Computational Engineering Commons^™

A Cellular Automation Which Incorporates Finite Element Method And Meshless Algorithm, Yong Cai, Zeyun Chen, Weifeng Yuan

The 8th International Conference on Physical and Numerical Simulation of Materials Processing

No abstract provided.

Numerical Modeling And Seismic Assessment Of Smart Isolation System For High-Speed Railway Rc Bridge Subjected To Near-Field Ground Motions, Lingkun Chen

The 8th International Conference on Physical and Numerical Simulation of Materials Processing

No abstract provided.

Application Of Numerical Simulation During The Development Of Ductile Iron Bearing Seat, Ping Li, Yanjie Zhao, Junquan Wei, Jitai Niu, Fengju Li

The 8th International Conference on Physical and Numerical Simulation of Materials Processing

No abstract provided.

Mhd Modeling Of A Copper Slag Cleaning Process, Hongkun Yang, Jörg Wolters, Helmut Soltner, Phillip Pischke, Sven Eckert, Jochen Fröhlich

The 8th International Conference on Physical and Numerical Simulation of Materials Processing

No abstract provided.

Assisting Children Action Association Through Visual Queues And Wearable Technology, Anthony Young

Computational and Data Sciences Theses

Autism Spectrum Disorder makes it difficult to for a child communicate, have social interactions and go through daily life. Visual cues are often used to help a child associate an image with an event. With technology becoming more and more advanced, we now have a way to remind a child of an event with wearable technology, such as a watch. This new technology can help a child directly with the Visual Scheduling Application and various other applications. These applications allow children and their families to be easily able to keep track of the events on their schedule and notify them …

Simulation Of The Influence Of Preheating On Stress Distribution During Multi-Pass Repair Welding Of Cast Steel, Wen Wang, Jian-Xin Zhou, Ya-Jun Yin

The 8th International Conference on Physical and Numerical Simulation of Materials Processing

No abstract provided.

Dynamic Secondary Cooling Control With Incremental Pid Algorithm In Continuous Bloom Casting, Jian Cheng, Zhiwei Han, Qiang Liu, Houfa Shen

The 8th International Conference on Physical and Numerical Simulation of Materials Processing

No abstract provided.

Assessment Of High Cycle Fatigue Crack Growth Under Different Stages Based On Crystal Plasticity Modeling, Duoqi Shi, Shiwei Han, Xiaoguang Yang

The 8th International Conference on Physical and Numerical Simulation of Materials Processing

No abstract provided.

Mpfem Simulation On 2d Compaction Of Core–Shell Particulate Composites, Yu Liu, Fen Huang, Peng Han, Xizhong An, Haitao Fu

The 8th International Conference on Physical and Numerical Simulation of Materials Processing

No abstract provided.

Laff-O-Tron: Laugh Prediction In Ted Talks, Andrew D. Acosta

Master's Theses

Did you hear where the thesis found its ancestors? They were in the "parent-thesis"! This joke, whether you laughed at it or not, contains a fascinating and mysterious quality: humor. Humor is something so incredibly human that if you squint, the two words can even look the same. As such, humor is not often considered something that computers can understand. But, that doesn't mean we won't try to teach it to them.

In this thesis, we propose the system Laff-O-Tron to attempt to predict when the audience of a public speech would laugh by looking only at the text of …

Modelling Of Coal-Biomass Blends Gasification And Power Plant Revamp Alternatives In Egypt’S Natural Gas Sector, Dalia A. Ali Eng, Mamdouh A. Gadalla Prof., Omar Y. Abdelaziz, Fatma H. Ashour Prof.

Chemical Engineering

Recently, there has been a growing research interest in the co-gasification of biomass with coal to produce syngas and electricity in a sustainable manner. Co-gasification technology do not only decrease potentially the exploitation of a significant amount of conventional coal resources, and thus lower greenhouse gases (GHG) emissions, but also boost the overall gasification process efficiency. In the present work, a rigorous simulation model of an entrained flow gasifier is developed using the Aspen Plus® software environment. The proposed simulation model is tested for an American coal and the model validation is performed in good agreement with practical data. The …

Gpu-Arraysort: A Parallel, In-Place Algorithm For Sorting Large Number Of Arrays, Muaaz Awan, Fahad Saeed

Parallel Computing and Data Science Lab Technical Reports

Modern day analytics deals with big datasets from diverse fields. For many application the data is in the form of an array which consists of large number of smaller arrays. Existing techniques focus on sorting a single large array and cannot be used for sorting large number of smaller arrays in an efficient manner. Currently no such algorithm is available which can sort such large number of arrays utilizing the massively parallel architecture of GPU devices. In this paper we present a highly scalable parallel algorithm, called GPU-ArraySort, for sorting large number of arrays using a GPU. Our algorithm performs …

Multi-Objective Optimization Under Uncertainty Using The Hyper-Volume Expected Improvement, Martin Figura, Piyush Pandita, Rohit K. Tripathy, Ilias Bilionis

The Summer Undergraduate Research Fellowship (SURF) Symposium

The design of real engineering systems requires the optimization of multiple quantities of interest. In the electric motor design, one wants to maximize the average torque and minimize the torque variation. A study has shown that these attributes vary for different geometries of the rotor teeth. However, simulations of a large number of designs cannot be performed due to their high cost. In many problems, design optimization of multi-objective functions is a very challenging task due to the difficulty to evaluate the expectation of the objectives. Current multi-objective optimization (MOO) techniques, e.g., evolutionary algorithms cannot solve such problems because they …

Design Optimization Of A Stochastic Multi-Objective Problem: Gaussian Process Regressions For Objective Surrogates, Juan Sebastian Martinez, Piyush Pandita, Rohit K. Tripathy, Ilias Bilionis

The Summer Undergraduate Research Fellowship (SURF) Symposium

Multi-objective optimization (MOO) problems arise frequently in science and engineering situations. In an optimization problem, we want to find the set of input parameters that generate the set of optimal outputs, mathematically known as the Pareto frontier (PF). Solving the MOO problem is a challenge since expensive experiments can be performed only a constrained number of times and there is a limited set of data to work with, e.g. a roll-to-roll microwave plasma chemical vapor deposition (MPCVD) reactor for manufacturing high quality graphene. State-of-the-art techniques, e.g. evolutionary algorithms; particle swarm optimization, require a large amount of observations and do not …

Solution Of Fully-Coupled Shallow Water Equations And Contaminant Transport Using A Primitive Variable Riemann Solver And A Semi-Discrete Supg Method, Faranak Behzadi

Masters Theses and Doctoral Dissertations

In the present dissertation, a finite volume and a finite element model are developed and tuned for the solution of the fully-coupled two-dimensional Shallow Water and Contaminant transport Equations with arbitrary bed topography and wetting-drying fronts. A Riemann-solver finite volume scheme, using primitive variables rather than conserved variables, and a semi-discrete Streamline Upwind Petrov-Galerkin (SUPG) method in finite element context are applied to compare the performance of these two numerical models. The Riemann-solver scheme is based on the unstructured finite volume discretization using primitive-variable Roe-flux approximation with an entropy fix. Second-order accuracy in space and time, an implicit scheme based …

Least Squares Spectral Element Method For Laminar And Turbulent Flows, –Continuous And Discontinuous Approaches–, Jaber Javanshir Hasbestan

Masters Theses and Doctoral Dissertations

In this research, application of a least squares spectral element method for compressible laminar and turbulent flow problems is investigated. For the turbulent Reynolds Averaged Navier-Stokes (RANS), a modified Spalart-Allmaras (SA) turbulence model is employed and integrated with the mean flow equations in a segregated fashion. Two different approaches are presented for solving the SA model using the least squares method. The first method represents a simple rearrangement of the equation. However, proper arrangement of the SAmodel is required in order to produce a stable scheme for the least squares methodology. The second approach is into divide the SA equation …

Recognition Of Smoking Gesture Using Smart Watch Technology, Casey A. Cole, Bethany Janos, Dien Anshari, James Thrasher, Scott Strayer, Homayoun Valafar

Faculty Publications

Diseases resulting from prolonged smoking are the most common preventable causes of death in the world today. In this report we investigate the success of utilizing accelerometer sensors in smart watches to identify smoking gestures. Early identification of smoking gestures can help to initiate the appropriate intervention method and prevent relapses in smoking. Our experiments indicate 85%-95% success rates in identification of smoking gesture among other similar gestures using Artificial Neural Networks (ANNs). Our investigations concluded that information obtained from the x-dimension of accelerometers is the best means of identifying the smoking gesture, while y and z dimensions are helpful …

Energy Consumption Prediction With Big Data: Balancing Prediction Accuracy And Computational Resources, Katarina Grolinger, Miriam Am Capretz, Luke Seewald

Electrical and Computer Engineering Publications

In recent years, advances in sensor technologies and expansion of smart meters have resulted in massive growth of energy data sets. These Big Data have created new opportunities for energy prediction, but at the same time, they impose new challenges for traditional technologies. On the other hand, new approaches for handling and processing these Big Data have emerged, such as MapReduce, Spark, Storm, and Oxdata H2O. This paper explores how findings from machine learning with Big Data can benefit energy consumption prediction. An approach based on local learning with support vector regression (SVR) is presented. Although local learning itself is …

Quantum Computers Are Coming And Will Be Able To Solve Complex Aviation And Aerospace Problems, Nihad E. Daidzic

Aviation Department Publications

No abstract provided.

Automatic Generation And Grading Of Programming Exercises, Andrew Dufrene

Computer Science and Software Engineering

In our current age of technological advances, and rising education costs, it is becoming increasingly beneficial to use technology to aid in education, usually through automated lectures or grading. One missing feature from this automated education is complex grading and problem generation. The main objective of this project is to create a program that can automatically generate and grade problems of varying difficulties based on the topic of programming for loops. The project solution was created as a program designed for use in Dr. Clinton Staley’s Intelligent Homework System, which is used precisely for automated exercise grading and generation. Ultimately, …