Informs 2015

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INFORMS Philadelphia – 2015
308
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,
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,
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,
, 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,
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,
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,
Co-Chair: Yu Ding, Professor, Texas A&M University, ETB 4016,
MS 3131, College Station, YX, United States of America,
1 - Multi-stage Nanocrystal Growth Identifying and Modeling via
in-situ TEM Video
Yanjun Qian, PhD Candidate, TAMU, 1501 Harvey Rd, Apt. 806,
College Station, TX, 77840, United States of America,
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
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, 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, , 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,
Co-Chair: Arash Pourhabib, Assistant Professor, Oklahoma State
University, 322 Engineering North, Stillwater, OK, 74078,
United States of America,
1 - Multi-Component Replacement in a Markov
Modulated Environment
David Abdul-Malak, 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,
, 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, ,
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.
TB70