Main properties of sands hydrophobized by alkoxysilane emulsions

The results of laboratory tests and geotechnical view on sands hydrophobized by alkoxysilane emulsions are presented. For the soils subjected to this process, very low permeability and no capillary elevation was observed. Laboratory tests also indicate that other physical and mechanical properties of hydrophobized sands remain nearly untouched, i.e., the considered hydrophobisation process does not reduce the strength of soils. Properly composed alkoxysilane emulsions can also solidify in pores to produce a stabilizing silicate binder. The filtration barriers in ground and soil stabilization are thus considered as possible applications of the hydrophobized soils. The process of treatment of granular soils with alkoxysilanes is neutral for the environment and the cost of implementation of the method is relatively low.http://www.degruyter.com/view/j/acgeo.2014.62.issue-5/s11600-014-0223-8/s11600-014-0223-8.xml?format=IN

A multiscale multi-permeability poroplasticity model linked by recursive homogenizations and deep learning

Many geological materials, such as shale, mudstone, carbonate rock, limestone and rock salt are multi-porosity porous media in which pores of different scales may co-exist in the host matrix. When fractures propagate in these multi-porosity materials, these pores may enlarge and coalesce and therefore change the magnitude and the principal directions of the effective permeability tensors. The pore-fluid inside the cracks and the pores of host matrix may interact and exchange fluid mass, but the difference in hydraulic properties of these pores often means that a single homogenized effective permeability tensor field is insufficient to characterize the evolving hydraulic properties of these materials at smaller time scale. Furthermore, the complexity of the hydro-mechanical coupling process and the induced mechanical and hydraulic anisotropy originated from the micro-fracture and plasticity at grain scale also makes it difficult to propose, implement and validate separated macroscopic constitutive laws for numerical simulations. This article presents a hybrid data-driven method designed to capture the multiscale hydro-mechanical coupling effect of porous media with pores of various different sizes. At each scale, data-driven models generated from supervised machine learning are hybridized with classical constitutive laws in a directed graph that represents the numerical models. By using sub-scale simulations to generate database to train material models, an offline homogenization procedure is used to replace the up-scaling procedure to generate cohesive laws for localized physical discontinuities at both grain and specimen scales. Through a proper homogenization procedure that preserves spatial length scales, the proposed method enables field-scale simulations to gather insights from meso-scale and grain-scale micro-structural attributes. This method is proven to be much more computationally efficient than the classical DEM–FEM or FEM2 approach while at the same time more robust and flexible than the classical surrogate modeling approach. Due to the usage of bridging-scale technique, the proposed model may provide multiple opportunities to incorporate different types of simulations and experimental data across different length scales for machine learning. Numerical issues will also be discussed

An evolutionary approach to modelling the thermo-mechanical behaviour of unsaturated soils

A new data mining approach is presented for modelling of the stress-strain and volume change behaviour of unsaturated soils considering temperature effects. The proposed approach is based on the evolutionary polynomial regression (EPR), which unlike some other data mining techniques, generates a transparent and structured representation of the behaviour of systems directly from raw experimental (or field) data. The proposed methodology can operate on large quantities of data in order to capture nonlinear and complex relationships between contributing variables. The developed models allow the user to gain a clear insight into the behaviour of the system. Unsaturated triaxial test data from literature was used for development and verification of EPR models. The developed models were also used (in a coupled manner) to produce the entire stress path of triaxial tests. Comparison of the EPR model predictions with the experimental data revealed the robustness and capability of the proposed methodology in capturing and reproducing the constitutive thermo-mechanical behaviour of unsaturated soils. More importantly, the capability of the developed models in accurately generalising the predictions to unseen data cases was illustrated. The results of a sensitivity analysis showed that the models developed from data are able to capture and represent the physical aspects of the unsaturated soil behaviour accurately. The merits and advantages of the proposed methodology are also discussed

Some aspects of application of artificial neural network for numerical modeling in civil engineering

In order to obtain reliable results of computations in civil engineering, the numerical procedures that are used at the stage of design should be calibrated by comparison of the theoretical results with an observed behavior of previously modeled and then executed structures. The hybrid Finite Element code with an Artificial Neural Network inserted as a representation of a constitutive law, offers a possibility to adjust not only parameters of the constitutive relationships but also its qualitative form. Because of this, the representation of constitutive law by the ANN is presented in this paper. The constitutive data should be calibrated to fit well the observable values, measured in experiments. If the constitutive law is expressed by ANN, the inverse problem can be reduce to a training of the ANN inserted into the Finite Element code. An example of a solution of the inverse problem in calibration of constitutive law is presented. An identification of parameters of flow of pollutant in soils is described as another example of application of ANN in engineering

Zastosowanie sztucznych sieci neuronowych w modelowaniu numerycznym kompozytów przy pomocy metody elementów skończonych.

An application of Artificial Neural Networks for a definition of the effective constitutive law for a composite is described in the paper. First, a classical homogenisation procedure is directly interpreted with a use of this numerical tool. Next, a self-learning Finite Element code (FE with ANN inside) is used in the case when the effective constitutive law is deduced from a numerical experiment (substituting here a purely phenomenological approach). The new contribution to the classical self-learning procedure consists of its adaptation to a case of a non-monotonic loading (non-to-one load-deformation curve). This new ability of the method is principally due to the incremental form of the constitutive equation and the respective scheme of the neural network structure. Also an organisation of a constitutive data-base containing learning patterns is suitably modified. It is shown by examples that the training process is very quick. The error of this method is smaller, comparing to other schemes of data acquisition.W artykule opisano zastosowanie sztucznych sieci neuronowych do określenia efektywnego związku konstytutywnego dla kompozytów. To narzędzie numeryczne użyte zostało dwojako: do bezpośredniego zapisu wyników otrzymanych w ramach klasycznej metody homogenizacji oraz do wnioskowania o własnościach efektywnych na podstawie eksperymentu numerycznego (zastępującego eksperyment rzeczywisty) wykonanego na małej, lecz reprezentatywnej próbce kompozytu. W tym drugim przypadku zastosowano schemat "samouczącego się" programu metody elementów skończonych, w którym związek konstytutywny opisany jest siecią neuronową. Schemat ten zaadaptowano tak, że może być użyty w przypadku obciążeń niemonotonicznych oraz wtedy, gdy zależność: miara odkształcenia-miara naprężenia nie jest wzajemnie jednoznaczna. Te nowe możliwości uzyskane zostały dzięki przedstawieniu związku konstytutywnego w formie przyrostowej oraz opracowania odpowiedniej do tego budowy sieci neuronowej. Schemat "samouczącego się" programu MES charakteryzuje się tym, że proces formułowania nieznanego związku konstytutywnego jest szybki, a zgodność modelu numerycznego z eksperymentem większa niż dla innych metod

Monetary Policy Council’s resolutions as the acts of domestic law – issues with the classification

The article presents a detailed classification of Monetary Policy Council resolutions as acts of internal law. In the study the attention is focused on monetary policy which is specified by RPP regulation in the form of annual monetary guidelines and complementary acts of the appropriate Council. The RPP Acts of Will were broadened with reflections of political nature of the resolution as a law act as well as the analysis of the relation that occurs between the Council resolution and the Budget formed by the Council of Ministers. The correlation between the two subjects in the economic policy of the country, with the respect for their complete autonomy, is the sign of public finance safety and of the inflationary target realization on the assumed level

3-D finite element analysis of composite beams with parallel fibres, based on homogenization theory

The theoretical model of a beam of unidirectional composites, based on the homogenization theory and a refined kinematical hypothesis is presented. Effective material coefficients for the constitutive equation are computed. Description of the stresses on the level of the periodic microstructure is given. The kinematical hypothesis for the beam type behaviour includes the independent shear rotations. The resulting modelling strategy is presented for which a finite element code has been developed. Application of the theory to superconducting coils is shown