University of Nebraska-Lincoln Agricultural Research Division 122nd Annual Report July 1, 2007 to June 30, 2008

Our Mission ..... 4 Foreword..... 5 Faculty Awards and Recognitions.... 6 Graduate Student Awards and Recognitions...10 Undergraduate Honors Student Research Program...14 Variety and Germplasm Releases....15 Patents.....17 Administration..... 18 Administrative Personnel.... 18 Organizational Chart....19 Administrative Units....20 IANR Research Facilities.... 21 Faculty..... 22 Agricultural/Natural Resources Units... 23 Education and Human Sciences Departments...33 Off-Campus Research Centers....34 Interdisciplinary Activities....35 Visiting Scientists/Research Associates....36 Research Projects..... 43 Agricultural/Natural Resources Units... 43 Education and Human Sciences Departments...48 Off-Campus Research Centers....49 Interdisciplinary Activities ....50 Publications.....51 Agricultural/Natural Resources Units... 57 Education and Human Sciences Departments...77 Off-Campus Research Centers....80 Research Expenditures....8

Air Force Institute of Technology Research Report 2016

This Research Report presents the FY16 research statistics and contributions of the Graduate School of Engineering and Management (EN) at AFIT. AFIT research interests and faculty expertise cover a broad spectrum of technical areas related to USAF needs, as reflected by the range of topics addressed in the faculty and student publications listed in this report. In most cases, the research work reported herein is directly sponsored by one or more USAF or DOD agencies. AFIT welcomes the opportunity to conduct research on additional topics of interest to the USAF, DOD, and other federal organizations when adequate manpower and financial resources are available and/or provided by a sponsor. In addition, AFIT provides research collaboration and technology transfer benefits to the public through Cooperative Research and Development Agreements (CRADAs)

Application of Neural Networks to Evaluate Factors Affecting Drilling Performance

Achieving the highest Rate of Penetration (ROP) with the least possible Bit Tooth Wear Rate (BTWR) is the aim of every drilling engineer when selecting a drilling bit. Predicting the optimal ROP has become increasingly important given the rise in expenses involved in drilling a well. This has meant that oil companies engage in a perpetual struggle to predict the optimum rock mechanical property parameters. Predicting optimal rock mechanical property parameters, specifically Rate of Penetration (ROP), has become increasingly important given the rise in expenses involved in drilling a well. The prediction of ROP from the current available data is an important criterion for reduction of drilling costs. ROP represents rock bit interaction which relates rock compressive strength and bit aggressivity. ROP prediction is complex because of the numerous variables which lead to difficulties in evaluating drilling parameters. Several models and methods have been published for predicting, and therefore potentially optimizing rate of penetration. However, these models and methods have limitations, too many variables are included, their input parameters are often not readily available, and their relationships are complex and not easily modeled. Therefore, the application of Neural Network is suggested in this study. A new methodology has been developed to predict the rate of penetration using the Artificial Neural Network (ANN). Three case studies representing different formations in Kuwait have been conducted to investigate ROP prediction for various applications. These cases have investigated the prediction of ROP for a specific heterogeneous formation (CASE I); a semihomogenous formation (CASE II); a drilling section composed of a heterogeneous formation and for a drilling section composed of a complex heterogeneous set of formations (CASE III). Predicting ROP parameters is of particular interest, therefore finding a new method to predict ROP for the cases investigated in this study will be a valuable achievement. Application of the new network models would then be used for selecting the best parameters for an optimal drilling strategy based on field data. In addition to the prediction of ROP, several runs were carried out to predict Tooth Wear Rate (TWR) for a drilling section in case III. Rock bit interactions in the field as a function of rock mechanical property parameters was achieved by predicting ROP which relates to rock compressive strength and bit aggressivity; as well as TWR which relates to rock abrasiveness and wear resistance. History of bit runs, mud logging data, geological information, offset well bit records, drill bit characteristics, and wireline data all play an important role in the prediction of rock bit interactions in this study. Based on field data, the prediction of rock mechanical property parameters can be accomplished by the use of a neural network as an alternative prediction and optimization method. Neural network offers a new form of information processing that is fundamentally different from a traditional processing system. The system uses a knowledge base of various drilling parameters, to produce a “correlation” description of the optimal Rate of Penetration

Haptic-Enhanced Learning in Preclinical Operative Dentistry

Background: Virtual reality haptic simulators represent a new paradigm in dental education that may potentially impact the rate and efficiency of basic skill acquisition, as well as pedagogically influence the various aspects of students’ preclinical experience. However, the evidence to support their efficiency and inform their implementation is still limited. Objectives: This thesis set out to empirically examine how haptic VR simulator (Simodont®) can enhance the preclinical dental education experience particularly in the context of operative dentistry. We specify 4 distinct research themes to explore, namely: simulator validity (face, content and predictive), human factors in 3D stereoscopic display, motor skill acquisition, and curriculum integration. Methods: Chapter 3 explores the face and content validity of Simodont® haptic dental simulator among a group of postgraduate dental students. Chapter 4 examines the predictive utility of Simodont® in predicting subsequent preclinical and clinical performance. The results indicate the potential utility of the simulator in predicting future clinical dental performance among undergraduate students. Chapter 5 investigates the role of stereopsis in dentistry from two different perspectives via two studies. Chapter 6 explores the effect of qualitatively different types of pedagogical feedback on the training, transfer and retention of basic manual dexterity dental skills. The results indicate that the acquisition and retention of basic dental motor skills in novice trainees is best optimised through a combination of instructor and visualdisplay VR-driven feedback. A pedagogical model for integration of haptic dental simulator into the dental curriculum has been proposed in Chapter 7. Conclusion: The findings from this thesis provide new insights into the utility of the haptic virtual reality simulator in undergraduate preclinical dental education. Haptic simulators have promising potential as a pedagogical tool in undergraduate dentistry that complements the existing simulation methods. Integration of haptic VR simulators into the dental curriculum has to be informed by sound pedagogical principles and mapped into specific learning objectives

Robotics in Dentistry : A Narrative Review

Background: Robotics is progressing rapidly. The aim of this study was to provide a comprehensive overview of the basic and applied research status of robotics in dentistry and discusses its development and application prospects in several major professional fields of dentistry. Methods: A literature search was conducted on databases: MEDLINE, IEEE and Cochrane Library, using MeSH terms: [“robotics” and “dentistry”]. Result: Forty-nine articles were eventually selected according to certain inclusion criteria. There were 12 studies on prosthodontics, reaching 24%; 11 studies were on dental implantology, accounting for 23%. Scholars from China published the most articles, followed by Japan and the United States. The number of articles published between 2011 and 2015 was the largest. Conclusions: With the advancement of science and technology, the applications of robots in dental medicine has promoted the development of intelligent, precise, and minimally invasive dental treatments. Currently, robots are used in basic and applied research in various specialized fields of dentistry. Automatic tooth-crown-preparation robots, tooth-arrangement robots, drilling robots, and orthodontic archwire-bending robots that meet clinical requirements have been developed. We believe that in the near future, robots will change the existing dental treatment model and guide new directions for further development

The use of mechanical redundancy for fault detection in non-stationary machinery

The classical approach to machinery fault detection is one where a machinery’s condition is constantly compared to an established baseline with deviations indicating the occurrence of a fault. With the absence of a well-established baseline, fault detection for variable duty machinery requires the use of complex machine learning and signal processing tools. These tools require extensive data collection and expert knowledge which limits their use for industrial applications. The thesis at hand investigates the problem of fault detection for a specific class of variable duty machinery; parallel machines with simultaneously loaded subsystems. As an industrial case study, the parallel drive stations of a novel material haulage system have been instrumented to confirm the mechanical response similarity between simultaneously loaded machines. Using a table-top fault simulator, a preliminary statistical algorithm was then developed for fault detection in bearings under non-stationary operation. Unlike other state of the art fault detection techniques used in monitoring variable duty machinery, the proposed algorithm avoided the need for complex machine learning tools and required no previous training. The limitations of the initial experimental setup necessitated the development of a new machinery fault simulator to expand the investigation to include transmission systems. The design, manufacturing and setup of the various subsystems within the new simulator are covered in this manuscript including the mechanical, hydraulic and control subsystems. To ensure that the new simulator has successfully met its design objectives, extensive data collection and analysis has been completed and is presented in this thesis. The results confirmed that the developed machine truly represents the operation of a simultaneously loaded machine and as such would serve as a research tool for investigating the application of classical fault detection techniques to parallel machines in non-stationary operation.Master's These

Air Force Institute of Technology Research Report 2015

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems Engineering and Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

Air Force Institute of Technology Research Report 2015

This report summarizes the research activities of the Air Force Institute of Technology’s Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems Engineering and Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

Case-based drilling curricula using integrated HIL simulator and remote collaboration center

The university educational system has raised many concerns in recent years regarding the effectiveness of its curricula and implementation. The focus on course-based training in engineering programs does not provide students sufficient opportunities to apply the attained knowledge and skills to demonstrate their competency. To address this deficiency of academia, industry spends millions of dollars building development programs and on-the-job training. This creates an opportunity for the universities to address this deficiency and increase their students’ marketability, while also addressing problem solving in their curricula. Inspired by a successful program developed and offered at Harvard Business School, the advantages and disadvantages of the case-based method was investigated. It was concluded that the students can benefit the most from a combination of existing educational and case-based curricula elements. Further research expressed the engineering students’ interest and positive feedbacks towards utilization of this method supported by statistical analysis. The aviation industry experienced a great training cost reduction and eliminated the on-the-training accidents after adopting simulators to train their workforce. This encouraged the Drilling & Automation team at University of Texas at Austin to develop the existing surface simulator further and utilize it as a tool to train the next generation of engineers to carry out the appropriate performance at the time of failure and emergencies. By considering various effective skills development methods such as Triadic method and Kolb’s Four-Stage Learning Cycle, ten case-based laboratories were designed and proposed. These open-ended student-led laboratories provide the opportunity for students to experience life-like challenges associated with drilling operations using a realistic up-to-date virtual drilling simulator. Students are divided in teams and assigned to different roles (drilling engineer, remote supervising engineer, etc.) where they are required to make decisions and communicate with one another. This creates a realistic work environment where depending on difficulty of each case, different amounts of stress are experienced. To implement the proposed laboratories, down-hole physics models were identified and developed. These mathematical models were then simulated in MATLAB programing language and integrated with one another to form the down-hole simulator. An Application Program Interface, API, was developed to access the surface simulator data and to connect the surface and the down-hole simulators. The integrated developed simulator has potential for future research including automated rig design.Petroleum and Geosystems Engineerin

Objective assessment and feedback generation in dental surgical simulation : a framework based on correlating procedure and outcome

Fine motor skill is indispensable for a dentist. As in many other medical fields of study, the traditional surgical master-apprentice model is widely adopted in dental education. Recently, virtual reality (VR) simulators have been employed as supplementary components to the traditional skill-training curriculum, and numerous dental VR systems have been developed academically and commercially. However, the full promise of such systems has yet to be realized due to the lack of sufficient support for formative feedback. Without such a mechanism, evaluation still demands dedicated time of experts in scarce supply. With the aim to fill the gap of formative assessment using VR simulators in skill training in dentistry, this thesis presents a framework to objectively assess the surgical skill and generate formative feedback automatically. VR simulators enable collecting detailed data on relevant metrics throughout a procedure. Our approach to formative feedback is to correlate procedure metrics with the procedure outcome in order to identify the portions of a procedure that need to be improved. Prior to the correlation, the procedure outcome needs to be evaluated. The scoring algorithm designed in this thesis provides an overall score and identifies specific errors and their severity. Building upon this, we developed techniques to identify the portion of the procedure responsible for the errors. Specifically, for the errors in the outcome the responsible portions of the procedure are identified based on correlation of location of the error. For some types of feedback one mode may be more suitable than another. Tutoring formative feedback are provided using the video- and haptic- modalities. The effectiveness of the feedback systems have been evaluated with the dental students with randomized controlled trials and the findings show the feedback mechanisms to be effective and have potentials to use as valuable supplemental training resources