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See detailAvailability-based dynamic pricing on a round-trip carsharing service: an explorative analysis using agent-based simulation 
Giorgione, Giulio UL; Ciari, Francesco; Viti, Francesco UL

in Transportation Research Procedia (2019)

Carsharing companies aim to customize their service to increase fleet usage and revenues with different pricing schemes and offer types. Dynamic pricing policies can be designed to adjust and balance ... [more ▼]

Carsharing companies aim to customize their service to increase fleet usage and revenues with different pricing schemes and offer types. Dynamic pricing policies can be designed to adjust and balance temporally and spatially cars availability but may pose some question on customers’ fairness. In this paper, we propose an explorative analysis of how an availability-based dynamic pricing scheme impacts the demand and the supply performance. The policy is simulated in MATSim and compared to a fixed pricing policy scheme. This simulation consists of analyzing the behavior of a synthetic population of car-sharing members for Berlin and the surrounding region in which is applied an availability-based dynamic pricing in which price depends on vehicle availability in booking stations. Results show that when the dynamic pricing is applied there is a light decrease in the number of bookings and people with low value of time tend to abandon the carsharing mode in favor of other modes of transportation. [less ▲]

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See detailAWJC Nozzle simulation by 6-way coupling of DEM+CFD+FEM using preCICE coupling library
Adhav, Prasad UL; Besseron, Xavier UL; ROUSSET, Alban et al

Scientific Conference (2021, June 16)

The objective of this work is to study the particle-laden fluid-structure interaction within an Abrasive Water Jet Cutting Nozzle. Such coupling is needed to study the erosion phenomena caused by the ... [more ▼]

The objective of this work is to study the particle-laden fluid-structure interaction within an Abrasive Water Jet Cutting Nozzle. Such coupling is needed to study the erosion phenomena caused by the abrasive particles inside the nozzle. So far, the erosion in the nozzle was predicted only through the number of collisions, using only a simple DEM+CFD[1] coupling. To improve these predictions, we extend our model to a 6-way Eulerian-Lagrangian momentum coupling with DEM+CFD+FEM to account for deformations and vibrations in the nozzle. Our prototype uses the preCICE coupling library[2] to couple 3 numerical solvers: XDEM[3] (for the particle motion), OpenFOAM[4] (for the water jet), and CalculiX[5] (for the nozzle deformation). XDEM handles all the particle motions based on the fluid properties and flow conditions, and it calculates drag terms. In the fluid solver, particles are modeled as drag and are injected in the momentum equation as a source term. CalculiX uses the forces coming from the fluid solver and XDEM as boundary conditions to solve for the displacements. It is also used for computing the vibrations induced by particle impacts. . The preliminary 6-way DEM+CFD+FEM coupled simulation is able to capture the complex particle-laden multiphase fluid-structure interaction inside AWJC Nozzle. The erosion concentration zones are identified and are compared to DEM+CFD coupling[1]. The results obtained are planned to be used for predicting erosion intensity in addition to the concentration zones. In the future, we aim to compare the erosions predictions to experimental data in order to evaluate the suitability of our approach. The FEM module of the coupled simulation captures the vibration frequency induced by particles and compares it with the natural frequency of the nozzle. Thus opening up opportunities for further investigation and improvement of the Nozzle design. [less ▲]

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See detailB-Spline FEM for Time-Harmonic Acoustic Scattering and Propagation
Khajah, Tahsin; Antoine, Xavier; Bordas, Stéphane UL

in Journal of Theoretical and Computational Acoustics (2019), 27

We study the application of a B-splines Finite Element Method (FEM) to time-harmonic scattering acoustic problems. The infinite space is truncated by a fictitious boundary and second-order Absorbing ... [more ▼]

We study the application of a B-splines Finite Element Method (FEM) to time-harmonic scattering acoustic problems. The infinite space is truncated by a fictitious boundary and second-order Absorbing Boundary Conditions (ABCs) are applied. The truncation error is included in the exact solution so that the reported error is an indicator of the performance of the numerical method, in particular of the size of the pollution error. Numerical results performed with high-order basis functions (third or fourth order) showed no visible pollution error even for very high frequencies. To prove the ability of the method to increase its accuracy in the high frequency regime, we show how to implement a high-order Padé-type ABC on the fictitious outer boundary. The above-mentioned properties combined with exact geometrical representation make B-Spline FEM a very promising platform to solve high-frequency acoustic problems. [less ▲]

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See detailBalancing Shareability and Positive Interdependence to Support Collaborative Problem-Solving on Interactive Tabletops
Maquil, Valérie; Afkari, Hoorieh; Arend, Béatrice UL et al

in Advances in Human-Computer Interaction (2021)

To support collaboration, researchers from different fields have proposed the design principles of shareability (engaging users in shared interactions around the same content) and positive interdependence ... [more ▼]

To support collaboration, researchers from different fields have proposed the design principles of shareability (engaging users in shared interactions around the same content) and positive interdependence (distributing roles and information to make users dependent on each other). While, on its own, each principle was shown to successfully support collaboration in different contexts, these principles are also partially conflicting, and their combination creates several design challenges. This paper describes how shareability and positive interdependency were jointly implemented in an interactive tabletop-mediated environment called Orbitia, with the aim of inducing collaboration between three adult participants. We present the design details and rationale behind the proposed application. Furthermore, we describe the results of an empirical evaluation focusing on joint problem-solving efficiency, collaboration styles, participation equity, and perceived collaboration effectiveness. [less ▲]

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See detailBatch control of the master equation: a linear programming approach
Goncalves, Jorge UL; Martins, N.

Scientific Conference (2008)

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See detailA Bayesian framework to identify random parameter fields based on the copula theorem and Gaussian fields: Application to polycrystalline materials
Rappel, Hussein UL; Wu, Ling; Noels, Ludovic et al

in Journal of Applied Mechanics (in press)

For many models of solids, we frequently assume that the material parameters do not vary in space, nor that they vary from one product realization to another. If the length scale of the application ... [more ▼]

For many models of solids, we frequently assume that the material parameters do not vary in space, nor that they vary from one product realization to another. If the length scale of the application approaches the length scale of the micro-structure however, spatially fluctuating parameter fi elds (which vary from one realization of the fi eld to another) can be incorporated to make the model capture the stochasticity of the underlying micro-structure. Randomly fluctuating parameter fields are often described as Gaussian fields. Gaussian fi elds however assume that the probability density function of a material parameter at a given location is a univariate Gaussian distribution. This entails for instance that negative parameter values can be realized, whereas most material parameters have physical bounds (e.g. the Young's modulus cannot be negative). In this contribution, randomly fluctuating parameter fi elds are therefore described using the copula theorem and Gaussian fi elds, which allow di fferent types of univariate marginal distributions to be incorporated, but with the same correlation structure as Gaussian fields. It is convenient to keep the Gaussian correlation structure, as it allows us to draw samples from Gaussian fi elds and transform them into the new random fields. The bene fit of this approach is that any type of univariate marginal distribution can be incorporated. If the selected univariate marginal distribution has bounds, unphysical material parameter values will never be realized. We then use Bayesian inference to identify the distribution parameters (which govern the random fi eld). Bayesian inference regards the parameters that are to be identi fied as random variables and requires a user-defi ned prior distribution of the parameters to which the observations are inferred. For the homogenized Young's modulus of a columnar polycrystalline material of interest in this study, the results show that with a relatively wide prior (i.e. a prior distribution without strong assumptions), a single specimen is su ciffient to accurately recover the distribution parameter values. [less ▲]

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See detailBayesian inference for the stochastic identification of elastoplastic material parameters: Introduction, misconceptions and insights
Rappel, Hussein UL; Beex, Lars UL; Hale, Jack UL et al

E-print/Working paper (n.d.)

We discuss Bayesian inference (BI) for the probabilistic identification of material parameters. This contribution aims to shed light on the use of BI for the identification of elastoplastic material ... [more ▼]

We discuss Bayesian inference (BI) for the probabilistic identification of material parameters. This contribution aims to shed light on the use of BI for the identification of elastoplastic material parameters. For this purpose a single spring is considered, for which the stress-strain curves are artificially created. Besides offering a didactic introduction to BI, this paper proposes an approach to incorporate statistical errors both in the measured stresses, and in the measured strains. It is assumed that the uncertainty is only due to measurement errors and the material is homogeneous. Furthermore, a number of possible misconceptions on BI are highlighted based on the purely elastic case. [less ▲]

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See detailBayesian inference to identify parameters in viscoelasticity
Rappel, Hussein UL; Beex, Lars UL; Bordas, Stéphane UL

in Mechanics of Time-Dependent Materials (2017)

This contribution discusses Bayesian inference (BI) as an approach to identify parameters in viscoelasticity. The aims are: (i) to show that the prior has a substantial influence for viscoelasticity, (ii ... [more ▼]

This contribution discusses Bayesian inference (BI) as an approach to identify parameters in viscoelasticity. The aims are: (i) to show that the prior has a substantial influence for viscoelasticity, (ii) to show that this influence decreases for an increasing number of measurements and (iii) to show how different types of experiments influence the identified parameters and their uncertainties. The standard linear solid model is the material description of interest and a relaxation test, a constant strain-rate test and a creep test are the tensile experiments focused on. The experimental data are artificially created, allowing us to make a one-to-one comparison between the input parameters and the identified parameter values. Besides dealing with the aforementioned issues, we believe that this contribution forms a comprehensible start for those interested in applying BI in viscoelasticity. [less ▲]

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See detailA Bayesian inversion approach to recovering material parameters in hyperelastic solids using dolfin-adjoint
Hale, Jack UL; Farrell, Patrick E.; Bordas, Stéphane UL

Presentation (2015, July 01)

In the first part of the talk I will describe in general terms the link between classical optimisation techniques and the Bayesian approach to statistical inversion as outlined in the seminal book of ... [more ▼]

In the first part of the talk I will describe in general terms the link between classical optimisation techniques and the Bayesian approach to statistical inversion as outlined in the seminal book of [Kaipio and Somersalo, 2005]. Under the assumption of an additive Gaussian noise model, a Gaussian prior distribution and a linear parameter-to-observable map, it is possible to uniquely characterise the Bayesian posterior as Gaussian with the maximum aposteriori (MAP) point equal to the minimum of a classic regularised minimisation problem and covariance matrix equal to the inverse of the Hessian of the functional evaluated at the MAP point. I will also discuss techniques that can be used when these assumptions break down. In the second part of the talk I will describe a method implemented within dolfin-adjoint [Funke and Farrell, arXiv 2013] to quantify the uncertainty in the recovered material parameters of a hyperelastic solid from partial and noisy observations of the displacement field in the domain. The finite element discretisation of the adjoint and higher-order adjoint (Hessian) equations are derived automatically from the high-level UFL representation of the problem. The resulting equations are solved using PETSc. I will concentrate on finding the eigenvalue decomposition of the posterior covariance matrix (Hessian). The eigenvectors associated with the lowest eigenvalues of the Hessian correspond with the directions in parameter space least constrained by the observations [Flath et al. 2011]. This eigenvalue problem is tricky to solve efficiently because the Hessian is very large (on the order of the number of parameters) and dense (meaning that only its action on a vector can be calculated, each involving considerable expense). Finally, I will show some illustrative examples including the uncertainty associated with deriving the material properties of a 3D hyperelastic block with a stiff inclusion with knowledge only of the displacements on the boundary of the domain. J. Kaipio and E. Somersalo, Statistical and Computational Inverse Problems, vol. 160. New York: Springer-Verlag, 2005. S. W. Funke and P. E. Farrell, “A framework for automated PDE-constrained optimisation,” arXiv:1302.3894 [cs], Feb. 2013. H. P. Flath, L. C. Wilcox, V. Akçelik, J. Hill, B. van Bloemen Waanders, and O. Ghattas, “Fast Algorithms for Bayesian Uncertainty Quantification in Large-Scale Linear Inverse Problems Based on Low-Rank Partial Hessian Approximations,” SIAM J. Sci. Comput., vol. 33, no. 1, pp. 407–432, Feb. 2011. [less ▲]

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See detailBayesian statistical inference on the material parameters of a hyperelastic body
Hale, Jack UL; Farrel, Patrick E.; Bordas, Stéphane UL

in Proceedings of the ACME-UK 2016 24th Conference on Computational Mechanics (2016, March 31)

We present a statistical method for recovering the material parameters of a heterogeneous hyperelastic body. Under the Bayesian methodology for statistical inverse problems, the posterior distribution ... [more ▼]

We present a statistical method for recovering the material parameters of a heterogeneous hyperelastic body. Under the Bayesian methodology for statistical inverse problems, the posterior distribution encodes the probability of the material parameters given the available displacement observations and can be calculated by combining prior knowledge with a finite element model of the likelihood. In this study we concentrate on a case study where the observations of the body are limited to the displacements on the surface of the domain. In this type of problem the Bayesian framework (in comparison with a classical PDE-constrained optimisation framework) can give not only a point estimate of the parameters but also quantify uncertainty on the parameter space induced by the limited observations and noisy measuring devices. There are significant computational and mathematical challenges when solving a Bayesian inference problem in the case that the parameter is a field (i.e. exists infinite-dimensional Banach space) and evaluating the likelihood involves the solution of a large-scale system of non-linear PDEs. To overcome these problems we use dolfin-adjoint to automatically derive adjoint and higher-order adjoint systems for efficient evaluation of gradients and Hessians, develop scalable maximum aposteriori estimates, and use efficient low-rank update methods to approximate posterior covariance matrices. [less ▲]

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See detailBearing capacity of steel fiber reinforced concrete flat slabs
Michels, Julien UL

Doctoral thesis (2009)

Detailed reference viewed: 235 (11 UL)
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See detailBeyond Digitizing
Takats, Sean UL

in Burrows, Simon; Roe, Glenn (Eds.) Digitizing Enlightenment: Digital Humanities and the Transformation of Eighteenth-century Studies (2020)

Detailed reference viewed: 41 (1 UL)
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See detailA Big Data Demand Estimation Framework for Modelling of Urban Congested Networks
Cantelmo, Guido UL; Viti, Francesco UL

in CSUM 2018, AISC 879 proceedings (2019)

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See detailA Big Data Demand Estimation Model for Urban Congested Networks
Cantelmo, Guido; Viti, Francesco UL

in Transport and Telecommunication (2020)

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See detailBimodal and hysteretic expression in mammalian cells from a synthetic gene circuit
May, T.; Eccleston, L. J.; Markusic, D. et al

in Public Library of Science ONE (2008), 3(6),

In order to establish cells and organisms with predictable properties, synthetic biology makes use of controllable, synthetic genetic devices. These devices are used to replace or to interfere with ... [more ▼]

In order to establish cells and organisms with predictable properties, synthetic biology makes use of controllable, synthetic genetic devices. These devices are used to replace or to interfere with natural pathways. Alternatively, they may be interlinked with endogenous pathways to create artificial networks of higher complexity. While these approaches have been already successful in prokaryotes and lower eukaryotes, the implementation of such synthetic cassettes in mammalian systems and even animals is still a major obstacle. This is mainly due to the lack of methods that reliably and efficiently transduce synthetic modules without compromising their regulation properties. To pave the way for implementation of synthetic regulation modules in mammalian systems we utilized lentiviral transduction of synthetic modules. A synthetic positive feedback loop, based on the Tetracycline regulation system was implemented in a lentiviral vector system and stably integrated in mammalian cells. This gene regulation circuit yields a bimodal expression response. Based on experimental data a mathematical model based on stochasticity was developed which matched and described the experimental findings. Modelling predicted a hysteretic expression responsewhich was verified experimentally. Thereby supporting the idea that the system is driven by stochasticity. The results presented here highlight that the combination of three independent tools/methodologies facilitate the reliable installation of synthetic gene circuits with predictable expression characteristics in mammalian cells and organisms. [less ▲]

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See detailBiomechanical properties of five different currently used implants for open-wedge high tibial osteotomy
Diffo Kaze, Arnaud UL; Maas, Stefan UL; Waldmann, Danièle UL et al

in Journal of Experimental Orthopaedics (2015), 2(14),

Background: As several new tibial osteotomy plates recently appeared on the market, the aim of the present study was to compare mechanical static and fatigue strength of three newly designed plates with ... [more ▼]

Background: As several new tibial osteotomy plates recently appeared on the market, the aim of the present study was to compare mechanical static and fatigue strength of three newly designed plates with gold standard plates for the treatment of medial knee joint osteoarthritis. Methods: Sixteen fourth-generation tibial bone composites underwent a medial open-wedge high tibial osteotomyn(HTO) according to standard techniques, using five TomoFix standard plates, five PEEKPower plates and six iBalance implants. Static compression load to failure and load-controlled cyclic fatigue failure tests were performed. Forces, horizontal and vertical displacements were measured; rotational permanent plastic deformations, maximal displacement ranges in the hysteresis loops of the cyclic loading responses and dynamic stiffness were determined. Results: Static compression load to failure tests revealed that all plates showed sufficient stability up to 2400 N without any signs of opposite cortex fracture, which occurred above this load in all constructs at different load levels. During the fatigue failure tests, screw breakage in the iBalance group and opposite cortex fractures in all constructs occurred only under physiological loading conditions (<2400 N). The highest fatigue strength in terms of maximal load and number of cycles performed prior to failure was observed for the ContourLock group followed by the iBalance implants, the TomoFix standard (std) and small stature (sm) plates. The PEEKPower group showed the lowest fatigue strength. Conclusions: All plates showed sufficient stability under static loading. Compared to the TomoFix and the PEEKPower plates, the ContourLock plate and iBalance implant showed a higher mechanical fatigue strength during cyclic fatigue testing. These data suggest that both mechanical static and fatigue strength increase with a wider proximal T-shaped plate design together with diverging proximal screws as used in the ContourLock plate or a closed-wedge construction as in the iBalance design. Mechanical strength of the bone-implant constructs decreases with a narrow T-shaped proximal end design and converging proximal screws (TomoFix) or a short vertical plate design (PEEKPower Plate). Whenever high mechanical strength is required, a ContourLock or iBalance plate should be selected. [less ▲]

Detailed reference viewed: 232 (36 UL)