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See detailMulti-scale modelling of fracture
Bordas, Stéphane UL; Kerfriden, Pierre; Beex, Lars et al

Speeches/Talks (2016)

We present recent models on complexity reduction for computational fracture mechanics

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See detailA multifactorial evaluation framework for gene regulatory network reconstruction
Mombaerts, Laurent UL; Aalto, Atte UL; Markdahl, Johan UL et al

in Foundations of Systems Biology in Engineering (2019)

In the past years, many computational methods have been developed to infer the structure of gene regulatory networks from time series data. However, the applicability and accuracy presumptions of such ... [more ▼]

In the past years, many computational methods have been developed to infer the structure of gene regulatory networks from time series data. However, the applicability and accuracy presumptions of such algorithms remain unclear due to experimental heterogeneity. This paper assesses the performance of recent and successful network inference strategies under a novel, multifactorial evaluation framework in order to highlight pragmatic tradeoffs in experimental design. The effects of data quantity and systems perturbations are addressed, thereby formulating guidelines for efficient resource management. Realistic data were generated from six widely used benchmark models of rhythmic and nonrhythmic gene regulatory systems with random perturbations mimicking the effect of gene knock-out or chemical treatments. Then, time series data of increasing lengths were provided to five state-of-the-art network inference algorithms representing distinctive mathematical paradigms. The performances of such network reconstruction methodologies are uncovered under various experimental conditions. We report that the algorithms do not benefit equally from data increments. Furthermore, at least for the studied rhythmic system, it is more profitable for network inference strategies to be run on long time series rather than short time series with multiple perturbations. By contrast, for the non-rhythmic systems, increasing the number of perturbation experiments yielded better results than increasing the sampling frequency. We expect that future benchmark and algorithm design would integrate such multifactorial considerations to promote their widespread and conscientious usage. [less ▲]

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See detailA Multilayer Software Architecture for Safe Autonomous Robots
Gribov, Vladislav UL; Voos, Holger UL

in Proceedings of 19th IEEE International Conference on Emerging Technologies and Factory Automation, Barcelona, Spain, 16-19 Sept. 2014 (2014, September)

In this paper a safety-oriented model based software architecture for robotic solutions is proposed. The main focus herein is to consider aspects such as real-time, het- erogeneity, deployment, modeling ... [more ▼]

In this paper a safety-oriented model based software architecture for robotic solutions is proposed. The main focus herein is to consider aspects such as real-time, het- erogeneity, deployment, modeling and analysis of emerging effects as well as functional safety and to combine all aspects into an overall development approach. The architecture shall capture the complexity caused by the autonomy and mobility of the robot and support the developer with a suitable chain of evidence especially suited for the safety relevant functions. A use case comprising a lightweight robotic manipulator which will be integrated in a mobile service robot underlines the feasibility of this approach. [less ▲]

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See detailMultiline holding based control for lines merging to a shared transit corridor
Laskaris, Georgios UL; Cats, Oded; Jenelius, Erik et al

in Transportmetrica B: Transport Dynamics (2018)

In transit corridors, multiple lines share a sequence of consecutive stops to provide higher joint frequency in higher demand areas. A key challenge is to coordinate the transition from single line to ... [more ▼]

In transit corridors, multiple lines share a sequence of consecutive stops to provide higher joint frequency in higher demand areas. A key challenge is to coordinate the transition from single line to joint operation. A holding control strategy aimed at minimizing passenger travel times is introduced for lines merging into a shared corridor, accounting for the coordination of vehicle arrivals from the merging lines as well as the regularity of each line. The criterion is tested using an artificial network and a real-world network to analyze the impact of demand distribution and compare cooperative versus single line control. We illustrate how the real-time strategy yields overall passenger gains, depending on the composition of different user groups. Results are assessed based on operation and passenger performance indicators and show that coordination is achieved. When combined with joint control in the common part, the proposed approach achieves consistentnetwork-wide travel time benefits. [less ▲]

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See detailMultiphysics applications and computational challenges
Zilian, Andreas UL

Scientific Conference (2017, January 24)

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See detailMultiple crack detection in 3D using a stable XFEM and global optimization
Agathos, Konstantinos; Chatzi, Eleni; Bordas, Stéphane UL

in Computational Mechanics (2018)

A numerical scheme is proposed for the detection of multiple cracks in three dimensional (3D) structures. The scheme is based on a variant of the extended finite element method (XFEM) and a hybrid ... [more ▼]

A numerical scheme is proposed for the detection of multiple cracks in three dimensional (3D) structures. The scheme is based on a variant of the extended finite element method (XFEM) and a hybrid optimizer solution. The proposed XFEM variant is particularly well-suited for the simulation of 3D fracture problems, and as such serves as an efficient solution to the so-called forward problem. A set of heuristic optimization algorithms are recombined into a multiscale optimization scheme. The introduced approach proves effective in tackling the complex inverse problem involved, where identification of multiple flaws is sought on the basis of sparse measurements collected near the structural boundary. The potential of the scheme is demonstrated through a set of numerical case studies of varying complexity. [less ▲]

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See detailMultiscale Modelling of Damage and Fracture in Discrete Materials Using a Variational Quasicontinuum Method
Rokos, Ondrej; Peerlings, Ron; Beex, Lars UL et al

Scientific Conference (2017, September 05)

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See detailA multiscale partitioned reduced order model applied to damage simulation
Goury, Olivier; Kerfriden, Pierre; Bordas, Stéphane UL

Scientific Conference (2013, July)

Simulating fracture in realistic engineering components is computationally expensive. In the context of early-stage design, or reverse engineering, such simulations might need to be performed for a large ... [more ▼]

Simulating fracture in realistic engineering components is computationally expensive. In the context of early-stage design, or reverse engineering, such simulations might need to be performed for a large range of material and geometric parameters, which makes the solution to the parametric problem of fracture unaffordable. Model order reduction, such as the proper orthogonal decomposition (POD), is one way to reduce significantly the computational time by reducing the number of spatial unknowns. The solution is searched for in a reduced space spanned by a few well-chosen basis vectors only. In the context of solid mechanics involving structural softening, the strong topological changes in the zone where damage localises are extremely sensitive to variations of the parameters, which requires reduced spaces of prohibitively large dimensions in order to approximate the solution with a sufficiently high degree of accuracy. Introduced in [1], partitioned model order reduction is an alternative to global model order reduction that essentially divides up the problem into smaller regions. Each region can then be tackled using a reduced model of appropriate size, if at all, depending on the local material non-linearities in the region. In the context of multiscale homogenization, simulations of representative volume elements (RVE) have to be performed to obtain the material properties in the different elements of a coarse mesh. When considering a nonlinear material, those multiple RVE simulations can be com- putationally very expensive. They however only differ by the history of boundary conditions applied. This contribution proposes to apply partitioned model order reduction to those RVEs with reduced bases parametrized by the boundary conditions. REFERENCES [1] P. Kerfriden, O. Goury, T. Rabczuk, S. Bordas, A partitioned model order reduction approach to rationalise computational expenses in nonlinear fracture mechanics, Computer Methods in Applied Mechanics and Engineering, 256:169–188, 2013. [less ▲]

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See detailMultiscale Quasicontinuum Methods for Dissipative Truss Models and Beam Networks
Beex, Lars UL; Peerlings, Ron; Geers, Marc et al

Presentation (2014, November 05)

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See detailMultistability of genetic regulatory networks
Pan, Wei UL; Zhang, Z.; Liu, H.

in International Journal of Systems Science (2010), 41(1), 107-118

Multistability is found to be an important recurring theme in synthesis biology. In this article, the multistability analysis problem is investigated by applying control theory and mathematical tools ... [more ▼]

Multistability is found to be an important recurring theme in synthesis biology. In this article, the multistability analysis problem is investigated by applying control theory and mathematical tools. Both the modelling and analysis issues are discussed. Specifically, the genetic regulatory networks (GRNs) with multistability are modelled as switched systems with interval time-varying delays and parameter uncertainties, where the piecewise-affine models are used to approximate the inherent non-linearities existing in the GRNs. Then, by using a novel Lyapunov functional approach and linear matrix inequality (LMI) techniques, a few delay-dependent criteria for the multistability of such genetic regulatory networks are established in the form of LMIs, which can be readily verified by using standard numerical software. A three-component network and a genetic toggle switch with bistability are employed to illustrate the applicability and usefulness of the developed theoretical results. [less ▲]

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See detailNASA-FDL Artificial Intelligence in Planetary Science; Lunar Resource Mission
Backes, Dietmar UL

Scientific Conference (2017, December 15)

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See detailNatural frequencies of cracked isotropic & specially orthotropic plates using the extended finite element method
Natarajan, S; Baiz, P; Mahapatra, D Roy et al

Scientific Conference (2011, April)

In this paper, the linear free flexural vibration of cracked isotropic and specially orthotropic plates is studied using the extended finite element method. The mixed interpolation technique of the well ... [more ▼]

In this paper, the linear free flexural vibration of cracked isotropic and specially orthotropic plates is studied using the extended finite element method. The mixed interpolation technique of the well- established MITC4 [1] quadrilateral finite element with 12 standard degrees of freedom per element is used for this study. The natural frequencies of simply supported square plates are computed as a function of crack length and crack location. [less ▲]

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See detailNecessary and sufficient conditions for dynamical structure reconstruction of LTI networks
Goncalves, Jorge UL; Warnick, S.

in IEEE Transactions on Automatic Control (2008), 53(7), 1670-1674

This paper formulates and solves the network reconstruction problem for linear time-invariant systems. The problem is motivated from a variety of disciplines, but it has recently received considerable ... [more ▼]

This paper formulates and solves the network reconstruction problem for linear time-invariant systems. The problem is motivated from a variety of disciplines, but it has recently received considerable attention from the systems biology community in the study of chemical reaction networks. Here, we demonstrate that even when a transfer function can be identified perfectly from input–output data, not even Boolean reconstruction is possible, in general, without more information about the system.We then completely characterize this additional information that is essential for dynamical reconstruction without appeal to ad-hoc assumptions about the network, such as sparsity or minimality. [less ▲]

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See detailNecessary conditions for robust stability of a class of nonlinear systems
Goncalves, Jorge UL; Dahleh, M. A.

in Automatica (1998), 34(6), 705-714

Input-output stability results for feedback systems are developed. Robust stability conditions are presented for nonlinear systems with nonlinear uncertainty defined by some function (with argument equal ... [more ▼]

Input-output stability results for feedback systems are developed. Robust stability conditions are presented for nonlinear systems with nonlinear uncertainty defined by some function (with argument equal to the norm of the input) that bounds its output norm. A sufficient small gain theorem for a class of these systems is known. Here, necessary conditions are presented for the vector space (L- infinity ll . ll infinity). These results capture the conservatism of the small gain theorem as it is applied to systems that do not have linear gain. The theory is also developed for the case of L2 signal norms, indicating some difficulties which make this case less natural than L-infinity. [less ▲]

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See detailNetwork Identifiability from Intrinsic Noise
Goncalves, Jorge UL; Hayden, David; Yuan, Ye

in IEEE Transactions on Automatic Control (in press)

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See detailNetwork observability information maximization through ad-hoc route enumeration approaches
Rinaldi, Marco UL; Corman, Francesco; Viti, Francesco UL

Scientific Conference (2016, June)

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See detailNetwork Reconstruction from Intrinsic Noise
Hayden, David; Yuan, Ye; Goncalves, Jorge UL

in The proceedings of the American Control Conference (2014)

This paper considers the problem of inferring the structure and dynamics of an unknown network driven by unknown noise inputs. Equivalently we seek to identify direct causal dependencies among manifest ... [more ▼]

This paper considers the problem of inferring the structure and dynamics of an unknown network driven by unknown noise inputs. Equivalently we seek to identify direct causal dependencies among manifest variables only from observations of these variables. We consider linear, time-invariant systems of minimal order and with one noise source per measured state. If the transfer matrix from the inputs to manifest states is known to be minimum phase, this problem is shown to have a unique solution irrespective of the network topology. This is equivalent to there being only one spectral factor (up to a choice of signs of the inputs) of the output spectral density that satisfies these assumptions. Hence for this significant class of systems, the network reconstruction problem is well posed. [less ▲]

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See detailNetwork Reconstruction from Intrinsic Noise: Non-Minimum-Phase Systems
Hayden, David; Yuan, Ye; Goncalves, Jorge UL

in The proceedings of the The 19th World Congress of The International Federation of Automatic Control (2014)

This paper considers the problem of inferring the structure and dynamics of an unknown network driven by unknown noise inputs. Equivalently we seek to identify direct causal dependencies among manifest ... [more ▼]

This paper considers the problem of inferring the structure and dynamics of an unknown network driven by unknown noise inputs. Equivalently we seek to identify direct causal dependencies among manifest variables only from observations of these variables. We consider linear, time-invariant systems of minimal order and with one noise source per manifest state. It is known that if the transfer matrix from the inputs to manifest states is minimum phase, then this problem has a unique solution, irrespective of the network topology. Here we consider the general case where the transfer matrix may be non-minimum phase and show that solutions are characterized by an Algebraic Riccati Equation (ARE). Each solution to the ARE corresponds to at most one spectral factor of the output spectral density that satisfies the assumptions made. Hence in general the problem may not have a unique solution, but all solutions can be computed by solving an ARE and their number may be finite. [less ▲]

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See detailNetwork reconstruction using knock-out and over-expression data
Hayden, David; Yuan, Ye; Goncalves, Jorge UL

in The proceedings of the 2013 European Control Conference (ECC) (2013)

This paper outlines necessary and sufficient conditions for network reconstruction of linear, time-invariant systems using data from either knock-out or over-expression experiments. These structural ... [more ▼]

This paper outlines necessary and sufficient conditions for network reconstruction of linear, time-invariant systems using data from either knock-out or over-expression experiments. These structural system perturbations, which are common in biological experiments, can be formulated as unknown system inputs, allowing the network topology and dynamics to be found. We assume that only partial state measurements are available and propose an algorithm that can reconstruct the network at the level of the measured states using either time-series or steady-state data. A simulated example illustrates how the algorithm successfully reconstructs a network from data. [less ▲]

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See detailNetwork structure preserving model reduction with weak a priori structural information
Yeung, E.; Goncalves, Jorge UL; Sandberg, H. et al

in The proceedings of the Joint 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference (2009)

This paper extends a state projection method for structure preserving model reduction to situations where only a weaker notion of system structure is available. This weaker notion of structure ... [more ▼]

This paper extends a state projection method for structure preserving model reduction to situations where only a weaker notion of system structure is available. This weaker notion of structure, identifying the causal relationship between manifest variables of the system, is especially relevant is settings such as systems biology, where a clear partition of state variables into distinct subsystems may be unknown, or not even exist. The resulting technique, like similar approaches, does not provide theoretical performance guarantees, so an extensive computational study is conducted, and it is observed to work fairly well in practice. Moreover, conditions characterizing structurally minimal realizations and sufficient conditions characterizing edge loss resulting from the reduction process, are presented. [less ▲]

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