Computational Engineering Commons^™

Towards Digital Twins For Optimizing Metrics In Distributed Storage Systems - A Review, May Itani, Layal Abu Daher, Ahmad Hammoud

BAU Journal - Science and Technology

With the exponential data growth, there is a crucial need for highly available, scalable, reliable, and cost-effective Distributed Storage Systems (DSSs). To ensure such efficient and fault tolerant systems, replication and erasure coding techniques are typically used in traditional DSSs. However, these systems are prone to failure and require different failure prevention and recovery algorithms. Failure recovery of DSS and data reconstruction techniques take into consideration different performance metrics optimization in the recovery process. In this paper, DSS performance metrics are introduced. Several recent papers related to adopting erasure coding in DSSs are surveyed together with highlighting related performance metrics …

Smart System For Wheat Diseases Early Detection, Rustam Baratov, Himola Sunnatillayeva, Almardon Mamatovich Mustafoqulov

Chemical Technology, Control and Management

This paper presents a smart system for early detection of wheat plant diseases in the vegetation period. The proposed smart system allows detecting three types of wheat diseases, particularly yellow rust, powdery mildew and septoria at early stage and significantly improves the soil and ecology by locally spraying harmful chemicals just to sickness plants. The proposed diagnostic program is created in the C++ programming language. The basic structure of the smart system consists of Raspberry PI 4 MODULE, Logitech HD Pro Webcam C920, buzzer, HC-SR04 distance sensor, DC motor driver, AC motor, power supply, relay and some digital devices.

Combined Risk Based Inspection And Fault Tree Analysis For Repetitive 3-Phase Line Piping Leakage At West Java Offshore Topside Facility, Dona Yuliati, Akhmad Herman Yuwono, Datu Rizal Asral, Donanta Dhaneswara

Journal of Materials Exploration and Findings (JMEF)

Hydrocarbon releases might result in serious consequences in various aspects. In addition to the contribution to environmental pollution, repetitive leakages need high repair costs. This study aim is to minimize potential repetitive leakage for other typical 3-phase piping systems. We conducted the risk assessment by adopting Risk Based Inspection (RBI) API 581 to identify risk level, calculating piping lifetime, recommended inspection plan and mitigations. The most relevant root causes can be obtained through quantitative Fault Tree Analysis (FTA). Observation and investigation was taken from eight 3-phase piping systems that experienced repetitive leakages. It has been found that the risk level …

Nitrogen Gas Quenching Pressure Effect On Bs S155 Alloy Steel In Vacuum Furnace, Agus Mulyadi Hasanudin, Eddy Sumarno Siradj

Journal of Materials Exploration and Findings (JMEF)

The production of metal and alloy products requires the use of heat treatment, when during the heat treatment process, quenching is a crucial step. The quenching medium can be anything from water, a salt bath, oil, air and gas. In a vacuum furnace, pressurized gas, most frequently nitrogen (N₂) gas, serves as one of the quenching mediums. One of the drawbacks of the quenching process is the distortion and dimensional change of the parts. This paper aims to investigate the influence of nitrogen gas quenching pressure on the distortion and dimensional change of aerospace actuator gear planet parts …

Pipeline Risk Analysis Optimization With Monte Carlo Method Using Gamma Distribution, Farhan Rama Digita, Jaka Fajar Fatriansyah, Abdul Rahim Ridzuan, Hanna Ovelia, Imam Abdillah Mas'ud, Irma Hartia Tihara, Baiq Diffa Pakarti Linuwih

Journal of Materials Exploration and Findings (JMEF)

The inspection process of piping components in the oil and gas industry is one of the most crucial things, given the high risk posed by pipeline system failures, which have a huge impact on losses, both from environmental and financial aspects. Risk-based inspection with the Monte Carlo method is one of the efforts that can be made to minimize failures in piping systems, by involving data distribution to calculate the probability of component failure. Although the normal distribution is commonly used for generating random variables, its use in corrosion rate calculation can lead to overestimation due to negative corrosion rate …

Early-Age Strength And Failure Characteristics Of 3d Printable Polymer Concrete: Numerical Modelling And Experimental Testing, Mohammad Amin Dehghani Najvani

Civil Engineering ETDs

The time-dependent rheological and early-age strength parameters of Polymer concrete (PC) were investigated. PC flow decreased, and the static yield stress and thixotropy increased as the specimen aged, while the dynamic yield stress remained unchanged. The study found that the Herschel-Bulkley model can accurately describe the PC’s rheological behavior over time. The change in cohesion strength and internal friction angle over time was observed using uniaxial unconfined compression and direct shear tests of fresh PC. A time-dependent MohrCoulomb failure criterion was established. Temperature analysis was used to determine the gel time and explain the evolution of the time-dependent early-age strength …

Numerical Investigation Of Subglottal Stenosis Effects On Human Voice Production, Dariush Bodaghi

Electronic Theses and Dissertations

This dissertation aimed to advance knowledge of how subglottal stenosis impacts voice production physiology. An in-house fluid-structure-acoustic interaction approach based on the hydrodynamic/acoustic splitting technique was employed. This technique was rigorously verified for simulating phonation by matching the acoustic behavior to a compressible flow solver for phonation-relevant geometries. Simulations of an idealized 2D vocal tract model demonstrated the effects of supraglottal acoustic resonance on vocal fold kinematics and glottal flow waveform. Results showed that the acoustic coupling between higher harmonics and formats generated pressure oscillations, modifying vocal fold dynamics and glottal flow rate.

A major novelty was the incorporation and …

An Investigation Into Applications Of Canonical Polyadic Decomposition & Ensemble Learning In Forecasting Thermal Data Streams In Direct Laser Deposition Processes, Jonathan Storey

Theses and Dissertations

Additive manufacturing (AM) is a process of creating objects from 3D model data by adding layers of material. AM technologies present several advantages compared to traditional manufacturing technologies, such as producing less material waste and being capable of producing parts with greater geometric complexity. However, deficiencies in the printing process due to high process uncertainty can affect the microstructural properties of a fabricated part leading to defects. In metal AM, previous studies have linked defects in parts with melt pool temperature fluctuations, with the size of the melt pool and the scan pattern being key factors associated with part defects. …

Convolution And Autoencoders Applied To Nonlinear Differential Equations, Noah Borquaye

Electronic Theses and Dissertations

Autoencoders, a type of artificial neural network, have gained recognition by researchers in various fields, especially machine learning due to their vast applications in data representations from inputs. Recently researchers have explored the possibility to extend the application of autoencoders to solve nonlinear differential equations. Algorithms and methods employed in an autoencoder framework include sparse identification of nonlinear dynamics (SINDy), dynamic mode decomposition (DMD), Koopman operator theory and singular value decomposition (SVD). These approaches use matrix multiplication to represent linear transformation. However, machine learning algorithms often use convolution to represent linear transformations. In our work, we modify these approaches to …

Automated Usability Evaluation Utilizing Log Files And Data Mining Techniques., Sima Shafaei

Electronic Theses and Dissertations

Usability evaluation is one of the essential aspects of software production. This evaluation should be done during the entire life cycle of a software application, from pre-production to production and post-production. However, the collection and evaluation of usability data can be a very challenging, time-consuming, and expensive task to be conducted manually, particularly for certain types of products and working conditions. These challenges may include the need to recruit participants fully engage and motivate them during evaluation, and factor in environmental conditions. Other challenges may include collecting data in real-world environments, especially when the users are geographically dispersed, minimizing evaluator …

Machine Learning For Kalman Filter Tuning Prediction In Gps/Ins Trajectory Estimation, Peter Wright

Electronic Theses, Projects, and Dissertations

This project is an exploration and implementation of an application using Machine Learning (ML) and Artificial Intelligence (AI) techniques which would be capable of automatically tuning Kalman-Filter parameters used in post-flight trajectory estimation software at Edwards Air Force Base (EAFB), CA. The scope of the work in this paper is to design and develop a skeleton application with modular design, where various AI/ML modules could be developed to plug-in to the application for tuning-switch prediction.

Steady And Transient Study Of Conjugate Heat Transfer In Regenerative Cooled Nozzle, Khaled Bensayah, Khadidja Kamri

Emirates Journal for Engineering Research

The Heat transfer is one of the most serious challenges that exist in a supersonic nozzle flow. The combustion chamber wall and the nozzle are exposed to high-temperature gases during combustion and gas expansion, which can eventually lead to structural failure. This paper reports a computational study of steady and transient conjugate heat transfer in regenerative water cooled nozzle. Numerical computation solved Reynolds-averaged equations based on RSM-Omega turbulence model coupling with solid-phase heat conduction equation and with coolant-phase. The effect of four inlet cooled approach length 0 inch, 6 inch, 12 inch and 18 inch are studied and validated against …

Multicellular And Multiscale Models Of Microbes And Host Systems, Elebeoba May

Annual Symposium on Biomathematics and Ecology Education and Research

No abstract provided.

Digital Twins Of The Living Knee: From Measurements To Model, Thor Erik Andreassen

Electronic Theses and Dissertations

Modern medicine has dramatically improved the lives of many. In orthopaedics, robotic surgery has given clinicians superior accuracy when performing interventions over conventional methods. Nevertheless, while these and many other methods are available to ensure treatments are performed successfully, far fewer methods exist to predict the proper treatment option for a given person. Clinicians are forced to categorize individuals, choosing the best treatment on “average.” However, many individuals differ significantly from the “average” person, for which many of these treatments are designed. Going forward, a method of testing, evaluating, and predicting different treatment options' short- and long-term effects on an …

I-Guide Climbers: A Model For Multidisciplinary Academic Labs For Early Career Development, Iman Haqiqi, Wei Hu, Ramya Kumaran, Pin-Ching Li, Nicholas Manning, Alex Michels, Ayman Nassar, Jinwoo Park, Jimeng Shi, Adam Tonks, Zhaonan Wang

I-GUIDE Forum

In this paper, we propose a new form of multidisciplinary academic collaboration that goes beyond the traditional modes of knowledge exchange. We argue that most research collaboration today is based on interactions between closely related disciplines, in which researchers share data, methods, and insights within a common framework or problem. However, such collaboration may not foster the development of the communication and management skills essential to a multi-disciplinary research career. Therefore, we suggest establishing a network of researchers from divergent, yet complementary, disciplines who are interested in improving these skills through regular interactions and feedback. The main goal of this …

Deep Semantic Hashing For Aerial Livestock Detection, Shosei Anegawa, Franz Kurfess, Sumona Mukhopadhyay

College of Engineering Summer Undergraduate Research Program

The goal of this project is to be able to accurately detect and count livestock in footage captured by a drone in real time. The main problems with this arise from the fact that a drone can only carry limited computing resources, and hashing is conventionally thought of as a great method of doing image classification very quickly and thus even on low-power devices. In this project, we use both a Faster-RCNN, which is a state-of-the art object detection model as a benchmark to develop a hashing model that can perform a similar task much more quickly. These two models …

Predictive Maintenance Of Base Transceiver Station Power System Using Xgboost Algorithm: A Case Study Of Econet Wireless, Zimbabwe, Tavengwa Masamha

African Conference on Information Systems and Technology

Faults incurred by Base Transceiver Stations pose challenges to telecommunication organisations. Mostly the faults are due to BTS failures. BTS power system failures can have a significant impact on organizational performance in the telecommunications industry. These failures can cause disruptions in mobile network coverage, leading to dropped calls, slow data speeds, and difficulty connecting to the network. ECONET Zimbabwe has been experiencing unprecedented BTS power system failures for the past five years. Team Data Science Process was the pillar of the study methodology. The XGBoost algorithm was employed to develop a predictive model for the maintenance of Base Transceiver Station …

Automatic Cardiac Mri Image Segmentation And Mesh Generation, Ziyuan Li

McKelvey School of Engineering Theses & Dissertations

Segmenting and reconstructing cardiac anatomical structures from magnetic resonance (MR) images is essential for the quantitative measurement and automatic diagnosis of cardiovascular diseases [1]. However, manual evaluation of the time-series cardiac MRI (CMRI) obtained during routine clinical care are laborious, inefficient, and tends to produce biased and non-reproducible results [2]. This thesis proposes an end-to-end pipeline for automatically segmenting short-axis (SAX) CMRI images and generating high-quality 2D and 3D meshes suitable for finite element analysis. The main advantage of our approach is that it can not only work as a stand-alone pipeline for the automatic CMR image segmentation and mesh …

Permeability Prediction For Expansive Soil Based On Physical Properties Using Artificial Neural Networks, Ferry Fatnanta, Imam Suprayogi, Nicola Rabb Ranata, Soewignjo Agus Nugroho, Agus Ika Putra

Makara Journal of Technology

Permeability is a soil parameter related to the construction industry to understand the processes of infiltration, runoff, and settlement. The risk of testing errors is inevitable in permeability investigations, especially in expansive soils. Trial and error in permeability testing becomes difficult due to soils with small pore sizes and large shrinkage expansion. Several studies related to soil physical properties that affect permeability have been conducted. However, the correlation results obtained still have poor accuracy. Artificial neural networks (ANN) are machine learning systems that can change their structure to solve problems that are included in the system. The use of ANNs …

Using Dynamic Task Allocation To Evaluate Driving Performance, Situation Awareness, And Cognitive Load At Different Levels Of Partial Autonomy, Viraj R. Patel

Theses and Dissertations

The state of the art of autonomous vehicles requires operators to remain vigilant while performing secondary tasks. The goal of this research was to investigate how dynamically allocated secondary tasks affected driving performance, cognitive load, and situation awareness. Secondary tasks were presented at rates based on the autonomy level present and whether the autonomous system was engaged. A rapid secondary task rate was also presented for two short periods regardless of whether autonomy was engaged. There was a three-minute familiarization phase followed by a data collection phase where participants responded to secondary tasks while preventing the vehicle from colliding into …

Singular Integration By Interpolation For Integral Equations, Ioannis Kyriakou

Doctoral Dissertations

Maxwell’s equations and the laws of Electromagnetics (EM) govern a plethora of electrical, optical phenomena with applications on wireless, cellular, communications, medical and computer hardware technologies to name a few. A major contributor to the technological progress in these areas has been due to the development of simulation and design tools that enable engineers and scientists to model, analyze and predict the EM interactions in their systems of interest. At the core of such tools is the field of Computational Electromagnetics (CEM), which studies the solution of Maxwell’s equations with the aid of computers. The advances in these applications technologies, …

Visualizing Transaction-Level Modeling Simulations Of Deep Neural Networks, Nataniel Farzan, Emad Arasteh

Engineering Technical Reports

The growing complexity of data-intensive software demands constant innovation in computer hardware design. Performance is a critical factor in rapidly evolving applications such as artificial intelligence (AI). Transaction-level modeling (TLM) is a valuable technique used to represent hardware and software behavior in a simulated environment. However, extracting actionable insights from TLM simulations is not a trivial task. We present Netmemvisual, an interactive, cross-platform visualization tool for exposing memory bottlenecks in TLM simulations. We demonstrate how Netmemvisual helps system designers rapidly analyze complex TLM simulations to find memory contention. We describe the project’s current features, experimental results with two state-of-the-art deep …

Evaluation Of Static Horizontal Louvers On Annual Daylighting Performance In Classrooms, Kamal A. Saleem, Samir S. Hosny, Ashraf Nessim

Future Engineering Journal

Daylighting has a great impact on students’ health, learning performance, and productivity. The goal of this paper is to enhance daylighting performance by examining year-round daylighting performance of Southern facades in the case of one central window in a classroom located in Cairo, Egypt by using static external horizontal shading devices during the Fall, Spring and Summer semesters The scope of the study is to evaluate and assess the effect of the window-to-wall ratio (WWR) in addition to the louvers’ configurations of depth and count parameters of the classroom on annual daylighting performance metrics for classrooms’ southern facades by using …

One Formula For Non-Prime Numbers: Motivations And Characteristics, Kamal Hassan Prof., Mahmoud Mansour

Basic Science Engineering

Abstract: Primes are essential for computer encryption and cryptography, as they are fundamental units of whole numbers and are of the highest importance due to their mathematical qualities. However, identifying a pattern of primes is not easy. Thinking in a different way may get benefits, by considering the opposite side of the problem which means focusing on non-prime numbers. Recently, researchers introduced, the pattern of non-primes in two maximal sets while in this paper, non-primes are presented in one formula. Getting one-way formula for non-primes may pave the way for further applications based on the idea of primes.

Who Is (Communicatively More) Responsible Behind The Wheel? Applying The Theory Of Communicative Responsibility To Tam In The Context Of Using Navigation Technology, Sungbin Youk, Hee Sun Park

Human-Machine Communication

By examining how perceived usefulness and ease of use relate to the user’s perception (i.e., communicative responsibility), the communicative behavior of the navigation system (i.e., the landmarks used to give directions), and the context of driving (i.e., familiarity of the driving location), this study applies the theory of communicative responsibility to the technology acceptance model to better understand why users are more likely to adopt certain navigation technologies while driving. We hypothesized that users’ perceived symmetry in communicative responsibility independently and interactively (with communicative behavior of the navigation system and the driving situation) affects perceived ease of use and usefulness …

Human-Machine Communication: Complete Volume. Volume 6

Human-Machine Communication

This is the complete volume of HMC Volume 6.

Resilience Model For Teams Of Autonomous Unmanned Aerial Vehicles (Uav) Executing Surveillance Missions, Robert Koeneke

Doctoral Dissertations and Master's Theses

Teams of low-cost Unmanned Aerial Vehicles (UAVs) have gained acceptance as an alternative for cooperatively searching and surveilling terrains. These UAVs are assembled with low-reliability components, so unit failures are possible. Losing UAVs to failures decreases the team's coverage efficiency and impacts communication, given that UAVs are also communication nodes. Such is the case of a Flying Ad Hoc Network (FANET), where the failure of a communication node may isolate segments of the network covering several nodes. The main goal of this study is to develop a resilience model that would allow us to analyze the effects of individual UAV …

Deep Cnn-Based Automated Optical Inspection For Aerospace Components, Shashi Bhushan Jha

Doctoral Dissertations and Master's Theses

ABSTRACT

The defect detection problem is of outmost importance in high-tech industries such as aerospace manufacturing and is widely employed using automated industrial quality control systems. In the aerospace manufacturing industry, composite materials are extensively applied as structural components in civilian and military aircraft. To ensure the quality of the product and high reliability, manual inspection and traditional automatic optical inspection have been employed to identify the defects throughout production and maintenance. These inspection techniques have several limitations such as tedious, time- consuming, inconsistent, subjective, labor intensive, expensive, etc. To make the operation effective and efficient, modern automated optical inspection …

Neurocomputing And Interfacing Digital Tasting System: Research, Design, And Evaluation, Amira J. Zaylaa, Ahmad El Hajj

BAU Journal - Science and Technology

The continuous evolution in computing and interfacing has been extended to develop multi-sensory experiences in many domains such as neurological, auditory, vision, and haptic domains. So far, only a few remarkable system approaches have been approved to be serving the taste sensation digitally. Although taste sensation is linked to the brain, there is a lack of optimal neurocomputing digital taste sensation systems. Our study provides a new neurocomputing method to digitally stimulate the sense of taste by electrical stimulation on the human tongue. We aim to link chemical stimulation and electrical stimulation in order to design an electronic interface for …

Resources Based Planning Framework For Infrastructure Maintenance And Rehabilitation Projects, Heba Gad

Theses and Dissertations

Infrastructure maintenance and rehabilitation projects involve activities scattered over a large geographical area (e.g., scattered road segments maintenance, telecom towers maintenance program, etc.). Planning such projects require a resource-based approach that accounts for the implications of resource mobility between activities’ locations in terms of time & cost. Existing scheduling techniques fall short of addressing the unique challenges of the scattered nature of these projects in combination with organization's limited resources availability. To address this need, this research presents a resources-based planning framework for infrastructure maintenance and rehabilitation scattered projects with the objective of enhancing resources utilization achieving time and cost …