Éditeur(s) : HAL CCSD Springer Verlag (Germany) Springer Verlag
Résumé : Direct numerical simulations of flow through two millimeter-scale rock samples of limestone and sandstone are performed using three diverse fluid dynamic simulators. The resulting steady-state velocity fields are compared in terms of the associated empirical probability density functions (PDFs) and key statistics of the velocity fields. The pore space geometry of each sample is imaged at 5.06−μm voxel size resolution using X-ray microtomography. The samples offer contrasting characteristics in terms of total connected porosity (about 0.31 for the limestone and 0.07 for the sandstone) and are typical of several applications in hydrogeology and petroleum engineering. The three-dimensional fluid velocity fields within the explicit pore spaces are simulated using ANSYS® FLUENT® ANSYS Inc. (2009), EULAG Prusa et al. (Comput. Fluids 37, 1193–1207 2008), and SSTOKES Sarkar et al. (2002). These computational approaches are highly disperse in terms of algorithmic complexity, differ in terms of their governing equations, the adopted numerical methodologies, the enforcement of internal no-slip boundary conditions at the fluid-solid interface, and the computational mesh structure. As metrics of comparison to probe in a statistical sense the internal similarities/differences across sample populations of velocities obtained through the computational systems, we consider (i) integral quantities, such as the Darcy flux and (ii) main statistical moments of local velocity distributions including local correlations between velocity fields. Comparison of simulation results indicates that mutually consistent estimates of the state of flow are obtained in the analyzed samples of natural pore spaces despite the considerable differences associated with the three computational approaches. We note that in the higher porosity limestone sample, the structures of the velocity fields obtained using ANSYS FLUENT and EULAG are more alike than either compared against the results obtained using SSTOKES. In the low-porosity sample, the structures of the velocity fields obtained by EULAG and SSTOKES are more similar than either is to the fields obtained using ANSYS FLUENT. With respect to macroscopic quantities, ANSYS FLUENT and SSTOKES provide similar results in terms of the average vertical velocity for both of the complex microscale geometries considered, while EULAG tends to render the largest velocity values. The influence of the pore space structure on fluid velocity field characteristics is also discussed.
ISSN: 1420-0597

hal-01174152
https://hal.archives-ouvertes.fr/hal-01174152
DOI : 10.1007/s10596-015-9486-7

Éditeur(s) : HAL CCSD Springer Verlag (Germany)
Résumé : International audience
Surface displacements due to temporal changes in environmental mass redistributions are observable in the coordinate time series of many Global Navigation Satellite System (GNSS) sites. In this study, we investigated the effect of loading on estimates of tectonic velocity computed from campaign-style GNSS observations. The study region is in the Pyrenees mountain range between France and Spain (ResPyr campaigns). In this area, seismic activity is continuous and moderate and the expected amplitude of the horizontal tectonic velocity is less than 0.5 mm/yr. In order to determine the velocity, 4 sparse GNSS campaigns were carried out from 1995 to 2010. Considering this small rate of deformation, loading phenomena can contribute a non-negligible artifact to the velocity computation that could affect our geodynamical interpretation. In this investigation, we specifically considered the atmospheric, hydrological, and non-tidal ocean loading phenomena. The computed loading deformations for this region show the horizontal displacements are dominated by the non-tidal ocean loading (maximum 4 mm for the North and 3.1 mm for the East components); the main vertical contributions are due to the atmospheric and continental water storage loading (maximum 14.3 for the atmosphere and 8.1 mm for the hydrology, respectively). We have found that the dominant loading effect on the horizontal velocity is the non-tidal ocean loading (mean of 0.11 mm/yr), whereas the vertical component is dominated by the hydrological loading (mean of 0.21 mm/yr). Since the study area is in a mountainous region, we also analyzed the difference between the atmospheric and the topography dependent atmospheric loading models at our GNSS campaign sites. We did not find any significant difference between the two atmospheric loading models in terms of horizontal velocity. Finally, we performed simulations to identify the optimum timing and frequency of future GNSS campaigns in this area that would minimize the loading effects on tectonic velocity estimates.
ISSN: 0039-3169

hal-00963629
https://hal.archives-ouvertes.fr/hal-00963629
DOI : 10.1007/s11200-012-0458-2

Éditeur(s) : HAL CCSD
Résumé : 6 pages
In a Spiking Neural Networks (SNN), spike emissions are sparsely and irregularly distributed both in time and in the network architecture. Since a current feature of SNNs is a low average activity, efficient implementations of SNNs are usually based on an Event-Driven Simulation (EDS). On the other hand, simulations of large scale neural networks can take advantage of distributing the neurons on a set of processors (either workstation cluster or parallel computer). This article presents DAMNED, a large scale SNN simulation framework able to gather the benefits of EDS and parallel computing. Two levels of parallelism are combined: Distributed mapping of the neural topology, at the network level, and local multithreaded allocation of resources for simultaneous processing of events, at the neuron level. Based on the causality of events, a distributed solution is proposed for solving the complex problem of scheduling without synchronization barrier.
https://hal.archives-ouvertes.fr/hal-00015137

hal-00015137
https://hal.archives-ouvertes.fr/hal-00015137
https://hal.archives-ouvertes.fr/hal-00015137v2/document
https://hal.archives-ouvertes.fr/hal-00015137/file/hal_damned.pdf
ARXIV : cs.NE/0512018

Éditeur(s) : HAL CCSD
Résumé : International audience
After defining the High Performance Pre- Computing --referred as HPPC-- concept, the aim of the present study is to develop a prototype whether to approve or not the benefits of this concept. Our application case tries to answer the geophysical issue of coastal flooding. This is an example of an alert system based on the HPPC architecture, thus on pre-computed scenarios. The prototype provides the scientists with an ergonomic and on-demand tool allowing the run of scenarios of any implemented numerical models. These runs are available through a web application which submits the corresponding jobs on the remote french public cluster of HPC@LR. In this study we simulate the waves propagation over a Mediterranean grid using the wave model WaveWatch III⃝R . A reference simulation using usual conditions is approximated using the k-NN algorithm over 12, 98 and then 980 pre-computed scenarios. This simple experiment demonstrates how useful the pre-computing of scenarios is for alert systems as far as enough and relevant scenarios are pre-computed. This is the reason why searches continue in each critical points of the HPPC architecture such as the design of experiment, the approximation of the results by meta-models and the research of the closest scenarios in this big data context.
4th International Conference on Knowledge and Systems Engineering
Danang, Vietnam

lirmm-00736797
https://hal-lirmm.ccsd.cnrs.fr/lirmm-00736797
https://hal-lirmm.ccsd.cnrs.fr/lirmm-00736797/document
https://hal-lirmm.ccsd.cnrs.fr/lirmm-00736797/file/PID2396685.pdf
DOI : 10.1109/KSE.2012.36

Éditeur(s) : Springer
Résumé : Terrestrial and marine biodiversity provides the basis for both ecosystems functioning and numerous commodities or services that underpin human well-being. From several decades, alarming trends have been reported worldwide for both biodiversity and ecosystem services. Therefore the sustainable management of biodiversity requires a double viewpoint balancing ecological conservation with the welfare of human societies. Understanding the underlying trade-offs, synergies and interactions imposes the development of interdisciplinary researches and methods. In that respect, bio-economic or ecological economic modeling is likely to play a major role. The present paper intends to elicit the key features, strengths and challenges of bio-economic approaches especially in mathematical and computational terms. It first recall the main bio-economic methods, models and decisional instruments used in these types of analyses. Then the paper shows to what extent bio-economic sustainability lies between equilibrium, viability and optimality mathematical frameworks. It ends up by identifying new major challenges among which the operationalization of ecosystem based management, the precautionary principle and the implementation of governance are especially important. Computational Management Science Computational Management Science Look Inside
Computational Management Science (1619-697X) (Springer), 2013-12 , Vol. 10 , N. 4 , P. 353-364

Droits : Springer-Verlag Berlin Heidelberg 2013
http://archimer.ifremer.fr/doc/00171/28208/26510.pdf
DOI:10.1007/s10287-013-0194-2
http://archimer.ifremer.fr/doc/00171/28208/

Éditeur(s) : HAL CCSD Institute of Electrical and Electronics Engineers
Résumé : International audience
This paper presents our response to the first interna- tional challenge on Facial Emotion Recognition and Analysis. We propose to combine different types of features to automatically detect Action Units in facial images. We use one multi-kernel SVM for each Action Unit we want to detect. The first kernel matrix is computed using Local Gabor Binary Pattern histograms and a histogram intersection kernel. The second kernel matrix is computed from AAM coefficients and an RBF kernel. During the training step, we combine these two types of features using the recently proposed SimpleMKL algorithm. SVM outputs are then averaged to exploit temporal information in the sequence. To eval- uate our system, we perform deep experimentations on several key issues: influence of features and kernel function in histogram- based SVM approaches, influence of spatially-independent in- formation versus geometric local appearance information and benefits of combining both, sensitivity to training data and interest of temporal context adaptation. We also compare our results to those of the other participants and try to explain why our method had the best performance during the FERA challenge.
ISSN: 1083-4419

hal-00731864
http://hal.upmc.fr/hal-00731864
http://hal.upmc.fr/hal-00731864/document
http://hal.upmc.fr/hal-00731864/file/senechal12tsmc_preprint.pdf
DOI : 10.1109/TSMCB.2012.2193567

Éditeur(s) : HAL CCSD
Résumé : International audience
In the area of the link mining, frequent pattern discovery tasks generally consist in the search for subgraphs frequently found in a network or a set of networks. Very recently, new axes of this problem has been proposed through the search for frequent links. Unlike traditional approaches that focus solely on structural regularities, frequent link mining methods exploit both the network structure and the attributes of nodes for extracting regularities in the links existing between node groups that share common characteristics. However, extracting frequent links is still a particularly challenging and computationally intensive issue since it is much dependent on the number of links. In this study, we propose a solution that is able to reduce the computing time by reducing the search to only a subset of of nodes. Experiments were conducted to understand the effects of different thresholds of the subset size on the loss of patterns and the gain in terms of computation time. Our solution proves to be efficient for a rather wide range of thresholds.
Research Challenges in Information Science
Vallence, Spain

hal-00767039
https://hal.archives-ouvertes.fr/hal-00767039
DOI : 10.1109/RCIS.2012.6240432

Éditeur(s) : HAL CCSD Oxford University Press (OUP)
Résumé : International audience
We analyse P-wave receiver functions across the western Gulf of Aden and southern Red Sea continental margins in Western Yemen to constrain crustal thickness, internal crustal structure and the bulk seismic velocity characteristics in order to address the role of magmatism, faulting and mechanical crustal thinning during continental breakup. We analyse teleseismic data from 21 stations forming the temporary Young Conjugate Margins Laboratory (YOCMAL) network together with GFZ and Yemeni permanent stations. Analysis of computed receiver functions shows that (1) the thickness of unextended crust on the Yemen plateau is ∼35km; (2) this thins to ∼22km in coastal areas and reaches less than 14km on the Red Sea coast, where presence of a high-velocity lower crust is evident. The average Vp/Vs ratio for the western Yemen Plateau is 1.79, increasing to ∼1.92 near the Red Sea coast and decreasing to 1.68 for those stations located on or near the granitic rocks. Thinning of the crust, and by inference extension, occurs over a ∼130-km-wide transition zone from the Red Sea and Gulf of Aden coasts to the edges of the Yemen plateau. Thinning of continental crust is particularly localized in a <30-km-wide zone near the coastline, spatially co-incident with addition of magmatic underplate to the lower crust, above which on the surface we observe the presence of seaward dipping reflectors (SDRs) and thickened Oligo-Miocene syn-rift basaltic flows. Our results strongly suggest the presence of high-velocity mafic intrusions in the lower crust, which are likely either synrift magmatic intrusion into continental lower crust or alternatively depleted upper mantle underplated to the base of the crust during the eruption of the SDRs. Our results also point towards a regional breakup history in which the onset of rifting was synchronous along the western Gulf of Aden and southern Red Sea volcanic margins followed by a second phase of extension along the Red Sea margin.
ISSN: 0956-540X

hal-00825194
https://hal.archives-ouvertes.fr/hal-00825194
https://hal.archives-ouvertes.fr/hal-00825194/document
https://hal.archives-ouvertes.fr/hal-00825194/file/RF_Hakim2012_GJI.pdf
DOI : 10.1093/gji/ggt072

Éditeur(s) : HAL CCSD
Résumé : International audience
We present a study on the optimasation of the number of messages for medical diagnosis over wireless sensors networks (WSNs). We suggest distributed algorithms to diagnosis some diseases while monitoring a patient. Then, we compare the number of messages needed to make a decision between the algorithms. In our approach, each sensor will make some computations in order to participate to the decision. Indeed, some computation and collaboration tasks are performed over the sensors and the final diagnosis is performed in a distributed way. During the experimentation of our algorithms, we used a real data flow extracted from hospital monitoring.
Proceedings of the 14th IEEE Symposium on Computers and Communications (ISCC 2009), July 5-8, Sousse, Tunisia
Sousse, Tunisia

hal-00519593
https://hal.archives-ouvertes.fr/hal-00519593

Éditeur(s) : HAL CCSD IEEE
Résumé : International audience
Recent works display that large scale image classification problems rule out computationally demanding methods. On such problems, simple approaches like k-NN are affordable contenders, with still room space for statistical improvements under the algorithmic constraints. A recent work showed how to leverage k-NN to yield a formal boosting algorithm. This method, however, has numerical issues that make it not suited for large scale problems. We propose here an Adaptive Newton-Raphson scheme to leverage k-NN, N³, which does not suffer these issues. We show that it is a boosting algorithm, with several key algorithmic and statistical properties. In particular, it may be sufficient to boost a subsample to reach desired bounds for the loss at hand in the boosting framework. Experiments are provided on the SUN, and Caltech databases. They confirm that boosting a subsample -- sometimes containing few examples only -- is sufficient to reach the convergence regime of N³. Under such conditions, N³ challenges the accuracy of contenders with lower computational cost and lower memory requirement.
IEEE International Workshop on Machine Learning for Signal Processing
Southampton, United Kingdom

hal-00959125
https://hal.archives-ouvertes.fr/hal-00959125
https://hal.archives-ouvertes.fr/hal-00959125/document
https://hal.archives-ouvertes.fr/hal-00959125/file/BNNB_mlsp2013.pdf

Éditeur(s) : HAL CCSD
Résumé : International audience
The k-nearest neighbors (k-NN) classification rule is still an essential tool for computer vision applications, such as scene recognition. However, k-NN still features some major drawbacks, which mainly reside in the uniform voting among the nearest prototypes in the feature space. In this paper, we propose a new method that is able to learn the "relevance" of prototypes, thus classifying test data using a weighted k-NN rule. In particular, our algorithm, called Multi-class Leveraged k-nearest neighbor (MLNN), learns the prototype weights in a boosting framework, by minimizing a surrogate exponential risk over training data. We propose two main contributions for improving computational speed and accuracy. On the one hand, we implement learning in an inherently multiclass way, thus providing significant computation time reduction over one-versus-all approaches. Furthermore, the leveraging weights enable effective data selection, thus reducing the cost of k-NN search at classification time. On the other hand, we propose a kernel generalization of our approach to take into account real-valued similarities between data in the feature space, thus enabling more accurate estimation of the local class density. We tested MLNN on three datasets of natural images. Results show that MLNN significantly outperforms classic k-NN and weighted k-NN voting. Furthermore, using an adaptive Gaussian kernel provides significant performance improvement. Finally, the best results are obtained when using MLNN with an appropriate learned metric distance.
Proceedings of the 10th Asian Conference on Computer Vision, ACCV 2010, November 8-12, 2010, Queenstown, New Zealand
Queenstown, New Zealand

hal-00664606
https://hal.inria.fr/hal-00664606
https://hal.inria.fr/hal-00664606/document
https://hal.inria.fr/hal-00664606/file/mlnn_accvfinal.pdf

Éditeur(s) : HAL CCSD Nature Publishing Group
Résumé : International audience
Lateral variations along the Himalayan arc are suggested by an increasing number of studies and carry important information about the orogen’s segmentation. Here we compile the hitherto most complete land gravity dataset in the region which enables the currently highest resolution plausible analysis. To study lateral variations in collisional structure we compute arc-parallel gravity anomalies (APaGA) by subtracting the average arc-perpendicular profile from our dataset; we compute likewise for topography (APaTA). We find no direct correlation between APaGA, APaTA and background seismicity, as suggested in oceanic subduction context. In the Himalayas APaTA mainly reflect relief and erosional effects, whereas APaGA reflect the deep structure of the orogen with clear lateral boundaries. Four segments are outlined and have disparate flexural geometry: NE India, Bhutan, Nepal & India until Dehradun, and NW India. The segment boundaries in the India plate are related to inherited structures, and the boundaries of the Shillong block are highlighted by seismic activity. We find that large earthquakes of the past millennium do not propagate across the segment boundaries defined by APaGA, therefore these seem to set limits for potential rupture of megathrust earthquakes.
ISSN: 2045-2322

hal-01420404
https://hal.archives-ouvertes.fr/hal-01420404
https://hal.archives-ouvertes.fr/hal-01420404/document
https://hal.archives-ouvertes.fr/hal-01420404/file/hetenyi2016.pdf
DOI : 10.1038/srep33866

Éditeur(s) : HAL CCSD
Résumé : International audience
In this paper we study how to detect anomalies in a distributed manner by using wireless sensor networks (WSN). We focus on a medical context, where existing works generally provide large environments to monitor patients using sensors as simple transducers. Those devices forward sensed health parameters to a main base station. This station collects received data and may perform some computations. In this paper, we perform some distributed tasks on the sensors. We propose a distributed algorithm which allows to raise alarms under some initial rules to alert efficiently medical staff in case of critical situations without needles warnings.
10th IEEE International Symposium on a World of Wireless, Mobile and Multimedia Networks, WOWMOM 2009.
KOS, Greece

hal-00519589
https://hal.archives-ouvertes.fr/hal-00519589

Éditeur(s) : HAL CCSD IEEE
Résumé : International audience
In this paper, we present an evolutionary approach for extracting a model of flood prediction from hydrological data observed timely on water heights in a river watershed. Since this kind of data recorded by sensors on river basins is highly scarce and hopefully much unbalanced between cases of floods and non-floods, we have adopted the notion of aggregate variables which values are computed as aggregates on raw data. An evolutionary algorithm is involved to allow selecting the best sets - juries of classifiers- of such variables as predictive variables. Two real hydrological data sets are trained and they both show the efficiency of the method compared to traditional solutions for prediction.
IEEE Congress on Evolutionary Computation 2012
Brisbane, Australia

hal-00840739
https://hal.archives-ouvertes.fr/hal-00840739
DOI : 10.1109/CEC.2012.6252897

Éditeur(s) : HAL CCSD
Résumé : International audience
This work proposes an original approach using mutual information and Pareto curve jointly for feature selection. Mutual information is used to estimate dependency criterion between features and classes and redundancy criterion between features taken two by two. Unlike some studies, these criteria are used simultaneously to compute Pareto curve and determine the optimal feature sets. This approach is tested on more reference data. Several clustering algorithms are used to compute classification accuracy. The obtained results show the importance of our tools and its ability to select the best feature sets that give the better description.
GRETSI Proceedings
Bordeaux, France

hal-00602260
https://hal.archives-ouvertes.fr/hal-00602260

Éditeur(s) : HAL CCSD
Résumé : International audience
This paper shows the information criteria (IC) performances in feature selection framework. Feature selection aims to select a representative subset among a wide set of features. We apply this approach to classify an hand segmented image. The performance is tested using various feature selection schemes (SFS, SBS, SFFS and SBFS) to select the candidate subsets. The accuracy of the approach is based on a good quality of the joint probability density approximation of the combined features. They are obtained using histogram optimized thanks to the adaptive arithmetic coding principles. Our approach is tested on different reference data. The subsets quality is evaluated using correct classification rate computed on multiple classifiers. Results show stability and convergence properties of this tool and its ability to select representative subsets (in the sense that the subset of feature is a good characterization of the classes in which the data belong). Information Criteria could be used for feature selection as a good alternative to other criteria.
CISP Proceedings
Shangay, China

hal-00634749
https://hal.archives-ouvertes.fr/hal-00634749

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
Given a graph, its hyperbolicity is a measure of how close its distance distribution is to the one of a tree. This parameter has gained recent attention in the analysis of some graph algorithms and the classification of complex networks. We study on practical improvements for the computation of hyperbolicity in large graphs. Precisely, we investigate on relations between the hyperbolicity of a graph G and the hyperbolicity of its atoms, that are the subgraphs output by the clique-decomposition invented by Tarjan [51, 65]. We prove that the maximum hyperbolicity taken over the atoms is at most one unit off from the hyperbol-icity of G and the bound is sharp. We also give an algorithm to slightly modify the atoms, called the " substitution method " , which is at no extra cost than computing the clique-decomposition, and so that the maximum hyperbolicity taken over the resulting graphs is exactly the hyperbolicity of the input graph G. An experimental evaluation of our method for computing the hyperbolicity of a given graph from its atoms is provided for collaboration networks and biological networks. Finally, on a more theoretical side, we deduce from our results the first linear-time algorithm for computing the hyperbolicity of an outerplanar graph.
ISSN: 0304-3975

hal-01540756
https://hal.inria.fr/hal-01540756
https://hal.inria.fr/hal-01540756/document
https://hal.inria.fr/hal-01540756/file/CCDL-2017.pdf
DOI : 10.1016/j.tcs.2017.06.001

Éditeur(s) : HAL CCSD Oxford University Press (OUP)
Résumé : International audience
Several studies, both theoretical and experimental, show that sedimentary rocks have a fractal pore-grain interface. In this paper a computer simulated 3-D sedimentary rock structure generated by the Relaxed Ballistic Bidisperse Deposition Model (RBBDM), is investigated to characterize the micro structure of its pores. The pore volume and the rock-pore interface show the same fractal dimension indicating that the pore volume is a fractal. The two point density correlation is computed for the pore space and the results compare favourably with the range reported from experiments. An array of 2-D X-ray tomography micrograph sections of a real sedimentary rock, an oolitic limestone (pure calcite) from the Mondeville formation of Middle Jurassic age (Paris Basin, France), was used to generate a 3-D bitmap. The 3-D real rock sample generated in this manner, was analysed for similar studies as the simulated structure. The results were compared with those obtained from simulation. The simulation results agree qualitatively with the real rock sample. Diffusion through the connected pore space of the simulated structure was studied using a random walk algorithm and the results compared with the similar simulation study done on the 3-D oolitic limestone specimen. In both cases diffusion was found to be anomalous indicating that the sedimentary rock has a fractal geometry. The favourable comparability of results between the simulated and real rock supports the usefulness of the model of sedimentary rock generation which can be applicable to transport phenomena.
ISSN: 0956-540X

hal-00823061
https://hal.archives-ouvertes.fr/hal-00823061
DOI : 10.1093/gji/ggs084

Éditeur(s) : HAL CCSD
Résumé : The Voronoi diagram of a finite set of objects is a fundamental geometric structure that subdivides the embedding space into regions, each region consisting of the points that are closer to a given object than to the others. We may define many variants of Voronoi diagrams depending on the class of objects, the distance functions and the embedding space. In this paper, we investigate a framework for defining and building Voronoi diagrams for a broad class of distance functions called Bregman divergences. Bregman divergences include not only the traditional (squared) Euclidean distance but also various divergence measures based on entropic functions. Accordingly, Bregman Voronoi diagrams allow to define information-theoretic Voronoi diagrams in statistical parametric spaces based on the relative entropy of distributions. We define several types of Bregman diagrams, establish correspondences between those diagrams (using the Legendre transformation), and show how to compute them efficiently. We also introduce extensions of these diagrams, e.g. k-order and k-bag Bregman Voronoi diagrams, and introduce Bregman triangulations of a set of points and their connexion with Bregman Voronoi diagrams. We show that these triangulations capture many of the properties of the celebrated Delaunay triangulation. Finally, we give some applications of Bregman Voronoi diagrams which are of interest in the context of computational geometry and machine learning.
https://hal.inria.fr/inria-00137865

Report N° : RR-6154
inria-00137865
https://hal.inria.fr/inria-00137865
https://hal.inria.fr/inria-00137865v2/document
https://hal.inria.fr/inria-00137865/file/bregman.pdf

Éditeur(s) : HAL CCSD Wiley
Résumé : International audience
The paper is motivated by the long term safety analysis of the CO 2 geological storage. We present a methodology for the assessment of the ge-omechanical impact of progressive rock dissolution. The method is based on the use of X-ray tomography and the numerical dissolution technique. The influence of evolution of the microstructure on the macroscopic properties of the rock is analysed by using periodic homogenization method. The numerical computations show progressive degradation of all components of the stiffness (orthotropic) tensor. Moreover, the evolution of associated mass transfer properties (as tortuosity and conductivity tensors), by using the periodic homogenization method, is also calculated. The correlation between the mechanical parameters and the transfer properties during the dissolution pro-cess is presented. The results show that the highest increase of the hydraulic conductivity (in direction Y) is not associated with the highest decrease of Young modulus in this direction. Moreover, the highest decrease of Young modulus (in the direction X) is not associated with percolation in this direction. Finally, an incremental law to calculate settlement, in case of a rock with evolving microstructure, is proposed. The solution of the macroscopic settlement problem under constant stress and drained conditions showed that the geomechanical effects of the rock dissolution are rather limited.
ISSN: 0363-9061

hal-01104204
https://hal.archives-ouvertes.fr/hal-01104204
https://hal.archives-ouvertes.fr/hal-01104204/document
https://hal.archives-ouvertes.fr/hal-01104204/file/Numerical_computations_rock_dissolution_Wojtacki_al_2014.pdf
DOI : 10.1002/nag.2316