Impact of foundation layer characteristics on the seismic response of a tailings dam

The foundation layer thickness and stiffness impact the site response by influencing the fundamental frequencies and vibration modes in soil structure interaction (SSI) problems. From a practical perspective, the geotechnical characterisation of earthfill dams is typically focused on the borrow materials comprising the dam, while the foundation materials are often under-characterised, with the depth to the bedrock commonly only approximately estimated. In the seismic response of dams, these unknowns may also impact the deformation patterns affecting the overall stability of the dam. A back-analysis of seismic recorded data for an existing tailings sand dam is performed, to determine the thickness and stiffness of the soil foundation layer by finite element analysis. A cyclic non-linear model (CNL) is employed in the Finite Element analyses which consider different depths to bedrock and soil stiffness profiles. The results suggest satisfactory agreement with the recorded data in terms of acceleration response spectra and amplification ratios and highlight the impact of the foundation layer characteristics on the overall dam response

12 didactic best practices to develop the most efficient Learning Virtual Environment

In this paper, We build the best Learning Virtual Environment pedagogic structure for keep inside the best methodology and resources areas for students, teachers, canal, relationship… and whatever element into an educational community. For this, we draw twelve didactic best practices to be followed for an efficient elearning system

Representing CSCL macro-scripts using IMS LD lessons learned

Extended version of Hernández-Leo, D., Burgos, D., Tattersall, C., Koper, R. Representing Computer-Supported Collaborative Learning macro-scripts using IMS Learning Design Proceedings of the Second European Conference on Technology Enhanced Learning, CEUR Workshop Proceedings, EC-TEL'07, Crete, Greece, September 2007.This paper analyses how CSCL (Computer-Supported Collaborative Learning) macro-scripts can be implemented using IMS Learning Design (LD). CSCL macro-scripts are machine-readable collaboration scripts that structure the activities making up a learning process. In order to support a systematic analysis of the problem, we point out the requirements of CSCL macro-scripts for their representation using LD. These requirements include common collaborative learning mechanisms (group composition, role and resource distribution and coordination) and flexibility demands (such as flexible group composition). Each of these needs is described and illustrated by means of two examples proposed in the literature and which reflect the identified requirements well: Universanté and ArgueGraph Scripts. These scripts are used in the article to expose and exemplify the realization of the requirements using LD. The problem is approached from two angles – that of the LD notation itself and also from related tools and specifications. The paper positions related work and discusses the possibility of generalizing the lessons learned to the representation of CSCL micro-scripts

Fostering participation in learning networks by using reward systems and face-to-face meetings

Hummel, H. G. K., Tattersall, C., Burgos, D., Brouns, F. M. R., & Koper, E. J. R. (Submitted). Fostering participation in learning networks by using reward systems and face-to-face meetings. In Proceedings of ICALT 2006 Conference. July 5-7, Kerkrade, The NetherlandsThis paper investigates conditions for increasing participation in learning networks. ‘Lessons learned’ over a period of almost five years are phrased as recommendations for future learning network implementations. We describe three generations of facilities designed to promote learning of educational modelling languages, from a conventional website through a community site offering facilities for collaboration towards a learning network for the effective exchange of information. The paper focuses on the influence of incentive mechanisms and face-to-face meetings on participation in the LN4LD (Learning Network for Learning Design). These interventions are explained from Self-Organization and Social Exchange Theory. Repeated measurements show that the levels of both passive (accessing and reading information) and active participation (posting, replying and rating) are indeed significantly increased as a result of both interventions. Both the use of reward systems and face-to-face meetings can therefore be considered as valuable ‘add-ons’

Comparison of a tailings material and a natural sand in seismic site response analyses

This article investigates the seismic response of a tailings sand material in the context of site response analysis. The computed response is contrasted with that obtained for an equivalent deposit consisting of a well-characterised natural sand. Initially, the fundamental properties of both materials are used to interpret and compare their behaviour in the framework of Critical State Soil Mechanics (CSSM). Subsequently, both materials' monotonic and cyclic responses are calibrated for an advanced bounding surface plasticity model. Finally, the impact of different calibration approaches is examined through site response analyses under a strong motion. This process identifies fundamental differences between the two geo-materials, impacting the single elements simulations, especially the accuracy of undrained cyclic triaxial tests. The site response analyses examined herein show the impact of the calibrations adopted for both materials in terms of acceleration response spectra, displacements, and excess of pore water pressures (PWP). Although a relatively deep phreatic surface is adopted, the cyclic resistance and permeability of both materials plays a dominant role in the site response characteristics, controlling the excess PWP generation and hence the non-linear behaviour in the soil deposit. Finally, parametric studies are also conducted to explore the impact of permeability of the sands in the site response