This study focuses on the utilisation of lab-based activities to enhance the learning experience of engineering students studying water engineering and geosciences courses. Specifically, the use of “floodopoly” as a physical model demonstration in improving the students’ understanding of the relevant processes of flooding, infrastructure scour and sediment transport, and improve retention and performance in simulation of these processes in engineering design courses, is discussed. The effectiveness of lab-based demonstration is explored using a survey assessing the weight of various factors that might influence students’ performance and satisfaction. It reveals how lab-centred learning, overall course success is linked with student motivation and the students’ perception of an inclusive teaching environment. It also explores the effectiveness of the implementation of student-centred and inquiry-guided teaching and various methods of assessment. The analysis and discussion are informed by students’ responses to a specifically designed questionnaire, showing an improvement of the satisfaction rates compared to traditional class-based learning modules. For example, more students (85%) reported that they perceived the lab-based environment as an excellent contribution to their learning experience, while less students (about 57%) were as satisfied for a traditional class-based course delivery. Such findings can be used to improve students’ learning experience by introducing physical model demonstrations, similar to those offered herein.
<p>Ageing infrastructure alongside with extreme climatic conditions pose a major threat for the sustainability of civil infrastructure systems with significant societal and economic impacts [1]. A main issue also arises from the fact that past and existing methods that incorporate the risk of climatic hazards into infrastructure design and assessment methods are based on historical records [2].</p><p>Major flood incidents are the factor of evolving geomorphological processes, which cause a drastic reduction in the safe capacity of structures (e.g. bridges, dams). Many efforts focused on the development and application of monitoring techniques to provide real-time assessment of geomorphological conditions around structural elements [1, 3, 4]. However, the current qualitative visual inspection practice cannot provide reliable assessment of geomorphological effects at bridges and other water infrastructure.</p><p>This work presents an analysis of the useful experience and lessons learnt from past monitoring efforts applied to assess geomorphological conditions at bridges and other types of water infrastructure. The main advantages and limitations of each monitoring method is summarized and compared, alongside with the key issues behind the failure of existing instrumentation to provide a solution. Finally, future directions on scour monitoring is presented focusing on latest advances in soil and remote sensing methods to provide modern and reliable alternatives for real-time monitoring and prediction [5, 6] of climatic hazards of infrastructure at risk.</p><p>&#160;</p><p>References</p><p>[1] Michalis, P., Konstantinidis, F. and Valyrakis, M. (2019) The road towards Civil Infrastructure 4.0 for proactive asset management of critical infrastructure systems. Proceedings of the 2nd International Conference on Natural Hazards & Infrastructure (ICONHIC2019), Chania, Greece, 23&#8211;26 June 2019.</p><p>[2] Pytharouli, S., Michalis, P. and Raftopoulos, S. (2019) From Theory to Field Evidence: Observations on the Evolution of the Settlements of an Earthfill Dam, over Long Time Scales. Infrastructures 2019, 4, 65.</p><p>[3] Koursari, E., Wallace, S., Valyrakis, M. and Michalis, P. (2019). The need for real time and robust sensing of infrastructure risk due to extreme hydrologic events, 2019 UK/ China Emerging Technologies (UCET), Glasgow, United Kingdom, 2019, pp. 1-3.&#160;doi: 10.1109/UCET.2019.8881865</p><p>[4] Michalis, P., Saafi, M. and M.D. Judd. (2012) Integrated Wireless Sensing Technology for Surveillance and Monitoring of Bridge Scour. Proceedings of the 6th International Conference on Scour and Erosion, France, Paris, pp. 395-402.</p><p>[5] Valyrakis, M., Diplas, P., and Dancey, C.L. (2011) Prediction of coarse particle movement with adaptive neuro-fuzzy inference systems, Hydrological Processes, 25 (22). pp. 3513-3524. ISSN 0885-6087, doi:10.1002/hyp.8228.</p><p>[6] Valyrakis, M., Michalis, P. and Zhang, H. (2015) A new system for bridge scour monitoring and prediction. Proceedings of the 36th IAHR World Congress, The Hague, the Netherlands, pp. 1-4.</p>
<p>Several studies have documented high concentration of microplastics on fresh water sources, oceans and even on treated tap and bottled water. Understanding the physics behind these particles in the water environment has become one of the key research needs identified in the World Health Organization Report (2019). In order to develop novel and efficient methodologies for sampling, treating and removing microplastics from water bodies, a thorough understanding of the sources and transportation and storage mechanisms of these particles is required.</p><p>In this article, the settlement velocity affecting the transport [1, 2] of low-density particles (1<r<1.4 g.cm<sup>-3</sup>) and drag coefficients is assessed through numerical modelling. The effects of fluid and particle relative densities and media temperatures are analysed, as well as the impact of the particle size and shapes [3].</p><p>Computational Fluid Dynamics (CFD) techniques are applied to solve the fluid dynamics while the Discrete Element Method (DEM) approach is used to model the particle trajectories [4]. These two modules are coupled under the CFDEM module, which transmits the forces from the fluid into the particle and from the particle into the surrounding water through the Fictitious Boundary Method approach.</p><p>Several tests are run under the same particle conditions in order to estimate the influence of turbulent flows on these experiments. The influence from different particle densities and diameters on settling velocities and drag coefficients is assessed. The numerical results are validated against a wide range of experimental data [2, 3] and compared against empirical predictions.</p><p>There is an urge for gaining a better understanding of the sources and transport of microplastics through fresh water bodies. In this sense, sampling and quantification of microplastics in a drinking water source is key to evaluate the environment status and to design the most appropriate techniques to reduce or remove the microplastics from the aquatic environments. The implementation of coupled CFD-DEM models provides a very powerful tool for the understanding and prediction of the transport processes and the accumulation of microplastics along the fluvial vectors.</p><p>&#160;</p><p>References</p><p>[1] Valyrakis M., Diplas P. and Dancey C.L. 2013. Entrainment of coarse particles in turbulent flows: An energy approach. J. Geophys. Res. Earth Surf., Vol. 118, No. 1., pp 42- 53, doi:340210.1029/2012JF002354.</p><p>[2] Valyrakis, M., Farhadi, H. 2017. Investigating coarse sediment particles transport using PTV and &#8220;smart-pebbles&#8221; instrumented with inertial sensors, EGU General Assembly 2017, Vienna, Austria, 23-28 April 2017, id. 9980.</p><p>[3] Valyrakis, M., J. Kh. Al-Hinai, D. Liu (2018), Transport of floating plastics along a channel with a vegetated riverbank, 12th International Symposium on Ecohydraulics, Tokyo, Japan, August 19-24, 2018, a11_2705647.</p><p>[4] Valyrakis M., P. Diplas, C.L. Dancey, and A.O. Celik. 2008. Investigation of evolution of gravel river bed microforms using a simplified Discrete Particle Model, International Conference on Fluvial Hydraulics River Flow 2008, Ismir, Turkey, 03-05 September 2008, 10p.</p>
<p>Numerical simulations for the transport of coarse sediment particles in turbulent flows are performed, with particular emphasis on the energy and momentum exchange [1, 2, 3] between the two phases at the particle scale. &#160;The solid particles positions and velocities are solved through the Discrete Element Method (DEM), coupled with a Computational Fluid Dynamics (CFD) model which updates the dynamically evolving flow field through the numerical solution of the Reynolds Averaged of Navier-Stokes equations (RANS).</p><p>At the core of this work, the coupling of these two models (DEM-CFD) based on the Fictitious Boundary Method, is analysed. The models have a high mesh resolution, by adopting a meshing strategy which aims at sufficiently discretising the flow field surrounding each particle. Smooth and rough bed cases are simulated, under a wide range of Reynolds numbers covering applications from particle entrainment, up to bulk bedload transport through rolling and saltation. The numerical results are benchmarked against experimental data obtained from controlled laboratory experiments [4, 5, 6].</p><p>The implementation of coupled CFD-DEM models provides a very powerful tool for improving the understanding of fluid and particle physics in sediment transport. Particularly, the potential to perform a large number of validated numerical that robustly predict geomorphological changes in aquatic environments and fluvial systems.</p><p><strong>References</strong></p><p>[1] Valyrakis M., P. Diplas, C.L. Dancey, and A.O. Celik. 2008. Investigation of evolution of gravel river bed microforms using a simplified Discrete Particle Model, International Conference on Fluvial Hydraulics River Flow 2008, Ismir, Turkey, 03-05 September 2008, 10p.</p><p>[2] Valyrakis M., Diplas P. and Dancey C.L. 2013. Entrainment of coarse particles in turbulent flows: An energy approach. J. Geophys. Res. Earth Surf., Vol. 118, No. 1., pp 42- 53, doi:340210.1029/2012JF002354.</p><p>[3] P&#228;htz, Th., Clark, A., Duran, O., Valyrakis, M. 2019. The physics of sediment transport initiation, cessation and entrainment across aeolian and fluvial environments, Reviews of Gephysics, https://doi.org/10.1029/2019RG000679.</p><p>[4] Valyrakis, M. & Pavlovskis, E. 2014. "Smart pebble&#8221; design for environmental monitoring applications, In Proceedings of the 11th International Conference on Hydroinformatics, Hamburg, Germany.</p><p>[5] Valyrakis M., A. Alexakis. 2016. Development of a &#8220;smart-pebble&#8221; for tracking sediment transport. International Conference on Fluvial Hydraulics River Flow 2016, St. Liouis, MO, 8p.</p><p>[6] Valyrakis, M., Farhadi, H. 2017. Investigating coarse sediment particles transport using PTV and &#8220;smart-pebbles&#8221; instrumented with inertial sensors, EGU General Assembly 2017, Vienna, Austria, 23-28 April 2017, id. 9980.</p>
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