Maritime-Port Technology and Development

247 Pages·2014·6.232 MB·English

by  Sören Ehlers, Bjorn Egil Asbjornslett, Ornulf Jan Rodseth, Tor Einar Berg

Maritime-Port Technology and Development contains the latest Editors: Maritime-Port
Ehlers
research results and innovations as presented at the 2014 International
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Maritime and Port Technology and Development Conference
Rødseth
(Trondheim, Norway, 27- 29 October 2014). The volume is divided into & Berg
Technology and
a wide range of topics:
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• Efficient and environmentally friendly energy use in ships and ports
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• Demanding and safe maritime operations and intervention t
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• Maritime transport and operations in the Arctic
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• Remotely controlled and monitored shipping, traffic surveillance
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• Port-ship interface optimization
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• Effective port infrastructure
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• LNG and other novel fuels: Distribution and use e
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• Optimization in maritime logistics, fleet and vessel design h
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Maritime-Port Technology and Development contributes to
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efficiency and reliability of seaborne transport and operations,
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and will be useful to academics and engineers involved in marine y

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Editors: Sören Ehlers, Bjørn Egil Asbjørnslett,
Ørnulf Jan Rødseth & Tor Einar Berg
an informa business
MTEC cover FINAL.indd 1 03-09-14 14:26
MARITIME-PORT TECHNOLOGY AND DEVELOPMENT
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PROCEEDINGS OF THE CONFERENCE ON MARITIME-PORT TECHNOLOGY (MTEC 2014),
TRONDHEIM, NORWAY, 27–29 OCTOBER 2014
Maritime-Port Technology
and Development
Editors
Sören Ehlers & Bjørn Egil Asbjørnslett
Norwegian University of Science and Technology (NTNU), Trondheim, Norway
Ørnulf Jan Rødseth & Tor Einar Berg
Norwegian Marine Technology Research Institute (MARINTEK), Trondheim,
Norway
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CRC Press/Balkema is an imprint of the Taylor & Francis Group, an informa business
© 2015 Taylor & Francis Group, London, UK
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Published by: CRC Press/Balkema
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ISBN: 978-1-138-02726-8 (Hbk + CD-ROM)
ISBN: 978-1-315-73162-9 (eBook PDF)
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Maritime-Port Technology and Development – Ehlers et al. (Eds)
© 2015 Taylor & Francis Group, London, ISBN 978-1-138-02726-8
Table of contents
Foreword vii
Congestion and truck service time minimization in a container terminal 1
D. Ambrosino & C. Caballini
A dynamic discrete berth allocation problem for container terminals 11
M.M. Gargari & M.S.F. Niasar
Ontology based management of maritime rules and compliance 19
M. Hagaseth, Ø.J. Rødseth, P. Lohrmann, D. Griffiths & M. Seizou
Maritime Single Windows: Lessons learned from the eMAR Project 27
I. Koliousis, P. Koliousis & T. Katsoulakos
A study on estimation methodology of GHG emission from vessels by using energy
efficiency index and time series monitoring data 35
T. Kano & S. Namie
A pathway towards more sustainable shipping in 2050: A possible future
for automation and remote operations 43
G. Manno
Ship retrofit solutions: Economic, energy and environmental impacts 57
R. Aronietis, C. Sys & T. Vanelslander
Model and simulation of operational energy efficiency for inland river ships 67
X. Sun, X.P. Yan & Q.Z. Yin
Reinforcing existing port facilities to withstand natural disasters: An analysis
of increased construction costs 73
K. Takahashi, Y. Kasugai & I. Fukuda
Designing an autonomous collision avoidance controller respecting COLREG 83
H.-C. Burmeister & W. Bruhn
A generic modelling approach for heavy lifting marine operations 89
J. Xu & K.H. Halse
Model Predictive Control of a waterborne AGV at the operational level 99
H. Zheng, R.R. Negenborn & G. Lodewijks
Estimation of Dynamic Positioning performance by time-domain simulations—a step
toward safer operations 109
D.T. Nguyen, L. Pivano & Ø. Smogeli
Possibilities to determine design loads for thrusters and drivetrain components using
the flexible multibody-system method 117
B. Schlecht & T. Rosenlöcher
Computational Fluid Dynamics simulations of propeller wake effects on seabed 125
V.T. Nguyen, H.H. Nguyen, J. Lou & L. Yde
Enhanced electrochemical performance in merged olivine structured cathode materials 133
S. Saadat & R. Yazami
v
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Sea trials for validation of shiphandling simulation models—a case study 141
Ø. Selvik, T.E. Berg & S. Gavrilin
Anti-corrosion method for marine steel structure by the calcareous deposits 147
T. Iwamoto, Y. Suzuki, K. Ohta, K. Akamine & Y. Yamanouchi
A risk based approach to the design of unmanned ship control systems 153
Ø.J. Rødseth & Å. Tjora
Offshore upstream logistics for operations in arctic environment 163
A.-S. Milaković, S. Ehlers, M.H. Westvik & P. Schütz
An evaluation of evacuation systems for arctic waters 171
O.E. Staalesen & S. Ehlers
An approach towards the design of robust arctic maritime transport systems 185
M. Bergström, S. Ehlers & S.O. Erikstad
Defining operational criteria for offshore vessels 193
T.E. Berg, Ø. Selvik & B.O. Berge
Real time ship exhaust gas monitoring for compliance to SO and NO regulation
x x
and CO footprint 201
2
T. Wijaya, T. Tjahjowidodo & P. Thepsithar
Modelling of LNG fuel systems for simulations of transient operations 205
E.L. Grotle, V. Æsøy & E. Pedersen
Future Internet enabled ship-port coordination 217
A. Rialland & Å. Tjora
Ship port pre-arrival reporting and ship survey status as eMar services 227
E. Vanem, D. Yarmolenka & G. Korody
Author index 237
vi
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Maritime-Port Technology and Development – Ehlers et al. (Eds)
© 2015 Taylor & Francis Group, London, ISBN 978-1-138-02726-8
Foreword
We are pleased to host the International Maritime and Port Technology and Development Conference in
Trondheim, Norway, in 2014. This conference has served in the past as an important and internationally
recognised platform to disseminate the latest research results in the field of Maritime and Port Tech-
nology and Development with strong contributions in the field of efficiency and reliability of seaborne
transport and operations.
The preparations of this conference and proceedings would not have been possible without the support
of the numerous reviewers and the efforts of Martin Bergsröm, Jitapriya Das, Boris Erceg, Sandro Erceg,
Aleksandar-Sasa Milakovic and Drazen Polic in formatting the manuscripts where needed. Furthermore,
we would like to thank the steering committee for promoting and supporting the conference. The financial
support of our sponsors is greatly acknowledged. Finally, we are wishing all participants a fruitful, stimu-
lating and professionally rewarding stat and the Marine Technology Center in Trondheim, Norway.
Sören Ehlers
Ørnulf Jan Rødseth
Tor Einar Berg
Bjørn Egil Asbjørnslett
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Maritime-Port Technology and Development – Ehlers et al. (Eds)
© 2015 Taylor & Francis Group, London, ISBN 978-1-138-02726-8
Congestion and truck service time minimization in a container terminal
D. Ambrosino
DIEC-Department of Economics and Business Studies, University of Genova, Italy
C. Caballini
DIBRIS-Department of Informatics, BioEngineering, Robotics and Systems Engineering,
University of Genova, Italy
ABSTRACT: The objective of this paper is to address the minimization of truck service times at con-
tainer terminals while respecting a certain level of congestion. Truck congestion at terminal gates is a
major concern for container terminals, especially considering the increasing volumes of goods they have
to manage. Truck arrivals, if not properly managed, can result in long queues of trucks, decreasing their
service level and can lower the terminal productivity, affecting all the other areas of the terminal. The
terminal road cycle is described through some mathematical relations implemented in a spreadsheet; these
relations are the basis of a decision support system that, for each truck having executed the check-in,
decides if it should be allowed to enter the terminal and, if yes, which service level it will be given. Based
on a big container terminal located in Northern Mediterranean, the proposed approach has been suc-
cessfully tested on different scenarios, with different level of terminal congestions, yard filling and trucks
arrivals. The results obtained have shown that the tool is able to effectively reduce congestion inside the
terminal by indicating if a truck can enter the gate in order to be served within a predetermined service
time, or if it has to stop outside due to the high congestion level inside the terminal. Moreover, a series
of KPIs have been defined and analyzed to assess various scenarios which differ in the number of truck
arrivals and in the initial state of the terminal; this evaluation also enables to size the number of equip-
ment needed by the container terminal in order to properly carried out all its operations.
1 INTRODUCTION terminal performances. For this reason, advanced
methodologies should be found in order to guaran-
The increasing volume of goods passing through tee a certain level of service to trucks while both not
ports, and more general logistic nodes, imposes to decreasing terminal throughput and productivity,
carefully manage trucks at port gates and inside and not generating negative externalities (environ-
terminal areas in order to guarantee short and cer- mental pollution, social congestion, noise, etc.).
tain service times to road transport and, at the same Congestion issues at container terminals have
time, to not affect the productivity of all the other been addressed by several authors in the past few
activities inside the terminal (ships, trains, etc.). years. Chena et al. (2013) tried to reduce gate con-
Big container terminals, managing up to and gestion by applying the Vessel Dependent Time
beyond one million TEUs per year, can have to Windows (VDTWs) method to control truck
handle 1500–2000 trucks per day. Unluckily, this arrivals. Han et al. (2008) developed a model and
flow of trucks, is not uniformly distributed along a tabu search heuristic to decrease traffic conges-
check-in hours unless particular systems are imple- tion of prime movers inside a container terminal.
mented. During a day, high flow peaks usually Zehendner & Feillet (2014) proposed to reduce
occur, risking to cause high congestion and delays truck turnaround and, consequently, terminal
both to trucks and to the other transport means congestion, by developing a mixed integer lin-
of the terminal. Truck appointment systems allow ear programming model devoted to size a Truck
terminals to know in advance the trucks that will Appointment System (TAS). They simultaneously
arrive at the terminal gate in each time window of determined the number of truck appointments to
the day. However, these functionalities may cause offer and allocates straddle carriers to different
other organizational issues as stressed in (Sharif transport modes. Also Zhang et al. (2013) provided
et al., 2011). an optimization model for truck appointments, by
Hence, if not properly managed, the truck cycle developing a BCMP queuing network to describe
in a container terminal can strongly affect overall the queuing process of trucks in the terminal.
1
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