2015 Informs Annual Meeting

TB70

INFORMS Philadelphia – 2015

TB70 70-Room 202A, CC Yard and Terminal Simulation Sponsor: Railway Applications Sponsored Session Chair: Roger Baugher, President, TrAnalytics, LLC, 100 Villamoura Way, Johns Creek, GA, 30097, United States of America, rwbaugher@aol.com 1 - Exploiting Data to Create Yard and Terminal Replay Capabilities Roger Baugher, President, TrAnalytics, LLC, 100 Villamoura Way, Johns Creek, GA, 30097, United States of America, rwbaugher@aol.com Yard automation technology, GPS sensors, time lapse cameras and new low cost computer processors enable large amounts of yard operation data to be captured inexpensively. Processes can transform these data, and the yard’s GIS data, into inputs for simulation, enabling the deployment of yard replay systems. With such a system, management can analyze operational failures, develop improved processes, train new employees, examine the impact of proposed capital improvements and more. 2 - Simulation Model for a Large Railroad Flat Switching Yard Clark Cheng, Senior Director Operations Research, Norfolk Southern Railway, Atlanta, GA, 30309, United States of America, Clark.Cheng@nscorp.com, Rajesh Kalra, Mabby Amouie, Edward Lin We will present a discrete-event simulation model for the largest railroad flat switching yard in the Western Hemisphere. The model is being used to evaluate yard capacity and improve yard operations and customer service. 3 - Conflict Avoidance in Yards and Terminals Brigitte Jaumard, Professor And Concordia Research Chair On The Optimization Of Communication Networks, Concordia University, Computer Science and Software Eng., 1455 de Maisonneuve Blvd. West, Montreal, QC, H3G 1M8, Canada, bjaumard@cse.concordia.ca, Roger Baugher, Thai Hoa Le, Bertrand Simon Activities of a rail yard focus on freight delivery and vehicle maintenance, while train movements are generally line-of-sight ones. Many of the yard activities share one or two connecting tracks for through traffic. While these tracks need to remain clear for through traffic, stopping yard activities on them to let a passenger train through may result in disruption to freight operations, and in conflicts. We will propose different mechanisms and tools in order to avoid conflicts. 4 - Applying Dynamic Simulation to Validate and Improve New Transloading Terminal Operations Martin Franklin, Partner, MOSIMTEC LLC, 297 Herndon Parkway, Suite 301, Herndon, VA, 20170, United States of America, martin@mosimtec.com A chemical manufacturing and handling company is expanding and re- configuring facilities to create a new interface point between rail transport and pipeline transport. The client recognized the need to apply modeling and simulation technology to represent the system in a dynamic environment, therein incorporating inherent variability, to validate the design and make informed decisions. Simulation analysis of the rail network and operators and related integration will also be reviewed. TB72 72-Room 203A, CC DDDAS for Industrial and System Engineering Applications II Sponsor: Quality, Statistics and Reliability Sponsored Session Chair: Shiyu Zhou, Professor, University of Wisconsin-Madison, Department of Industrial and Systems Eng, 1513 University Avenue, Madison, WI, 53706, United States of America, shiyuzhou@wisc.edu Co-Chair: Yu Ding, Professor, Texas A&M University, ETB 4016, MS 3131, College Station, YX, United States of America, yuding@iemail.tamu.edu 1 - Multi-stage Nanocrystal Growth Identifying and Modeling via in-situ TEM Video Yanjun Qian, PhD Candidate, TAMU, 1501 Harvey Rd, Apt. 806,

quantitative analytic tools. We introduce an automated tool suitable for analyzing the in-situ TEM videos. It learns and tracks the normalized particle size distribution and identifies the phase change points delineating the stages in nanocrystal growth. We furthermore produce a quantitative physical-based model. 2 - Cooperative Unmanned Vehicles for Vision-based Detection and Real-world Localization of Human Crowds Sara Minaeian, The University of Arizona, 1127 E James E. Rogers Way, Room 111, Tucson, AZ, 85716, United States of America, minaeian@email.arizona.edu, Young-jun Son, Jian Liu In crowd control using unmanned vehicles (UVs), the crowd detection and real- world localization are required to perform key functions such as tracking and motion planning. In this work, a team of UVs cooperates under a DDDAMS framework to detect the moving crowds by applying computer-vision techniques and to localize them using a new perspective transformation. A simulation model is also developed for validation, and the experimental results reveal the effectiveness of the proposed approach. 3 - Fault Identifiability Analysis of Beam Structures using Dynamic Data-driven Approaches Yuhang Liu, Research Assistant, University of Wisconsin- Madison, 1513 University Ave, ME3255, Madison, WI, 53706, United States of America, liu427@wisc.edu, Shiyu Zhou In this research, we study the parameterization and localization identifiability of beam structures based on the dynamic response information. We show that the stiffness parameters can be locally identifiable in general cases for the collocated single input and single output system. The unique relationship between the damage location and the dynamic response are also investigated. The identifiable sensitivity is studied for practical damage identification. TB73 73-Room 203B, CC Joint Session QSR/Energy: Data Analytics in Energy Systems Sponsor: Quality, Statistics and Reliability Sponsored Session Chair: Eunshin Byon, Assistant Professor, University of Michigan, 1205 Beal Avenue, Ann Arbor, MI, 48109, United States of America, ebyon@umich.edu Co-Chair: Arash Pourhabib, Assistant Professor, Oklahoma State University, 322 Engineering North, Stillwater, OK, 74078, United States of America, arash.pourhabib@okstate.edu 1 - Multi-Component Replacement in a Markov Modulated Environment David Abdul-Malak, dta10@pitt.edu, Jeffrey Kharoufeh In this talk we will present a model for jointly replacing multiple components that degrade in a shared, exogenous, Markov modulated environment. Continuous state variables and a high dimensional state space cause the problem to be computationally intractable. To overcome this complication, an approximate dynamic programming (ADP) approach is employed and illustrated through multiple numerical examples. 2 - Importance Sampling with a Novel Information Criterion for Efficient Reliability Evaluation Youngjun Choe, PhD Candidate, University of Michigan, 1205 Beal Avenue, Ann Arbor, MI, 48109, United States of America, yjchoe@umich.edu, Eunshin Byon Importance sampling can significantly accelerate the rare event probability estimation. However, the theoretically optimal sampling requires some approximation in practice, such as the cross-entropy method. We extend the cross-entropy method by incorporating the expectation-maximization (EM) algorithm and deriving a model selection criterion analogous to Akaike information criterion. We apply the proposed method to the reliability evaluation of the wind turbine. 3 - Monitoring Performance of Wind Turbines Based on Power Curve Estimation Hoon Hwangbo, PhD Student, Texas A&M University, College Station, TX, United States of America, hhwangbo@tamu.edu, Andrew Johnson, Yu Ding Quantifying performance of a wind turbine is crucial for decision makings such as turbine upgrade or replacement. Yet, there is a lack of systematic ways to quantify a turbine’s performance, while considering the diverse sources of variation in the energy generation. In this study, we estimate power curves and quantify performance of a wind turbine while controlling for some significant factors of variation. Using the measures we derive, we monitor performance change of a wind turbine over time.

College Station, TX, 77840, United States of America, qianyanjun09@gmail.com, Yu Ding, Jianhua Huang

While in-situ transmission electron microscopy technique has caught a lot of recent attention, one of the bottlenecks appears to be the lack of automated and

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