Onset of Convection in Porous Media Induced by Transient Heat Conduction

In this study a computational fluid dynamics (CFD) package – FLUENT/UNS was adopted to simulate the occurrence of convection in an isotropic porous media. The porous layer was homogenous and bounded by two horizontal rigid surfaces. 2-D simulation for steady state and time-dependent were conducted for the bottom surface with two boundary conditions: i) Fixed Surface Temperature – FST, ii) Constant Heat Flux – CHF. The top surface was maintained at FST boundary condition and the vertical wall was adiabatic. The 2-D steady state simulations were carried out to investigate the occurrence of convection as predicted by the linear theory. The 2-D time-dependent were conducted to investigate the possibility of adopting Tan and Thorp’s transient Rayleigh number theory in deep layer of porous media saturated with water. The CFD was successful in modeling the onset of convection in saturated porous media. The range of maximum velocity at the onset of convection and the finger shape of the thermal plume were in agreement with the literatures (Horton and Roger 1949, Elder 1968). The maximum Nusselt number based on кm for the FST and CHF boundary condition were in the range between 3-4, depending on the rate of heat transfer. The steady state and time-dependent simulation results showed no significant difference in the Rayleigh number as predicted by Lapwood (1948) Rac = 39.5, Ribando and Torrance (1976) Rac = 27.1 for the FST and CHF boundary condition. The average Rayleigh numbers based on кm for the steady state simulation were respectively 32.02 and 32.71 for the FST and CHF boundary conditions. The average transient numbers for the time-dependent simulations were respective 30.90 and 30.40 for FST and CHF boundary conditions respectively. The deviation of the Rayleigh number may be due to the complexity of the heat transfer in porous media as wide difference of thermal diffusivity of the solid and liquid that are existing in the saturated porous media. Beside this, large temperature difference ATs or heat flux qº, imposed on the porous media to induce the convection was against the assumption of perturbation theory in which allows only a small disturbance or change in density of the fluid and constant fluid properties

Can cognitive load theory be integrated with self-regulated learning? Contributing empirically to the debate from a financial reporting perspective

Some recent studies have proposed the integration of two prominent learning theories: Cognitive Load Theory (CLT) and self-regulated learning (SRL); whilst other studies have argued against their integration. The purpose of this study is to firstly, explore these arguments regarding the theoretical feasibility of integrating CLT and SRL, and secondly, to assess whether the integration can be empirically validated using the Conceptual Model proposed by Seufert (2018). Regarding the first objective, the findings of this study support the view that the commonalities between the independent learning paradigms outweigh the differences, providing theoretical support for the integration of CLT and SRL. The second objective was achieved by statistically analysing data collected from a postgraduate accounting class. Each participant completed one of three tasks of varying levels of difficulty, followed by a questionnaire that subjectively assessed each participants' cognitive load and self-regulation. The results indicate a statistically significant positive relationship between cognitive load and perceived task difficulty, in line with existing literature. No direct significant relationships were found for the negative relationship theorised between cognitive load and mental resources available, although certain descriptive tests indirectly supported the presence of the negative relationship. Finally, there is partial support for the parabolic relationship proposed by Seufert (2018): there is a significant negative relationship between cognitive load and self-regulation, as theorised in part of the parabola. However, no significant relationship was found for the positive relationship between cognitive load and self-regulation in the parabola. Therefore, this study contributes theoretical support and partial empirical validation, using Seufert's (2018) Conceptual Model, for the integration of CLT and SRL. This study is useful to educators, researchers and professional bodies who are interested in gaining a further understanding, through the integration of CLT and SRL, of the trade-off between the cognitive load experienced during learning, and the learner's ability to self-regulate while learning from various tasks and developing adaptable learners who can self regulate and improve their learning efficiency

On-Bottom Stability Study of Non-Metallic Pipeline Due To Hydrodynamic Loadings

In order to prolong the service life, the integrity and stability of the submarine pipeline always been a concern of the oil and gas industry. However, conventional steel subsea are subjected to corrosion in sour service and even sweet service. Inspection of the subsea pipeline are frequently scheduled to ensure the integrity of the pipeline which is very costly. The non-metallic pipeline are introduced to be replacement of the steel pipeline. The non-metallic properties is known to have highly resistance to corrosion yet it also has lighter weight which lead to on-bottom stability problem. Hence, this project aim to determine the minimum weight of chain per unit length for the subsea non-metallic pipeline to be stabilized. The on-bottom stability study will based of DNV recommended practice with the use of finite element analysis package. This project also will include a finite element analysis of the submarine pipeline by using ABAQUS. The water velocity and acceleration are generated from the sea surface wave and current given the sea state in the South China Sea. The weight of chain is determine from the optimization of the simulation. The simulation’s result by using one year return waves and currents show 32.32kg/m of chain can stabilize the non-metallic pipeline with 0.7654 m lateral displacemen

Using Avida to test the effects of natural selection on phylogenetic reconstruction methods

Phylogenetic trees group organisms by their ancestral relationships. There are a number of distinct algorithms used to reconstruct these trees from molecular sequence data, but different methods sometimes give conflicting results. Since there are few precisely known phylogenies, simulations are typically used to test the quality of reconstruction algorithms. These simulations randomly evolve strings of symbols to produce a tree, and then the algorithms are run with the tree leaves as inputs. Here we use Avida to test two widely used reconstruction methods, which gives us the chance to observe the effect of natural selection on tree reconstruction. We find that if the organisms undergo natural selection between branch points, the methods will be successful even on very large time scales. However, these algorithms often falter when selection is absent

Predicted Binders for MNK2 but not MNK1 Protein Targets from Machine Learning

We used datasets from affinity screening to train machine learning models. The models were then used to rank compounds from commercially available compound collections to generate the following lists of predicted binders for MNK2 but non-binders for MNK1