Numerical Analysis and Computation Commons^™

Design And Optimization Of An Azeotropic Distillation Pilot Plant For The Production Of Pure Ethanol, Samwel V. Manyele

Tanzania Journal of Engineering and Technology (TJET)

This study aimed to design an azeotropic distillation plant using Aspen Plus® V10 software and determine optimal process conditions for producing pure ethanol greater than 95% from pre-concentrated near-azeotropic ethanol-water solution. The non-random two-liquid Redlich-Kwong thermodynamic model was the base method for property analysis and performance prediction. Modelling and simulation of the converged process were conducted for fixed column variables (R = 5, N = 12 and p = 1 atm). Plant operating parameters were varied in the range of 0 to 1 for the pre-heater vapour fraction, 2 to 10 for the column feed plates (NFP), 2 to 6 …

Sol-Gel Synthesis And Microstructure Characterization Of Nio-Tio2 Semiconductor, Godlisten N. Shao

Tanzania Journal of Engineering and Technology (TJET)

NiO-TiO2 is a fascinating p-n semiconducting binary metal oxide with unique electronic and optical properties. The NiO-TiO2 has been synthesized using complicated preparation methods and expensive precursors that hamper their large-scale production. The present study reports the preparation of NiO-TiO2 semiconductor with improved physicochemical properties. NiO-TiO2 samples were prepared through one-pot sol-gel synthesis process followed by sintering of the as-synthesized materials at temperatures ranging from 600 to 1000 °C. The role of thermal treatment and NiO content on the microstructures was exquisitely studied. The microstructure of the NiO-TiO2 samples was examined by Raman spectroscopy, XRD, XRF, SEM-EDAX, high resolution TEM, …

General Hydrogeochemical Characterization Of Groundwater In Coastal Aquifers Of Kilwa Kisiwani Oceanic Island, South East Tanzania, Simon R Melchioly

Tanzania Journal of Engineering and Technology (TJET)

The main objective of this study was to determine the hydrogeochemical processes controlling the groundwater chemistry on the Island and assess its suitability for human consumption and irrigation. The methodology used in the study include hydrogeological assessment of the study area and laboratory analysis for general physico-chemical parameters of groundwater. Other parameters such as Soluble sodium percentage (SSP) or % Na+, Sodium Adsorption Ratio (SAR), Magnesium adsorption ratio (MAR), Residual sodium carbonate (RSC), hydrochemical facies classification, and Water Quality Index (WQI) were calculated using empirical formulae. The effects of salinization of groundwater were classified using the chloride-Bicarbonate (Cl/HCO3) and the …

Study Of The Effects Of Thermal Aging Coupled With Shot-Peening Treatment Of Carbonitrided Din 1.6587 Low Alloy Steel On Retained Austenite And Residual Stresses, Richard J. Katemi

Tanzania Journal of Engineering and Technology (TJET)

This work investigated the effects of thermal aging and shot-peening of carbonitrided 1.6587 steel grade on retained austenite and residual stresses. After carbonitriding samples contained maximum of 0.87% carbon, 0.34% nitrogen and 50 mass. -% retained austenite. Thermal aging conditions investigated were -30°C, 90°C and 150°C while the aging period were 14, 96 and 720 hours. After thermal aging, some of the samples were subjected to shot-peening treatment using standard cut wire shots StD – G3 - 0.6 mm VDFI 8001 with intensity in the range of 0.25 to 0.30 mmA and coverage of 1.00 to 1.24 x 98%. It …

Optimization Pump As Turbine Coupled To A Self-Excited Induction Generator Using Multi-Objective Genetic Algorithm, Emanuel J. Nyirenda

Tanzania Journal of Engineering and Technology (TJET)

As a way of accelerating the deployment of affordable and clean renewable energy generation technologies, applying a pump working as a turbine coupled to a self-excited induction generator is gaining popularity in various areas including energy recovery and micro hydro systems. However, it is currently challenging to predict the performance of the PAT-SEIG system and there is no agreed-upon rule on the selection of the appropriate system to be installed at a particular site. This paper has presented multi-objective optimization to select the best operating point of the PAT-SEIG system. The results show that the peak efficiencies for the PAT …

Optimal Load Shedding During Service Restoration In Electrical Secondary Distribution Network Based On Reinforcement Learning, Rukia J. Mwifunyi

Tanzania Journal of Engineering and Technology (TJET)

Increased stress in traditional power systems results in blackouts due to voltage instability attributed to a mismatch between available capacity and load demand, especially in distribution networks. Service restoration schemes are designed to return power supply to the affected parts of the networks. The availability of insufficient supply is a complex problem that requires operational experience or an automatic system. The stochastic nature of load demand significantly impacts service restoration as it results in increased restored demand in case a fault occurs during off-peak hours and helps reduce overload if the fault occurs during peak hours. The study adopts an …

Causes And Consequences Of Inefficient Drilling And Blasting In Mine Development Headings: A Case Study Of Hard Rock Gold Mining Operations In Northern Tanzania, George Bennett

Tanzania Journal of Engineering and Technology (TJET)

Despite the introduction of the perimeter blasting technique at the Tulawaka Gold Mine, the mine continued to suffer from an overbreak of mine development headings, with an average overbreak of 24% every 22 m, which is approximately twice the acceptable 10% overbreak. The causes of this problem include ineffective drilling practices and uneven and excessive charging of explosives, resulting in a slightly high powder factor of 3.94 kg/m3 instead of 3.8 kg/m3, as per the design. The problem of overbreak resulted in ore dilution, a longer mine development cycle time and additional costs of approximately US$ 45 per cut, especially …

Evaluation Of Cybersecurity In Remote Working Settings For Mobile Network Operators, Victoria Mahabi

Tanzania Journal of Engineering and Technology (TJET)

Cybersecurity has increasingly been a primary concern to people as technology advances and allows them to work remotely. This study thus evaluated the cybersecurity posture for organisations that have opted for remote working culture, whereas emerging cyber threats, practices to combat them, and appropriate guidelines for managing cyber threats were discussed. The study used a descriptive design with a quantitative approach from 118 information technology personnel working for Tanzania's three major mobile network operators (MNOs). SPSS analysed the collected data. The study revealed that predominant cyber-threats affecting MNOs in remote working include human errors, phishing attacks, malicious domains, denial of …

Normrank Correlations For Testing Associations And For Use In Latent Variable Models, Daniel B. Wright

Educational Psychology, Leadership, and Higher Education Faculty Research

Pearson’s correlation is widely used to test for an association between two variables and also forms the basis of several multivariate statistical procedures including many latent variable models. Spearman’s p is a popular alternative. These procedures are compared with ranking the data and then applying the inverse normal transformation, or for short the normrank transformation. Using the normrank transformation was more powerful than Pearson’s and Spearman’s procedures when the distributions have less than normal kurtosis (platykurtic), when the distributions have greater than normal kurtosis (leptokurtic), and when the distribution is skewed. This is examined for testing if there is an …

A 2-D Numerical Model For Evaluating Daylight Penetration In Short Tunnels For Enhanced Driver Safety, Joachim James

Master's Theses

It is commonly assumed that daylight will adequately penetrate short tunnels, leading to the misconception that artificial lighting is unnecessary during the daytime. Past studies revealed higher frequency of crashes in short tunnels and despite that there is lack of national guidelines warranting artificial lighting for short tunnels. Inadequately lit tunnels pose safety risks, while excessive lighting can be costly. Hence, it becomes crucial to investigate the extent of daylight penetration in short tunnels and identify disappearance zones within these tunnels. This research can help determine the necessity of artificial lighting, and which specific areas of the tunnel require lighting. …

Mathematically Rigorous Deep Learning Paradigms For Data-Driven Scientific Modeling, Owen Nicholas Davis

Mathematics & Statistics ETDs

This dissertation explores the crucial role of data-driven modeling in science and engineering, with a focus on developing surrogate models to accelerate large-scale computational tasks, aiding in both outer-loop functions like uncertainty quantification and expensive inner-loop tasks within broader computational frameworks. Challenges arise with increased problem dimension and sparse, noisy training data, particularly significant when constructing surrogates for very expensive computational models where acquiring sufficient high-fidelity training data is unfeasible. In such scenarios, training surrogates from an ensemble of multifidelity information sources of varying accuracy and cost becomes essential. We emphasize neural network-based modeling paradigms, which are flexible in integrating …

Modeling An Infection Outbreak With Quarantine: The Sibkr Model, Mikenna Dew, Amanda Langosch, Theadora Baker-Wallerstein

Rose-Hulman Undergraduate Mathematics Journal

Influenza is a respiratory infection that places a substantial burden in the world population each year. In this project, we study and interpret a data set from a flu outbreak in a British boarding school in 1978 with mathematical modeling. First, we propose a generalization of the SIR model based on the quarantine measure in place and establish the long-time behavior of the model. By analyzing the model mathematically, we determine the analytic formulas of the basic reproduction number, the long-time limit of solutions, and the maximum number of infection population. Moreover, we estimate the parameters of the model based …

Enhancing Rotating Machinery Fault Diagnosis: A Dual-Head Attention Mechanism In Deep Learning Neural Networks, Qing Snyder

Dissertations

Rotating machinery is crucial to production efficiency and safety in manufacturing industries for an extended time. Ensuring machinery reliability necessitates effective diagnostic systems, particularly for rotating bearings, the key components of such equipment. Fault diagnosis in rotating machinery is essential to prevent failures and minimize downtime, thereby playing an important role in industrial operations. The application of advanced neural network techniques in industry has risen recently. Among these, attention-based neural networks, especially the Transformer models, are originally noteworthy for their sequential data handling capability. This research delves into attention-based algorithms for rotating machinery fault diagnosis, signifying a substantial advancement in …

Modeling And Numerical Analysis Of The Cholesteric Landau-De Gennes Model, Andrew L. Hicks

LSU Doctoral Dissertations

This thesis gives an analysis of modeling and numerical issues in the Landau-de Gennes (LdG) model of nematic liquid crystals (LCs) with cholesteric effects. We derive various time-step restrictions for a (weighted) $L^2$ gradient flow scheme to be energy decreasing. Furthermore, we prove a mesh size restriction, for finite element discretizations, that is critical to avoid spurious numerical artifacts in discrete minimizers that is not well-known in the LC literature, particularly when simulating cholesteric LCs that exhibit ``twist''. Furthermore, we perform a computational exploration of the model and present several numerical simulations in 3-D, on both slab geometries and spherical …

Tools For Biomolecular Modeling And Simulation, Xin Yang

Mathematics Theses and Dissertations

Electrostatic interactions play a pivotal role in understanding biomolecular systems, influencing their structural stability and functional dynamics. The Poisson-Boltzmann (PB) equation, a prevalent implicit solvent model that treats the solvent as a continuum while describes the mobile ions using the Boltzmann distribution, has become a standard tool for detailed investigations into biomolecular electrostatics. There are two primary methodologies: grid-based finite difference or finite element methods and body-fitted boundary element methods. This dissertation focuses on developing fast and accurate PB solvers, leveraging both methodologies, to meet diverse scientific needs and overcome various obstacles in the field.

A Novel Fuzzy Time Series Forecasting Method Based On Probabilistic Fuzzy Set And Cpbd Approach, Krishna Kumar Gupta, Suneet Saxena

Applications and Applied Mathematics: An International Journal (AAM)

Probabilistic fuzzy set is used to model the non-probabilistic and probabilistic uncertainties simultaneously in the system. This study proposes a cumulative probability-based discretization and probabilistic fuzzy set based novel fuzzy time series forecasting method. It also proposes a novel discretization approach based on cumulative probability to tackle the probabilistic uncertainty in partitioning of datasets. Gaussian probability distribution function has been used to construct probabilistic fuzzy set. The advantage of the proposed work is that it addresses the uncertainties due to randomness and fuzziness simultaneously and also improves accuracy rate in time series forecasting. A proposed forecasting method is applied on …

Stack For Computational Science, Mathematics And Engineering E-Learners, Idrissa S. Amour

Tanzania Journal of Engineering and Technology (TJET)

Petroleum economic evaluation involves estimating revenues from forecasted production profiles and field costs including capital expenditures (CAPEX), drilling expenses (DRILLEX), and operating expenses (OPEX). The existing cost-estimating tool requires several inputs making it time-intensive and difficult to use with few data during the early stages of projects. Majority of the previously developed time saving cost estimations proxy models rely on unrealistic assumptions that include uniform operational costs for different fields with a different number of wells, casings, and drilled depths. This work focused at developing proxy models that consider the variability of the development costs with different parameters. The developed …

New Algorithmic Support For The Fundamental Theorem Of Algebra, Vitaly Zaderman

Dissertations, Theses, and Capstone Projects

Univariate polynomial root-finding is a venerated subjects of Mathematics and Computational Mathematics studied for four millenia. In 1924 Herman Weyl published a seminal root-finder and called it an algorithmic proof of the Fundamental Theorem of Algebra. Steve Smale in 1981 and Arnold Schonhage in 1982 proposed to classify such algorithmic proofs in terms of their computational complexity. This prompted extensive research in 1980s and 1990s, culminated in a divide-and-conquer polynomial root-finder by Victor Pan at ACM STOC 1995, which used a near optimal number of bit-operations. The algorithm approximates all roots of a polynomial p almost as fast as one …

Fitting A Covid-19 Model Incorporating Senses Of Safety And Caution To Local Data From Spartanburg County, South Carolina, D. Chloe Griffin, Amanda Mangum

CODEE Journal

Common mechanistic models include Susceptible-Infected-Removed (SIR) and Susceptible-Exposed-Infected-Removed (SEIR) models. These models in their basic forms have generally failed to capture the nature of the COVID-19 pandemic's multiple waves and do not take into account public policies such as social distancing, mask mandates, and the ``Stay-at-Home'' orders implemented in early 2020. While the Susceptible-Vaccinated-Infected-Recovered-Deceased (SVIRD) model only adds two more compartments to the SIR model, the inclusion of time-dependent parameters allows for the model to better capture the first two waves of the COVID-19 pandemic when surveillance testing was common practice for a large portion of the population. We find …

Human System Composite Performance Measures: General Systems Performance Theory Insights, Lawrence Disalvi

Bioengineering Dissertations - Archive

Composite Performance Measures (CPMs) of human performance are widely employed in applications that range from mundane to life-changing, yet they are frequently presented without explanation or reference to theoretical underpinnings. The conceptual soundness of a widely used CPM approach, based on additive combination of constituent components, has been called into question by Kondraske. He argues the relevance of General Systems Performance Theory (GSPT) and performance capacity envelope concepts when applied to multidimensional CPM measures.

To obtain evidence-based answers to assertions regarding CPM types and rationale employed in medical and non-medical contexts, a Systematic Descriptive Review was conducted. Separately, the GSPT-based …