Computational Engineering Commons^™

Investigating Features And Output Correlation Coefficient Of Natural Fiber-Reinforced Poly(Lactic Acid) Biocomposites, Andreas Federico, Siti Norasmah Surip, Wan Nor Raihan Wan Jaafar, Jaka Fajar Fatriansyah, Agrin Febrian Pradana

Journal of Materials Exploration and Findings

Polylactic acid (PLA) material has the potential to be applied in various industrial fields, but this material has shortcomings in terms of mechanical properties, especially mechanical strength, due to brittleness nature of PLA. The manufacture of PLA composite material with the addition of natural fibers as a reinforcing phase is one of the methods to increase the impact strength and maintain the biodegradable properties of the material. However, in theory, there are many factors that affect the mechanical properties of composite materials, thus making the mechanical properties of composites more complex than monolithic materials. The mechanical properties of these composite …

Quantum-Mechanical Evaluation Of Defects In Uranium-Bearing Materials, Megan Hoover

All Dissertations

Quantum-mechanical calculations using density functional theory with the generalized gradient approximation were employed to investigate the effects dopants have on the uranium dioxide (UO₂) structure. Uraninite is a common U⁴⁺ mineral in the Earth's crust and an important material used to produce energy and medical isotopes. Though the incorporation mechanism remains unclear, divalent cations are known to incorporate into the uranium dioxide system. Three charge-balancing mechanisms were evaluated to achieve a net neutral system, including the substitution of (1) a divalent cation for a tetravalent uranium atom and oxygen atom; (2) two divalent cations for a tetravalent …

Application Of Deep Learning For Medical Sciences And Epidemiology Data Analysis And Diagnostic Modeling, Somenath Chakraborty

Dissertations

Machine Learning and Artificial Intelligence have made significant progress concurrent with new advancements in hardware and software technologies. Deep learning methods heavily utilize parallel computing and Graphical Processing Units(GPU). It is already used in many applications ranging from image classification, object detection, segmentation, cyber security problems and others. Deep Learning is emerging as a viable choice in dealing with today’s real-time medical problems. We need new methods and technologies in the field of Medical Science and Epidemiology for detecting and diagnosing emerging threats from new viruses such as COVID-19. The use of Artificial Intelligence in these domains is becoming more …

Passive Prosthetic Ankle Design Based On Indonesian Anthropometry, Wahyu Dwi Lestari

Journal of Mechanical Engineering Science and Technology (JMEST)

Foot prosthesis is a replacement for the foot to overcome activity limitations due to disease, birth defects, accidents, or amputations. Many foot prosthetics have been developed in recent years to treat patients. However, prostheses on the market today have drawbacks, including their high price, lack of comfort, stiff ankles, and low durability. The main objective of this study is to develop an existing ankle-foot prosthesis design that approximates the resemblance of a human foot according to the anthropometry of Asians, especially Indonesians. This study contains the design of a prosthetic foot with a skin design model and a support core. …

Effect Of Homogenization Pressure On Bacterial Cellulose Membrane Characteristic Made From Pineapple Peel Waste, Muhamad Muhajir, Heru Suryanto, Yanuar Rohmat Aji Pradana, Uun Yanuhar

Journal of Mechanical Engineering Science and Technology (JMEST)

Many studies were conducted to maintain the environment by reducing the waste, especially pineapple peel waste. This study aims to explore the effect of various pressure of the homogenization process on bacterial cellulose membrane surface morphology and structure produced using extract of pineapple peel waste. The methods include the preparation of pellicle samples from the product of the fermentation process of Acetobacter xylinum using a medium from the extract of pineapple peel waste. Bacterial cellulose pellicles were crushed using a blender. Mashed bacterial cellulose pellicle was homogenized in High-Pressure Homogenizer with pressure variation of 150 bar, 300 bar, 450 bar, …

Gasohol Engine Performance With Various Ignition Timing, Hendry Y. Nanlohy, Suyatno Suyatno, Helen Riupassa, Marthina Mini, Trismawati Trismawati, Mebin Panithasan

Journal of Mechanical Engineering Science and Technology (JMEST)

Experimental research has been conducted on the effect of ignition timings on the characteristics and performance of gasohol engines such as power, torque, specific fuel consumption, and thermal efficiency. The fuel used in this research is pure gasoline and a mixture of 50% bioethanol (BE50). The results show that the ignition timing that gives the maximum effect occurs at the top and bottom dead points of 9 degrees for gasoline and 12 degrees for BE50 fuel. Furthermore, the maximum power is obtained at 6,500 rpm, and at an ignition time of 12 degrees BTDC the maximum power generated is 4.63 …

Surface Quality Of Fe, Ni And Cr Added Hyper-Eutectic Al-Si Automotive Alloys Under Up-Milling And Down-Milling Operation, Akib Abdullah Khan, Mashiur Rahman Shoummo, Mohammad Salim Kaiser

Journal of Mechanical Engineering Science and Technology (JMEST)

Effect of the elements Fe, Ni, and Cr on the surface quality under machining of hyper-eutectic aluminiumbased Al-Si automotive alloys has been carried out as the elements improve the properties of this alloy. Machining is done on a horizontal type milling machine using a high-speed steel slab milling cutter in dry condition. Only the cutting speed varies throughout the experiment, while the machining feed and depth of cut remain fixed. The experimental results show that the addition of these alloying elements increases the roughness and hardness specially due to formation of Fe-rich intermetallic ��-����5��������. However, the needle-like ��-����5�������� has been …

Effect Of Variation Of Sic Mass Fraction On Mechanical Properties Of Al-Sic Composite Using Stir Casting Method, Sumarji Sumarji, Naufal Fardio Albajili, Mahros Darsin, Rahma Rei Sakura, Andi Sanata

Journal of Mechanical Engineering Science and Technology (JMEST)

Al-SiC is a composite composed of AA6061 as a matrix and SiC as a reinforcement particle. The variation of mass added will affect the mechanical properties of the composite because Al-SiC is hardenable, which means that its mechanical properties can be improved by adding the reinforcement component. However, an excessive portion of SiC leads to a decrease in mechanical properties. The purpose of this study was to find the optimal composition of the addition of SiC into the aluminium matrix to gain maximum tensile strength and hardness. The mass fraction variation that would be used in this composite was the …

Machine Vision For The Various Road Surface Type Classification Based On Texture Feature, Susi Marianingsih, Widodo Widodo, Marla Sheilamita S. Pieter, Evanita Veronica Manullang, Hendry Y. Nanlohy

Journal of Mechanical Engineering Science and Technology (JMEST)

The mechanized ability to specify the way surface type is a piece of key enlightenment for autonomous transportation machine navigation like wheelchairs and smart cars. In the present work, the extracted features from the object are getting based on structure and surface evidence using Gray Level Co-occurrence Matrix (GLCM). Furthermore, K-Nearest Neighbor (K-NN) Classifier was built to classify the road surface image into three classes, asphalt, gravel, and pavement. A comparison of KNN and Naïve Bayes (NB) was used in present study. We have constructed a road image dataset of 450 samples from real-world road images in the asphalt, gravel, …

Lightweight Privacy-Preserving Spatial Keyword Query Over Encrypted Cloud Data, Yutao Yang, Yinbin Miao, Kim-Kwang Raymond Choo, Robert H. Deng

Research Collection School Of Computing and Information Systems

With the rapid development of geographic location technology and the explosive growth of data, a large amount of spatio-textual data is outsourced to the cloud server to reduce the local high storage and computing burdens, but at the same time causes security issues such as data privacy leakage. Thus, extensive privacy-preserving spatial keyword query schemes have been proposed. Most of the existing schemes use Asymmetric Scalar-Product-Preserving Encryption (ASPE) for encryption, but ASPE has proven to be insecure. And the existing spatial range query schemes require users to provide more information about the query range and generate a large amount of …

Machine Learning, The Mortar Of Modernization, Vishnu Pendyala

Open Educational Resources

Machine Learning is advancing civilization and is one of the key drivers of the economy today. Machine Learning literacy may one day become essential, the way computer literacy is today. This talk intends to explain Machine Learning concepts to wider audiences by using easy-to-relate real-world analogies and serves as a refresher to those already initiated. A fundamental concept in machine learning is similarity. The dot product that is ubiquitously present in machine learning is a measure of similarity. Similarity is key to human learning as well. We learn in delta increments by comparing and contrasting with what we already know. …

Cardio-Net: A Matlab-Based Software For The Display And Diagnostic Utilization Of Vectorcardiograms, Ali H. Mannaa, Domenico Gatti

Medical Student Research Symposium

Background: The 12-lead technique is the standard in ECG, however alternate cardiography modalities such as vectorcardiography (VCG) exist . While the VCG modality offers unique clinical metrics and certain advantages over ECG, it is hardly utilized due to it being more difficult to obtain than ECG. Here we introduce Cardio-Net, a MATLAB-based software that uses standard 12-lead ECG data to generate and visualize VCGs. Furthermore, we demonstrate the diagnostic potential of VCG by utilizing a recurrent neural network (RNN) to accurately classify vectorcardiograms.

Methods: MATLAB version 2019b and the following toolboxes were used for data processing: Deep learning, …

Numerical Investigation Of Sediment Flushing And Morphological Changes In Tamsui River Estuary Through Monsoons And Typhoons, Tung Chou Hsieh, Yan Ding, Keh Chia Yeh, Ren Kai Jhong

Faculty and Student Publications

The removal of reservoir silt and the restoration of existing reservoir capacities through land excavation and hydraulic sediment flushing have become necessary. Hydraulic sediment flushing discharge changes flow and sediment conditions of the downstream river channel. In the Tamsui River estuary in Taiwan, sediment flushing from the Shihmen reservoir upstream has potential impacts on the morphology of the navigation channels and the adjacent coasts. This study employed a validated coastal and estuarine processes model to investigate: (1) the influence of sediment flushing and tidal levels on morphological changes during flood and flushing‐discharge operations of the reservoir, and (2) the differences …

Single-Pass Inline Pipeline 3d Reconstruction Using Depth Camera Array, Zhexiong Shang, Zhigang Shen

Department of Construction Engineering and Management: Faculty Publications

A novel inline inspection (ILI) approach using depth cameras array (DCA) is introduced to create high-fidelity, dense 3D pipeline models. A new camera calibration method is introduced to register the color and the depth information of the cameras into a unified pipe model. By incorporating the calibration outcomes into a robust camera motion estimation approach, dense and complete 3D pipe surface reconstruction is achieved by using only the inline image data collected by a self-powered ILI rover in a single pass through a straight pipeline. The outcomes of the laboratory experiments demonstrate one-millimeter geometrical accuracy and 0.1-pixel photometric accuracy. …

Dynamic Response Of Elastic Two-Story Steel Moment Frame Scaled Structure Equipped With Viscous Dampers, Garrett L. Barker, Alexander L. Poirier

Architectural Engineering

The authors of this report are Architectural Engineering undergraduate students at California Polytechnic State University, San Luis Obispo. Damping is a complex, experimentally derived value that is affected by many structural properties and has a profound effect on the dynamic response of structures. Deducing the inherent damping of a steel moment frame and affecting the damping ratio with viscous dampers are two topics explored in this paper. Dampers are commonly implemented in resilient structures that perform better in a design basis earthquake, reducing the seismic cost and downtime. Undergraduate coursework does not delve into the factors that affect damping and …

Strainer: State Transcript Rating For Informed News Entity Retrieval, Thomas M. Gerrity

Master's Theses

Over the past two decades there has been a rapid decline in public oversight of state and local governments. From 2003 to 2014, the number of journalists assigned to cover the proceedings in state houses has declined by more than 30\%. During the same time period, non-profit projects such as Digital Democracy sought to collect and store legislative bill and hearing information on behalf of the public. More recently, AI4Reporters, an offshoot of Digital Democracy, seeks to actively summarize interesting legislative data.

This thesis presents STRAINER, a parallel project with AI4Reporters, as an active data retrieval and filtering system for …

Evaluating And Improving Domain-Specific Programming Education: A Case Study With Cal Poly Chemistry Courses, Will Fuchs

Master's Theses

Programming is a key skill in many domains outside computer science. When used judiciously, programming can empower people to accomplish what might be impossible or difficult with traditional methods. Unfortunately, students, especially non-CS majors, frequently have trouble while learning to program. This work reports on the challenges and opportunities faced by Physical Chemistry (PChem) students at Cal Poly, SLO as they learn to program in MATLAB. We assessed the PChem students through a multiple-choice concept inventory, as well as through “think-aloud” interviews. Additionally, we examined the students’ perceptions of and attitudes towards programming. We found that PChem students are adept …

Meta-Algorithms In Machine Learning, Vishnu Pendyala

Open Educational Resources

This presentation explores how to make the best of models impacted by bias and variance. Meta-learning minimizes loss. Ensemble methods, including Bagging, Adaboost, Random Forest, Gradient Boosting, and Stacking, are discussed. These methods perturb data (X or Y) using techniques like bootstrap sampling, k-fold sampling, weighted sampling, and random subspaces. Models are generated in parallel or sequentially, with aggregation strategies such as mean, mode, weighted response, and metamodel. The presentation also touches upon deep learning and one-shot learning, and explains how distances become less meaningful in high dimensions.

More details: https://events.vtools.ieee.org/m/315184

Video Recording: https://ieeetv.ieee.org/video/meta-algorithms-in-machine-learning

Semantic Segmentation To Extract Coronary Arteries In Invasive Coronary Angiograms, Chen Zhao, Robert Bober, Haipeng Ang, Jinshan Tang, Minghao Dong, Chaoyang Zhang, Zhuo He, Weihua Zhou, Et. Al.

Michigan Tech Publications, Part 1

Accurate semantic segmentation of each coronary artery using invasive coronary angiography (ICA) is important for stenosis assessment and coronary artery disease (CAD) diagnosis. In this paper, we propose a multi-step semantic segmentation algorithm based on analyzing arterial segments extracted from ICAs. The proposed algorithm firstly extracts the entire arterial binary mask (binary vascular tree) using a deep learning-based method. Then we extract the centerline of the binary vascular tree and separate it into different arterial segments. Finally, by extracting the underlying arterial topology, position, and pixel features, we construct a powerful coronary artery segment classifier based on a support vector …

Implementation Of A Least Squares Method To A Navier-Stokes Solver, Jada P. Lytch, Taylor Boatwright, Ja'nya Breeden

Rose-Hulman Undergraduate Mathematics Journal

The Navier-Stokes equations are used to model fluid flow. Examples include fluid structure interactions in the heart, climate and weather modeling, and flow simulations in computer gaming and entertainment. The equations date back to the 1800s, but research and development of numerical approximation algorithms continues to be an active area. To numerically solve the Navier-Stokes equations we implement a least squares finite element algorithm based on work by Roland Glowinski and colleagues. We use the deal.II academic library , the C++ language, and the Linux operating system to implement the solver. We investigate convergence rates and apply the least squares …

A Novel Method For Sensitivity Analysis Of Time-Averaged Chaotic System Solutions, Christian A. Spencer-Coker

Theses and Dissertations

The direct and adjoint methods are to linearize the time-averaged solution of bounded dynamical systems about one or more design parameters. Hence, such methods are one way to obtain the gradient necessary in locally optimizing a dynamical system’s time-averaged behavior over those design parameters. However, when analyzing nonlinear systems whose solutions exhibit chaos, standard direct and adjoint sensitivity methods yield meaningless results due to time-local instability of the system. The present work proposes a new method of solving the direct and adjoint linear systems in time, then tests that method’s ability to solve instances of the Lorenz system that exhibit …

Finite-Difference-Time-Domain Simulation Of Ultrafast Experiments, Alpha Ma

Macalester Journal of Physics and Astronomy

The Finite-Difference-Time-Domain (FDTD) method is a numerical method that calculates electric fields or magnetic fields by interleaving them in space and time. Using a python package called “MEEP”, I was able to write optical simulations of ultrafast experiments, especially the Terahertz Pump-Probe experiments. The goal of this project was to use FDTD simulation to measure the transmission of an electro-magnetic pulse passing through a thin film of conducting material on a dielectric substrate in order to study the characteristic conductivity of potential solar cell materials.

Numerical Analysis Of Taylor Impact With Various Nose Shapes, Jean C. Santiago Padilla, Erik M. Chappell

ME 4233/6233 Fundamentals of FEA

The Taylor impact test is an experimental technique used to determine dynamic material response and to validate constitutive models used in numerical simulations. It generally consists of shooting a cylinder rod of a select material against a rigid target at different velocities. After impact, the plastic deformation of the cylinder is recorded and is directly compared to numerical predictions. Another application for Taylor impact was proposed by Li et al. (2021) where the nose shape of the cylinder is modified to create different loading environments that can test electronic equipment in penetration weapons. FEA models where designed in ABAQUS/Explicit to …

Human-Centered Explainable Artificial Intelligence For Anomaly Detection In Quality Inspection: A Collaborative Approach To Bridge The Gap Between Humans And Ai, Srikanth Vemula

Theses & Dissertations

In the quality inspection industry, the use of Artificial Intelligence (AI) continues to advance to produce safer and faster autonomous systems that can perceive, learn, decide, and act independently. As observed by the researcher interacting with the local energy company over a one-year period, these AI systems’ performance is limited by the machine’s current inability to explain its decisions and actions to human users. Especially in energy companies, eXplainable-AI (XAI) is critical to achieve speed, reliability, and trustworthiness with human inspection workers. Placing humans alongside AI will establish a sense of trust that augments the individual’s capabilities at the workplace. …

Using Bluetooth Low Energy And E-Ink Displays For Inventory Tracking, David Whelan

Computer Science and Computer Engineering Undergraduate Honors Theses

The combination of Bluetooth Low energy and E-Ink displays allow for a low energy wire-less display. The application of this technology is far reaching especially given how the Bluetooth Low Energy specification can be extended. This paper proposes an extension to this specification specifically for inventory tracking. This extension combined with the low energy E-Ink display results in a smart label that can keep track of additional meta data and inventory counts for physical inventory. This label helps track the physical inventory and can help mitigate any errors in the logical organization of inventory.

Speaker Diarization And Identification From Single-Channel Classroom Audio Recording Using Virtual Microphones, Antonio Gomez

Electrical and Computer Engineering ETDs

Speaker identification in noisy audio recordings, specifically those from collaborative learning environments, can be extremely challenging. There is a need to identify individual students talking in small groups from other students talking at the same time. To solve the problem, we assume the use of a single microphone per student group without any access to previous large datasets for training.

This dissertation proposes a method of speaker identification using cross-correlation patterns associated to an array of virtual microphones, centered around the physical microphone. The virtual microphones are simulated by using approximate speaker geometry observed from a video recording. The patterns …

Strain-Based Design Of Steel-Polymer-Steel Composite Pipes, Vul Thang

LSU New Orleans Theses and Dissertations

Many offshore single-wall pipelines and structural failures have occurred in the past. As a result, lives were lost, and billions of dollars were spent. In addition, natural disasters such as earthquake fault zones can cause a large volume of soil movement. This can easily damage single-wall pipelines or piles of fixed offshore platforms in the earthquake fault zone.

Currently, the single-wall pipelines are used for the offshore and onshore oil and gas industry. This research investigated the use of double-wall composite pipe steel-polymer-steel (SPS) in place of single-wall pipe to prevent such failures. The double-wall composite pipe has a larger …

Characterization Of Friction Element Welding Using Finite Element Modeling, Ankit Varma

All Dissertations

Friction element welding (FEW) has been advocated as a solution to weld different materials together, with the ability to join high-strength materials for a range of thicknesses with low input energy and a short processing time. This work develops a coupled thermal-mechanical finite element model to better understand the physical mechanisms involved in the process and to predict temperature and material flow during the process. Furthermore, microstructural analysis is performed for the steel layer using a scanning electron microscope and Vickers microhardness tester to understand the variation in its grain structure and hardness. Results from the finite element model and …

Computational Study Of Dense Gas Dispersion In Urban Areas, Rasna Sharmin

All Dissertations

A series of steady-state simulations have been conducted to investigate removal of dense gas from a simple square canyon formed between two square cross-section obstacles. Due to urbanization and industrialization, there always lies a high risk of exposure to harmful pollutants which can result from accidental release of toxic gasses. Those are often denser than the atmosphere. and can easily get trapped in between buildings in urban canopies. It is important to have full understanding of flushing mechanism of dense fluid inside urban canopies by steady turbulent flow because the exposure to these toxic dense gasses can be catastrophic. There …

Tell It Slant: Investigating The Engagement, Discourse, And Popularity Of Data Visualization In Online Communities, Emma Baker

McKelvey School of Engineering Graduate Student Theses & Dissertations

Data visualizations are increasingly accessible to people online, often to non-specialized audiences. However, what we know about how people make sense of data and engage with the visualized content is typically limited to observations from controlled user studies, sometimes with highly-specialized participants. As a result, there is a limited vocabulary to describe how visualizations as a technique of information sharing permeate organic communities. This thesis investigates how data visualization systems infiltrate online social settings and characterizes the conditions under which users engage or do not engage with them. We captured conversations on Reddit from March 2, 2021 to December 31, …