Engineering Commons^™

Material State Awareness For Composites Part Ii: Precursor Damage Analysis And Quantification Of Degraded Material Properties Using Quantitative Ultrasonic Image Correlation (Quic), Subir Patra, Sourav Banerjee

Faculty Publications

Material state awareness of composites using conventional Nondestructive Evaluation (NDE) method is limited by finding the size and the locations of the cracks and the delamination in a composite structure. To aid the progressive failure models using the slow growth criteria, the awareness of the precursor damage state and quantification of the degraded material properties is necessary, which is challenging using the current NDE methods. To quantify the material state, a new offline NDE method is reported herein. The new method named Quantitative Ultrasonic Image Correlation (QUIC) is devised, where the concept of microcontinuum mechanics is hybrid with the experimentally …

Material State Awareness For Composites Part I: Precursor Damage Analysis Using Ultrasonic Guided Coda Wave Interferometry (Cwi), Subir Patra, Sourav Banerjee

Faculty Publications

Detection of precursor damage followed by the quantification of the degraded material properties could lead to more accurate progressive failure models for composite materials. However, such information is not readily available. In composite materials, the precursor damages—for example matrix cracking, microcracks, voids, interlaminar pre-delamination crack joining matrix cracks, fiber micro-buckling, local fiber breakage, local debonding, etc.—are insensitive to the low-frequency ultrasonic guided-wave-based online nondestructive evaluation (NDE) or Structural Health Monitoring (SHM) (~100–~500 kHz) systems. Overcoming this barrier, in this article, an online ultrasonic technique is proposed using the coda part of the guided wave signal, which is often neglected. Although …

Sexual Recombination And Increased Mutation Rate Expedite Evolution Of Escherichia Coli In Varied Fitness Landscapes, George Peabody, Hao Li, Katy Kao

Faculty Publications

Sexual recombination and mutation rate are theorized to play different roles in adaptive evolution depending on the fitness landscape; however, direct experimental support is limited. Here we examine how these factors affect the rate of adaptation utilizing a “genderless” strain of Escherichia coli capable of continuous in situ sexual recombination. The results show that the populations with increased mutation rate, and capable of sexual recombination, outperform all the other populations. We further characterize two sexual and two asexual populations with increased mutation rate and observe maintenance of beneficial mutations in the sexual populations through mutational sweeps. Furthermore, we experimentally identify …

Parallel Cosine Nearest Neighbor Graph Construction, David Anastasiu, George Karypis

Faculty Publications

The nearest neighbor graph is an important structure in many data mining methods for clustering, advertising, recommender systems, and outlier detection. Constructing the graph requires computing up to n2 similarities for a set of n objects. This high complexity has led researchers to seek approximate methods, which find many but not all of the nearest neighbors. In contrast, we leverage shared memory parallelism and recent advances in similarity joins to solve the problem exactly. Our method considers all pairs of potential neighbors but quickly filters pairs that could not be a part of the nearest neighbor graph, based on similarity …

Development And Field Testing Of An Interactive Transit Station Information System (Itsis) Using Connected Vehicle Technologies, Huadong Meng, Jacob Tsao, Kun Zhou, Justin Picar, Bradley Mizuno, Wei-Bin Zhang

Faculty Publications

The objective of Interactive Transit Station Information System (ITSIS) is to better inform transit travelers during their trips and to enable dynamic transit operations to better serve travelers. The ultimate goal is to make transit more friendly and attractive to the traveling population such that transit will become a viable choice for travel and an integrated part of the solution for congestion relief. This report documents a research effort to develop and test a ITSIS prototype that uses Connected Vehicle technologies to enable the real-time interaction between passengers and transit systems at bus stations. The reports summarizes the findings from …

Trading Off Sound Pressure Level And Average Power Production For Wind Farm Layout Optimization, Eric Tingey, Andrew Ning

Faculty Publications

This research explores the trade-offs between a wind farm’s average power production and noise impact on nearby observers. Two specific wind farm designs were studied and optimized using the FLORIS wake model and an acoustic model based on semi-empirical turbine noise calculations. It was found in the two wind farms that the average power production could be increased, up to 8.01% in one and 3.63% in the other, ignoring sound level considerations. Including a noise restriction in the optimization had a minimal impact on the optimal average power production within about a five-decibel range. Past this range, sound limitations decreased …

Document Clustering, David Anastasiu, Andrea Tagarelli

Faculty Publications

In a world flooded with information, document clustering is an important tool that can help categorize and extract insight from text collections. It works by grouping similar documents, while simultaneously discriminating between groups. In this article, we provide a brief overview of the principal techniques used to cluster documents, and introduce a series of novel deep-learning based methods recently designed for the document clustering task. In our overview, we point the reader to salient works that can provide a deeper understanding of the topics discussed.

Reaching In Clutter With Whole-Arm Tactile Sensing, Advait Jain, Marc D. Killpack, Aaron Edsinger, Charles Kemp

Faculty Publications

Clutter creates challenges for robot manipulation, including a lack of non-contact trajectories and reduced visibility for line-of-sight sensors. We demonstrate that robots can use whole-arm tactile sensing to perceive clutter and maneuver within it, while keeping contact forces low. We first present our approach to manipulation, which emphasizes the benefits of making contact across the entire manipulator and assumes the manipulator has low-stiffness actuation and tactile sensing across its entire surface. We then present a novel controller that exploits these assumptions. The controller only requires haptic sensing, handles multiple contacts, and does not need an explicit model of the environment …

Reconstructing Yeasts Phylogenies And Ancestors From Whole Genome Data, Bing Feng, Yu Lin, Lingxi Zhou, Yan Guo, Robert Friedman, Roufan Xia, Chao Liu, Jijun Tang

Faculty Publications

Phylogenetic studies aim to discover evolutionary relationships and histories. These studies are based on similarities of morphological characters and molecular sequences. Currently, widely accepted phylogenetic approaches are based on multiple sequence alignments, which analyze shared gene datasets and concatenate/coalesce these results to a final phylogeny with maximum support. However, these approaches still have limitations, and often have conflicting results with each other. Reconstructing ancestral genomes helps us understand mechanisms and corresponding consequences of evolution. Most existing genome level phylogeny and ancestor reconstruction methods can only process simplified real genome datasets or simulated datasets with identical genome content, unique genome markers, …

Reconstructing Yeasts Phylogenies And Ancestors From Whole Genome Data, Bing Feng, Yu Ling, Lingxi Zhou, Roufan Xia, Fei Hu, Chao Liu

Faculty Publications

Phylogenetic studies aim to discover evolutionary relationships and histories. These studies are based on similarities of morphological characters and molecular sequences. Currently, widely accepted phylogenetic approaches are based on multiple sequence alignments, which analyze shared gene datasets and concatenate/coalesce these results to a final phylogeny with maximum support. However, these approaches still have limitations, and often have conflicting results with each other. Reconstructing ancestral genomes helps us understand mechanisms and corresponding consequences of evolution. Most existing genome level phylogeny and ancestor reconstruction methods can only process simplified real genome datasets or simulated datasets with identical genome content, unique genome markers, …

High Temperature Magneto-Structural Transition In Van Der Waals-Layered -Mocl3, Michael Mcguire, Jiaqiang Yan, Paula Lampen-Kelley, Andrew May, Valentino Cooper, Lucas Lindsay, Alexander Puretzky, Liangbo Liang, Santosh Kc, Ercan Cakmak, Stuart Calder, Brian Sales

Faculty Publications

The crystallographic and magnetic properties of the cleavable 4d3 transition metal compound α−MoCl3 are reported, with a focus on the behavior above room temperature. Crystals were grown by chemical vapor transport and characterized using temperature dependent x-ray diffraction, Raman spectroscopy, and magnetization measurements. A structural phase transition occurs near 585 K, at which the Mo-Mo dimers present at room temperature are broken. A nearly regular honeycomb net of Mo is observed above the transition, and an optical phonon associated with the dimerization instability is identified in the Raman data and in first-principles calculations. The crystals are diamagnetic at room temperature …

Load Planning Processes To Enhance Cargo Compartment Utilization, Nathan J. Carlson, Adam D. Reiman, Robert E. Overstreet, Matthew A. Douglas

Faculty Publications

Purpose: The United States Air Force often provides effective airlift for cargo distribution, but is at times inefficient. This paper aims to address the under-utilization of military airlift cargo compartments that plagues the airlift system.
Design/methodology/approach: The authors examine seven techniques designed to increase cargo compartment utilization and increase airlift utilization rates. The techniques were applied through load planning software to 30 real-world movements consisting of 159 sorties. They then ran each post-technique movement through a modeled flight environment to obtain cycle movement data. The metrics gained from both the load planning software and the modeled environment were regressed to …

Efficient Identification Of Tanimoto Nearest Neighbors; All Pairs Similarity Search Using The Extended Jaccard Coefficient, David Anastasiu, George Karypis

Faculty Publications

Tanimoto, or extended Jaccard, is an important similarity measure which has seen prominent use in fields such as data mining and chemoinformatics. Many of the existing state-of-the-art methods for market basket analysis, plagiarism and anomaly detection, compound database search, and ligand-based virtual screening rely heavily on identifying Tanimoto nearest neighbors. Given the rapidly increasing size of data that must be analyzed, new algorithms are needed that can speed up nearest neighbor search, while at the same time providing reliable results. While many search algorithms address the complexity of the task by retrieving only some of the nearest neighbors, we propose …

Classifying And Predicting Occupational Incident Severity, Fatemeh Davoudi Kakhki, Steven Freeman, Gretchen Mosher

Faculty Publications

The focus of the study is to build a predictive model and assess its performance in classifying the financial severity of occupational injuries in agribusiness bulk storage facilities (i.e. grain elevators). The data specifically look at food processing and feed milling operations within these facilities. The severity of occupational injuries is determined by the total dollar amount incurred on medical costs, indemnity costs and other expenses in workers’ compensation claims. The data is available from an agribusiness insurance provider in Midwest USA. First, the most important independent variables that affect the total cost of claims are extracted from the original …

Improving Rolling Bearing Fault Diagnosis By Ds Evidence Theory Based Fusion Model, Xuemei Yao, Shaobo Li, Jianjun Hu

Faculty Publications

Rolling bearing plays an important role in rotating machinery and its working condition directly affects the equipment efficiency. While dozens of methods have been proposed for real-time bearing fault diagnosis and monitoring, the fault classification accuracy of existing algorithms is still not satisfactory. This work presents a novel algorithm fusion model based on principal component analysis and Dempster-Shafer evidence theory for rolling bearing fault diagnosis. It combines the advantages of the learning vector quantization (LVQ) neural network model and the decision tree model. Experiments under three different spinning bearing speeds and two different crack sizes show that our fusion model …

The Aspergillus Flavus Homeobox Gene, Hbx1, Is Required For Development And Aflatoxin Production, Jeffrey W. Cary, Pamela Y. Harris-Coward, Leslie Scharfenstein, Brian M. Mack, Perng-Kuang Chang, Qijian Wei, Matthew Lebar, Carol Carter-Wientjes, Rajtilak Majumdar, Chandrani Mitra, Sourav Banerjee, Anindya Chanda

Faculty Publications

Homeobox proteins, a class of well conserved transcription factors, regulate the expression of targeted genes, especially those involved in development. In filamentous fungi, homeobox genes are required for normal conidiogenesis and fruiting body formation. In the present study, we identified eight homeobox (hbx) genes in the aflatoxin-producing ascomycete, Aspergillus flavus, and determined their respective role in growth, conidiation and sclerotial production. Disruption of seven of the eight genes had little to no effect on fungal growth and development. However, disruption of the homeobox gene AFLA_069100, designated as hbx1, in two morphologically different A. flavus strains, CA14 and AF70, resulted in …

Formal Performance Guarantees For An Approach To Human In The Loop Robot Missions, Damian Lyons, Ron Arkin, Shu Jiang, Matt O'Brien, Feng Tang, Peng Tang

Faculty Publications

Abstract— A key challenge in the automatic verification of robot mission software, especially critical mission software, is to be able to effectively model the performance of a human operator and factor that into the formal performance guarantees for the mission. We present a novel approach to modelling the skill level of the operator and integrating it into automatic verification using a linear Gaussians model parameterized by experimental calibration. Our approach allows us to model different skill levels directly in terms of the behavior of the lumped, robot plus operator, system.

Using MissionLab and VIPARS (a behavior-based robot mission verification …

Optimization Of The Hot Embossing Parameters And Sintering Characterization For Alumina/Berea Sandstone Ceramics, Justin F. Robbins

Faculty Publications

The purpose of this study is to investigate the process of hot embossing on alumina based ceramics as a cost-efficient procedure for manufacturing microfluidic testing components. Alumina ceramics were used as an exploratory phase for the final objective of the project, manufacturing of Berea sandstone based ceramic samples. These testing components are vital to the growth of various fields ranging from the retrieval of oil and natural gas to studying the water purification process of aquifers. Previous research has shown potential in using hot embossing on Alumina based ceramics; however, complications with extrusion and micro-structure quality were observed. For this …

A Framework For Recommendation Of Highly Popular News Lacking Social Feedback, Nuno Moniz, Luís Torgo, Magdalini Eirinaki, Paula Branco

Faculty Publications

Social media is rapidly becoming the main source of news consumption for users, raising significant challenges to news aggregation and recommendation tasks. One of these challenges concerns the recommendation of very recent news. To tackle this problem, approaches to the prediction of news popularity have been proposed. In this paper, we study the task of predicting news popularity upon their publication, when social feedback is unavailable or scarce, and to use such predictions to produce news rankings. Unlike previous work, we focus on accurately predicting highly popular news. Such cases are rare, causing known issues for standard prediction models and …

Use Of A Novel Infrared Wavelength-Tunable Laser Mueller-Matrix Polarimetric Scatterometer To Measure Nanostructured Optical Materials, Jason C. Vap, Stephen E. Nauyoks, Michael R. Benson, Michael A. Marciniak

Faculty Publications

Nanostructured optical materials, for example, metamaterials, have unique spectral, directional, and polarimetric properties. Samples designed and fabricated for infrared (IR) wavelengths have been characterized using broadband instruments to measure specular polarimetric transmittance or reflectance as in ellipsometry or integrated hemisphere transmittance or reflectance. We have developed a wavelength-tunable IR Mueller-matrix (Mm) polarimetric scatterometer which uses tunable external-cavity quantum-cascade lasers (EC-QCLs) to tune onto and off of the narrowband spectral resonances of nanostructured optical materials and performed full polarimeteric and directional evaluation to more fully characterize their behavior. Using a series of EC-QCLs, the instrument is tunable over 4.37-6.54 μm wavelengths …

Spin-Imbalance In A 2d Fermi-Hubbard System, Peter Brown, Debayan Mitra, Elmer Guardado-Sanchez, Peter Schauß, Stanimir Kondov, Ehsan Khatami, Thereza Paiva, Nandini Trivedi, David Huse, Waseem Bakr

Faculty Publications

The interplay of strong interactions and magnetic fields gives rise to unusual forms of superconductivity and magnetism in quantum many-body systems. Here, we present an experimental study of the two-dimensional Fermi-Hubbard model—a paradigm for strongly correlated fermions on a lattice—in the presence of a Zeeman field and varying doping. Using site-resolved measurements, we revealed anisotropic antiferromagnetic correlations, a precursor to long-range canted order. We observed nonmonotonic behavior of the local polarization with doping for strong interactions, which we attribute to the evolution from an antiferromagnetic insulator to a metallic phase. Our results pave the way to experimentally mapping the low-temperature …

Relationships Between Access To Mobile Devices, Student Self-Directed Learning, And Achievement, Scott R. Bartholomew, Ed Reeve, Raymond Veon, Wade Goodridge, Victor Lee, Louis Nadelson

Faculty Publications

Today’s students are growing up in a world of constant connectivity, instant information, and ever-changing technological advancements. The increasingly ubiquitous nature of mobile devices among K–12 students has led many to argue for and against the inclusion of these devices in K–12 classrooms. Arguments in favor cite instant access to information and collaboration with others as positive affordances that enable student self-directed learning. In this study, 706 middle school students from 18 technology and engineering education classes worked in groups of 2–3 to complete an openended engineering design challenge. Students completed design portfolios and constructed prototypes in response to the …

Improvement Of Phylogenetic Method To Analyze Compositional Heterogeneity, Zehua Zhang, Kecheng Guo, Gaofeng Pan, Jijun Tang, Fei Guo

Faculty Publications

Background: Phylogenetic analysis is a key way to understand current research in the biological processes and detect theory in evolution of natural selection. The evolutionary relationship between species is generally reflected in the form of phylogenetic trees. Many methods for constructing phylogenetic trees, are based on the optimization criteria. We extract the biological data via modeling features, and then compare these characteristics to study the biological evolution between species.

Results: Here, we use maximum likelihood and Bayesian inference method to establish phylogenetic trees; multi-chain Markov chain Monte Carlo sampling method can be used to select optimal phylogenetic tree, resolving local …

Examining Accident Reports Involving Autonomous Vehicles In California, Francesca Favaro, Nazanin Nader, Sky Eurich, Michelle Tripp, Naresh Varadaraju

Faculty Publications

Autonomous Vehicle technology is quickly expanding its market and has found in Silicon Valley, California, a strong foothold for preliminary testing on public roads. In an effort to promote safety and transparency to consumers, the California Department of Motor Vehicles has mandated that reports of accidents involving autonomous vehicles be drafted and made available to the public. The present work shows an in-depth analysis of the accident reports filed by different manufacturers that are testing autonomous vehicles in California (testing data from September 2014 to March 2017). The data provides important information on autonomous vehicles accidents’ dynamics, related to the …

Synthesis Of Non-Uniformly Correlated Partially Coherent Sources Using A Deformable Mirror, Milo W. Hyde Iv, Santasri Bose-Pillai, Ryan A. Wood

Faculty Publications

The near real-time synthesis of a non-uniformly correlated partially coherent source using a low-actuator-count deformable mirror is demonstrated. The statistical optics theory underpinning the synthesis method is reviewed. The experimental results of a non-uniformly correlated source are presented and compared to theoretical predictions. A discussion on how deformable mirror characteristics such as actuator count and pitch affect source generation is also included.

Combined Model Predictive Control And Scheduling With Dominant Time Constant Compensation, Logan Beal, Junho Park, Damon Petersen, Sean C. Warnick, John Hedengren

Faculty Publications

Linear model predictive control is extended to both control and optimize a product grade schedule. The proposed methods are time-scaling of the linear dynamics based on throughput rates and grade-based objectives for product scheduling based on a mathematical program with complementarity constraints. The linear model is adjusted with a residence time approximation to time-scale the dynamics based on throughput. Although nonlinear models directly account for changing dynamics, the model form is restricted to linear differential equations to enable fast online cycle times for large-scale and real-time systems. This method of extending a linear time-invariant model for scheduling is designed for …

Deep Visual Gravity Vector Detection For Unmanned Aircraft Attitude Estimation, Gary J. Ellingson, David Wingate, Tim Mclain

Faculty Publications

This paper demonstrates a feasible method for using a deep neural network as a sensor to estimate the attitude of a flying vehicle using only flight video. A dataset of still images and associated gravity vectors was collected and used to perform supervised learning. The network builds on a previously trained network and was trained to be able to approximate the attitude of the camera with an average error of about 8 degrees. Flight test video was recorded and processed with a relatively simple visual odometry method. The aircraft attitude is then estimated with the visual odometry as the state …

Simplex Solutions For Optimal Control Flight Paths In Urban Environments, Michael D. Zollars, Richard G. Cobb, David J. Grymin

Faculty Publications

This paper identifies feasible fight paths for Small Unmanned Aircraft Systems in a highly constrained environment. Optimal control software has long been used for vehicle path planning and has proven most successful when an adequate initial guess is presented flight to an optimal control solver. Leveraging fast geometric planning techniques, a large search space is discretized into a set of simplexes where a Dubins path solution is generated and contained in a polygonal search corridor free of path constraints. Direct optimal control methods are then used to determine the optimal flight path through the newly defined search corridor. Two scenarios …

Relative Navigation Of Autonomous Gps-Degraded Micro Air Vehicles, David O. Wheeler, Daniel P. Koch, James S. Jackson, Gary J. Ellingson, Paul W. Nyholm, Timothy W. Mclain, Randal W. Beard

Faculty Publications

Many current approaches for navigation of micro air vehicles (MAVs) in GPS-degraded environments use a globally-referenced state for estimation and control, even though this state is not observable when GPS is unavailable. By working with respect to a local reference frame, the relative navigation (RN) framework presented in this paper ensures that the state maintains observability and that the uncertainty remains bounded, consistent, and normally-distributed. RN further insulates flight-critical estimation and control processes from the large global updates common in GPS-degraded MAV flight. This paper provides a thorough description of the details needed to successfully implement the RN framework on …

Relative Multiplicative Extended Kalman Filter For Observable Gps-Denied Navigation, Daniel P. Koch, David O. Wheeler, Randal Beard, Tim Mclain, Kevin M. Brink

Faculty Publications

This work presents a multiplicative extended Kalman filter for estimating the relative state of a multirotor vehicle operating in a GPS-denied environment. The filter fuses data from an inertial measurement unit and altimeter with relative-pose updates from a keyframe-based visual odometry or laser scan-matching algorithm. Because the global position and heading states of the vehicle are unobservable in the absence of global measurements such as GPS, the filter in this paper estimates the state with respect to a local frame that is colocated with the odometry keyframe. As a result, the odometry update provides nearly-direct measurements of the relative vehicle …