Damage Assessment of civil engineering structures and bridges using nonlinear dynamic characteristics

Doctoral thesis (2009)

Data driven discovery of cyber physical systems

in Nature Communications (2019)

Cyber-physical systems embed software into the physical world. They appear in a wide range of applications such as smart grids, robotics, and intelligent manufacturing. Cyber-physical systems have proved ... [more ▼]

Cyber-physical systems embed software into the physical world. They appear in a wide range of applications such as smart grids, robotics, and intelligent manufacturing. Cyber-physical systems have proved resistant to modeling due to their intrinsic complexity arising from the combination of physical and cyber components and the interaction between them. This study proposes a general framework for discovering cyber-physical systems directly from data. The framework involves the identification of physical systems as well as the inference of transition logics. It has been applied successfully to a number of real-world examples. The novel framework seeks to understand the underlying mechanism of cyber-physical systems as well as make predictions concerning their state trajectories based on the discovered models. Such information has been proven essential for the assessment of the performance of cyber- physical systems; it can potentially help debug in the implementation procedure and guide the redesign to achieve the required performance. [less ▲]

Data mining in geographical contexts and texts

Presentation (2010)

An increasing number of institutions, acting at different scales and within different sectors, create in-house geographical information systems, e.g. for regional statistics, for land and transport ... [more ▼]

An increasing number of institutions, acting at different scales and within different sectors, create in-house geographical information systems, e.g. for regional statistics, for land and transport management, for local urban planning, etc. In addition, with the advent of new technologies, such as GPS's or web-mapping facilities, the use of such geographical data is being more and more popular and data is made more easily accessible (sometimes even contributed by the end-users). Geographers find themselves in rather data rich environments today (irrespective of homogeneity and quality). Also geographical objects require specific visualization and statistical methods. The application and adaptation of data mining approaches in geographical contexts is an increasingly important research topic. In this lecture we will start from theoretical considerations on data mining in geography, particularly emphasizing what is special with exploratory spatial data analysis. We will then refer to ongoing research related to geographical data mining undertaken at the University of Luxembourg in collaboration with colleagues from other institutions. A first example will refer to a large and homogeneous dataset of all dwellings within a Belgian province. Using graph theory and local spatial statistics, the data is used to identify and categorize urbanisation patterns across scales in an iterative way. A second example will depict an application of 'self-organizing maps' to understand patterns of 'territorial cohesion' in Europe using a rather small and lacunary dataset. The third example will be dedicated to a text-mining application to a rather large corpus of documents related to spatial development in Europe. This work funded under the ESPON (European Spatial Observatory Network) aims at producing a relevant thematic structure to the online regional statistics database of the ESPON network. [less ▲]

Data Science and Environmental Cheminformatics (SanDAL Workshop, Uni Lu)

Presentation (2020, October 13)

Data science meets computational mechanics

Report (2021)

Data-driven constitutive laws for hyperelasticity in principal space using symbolic representations of Pytorch ANNs in FEniCS

Poster (2021, May 21)

DATA-INTEGRATED MULTISCALE MODELLING OF FIBROUS EXTRACELLULAR MATRIX

Poster (2021, May 21)

Dealing with interfaces in partitioned model order reduction for application to nonlinear problems

Scientific Conference (2013)

We propose a reduced order modelling technique based on a partitioning of the domain of study in the context of para- metric nonlinear problems. A formulation of the reduction of the displacement and of ... [more ▼]

We propose a reduced order modelling technique based on a partitioning of the domain of study in the context of para- metric nonlinear problems. A formulation of the reduction of the displacement and of the interface tractions linking subdomains to each others will be performed in a FETI context. [less ▲]

Decentralised minimal-time consensus

in The proceedings of the 2011 50th IEEE Conference on Decision and Control and European Control Conference (CDC-ECC) (2011)

This study considers the discrete-time dynamics of a network of agents that exchange information according to the nearest-neighbour protocol under which all agents are guaranteed to reach consensus ... [more ▼]

This study considers the discrete-time dynamics of a network of agents that exchange information according to the nearest-neighbour protocol under which all agents are guaranteed to reach consensus asymptotically. We present a fully decentralised algorithm that allows any agent to compute the consensus value of the whole network in finite time using only the minimal number of successive values of its own history. We show that this minimal number of steps is related to a Jordan block decomposition of the network dynamics and present an algorithm to obtain the minimal number of steps in question by checking a rank condition on a Hankel matrix of the local observations. Furthermore, we prove that the minimal number of steps is related to other algebraic and graph theoretical notions that can be directly computed from the Laplacian matrix of the graph and from the underlying graph topology. [less ▲]

Decentralised minimum-time consensus

in Automatica (2013), 49(5), 1227-1235

We consider the discrete-time dynamics of a network of agents that exchange information according to a nearest-neighbour protocol under which all agents are guaranteed to reach consensus asymptotically ... [more ▼]

We consider the discrete-time dynamics of a network of agents that exchange information according to a nearest-neighbour protocol under which all agents are guaranteed to reach consensus asymptotically. We present a fully decentralised algorithm that allows any agent to compute the final consensus value of the whole network in finite time using the minimum number of successive values of its own state history. We show that the minimum number of steps is related to a Jordan block decomposition of the network dynamics, and present an algorithm to compute the final consensus value in the minimum number of steps by checking a rank condition of a Hankel matrix of local observations. Furthermore, we prove that the minimum number of steps is related to graph theoretical notions that can be directly computed from the Laplacian matrix of the graph and from the minimum external equitable partition. [less ▲]