Climate change impact on wave energy in the Persian Gulf

Excessive usage of fossil fuels and high emission of greenhouse gases have increased the earth’s temperature, and consequently have changed the patterns of natural phenomena such as wind speed, wave height, etc. Renewable energy resources are ideal alternatives to reduce the negative effects of increasing greenhouse gases emission and climate change. However, these energy sources are also sensitive to changing climate. In this study, the effect of climate change on wave energy in the Persian Gulf is investigated. For this purpose, future wind data obtained from CGCM3.1 model were downscaled using a hybrid approach and modification factors were computed based on local wind data (ECMWF) and applied to control and future CGCM3.1 wind data. Downscaled wind data was used to generate the wave characteristics in the future based on A2, B1, and A1B scenarios, while ECMWF wind field was used to generate the wave characteristics in the control period. The results of these two 30-yearly wave modelings using SWAN model showed that the average wave power changes slightly in the future. Assessment of wave power spatial distribution showed that the reduction of the average wave power is more in the middle parts of the Persian Gulf. Investigation of wave power distribution in two coastal stations (Boushehr and Assalouyeh ports) indicated that the annual wave energy will decrease in both stations while the wave power distribution for different intervals of significant wave height and peak period will also change in Assalouyeh according to all scenarios

Microplastics transport and mixing mechanisms in the nearshore region

Microplastics (MP) are emerging pollutants in the marine environment with potential ecotoxicological effects on littoral and coastal ecosystems. A dominate contributing source of microplastic particles is the fragmentation of macroplastics from manufactured goods, alongside laundered synthetic material, abrasion of vehicle tyres and personal care products. The indiscriminate use of plastic and poor management of plastic waste pose serious threat to ecosystem functionality and resilience. Understanding the key underlying transport and mixing mechanisms which influence the behavior of microplastics and their environmental fate are crucial for identify potential microplastic fate-transport pathways from source to sink. This is fundamental for evaluating microplastic interactions and impact on ecosystems. This paper presents laboratory-based tracer measurements for solute and polyethylene (PE) microplastics in the presence of waves. The tests were undertaken in a wave tank equipped with an active absorption paddle-type wave-maker. Fluorescent dye was used to stain the PE particles using a novel staining technique. Rhodamine dye was used as a proxy for the transport of solute pollutants. The temporal and spatial behavior of both microplastics and solute across the nearshore zone was measured using submersible fiber optic fluorometers. Hydrodynamic conditions were designed to create monochromatic waves with a range of wave steepness Sop = 2 - 5 percent. Tracer measurements were conducted at three locations, seaward of the breaker region, breaker region and inner surf zone to provide a comprehensive understanding of mixing across the nearshore. The dispersion coefficients were determined for both solute and PE particles. The results indicate the dominant role of surface and bed generated turbulence in determining mixing and dispersion influenced by wave breaker type and width of the surf zone. The comparison of tracer data suggests that PE particles, with similar density to water, and the solute tracer have a similar transport and mixing behavior under the influence of waves

Incorporating Deep Bagging Ensemble Method as a Surrogate Model for Simulating Hyper-Concentrated Sediment-Laden Flows

Macroscale and mesoscale simulations of hyper-concentrated sediment-laden flows rely on robust couplings of the Reynolds-Averaged Navier-Stokes equations in conjunction with the shear-stress transport k-ω turbulence model. Also other closure laws for modeling the momentum transfer between the fluid and dispersed particles phase are applied. A numerical framework is developed to couple and solve the various algebraic and Partial Differential Equations (PDEs) based on the Euler-Euler method. A 3D high-fidelity simulation of sediment transport based on two-phase modeling approaches (i.e., Euler-Lagrange and Euler-Euler models) can be computationally prohibitive. A deep bagging ensemble method based on Regression Tree and Model Tree approaches is incorporated into the coupling procedure of the ten PDEs involved in the problem to improve computational efficiency. The performance of the surrogate model was also compared with two traditional surrogate models, i.e., Artificial Neural Network and Kriging meta-modeling. The CFD and surrogate-based models were validated for horizontal transport of cuttings created during an offshore drilling process. In particular, during the hole cleaning procedure, it was challenging to simulate the two-phase flow of the cuttings and non-Newtonian drilling fluid due to the complex interactions between fluid-particle, particle-particle, and particle-wall. Therefore, a four way coupling method was utilized to consider the interdependency of motions between two phases. The values of sediment and fluid concentrations, the velocities of both phases, and pressure loss estimated by the surrogate models were compared with the results of CFD simulations and experimental investigations. The results indicate that the proposed hybrid CFD-surrogate model is capable of providing physical insights into the dynamics of cutting transport, and the resulting computational observations are in line with the relevant CFD simulations and experimental investigations

高せん断力の作用下における掃流層の流動過程の計算力学的研究

京都大学0048新制・課程博士博士(工学)甲第7803号工博第1783号新制||工||1134(附属図書館)UT51-99-G397京都大学大学院工学研究科土木工学専攻(主査)教授 酒井 哲郎, 教授 髙橋 保, 助教授 後藤 仁志学位規則第4条第1項該当Doctor of EngineeringKyoto UniversityDA

Lagrangian coupling two-phase flow model to simulate current-induced scour beneath marine pipelines

This paper presents a Lagrangian coupling two-phase flow model for simulating scour processes beneath a marine pipeline with respect to the sediment and fluid phase interactions. Smoothed Particle Hydrodynamics (SPH) capability is employed to simulate sediment and fluid particles movement, respectively as the Newtonian and non-Newtonian fluids in the framework of two-phase flow modeling. The Sub-Particle Scale (SPS) model also is closured to the fluid phase solver to account for the turbulence effects. The soft contact approach is incorporated in the sediment phase to simulate the interparticle collisions during the local scouring. Following to the Lagrangian coupling model development, the current-induced scour beneath a pipe at tunnel erosion and early stages of lee-wake erosion were explored and then compared with the experiments. The obtained results illustrated the efficiency of the proposed two-phase flow model to reproduce the scour profiles evolution up to the early stages of lee-wake erosion. Within the presented model, the parameters such as pressure field and non-dimensional sediment transport rate beneath the pipe were also estimated

Euler- Euler coupling two phase simulation of seepage through soils in artesian flow conditions

This paper presents the results of a two phase Euler-Euler simulation of seepage flow through granular media for upward flow conditions in soils. The simulation first deals with the fluidization process in a stable granular soil. The first fluidization in the sand column is studied and the stable fluidization condition is reached by the development of particle repulsion and the effect of inertia on the resistance of the granular bed. Considering Richardson’s expansion law, porosity changes with the flow rate variation are described based on the rarefaction waves. In this study the variation of water and soil phases before and after the critical hydraulic gradient are evaluated. The results of the simulation reveal that the variation of soil pressure before and after the critical hydraulic gradient are inverse and the Terzaghi’s effective stress theory is valid only to the onset of the first fluidization. In the second part of the paper, the fluidization and internal erosion processes in the artesian conditions in internally unstable soils are discussed. In internally unstable soils the finer soil particles are able to move through the constrictions of the coarse particles. This may lead to internal erosion and as a result the critical hydraulic gradient drastically increases. The erosion phenomenon is described using the theory of continuum mechanics for the soil consisting of stationary grains, movable grains and the fluid. The continuity and momentum equations are derived for the soil and based on this theory a numerical two phase model for the erosion and fluidization of particles are presented. The results reveal that by the commencement of erosion, the porosity of the soil decreases and the flux of eroded particles increases with time

Application of neuro-fuzzy approach in prediction of runup in swash zone

A prominent parameter in dealing with swash and morphological evolution is the runup length or height, defined as the limit of landward sea. Therefore, it is necessary to predict the runup height in this area. In this paper, the abilities of a new Adaptive-Network-Based Fuzzy Inference System (ANFIS) using subtractive fuzzy clustering method, Fuzzy Inference System (FIS), and existing empirical formulas are implemented for predicting and modeling wave runup in the swash zone. The ANFIS and FIS models are established using the slope angle; Iribarren number and antecedent wave runup data. The empirical formulas are also applied to the same data. Statistical measures were used to evaluate the performance of the models. The existing wave runup, bottom slope, and deep water Iribarren number data for regular and irregular waves on smooth, impermeable plane slopes were used as case studies. The comparison of results reveals that, the ANFIS model provides high accuracy and reliability for wave runup estimation, providing better predictions compared to other techniques. The paper demonstrates that the neurofuzzy approach developed is a good trade-off between the advantages of the Neural Network (supervised learning capabilities) and of the Fuzzy Logic (knowledge which can be explained and understood) without the generic drawbacks (overfitting, optimization problems, etc.) typical in other approaches