Supporting active learning in an undergraduate geotechnical engineering course using group-based audience response systems quizzes

The use of audience response systems (ARSs) or ‘clickers’ in higher education has increased over the recent years, predominantly owing to their ability to actively engage students, for promoting individual and group learning, and for providing instantaneous feedback to students and teachers. This paper describes how group-basedARSquizzes have been integrated into an undergraduate civil engineering course on foundation design. Overall, theARSsummary quizzes were very well received by the students. Feedback obtained from the students indicates that the majority believed the group-based quizzes were useful activities, which helped to improve their understanding of course materials, encouraged self-assessment, and assisted preparation for their summative examination. Providing students with clickers does not, however, necessarily guarantee the class will be engaged with the activity. If an ARS activity is to be successful, careful planning and design must be carried out and modifications adopted where necessary, which should be informed by the literature and relevant student feedback.

Geotechnical engineering characterization of sediments at DSDP Leg 72 Holes

The hydraulic piston coring device (HPC-15) allows recovery of deep ocean sediments with minimal disturbance. The device was used during Leg 72 of the Deep Sea Drilling Project (DSDP) aboard the Glomar Challenger. Core samples were recovered from bore holes in the Rio Grande Rise in the southwest Atlantic Ocean. Relatively undisturbed sediment cores were obtained from Holes 515A, 516, 517, and 518. The results of shipboard physical property measurements and on-shore geotechnical laboratory tests on these cores are presented in this chapter. A limited number of 0.3 m cores were obtained and used in a series of geotechnical tests, including one-dimensional consolidation, direct shear, Atterburg limit, particle size analysis, and specific gravity tests. Throughout the testing program, attention was focused on assessment of sample disturbance associated with the HPC-15 coring device. The HPC-15 device limits sample disturbance reasonably well in terrigenous muds (clays). However, sample disturbance associated with coring calcareous sediments (nannofossil-foraminifer oozes) is severe. The noncohesive, granular behavior of the calcareous sediments is vulnerable to severe disturbance, because of the design of the sampling head on the device at the time of Leg 72. A number of modifications to the sampling head design are recommended and discussed in this chapter. The modifications will improve sample quality for testing purposes and provide longer unbroken core samples by reducing friction between the sediment column and the sampling tool.

Application of Bayesian approach in geotechnical engineering

En esta Tesis Doctoral se emplean y desarrollan Métodos Bayesianos para su aplicación en análisis geotécnicos habituales, con un énfasis particular en (i) la valoración y selección de modelos geotécnicos basados en correlaciones empíricas; en (ii) el desarrollo de predicciones acerca de los resultados esperados en modelos geotécnicos complejos. Se llevan a cabo diferentes aplicaciones a problemas geotécnicos, como es el caso de: (1) En el caso de rocas intactas, se presenta un método Bayesiano para la evaluación de modelos que permiten estimar el módulo de Young a partir de la resistencia a compresión simple (UCS). La metodología desarrollada suministra estimaciones de las incertidumbres de los parámetros y predicciones y es capaz de diferenciar entre las diferentes fuentes de error. Se desarrollan modelos "específicos de roca" para los tipos de roca más comunes y se muestra cómo se pueden "actualizar" esos modelos "iniciales" para incorporar, cuando se encuentra disponible, la nueva información específica del proyecto, reduciendo las incertidumbres del modelo y mejorando sus capacidades predictivas. (2) Para macizos rocosos, se presenta una metodología, fundamentada en un criterio de selección de modelos, que permite determinar el modelo más apropiado, entre un conjunto de candidatos, para estimar el módulo de deformación de un macizo rocoso a partir de un conjunto de datos observados. Una vez que se ha seleccionado el modelo más apropiado, se emplea un método Bayesiano para obtener distribuciones predictivas de los módulos de deformación de macizos rocosos y para actualizarlos con la nueva información específica del proyecto. Este método Bayesiano de actualización puede reducir significativamente la incertidumbre asociada a la predicción, y por lo tanto, afectar las estimaciones que se hagan de la probabilidad de fallo, lo cual es de un interés significativo para los diseños de mecánica de rocas basados en fiabilidad. (3) En las primeras etapas de los diseños de mecánica de rocas, la información acerca de los parámetros geomecánicos y geométricos, las tensiones in-situ o los parámetros de sostenimiento, es, a menudo, escasa o incompleta. Esto plantea dificultades para aplicar las correlaciones empíricas tradicionales que no pueden trabajar con información incompleta para realizar predicciones. Por lo tanto, se propone la utilización de una Red Bayesiana para trabajar con información incompleta y, en particular, se desarrolla un clasificador Naïve Bayes para predecir la probabilidad de ocurrencia de grandes deformaciones (squeezing) en un túnel a partir de cinco parámetros de entrada habitualmente disponibles, al menos parcialmente, en la etapa de diseño. This dissertation employs and develops Bayesian methods to be used in typical geotechnical analyses, with a particular emphasis on (i) the assessment and selection of geotechnical models based on empirical correlations; on (ii) the development of probabilistic predictions of outcomes expected for complex geotechnical models. Examples of application to geotechnical problems are developed, as follows: (1) For intact rocks, we present a Bayesian framework for model assessment to estimate the Young’s moduli based on their UCS. Our approach provides uncertainty estimates of parameters and predictions, and can differentiate among the sources of error. We develop ‘rock-specific’ models for common rock types, and illustrate that such ‘initial’ models can be ‘updated’ to incorporate new project-specific information as it becomes available, reducing model uncertainties and improving their predictive capabilities. (2) For rock masses, we present an approach, based on model selection criteria to select the most appropriate model, among a set of candidate models, to estimate the deformation modulus of a rock mass, given a set of observed data. Once the most appropriate model is selected, a Bayesian framework is employed to develop predictive distributions of the deformation moduli of rock masses, and to update them with new project-specific data. Such Bayesian updating approach can significantly reduce the associated predictive uncertainty, and therefore, affect our computed estimates of probability of failure, which is of significant interest to reliability-based rock engineering design. (3) In the preliminary design stage of rock engineering, the information about geomechanical and geometrical parameters, in situ stress or support parameters is often scarce or incomplete. This poses difficulties in applying traditional empirical correlations that cannot deal with incomplete data to make predictions. Therefore, we propose the use of Bayesian Networks to deal with incomplete data and, in particular, a Naïve Bayes classifier is developed to predict the probability of occurrence of tunnel squeezing based on five input parameters that are commonly available, at least partially, at design stages.

Geotechnical engineering in the coastal zone /

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