Numerical Modeling of Free Surface Flows Using Depth Averaged and 3D Models

The objectives of the research presented in this dissertation are to develop and apply numerical models to study free surface flows under different boundary conditions, bedform geometry and channel configuration. A 2D depth-averaged model is developed by solving the Saint Venant or the shallow water equations using a finite volume method. An existing 3D model, developed in-house, that solves the Reynoldsaveraged Navier-Stokes equations and conservation equations for suspended sediment and conservative species is adapted for free surface flows by solving the volume of fluid (VOF) equation using a compressive interface capturing scheme for arbitrary meshes, CICSAM. The depth-averaged or shallow water and the free-surface capturing 3D model are verified against experimental data on dam-break flow over a sloping bed. The numerical models are used to resolve the discrepancy between earlier simulation results obtained with finite difference models of shallow water equations and a benchmark data set in an open channel contraction collected in the early 1950s. To verify possible experimental errors, the experiment is repeated in a laboratory flume made of smooth plexiglass. Measurements are taken for several flow rates. By applying the numerical models to the experimental conditions, it is found that the original data might have measurement errors, and shallow water models are incapable of properly predicting free surface elevation in an open channel contraction, especially in the uniform section downstream of the contraction. The shallow water models predict standing waves that are out of phase and steeper than those observed in the experiments. The 3D model satisfactorily predicts the water level in the contraction and wave peaks in the downstream uniform section measured in this study, but underpredicts the wave trough amplitudes. The limitation of the present 3D model in capturing sharp changes in water depth is likely associated with the diffusive nature of 2-equation isotropic turbulence models. The effects of freshwater discharge, dune amplitude and tidal amplitude on mixing between freshwater flow and an intruding salt wedge are studied using a 3D numerical model. Model results reveal intense mixing over bedforms, generation of large internal waves with salt concentration reaching the water surface and competing effects of freshwater discharge and the tidal amplitude. During the ebb tide, the freshwater discharge is able to push the salt wedge near or outside of the ocean side boundary. Four different types of disturbances over the dune field that are consistent with the field measurements are recognized. The morphology and fluid dynamics of meandering fluvial river channels have been studied extensively by others using analytical, numerical and analog physical models. These studies involve transport of sediment as bed load and often do not consider the transport and deposit of fine suspended sediment. Within point bar deposits, mud deposition as discrete layers has a significant effect on hydrocarbon reservoir performance, especially in unconventional (heavy oil) settings. This scale of stratigraphic heterogeneity is not represented in even relatively sophisticated static models. The present study is conducted using the 3D numerical model to investigate the controls, process and pattern for the fine deposits over preexisting point bars. The study covers the effect of river cross section and planform shape, suspended load grain size, the variation in river flow discharge, and the average streamwise bed slope. The distribution of the fine-grained deposits is found to be controlled by flow divergence from the base state of uniform flow in straight channel. Both cross section and planform shapes are found to be major controls in flow divergence, and thus sediment distribution within the channel. Seasonal variation in river flow affects the deposit volume and distribution over the point bars.; higher flow discharge results in thicker deposits over point bars. Also, increasing the suspended load grain size results in thicker deposits on the upstream part of the point bars, and the bar tail seems to attract the finer grain size more than the coarser sizes. Changing the slope has only nominal effect on the distribution of fine sediment

Using High Dimensional Computing on Arabic Language Speech to Text Classification

High-Dimensional Processing is the idea that mind register illustrations of neural activities which are not immediately related with numbers. The objective of the article is hyper- dimensional computation of data for categorization of text from two distinct speech datasets, namely the Arabic Corpus dataset and the MediaSpeech dataset with four languages (Arabic, Spanish, French, and Turkish). Through the use of an n-gram encoding scheme, hyper dimensional computing is used to conduct the analysis from the prior set of data. Using hyper dimensional computing, the MediaSpeech dataset accomplishes 100% accuracy for all 4-gram to 14-gram encoding schemes, while the Arabic Corpus dataset accomplishes 100% accuracy for 4-gram to 7-gram encoding schemes

Enhanced dynamic performance of grid feeding distributed generation under variable grid inductance

Controlling weak grid-connected systems is very challenging. In transient, frequency and voltage oscillations may lead to voltage and/or frequency stability problems and finally lead to system collapse. During steady-state operation and at the point of common coupling (PCC), voltage degradation and grid voltage background harmonics restrict the inverter's functionality, reduce the power flow capability and cause poor power quality. With weak grid connection, grid impedance variance will contaminate the voltage waveform by harmonics and augment the resonance, destabilizing the inverter operation. In this paper, complete mathematical modeling is carried out and state feedback-plus-integral control is implemented to support the stabilization of the system. The proposed controller is adopted to provide a smooth transient under sudden load change by controlling the injected grid current under different grid inductance values. Furthermore, the proposed control is used to reduce the order and size of the inverter output filter while maintaining system stability. The proposed control has been compared with the conventional proportional integral (PI) controller under different scenarios to validate its effectiveness and to strengthen its implementation as a simple controller for distributed generator applications

Assessment of predictive current control of six-phase induction motor with different winding configurations

Asymmetrical six-phase (A6P) induction motor-based drives can be considered as a well-established employed technology in high-power safety-critical industry sectors. Of the different control techniques proposed for multiphase machines, model predictive control (MPC) has recently been favored thanks to its simplicity, rapid dynamic response, and flexibility to define new control objectives. One of the main operating challenges when employing MPC to A6P induction machine is the poor quality of the phase current waveform due to the relatively low impedance of the secondary xy subspace. Although different controller structures have been introduced in the available literature to mitigate this problem, most of the available proposals, if not affecting the dc-link voltage utilization, will likely add to the control complexity. From the stator winding layout perspective, this paper attempts to investigate the effect of different winding configurations of six-phase stators with isolated neutral arrangements on the performance of predictive current control (PCC). This study shows that the winding configuration affect the mapping of the 64 available voltage vectors to the αβ and xy subspaces, the induced current ripples, and the required weighting factor employed in PCC. The theoretical findings have experimentally been validated using a 1kW twelve-phase machine that can externally be reconnected to form any of the three available six-phase winding configurations

Prevalence of overweight and obesity based on the body mass index; a cross-sectional study in Alkharj, Saudi Arabia

Background: Obesity and overweight are accompanied with several different chronic diseases. Overweight and obesity can be measured by using body mass index (BMI) and is also used widely as an index of relative adiposity among any population. The aim of the study is to evaluate the prevalence of overweight and obesity among general population in Al-Kharj, Saudi Arabia.Methods: Cross-sectional analysis was undertaken from a representative sample (N = 1019) of the Al Kharj population. Anthropometric measurements including the waist circumference (in centimeters), height (in meters), and weight (in kilograms) of the subjects were undertaken by means of standard apparatus. SPSS 24.0 was utilized for statistical analysis of the data.Results: Majority of respondents in this study were overweight and obese (54.3%) compared with 45.7% being non-obese. A linear positive association of increasing BMI with older age groups was present in males and females. Men had larger waist circumference, weight and height measures as compared with their female counterparts. Regression analysis showed increasing age, being married and high serum cholesterol to be the significant predictors of overweight and obesity while gender, education level, job status, and having diabetes were not.Conclusions: The obesity-overweight prevalence in the Saudi population is high mainly across both genders. However, the associated factors are potentially preventable and modifiable. The regional barriers to lifestyle modifications and interventions to encourage active lifestyles, especially among adolescents to limit the occurrence of obesity and ultimately promote health and wellbeing, are warranted. Furthermore, prospective studies are needed in future to confirm the aetiological nature of such associations

Fetal Biometric Charts and Reference Equations for Pregnant Women Living in Port Said and Ismailia Governorates in Egypt

AIM: To construct new fetal biometric charts and equations for some fetal biometric parameters for women between 12th and 41st  weeks living in Ismailia and Port Said Governorates in Egypt.MATERIAL AND METHODS: This cross-sectional study was carried out on 656 Egyptian women (from Ismailia and Port Said governorates) with an uncomplicated pregnancy, and all were sure of their dates. The selected group was between the 12th and 41st weeks of gestation, recruited from the district general hospital in Ismailia and Port Said to measure ultrasonographically biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC) and femur length (FL), then for each measurement separate regression models were fitted to estimate both the mean and the Standard deviation at each gestational age.RESULTS: New Egyptian charts were reported for BPD, HC, AC, and FL. Reference equations for the dating of pregnancy were presented. The mean of the previous measurements at 12th and 41st weeks were as follows: (23.37, 98.72), (83.05, 336.12), (67.85, 332.57) and (12.50, 74.92) respectively.CONCLUSION: New fetal biometric charts and regression equations for pregnant women living in Port Said & Ismailia governorates in Egypt

Unveiling the genetic basis of Fusarium wilt resistance in chickpea using GWAS analysis and characterization of candidate genes

Introduction: Chickpea is a legume crop that thrives in regions with semi-arid or temperate climates. Its seeds are an excellent source of proteins, carbohydrates, and minerals, especially high-quality proteins. Chickpea cultivation faces several challenges including Fusarium wilt (FW), a major fungal disease that significantly reduces productivity.Methods: In this study, a Genome-wide Association Analysis (GWAS) was conducted to identify multiple genomic loci associated with FW resistance in chickpea. We conducted a comprehensive evaluation of 180 chickpea genotypes for FW resistance across three distinct locations (Ethiopia, Tunisia, and Lebanon) during the 2-year span from 2015 to 2016. Disease infection measurements were recorded, and the wilt incidence of each genotype was calculated. We employed a set of 11,979 single nucleotide polymorphisms (SNPs) markers distributed across the entire chickpea genome for SNP genotyping. Population structure analysis was conducted to determine the genetic structure of the genotypes.Results and Discussion: The population structure unveiled that the analyzed chickpea germplasm could be categorized into four sub-populations. Notably, these sub-populations displayed diverse geographic origins. The GWAS identified 11 SNPs associated with FW resistance, dispersed across the genome. Certain SNPs were consistent across trials, while others were specific to particular environments. Chromosome CA2 harbored five SNP markers, CA5 featured two, and CA4, CA6, CA7, and CA8 each had one representative marker. Four SNPs demonstrated an association with FW resistance, consistently observed across a minimum of three distinct environments. These SNPs included SNP5826041, SNP5825086, SNP11063413, SNP5825195, which located in CaFeSOD, CaS13like, CaNTAQ1, and CaAARS genes, respectively. Further investigations were conducted to gain insights into the functions of these genes and their role in FW resistance. This progress holds promise for reducing the negative impact of the disease on chickpea production

Genome-wide identification, characterization, and validation of the bHLH transcription factors in grass pea

Background: The basic helix-loop-helix (bHLH) transcription factor is a vital component in plant biology, with a significant impact on various aspects of plant growth, cell development, and physiological processes. Grass pea is a vital agricultural crop that plays a crucial role in food security. However, the lack of genomic information presents a major challenge to its improvement and development. This highlights the urgency for deeper investigation into the function of bHLH genes in grass pea to improve our understanding of this important crop.Results: The identification of bHLH genes in grass pea was performed on a genome-wide scale using genomic and transcriptomic screening. A total of 122 genes were identified as having conserved bHLH domains and were functionally and fully annotated. The LsbHLH proteins could be classified into 18 subfamilies. There were variations in intron-exon distribution, with some genes lacking introns. The cis-element and gene enrichment analyses showed that the LsbHLHs were involved in various plant functions, including response to phytohormones, flower and fruit development, and anthocyanin synthesis. A total of 28 LsbHLHs were found to have cis-elements associated with light response and endosperm expression biosynthesis. Ten conserved motifs were identified across the LsbHLH proteins. The protein-protein interaction analysis showed that all LsbHLH proteins interacted with each other, and nine of them displayed high levels of interaction. RNA-seq analysis of four Sequence Read Archive (SRA) experiments showed high expression levels of LsbHLHs across a range of environmental conditions. Seven highly expressed genes were selected for qPCR validation, and their expression patterns in response to salt stress showed that LsbHLHD4, LsbHLHD5, LsbHLHR6, LsbHLHD8, LsbHLHR14, LsbHLHR68, and LsbHLHR86 were all expressed in response to salt stress.Conclusion: The study provides an overview of the bHLH family in the grass pea genome and sheds light on the molecular mechanisms underlying the growth and evolution of this crop. The report covers the diversity in gene structure, expression patterns, and potential roles in regulating plant growth and response to environmental stress factors in grass pea. The identified candidate LsbHLHs could be utilized as a tool to enhance the resilience and adaptation of grass pea to environmental stress