reducing the uncertainty related to the structural behaviour of an existing building in view of a vulnerability assessment regarding future earthquake actions. Estimating the lateral load resistance is a step towards e ...

2015

Multimodel Structural Performance Monitoring

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Comparison of data interpretation methodologies for geotechnical back analysis

Using Regularized Linear-Regression Surrogate Models for Accurate Probabilistic Structural Identification

Using Regularized Linear-Regression Surrogate Models for Accurate Probabilistic Structural Identification

Efficient Learning from Comparisons

Evaluating predictive performance of sensor configurations in wind studies around buildings

Stream temperature modeling in mountainous environments

Robust system identification and model predictions in the presence of systematic uncertainty

Stream temperature prediction in ungauged basins: review of recent approaches and description of a new physics-derived statistical model

Sparsistency of $\ell_1$-Regularized $M$-Estimators

Reducing the uncertainty on the structural behaviour of existing structures through data interpretation

Using Regularized Linear-Regression Surrogate Models for Accurate Probabilistic Structural Identification

Comparison of data interpretation methodologies for geotechnical back analysis

Using Regularized Linear-Regression Surrogate Models for Accurate Probabilistic Structural Identification

Efficient Learning from Comparisons

Evaluating predictive performance of sensor configurations in wind studies around buildings

Stream temperature modeling in mountainous environments

Robust system identification and model predictions in the presence of systematic uncertainty

Stream temperature prediction in ungauged basins: review of recent approaches and description of a new physics-derived statistical model

Reducing the uncertainty on the structural behaviour of existing structures through data interpretation

Sparsistency of $\ell_1$-Regularized $M$-Estimators