Engineering Commons^™

Modeling Of Gas Production From Shale Reservoirs Considering Multiple Transport Mechanisms, Chaohua Guo, Mingzhen Wei, Hong Liu

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Gas transport in unconventional shale strata is a multi-mechanism-coupling process that is different from the process observed in conventional reservoirs. In micro fractures which are inborn or induced by hydraulic stimulation, viscous flow dominates. And gas surface diffusion and gas desorption should be further considered in organic nano pores. Also, the Klinkenberg effect should be considered when dealing with the gas transport problem. In addition, following two factors can play significant roles under certain circumstances but have not received enough attention in previous models. During pressure depletion, gas viscosity will change with Knudsen number; and pore radius will increase when …

Real-Time Supervised Detection Of Pink Areas In Dermoscopic Images Of Melanoma: Importance Of Color Shades, Texture And Location, Ravneet Kaur, P. P. Albano, Justin G. Cole, Jason R. Hagerty, Robert W. Leander, Randy Hays Moss, William V. Stoecker

Electrical and Computer Engineering Faculty Research & Creative Works

Background/Purpose: Early detection of malignant melanoma is an important public health challenge. In the USA, dermatologists are seeing more melanomas at an early stage, before classic melanoma features have become apparent. Pink color is a feature of these early melanomas. If rapid and accurate automatic detection of pink color in these melanomas could be accomplished, there could be significant public health benefits.

Methods: Detection of three shades of pink (light pink, dark pink, and orange pink) was accomplished using color analysis techniques in five color planes (red, green, blue, hue, and saturation). Color shade analysis was performed using a logistic …

Clustering Data Of Mixed Categorical And Numerical Type With Unsupervised Feature Learning, Dao Lam, Mingzhen Wei, Donald C. Wunsch

Geosciences and Geological and Petroleum Engineering Faculty Research & Creative Works

Mixed-type categorical and numerical data are a challenge in many applications. This general area of mixed-type data is among the frontier areas, where computational intelligence approaches are often brittle compared with the capabilities of living creatures. In this paper, unsupervised feature learning (UFL) is applied to the mixed-type data to achieve a sparse representation, which makes it easier for clustering algorithms to separate the data. Unlike other UFL methods that work with homogeneous data, such as image and video data, the presented UFL works with the mixed-type data using fuzzy adaptive resonance theory (ART). UFL with fuzzy ART (UFLA) obtains …

System And Process For Upgrading Hydrocarbons, Dennis N. Bingham, Kerry M. Klingler, Joseph D. Smith, Terry D. Turner, Bruce M. Wilding

Chemical and Biochemical Engineering Faculty Research & Creative Works

In one embodiment, a system for upgrading a hydrocarbon material may include a black wax upgrade subsystem and a molten salt gasification (MSG) subsystem. The black wax upgrade subsystem and the MSG subsystem may be located within a common pressure boundary, such as within a pressure vessel. Gaseous materials produced by the MSG subsystem may be used in the process carried out within the black wax upgrade subsystem. For example, hydrogen may pass through a gaseous transfer interface to interact with black wax feed material to hydrogenate such material during a cracking process. In one embodiment, the gaseous transfer interface …

Real Time Mission Planning, Emad William Saad, Stefan Richard Bieniawski, Paul Edward Riley Pigg, John Lyle Vian, Paul Michael Robinette, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

The different advantageous embodiments provide a system comprising a number of computers, a graphical user interface, first program code stored on the computer, and second program code stored on the computer. The graphical user interface is executed by a computer in the number of computers. The computer is configured to run the first program code to define a mission using a number of mission elements. The computer is configured to run the second program code to generate instructions for a number of assets to execute the mission and monitor the number of assets during execution of the mission.

Preface, Gennady Fridman, Jeremy Levesley, Ivan Tyukin, Donald C. Wunsch

Electrical and Computer Engineering Faculty Research & Creative Works

In August 2014 a conference on “Model reduction across disciplines” was held in Leicester, UK. As a scientific field, model reduction is an important part of mathematical modelling and data analysis with very wide areas of applications. The main scientific goal of the conference was to facilitate interdisciplinary discussion of model reduction and coarse-graining methodologies in order to reveal their general mathematical nature. This time, however, the conference had an additional personal and more profound mission – it was dedicated to the 60th birthday of Professor Alexander Gorban (albeit with some delay) whose fantastic achievements in applying model reduction techniques …

A Study Of Mixing In A Magnetohydrodynamic (Mhd) Microfluidic Cell By Numerical Simulations, Fangping Yuan, Kakkattukuzhy M. Isaac

Collaborative Research: Actively Controllable Microfluidics with Film-Confined Redox-Magnetohydrodynamics -- Video and Data

No abstract provided.

Methods And Systems For Biclustering Algorithm, Donald C. Wunsch, Rui Xu, Sejun Kim

Electrical and Computer Engineering Faculty Research & Creative Works

Methods and systems for improved unsupervised learning are described. The unsupervised learning can consist of biclustering a data set, e.g., by biclustering subsets of the entire data set. In an example, the biclustering does not include feeding know and proven results into the biclustering methodology or system. A hierarchical approach can be used that feeds proven clusters back into the biclustering methodology or system as the input. Data that does not cluster may be discarded. Thus, a very large unknown data set can be acted on to learn about the data. The system is also amenable to parallelization.

Systems, Methods And Devices For Vector Control Of Permanent Magnet Synchronous Machines Using Artificial Neural Networks, Shuhui Li, Michael Fairbank, Xingang Fu, Donald C. Wunsch, Eduardo Alonso

Electrical and Computer Engineering Faculty Research & Creative Works

An example method for controlling an AC electrical machine can include providing a PWM converter operably connected between an electrical power source and the AC electrical machine and providing a neural network vector control system operably connected to the PWM converter. The control system can include a current-loop neural network configured to receive a plurality of inputs. The current-loop neural network can be configured to optimize the compensating dq-control voltage. The inputs can be d- and q-axis currents, d- and q-axis error signals, predicted d- and q-axis current signals, and a feedback compensating dq-control voltage. The d- and q-axis error …

Producing High Strength Aluminum Alloy By Combination Of Equal Channel Angular Pressing And Bake Hardening, Hamid Alihosseini, Mohsen Asle Zaeem, Kamran Dehghani, Ghader Faraji

Materials Science and Engineering Faculty Research & Creative Works

A combination of severe plastic deformation by equal channel angular pressing (ECAP) and bake hardening (BH) was used to produce high strength ultrafine-grained AA6061 aluminum alloy. 2, 4 and 8 passes of ECAP were performed, and the bake hardenability of samples was tested by 6% pre-straining followed by baking at 200 °C for 20 min. The microstructures obtained for various passes of ECAP were characterized by XRD, EBSD, and TEM techniques. The microstructures were refined from an average grain size of 20 µm to 212 nm after 8 passes of ECAP. Maximum bake hardenability of 110 MPa, and final yield …

Quantitative Modeling Of The Equilibration Of Two-Phase Solid-Liquid Fe By Atomistic Simulations On Diffusive Time Scales, Ebrahim Asadi, Mohsen Asle Zaeem, Sasan Nouranian, Michael I. Baskes

Materials Science and Engineering Faculty Research & Creative Works

In this paper, molecular dynamics (MD) simulations based on the modified-embedded atom method (MEAM) and a phase-field crystal (PFC) model are utilized to quantitatively investigate the solid-liquid properties of Fe. A set of second nearest-neighbor MEAM parameters for higherature applications are developed for Fe, and the solid-liquid coexisting approach is utilized in MD simulations to accurately calculate the melting point, expansion in melting, latent heat, and solid-liquid interface free energy, and surface anisotropy. The required input properties to determine the PFC model parameters, such as liquid structure factor and fluctuations of atoms in the solid, are also calculated from MD …

Dynamic Phases, Pinning, And Pattern Formation For Driven Dislocation Assemblies, Caizhi Zhou, Charles Reichhardt, Cynthia Olson Reichhardt, Irene J. Beyerlein

Materials Science and Engineering Faculty Research & Creative Works

We examine driven dislocation assemblies and show that they can exhibit a set of dynamical phases remarkably similar to those of driven systems with quenched disorder such as vortices in superconductors, magnetic domain walls, and charge density wave materials. These phases include pinned-jammed, fluctuating, and dynamically ordered states, and each produces distinct dislocation patterns as well as specific features in the noise fluctuations and transport properties. Our work suggests that many of the results established for systems with quenched disorder undergoing plastic depinning transitions can be applied to dislocation systems, providing a new approach for understanding pattern formation and dynamics …

Big Data -- A 21st Century Science Maginot Line? No-Boundary Thinking: Shifting From The Big Data Paradigm, Xiuzhen Huang, Steven F. Jennings, Barry Bruce, Alison Buchan, Liming Cai, Pengyin Chen, Carole Cramer, Weihua Guan, Uwe Kk Hilgert, Hongmei Jiang, Zenglu Li, Gail Mcclure, Donald F. Mcmullen, Bindu Nanduri, Andy Perkins, Bhanu Rekepalli, Saeed Salem, Jennifer Specker, Karl Walker, Donald C. Wunsch, Donghai Xiong, Shuzhong Zhang, Yu Zhang, Zhongming Zhao, Jason H. Moore

Electrical and Computer Engineering Faculty Research & Creative Works

Whether your interests lie in scientific arenas, the corporate world, or in government, you have certainly heard the praises of big data: Big data will give you new insights, allow you to become more efficient, and/or will solve your problems. While big data has had some outstanding successes, many are now beginning to see that it is not the Silver Bullet that it has been touted to be. Here our main concern is the overall impact of big data; the current manifestation of big data is constructing a Maginot Line in science in the 21st century. Big data is not …