29 utilisation of simulationfor training enhancement

International Journal of Humanities and Social Science Vol. 1 No. 3; March 2011

Utilization of Simulation for Training Enhancement
O. Sulaiman
Department of Maritime Technology, Faculty of Maritime Studies and Marine
Science University Malaysia Terengganu, Terengganu Malaysia
E-mail: o.sulaiman@umt.edu.my
A. H. Saharuddin
Department of Mritime Management
Faculty of Maritime Studies and Marine Science University Malaysia
E-mail: sdin@umt.edu.my
A.S.A. Kader
Department of Mechanical Engineering
University Technology Malaysia Malaysia
E-mail: absaman@fkm.edu.my

Abstract
Engineering system design, operation and maintenance has been handled for a long time through
mathematical and real time models. The advent of computers, multimedia age and improvement in
visualization has further proved the reality of fact that picture speaks more than words; also research in
education and training has proven that visualization has great effect in improving learning. The complexity of
real world situation of engineering education has obvious limitation of instructional presentation and
training. Simulation gives result from theoretical representation of complex phenomena when hardware for
the task is lacking, or in situations when enough time is not available for explanation. This paper will discuss,
opportunities brought about by simulator as a tool in the training and certification of Malaysian Maritime
Academy cadets training program. The usefulness of simulators in continuous education program to amplify
and enhance competency based education and instructional training to meet goals of safety, cleaner ocean
and protection of marine environment will be highlighted.. The paper will also present the potential of
simulators as training tool in other field of knowledge for enhanced outcome and competency based
education.
Keywords: Simulation; Engineering; competency, complexity, enhancement; safety; education; training
1.0 Introduction
The world of man and the quest for knowledge to facilitate human activities including developing things that
surround us has gone through various phases of development. The early man, used memorization as a tool, and
wrote information on leaves, trees and mountains to store knowledge which was to be passed to the next
generation. The main tools for everything related to learning has likewise gone through various phases of
change and the most significant of these changes has been the emergence of ICT in the last one decade. Today,
the developments in ICT have greatly accelerated the pace of knowledge delivery and the Simulation-Based
studies and training is one typical example of such an evolution. Simulation refers to the application of
computational models for the study and prediction of physical events or the behavior of engineered systems.
The development of computer simulation has drawn resources from a deep pool of scientific, mathematical,
computational, engineering knowledge and methodologies. From the depth of its intellectual development and
wide range of applications, computer simulation has emerged as a powerful tool, one that promises to
revolutionize the way research in engineering and science are conducted in the twenty-first century.
Simulation has long been identifies in several areas of knowledge and it is playing a remarkable role in
promoting developments vital to the health, security, and technological competitiveness of the nation.
Engineering and scientific communities have become increasingly aware that computer simulation is an
indispensable tool for resolving a multitude of technological problems. Basically, computer simulation
represents an extension of theoretical science in that it is based on mathematical models. Such models attempt
to characterize the physical predictions or consequences of scientific theories. With simulation engineers are
better able to predict and optimize systems affecting almost all aspects of our lives and work, including our
environment, our security and safety, and the products we use and export. The use of computer simulations in
engineering science began over half a century ago, but only in the past decade or so has simulation theory and
technology made a dramatic impact across the whole engineering fields. That remarkable change has come
about mainly because of developments in the computational and computer sciences and the rapid advances in
computing equipment and systems.
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Clearly, the use of simulation is quickly becoming indispensable for goal based engineering education.
Simulation is an important feature in engineering systems or any system that involves many processes. Most
engineering simulations entail mathematical modeling and computer assisted investigation. Mathematical
model used to dominate simulation world however mathematical modeling is not reliable and the
incorporation of physical model often helpe to improve today complex system simulation. The development
and use of such frameworks require the support of inter-disciplinary teams of researchers, including scientists,
engineers, applied mathematicians, and computer scientists. Maritime industry due to its nature and need for
safety to maintain Cleaner Ocean has institutionalized and incorporated opportunity offered by simulation to
training of marine personnel to fulfill objective of having competent personnel to man the ships that sail the
ocean of the world.
Encouraged by belief that knowledge, understanding, application and integration which are requirement for
outcome and competency based education could enhance traditional instruction delivery method, through
incorporating audio visual and multimedia tools, led the IMO to adopt resolution to use simulation as part of
STCW requirement. Simulation is thus becoming central to advancement in maritime competency based
training and education as well as educational training in biomedicine, nanomanufacturing, microelectronics,
energy and environmental sciences, advanced materials, and product development. And there is ample
evidence that developments in these new disciplines could significantly impact virtually every aspect of
human experience [1, 2]. This paper explores potentials and prospects of incorporating simulation in
engineering and science education structure. Good practice and experience enjoined by maritime industry
including ALAM will be discussed. The authors will also discuss the core issues of simulation, the major
obstacles to its development and the impact of simulation on training, educational and research.
2. Maritime simulation and simulators
Marine simulators bears similarity to flight simulators, which are used to train pilots on the ground in extreme
hazard situations such as landing with no engine, pilot to crash aircraft without being hurt or complete
electrical or hydraulic failures. The most advanced simulators have high-fidelity visual systems and hydraulic
motion systems. However, marine simulators train ships' personnel, Simulators like these are mostly used to
simulate large vessels. They consist of a replication of a ships' bridge, with operating desk, and a number of
screens on which the virtual surroundings are projected. The complexity of shipping activities from design to
operations training and maintenance remain one of the factors that have made IMO to enact strong regulations
to ensure safety at all times[3].
Due to new issues of imbalance in human activities and environmental behaviors, ship and its operating areas
in closest proximity to ocean that cover two third of the world has further put maritime work a target by public
and land based environmental agencies whose pressure has given IMO further challenges of protection of
environment that has called for new way of doing things based on risk and proactive manner. Simulator is
obviously one of the tools that fit in such proactive measures to prevent accidents as its consequence leads to
serious environmental problems [4,5]. While International laws are best implemented and enforced through
local authorities law, the performance and control are best achieved through third eyes. DNV is one such third
eye under classification society in maritime industry which has laid down some guidelines marine simulators.
Certification of the simulators by DNV ensures that simulator systems have qualified personnel giving
realistic and high quality simulator training conforming to SCTW requirement. Table and 1 and 2 show
approved STCW courses and DNV certified simulation institutions [6,7].
Table 1 - STCW Courses

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Table 2 Approved simulators (manufacturers) – Source DNV classification

However the use and the corresponding training program has been developed on ad hoc basis of individual
training center working with many shipping companies where simulation is often inserted into existing
program rather incorporating simulation as part of the objectives. Neither has there been any standardization
for simulation. The fact is that simulation itself does not train but its benefit to training comes from the way it
is used, it become imperative to make part of training aim and objective that comes with education
requirement. STCW was built on conventional approach that focus on knowledge to determine competency
with oblivion to job task and performance in training that arise from reality of mismatch between training
course and corresponding needs. The ability of simulation fidelity, producing real life task in a safe
environment and provide mitigation option to this where simulation come in as fundamental tool to bridge
gap between theory and application [7, 8].
3. Marine simulation curriculum and training process
In maritime industry, IMO classified simulation under STCW amendment into the following groups:
Category 1 - Full mission capable of simulating full visual navigation including maneuvering.
Category 2 -Multitask - full mission capable of simulating full visual navigation excluding maneuvering ie
radar simulator.
Category 3 -Limited task- capable of simulating environmental for limited extreme conditions.
Category 4 - Special task- capable of simulating maneuvering with operator outside the environment.
Simulation in STCW code is made of two parts, where:
Part A is mandatory and includes the minimum standards of competency for seagoing personnel,
simulator used in both training and assessment. And the requirement for ARPA (Automatic Radar Plotting
Aid - thus simulator equipment being used prior February 1, 2002 may be exempted at the discretion of
parties involved).
Part B deal with guidance to those involved in education, training or assessing the competence under
STCW provision concerning application of various safety and environmental regulation and conformity.
Maritime training is divided into two groups:
i. License – This include experience trainee that undergo additional training designed toward improving
their existing skill, performance and awareness. Such training includes: Watch keeping, ARPA,
Control, Ship resources management, Ship team management, Emergency procedure, Ship handling,
Vessel traffic management, Search and rescue, Area familiarization
ii. Unlicensed- this involved cadets working towards first certificate of competency under standard
structure program. Simulation application for this training includes: Watch keeping, knowledge of
international regulation, Communication, Radar, electronic navigation, main and auxiliary
machineries.
Most of these courses are not actually mandatory, how good it will have been if they shipping company could
incorporate them in their program. Thus recent amendment of STCW recommendation for use of simulation is
a significant stepping stone in this direction. The training should be designed by considering the following:
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i. Training need through identification of gaps between training, required knowledge, skills abilities and
actual knowledge, skills and ability.
ii. Specific training objectives which should include performance measurement
iii. Training method including assessment weather simulation is required to achieve the objective
iv. Total training program
v. Experience of trainee
vi. Level and type of simulation
vii. Instructor qualification and experience
viii. Effectiveness and benefit of the training
Once this is determined a scheme of work which includes: Aim and general objective, trainees and numbers,
structure and schedule.
i. Individual simulation exercise that include specific objective, planning, debriefing session and
instruction to staff on methods of debriefing
ii. Method of assessment
The instructional process itself required the following consideration: Instructional process, Scenario design,
Use of control and monitoring station, and Debriefing technique. Rational for simulation can be stressed out
from the fact that traditional class room method of teaching that use tool like chalk, overhead projector,
occasional use of video material to amplify training objective give unbalanced advantage to instructor to have
direct control that may not entertain training participation. Adding simulation to curriculum and allow the
instructor to fill gap between theory and practical could change this equation. Simulation is expected to have
programmed where and when it will be effective and useful in operation. Apart from concentration on fidelity
of simulation - the degree of realism of simulators and simulation learning process includes the following
factors [9,10]:
i. The progression from easy to more complex and difficult task and operation
ii. The involvement of more than one sense
iii. The need to concentrate interest on single problems
iv. The trainees control of his own activities and possible mistakes
Effectiveness of simulation based depends on the following attributes of simulation that add up to the
advantage simulation has for the future of man and knowledge.
i. Exceptional Bandwidth: The conceptual basis of materials modeling and simulation encompasses all
of the physical sciences.
ii. Elimination of Empiricism: A virtue of multiscale modeling is that the results from both modeling and
simulation are conceptually and operationally quantifiable.
iii. Visualization of Phenomena: The numerical outputs from a simulation are generally data on the
degrees of freedom characterizing the model.
iv. Prediction of the consequences of threats and Countermeasure responses -Extreme engineering
processes such as structural responses, fluid transport of contaminants, power distribution, and
transportation systems, as well as the response of the human population.
4. ALAM`s simulation and simulator experience
ALAM training towards a world class one stop maritime institution aims to deal with challenges of today and
future through ― beyond competency ― partnership with DnV seaskill in order to add value of soft and hard
skill required of marine personal and industry to conform with international local statutory requirements and
often multi-national operations.

.
Figure 1- ALAM`s simulator
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ALAM simulation adds value to competence for ships staffs to be able to plan, define, develop and improve
the competence of employees according to external requirements and established business goals to meet
targets of safer, efficient operations, cleaner ocean and protection of marine environment DNV SeaSkill
Standard for Competence under STCW focus on providing necessary tools and expertise to evaluate the
competence of individuals, through test questions and practical assignments, in relation to specific jobs or
positions wwith competence standards developed with the industry and outlining competence requirements for
given positions; individuals may both be assessed and certified. The program also helps ALAM to recruit
suitable mariners at suitable position good degree of reliability.
ALAM has undertaken a major effort in cooperation with DnV to improve the professional competency
importance of maritime vocational and qualification by basing them on standard of proficiency required in
employment. Towards this end, ALAM simulation is used as required as part of competency assessment on
the ability of trainee to perform on board ship according to standards. Thus it is very important to incorporate
cost comparison for necessary differentiation. ALAM invest on what to be achieved through simulation
training involve task analysis and performance criteria developed to meet trainee and employers needs, IMO
and classification society requirements whose aim concentrate on competency training. However ALAM
invest on what to be achieve
ALAM simulator was built by Transas Marine USA, a simulator manufacturer known for building of state of
the art simulators consisting of Transas Navi-Trainer Professional 3000 full mission ship simulator system
with integrated GMDSS communications simulation capabilities, as well as ARPA/Radar simulator. Transas
Marine‘s unique combination of simulation software, dedicated hardware (real ship controls) and commercial-
off-the-shelf components, the simulator is an ideal tool in the training and certification of Maritime education
programs. The ship simulator, IMO STCW training standards and the latest Det Norske Veritas ‗Standards
for Certification of Maritime Simulator Systems‘ to Class A as well as meet USCG. DnV has certification for
simulators that meet the need of the marine industry quality training solutions.
Transas simulators are based on mathematical model that allows processes to be accelerated without detriment
to physical realism at considerable reduced time. The simulations can be form under the following areas:
i. Full mission Ship - Handling simulation
ii. Engine room simulation
iii. Cargo operations simulation
The simulator has diverse cargo types databases that facilitate selection and on almost all types of cargo for
operation training. Cargo operation simulations include:
i. Large Crude Oil Carrier (LCC);
ii. Liquefied Petroleum Gas (LPG) Carrier;
iii. Chemical tanker (CHT);
iv. Liquefied Natural Gas (LNG) Carrier.
4.1 Full Mission Ship-handling Simulator
The Full Mission Ship-handling Simulator (FMSHS) with capacity to simulate extensive exercise scenarios is
certified by DNV as Class A Standard. Consisting of a single main bridge with nine high resolution projectors,
270° field of view visual scene (with a panning and tilting facilities to provide rear and over-the-side view), an
extensive bridge mockup complete with a full complement of bridge equipment, environmental effects
(consisting of wind, water current, depth, and bank forces), and high-fidelity own ship and passing ship
hydrodynamic effects, the system realistically presents the total marine scene.

Figure 1- ALAM``S Full Mission Simulator
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Three additional cubicle bridges with 120° field of view are similarly equipped to provide interconnected
operation and total ship-handling interaction between the simulators. In addition, one of the cubicle bridges is
equipped with a dynamic positioning system. With a library of more than a hundred geographic databases, 79
ship models and a facility to generate a new geographic database
4.2 Engine room simulator
Built to DNV Class A specification, the Engine Room Simulator (ERS) consist of the machinery space,
engine control room and a computer workstation laboratory. The machinery space is equipped with local
operation stations to provide appropriate indicators and controls for local power plant control. Four 42‖
plasma screens provide an innovative 3D virtual reality of the engine room compartments, the machinery
layout, and the physical realism of the ship environment. The engine control room is equipped with main
engine control console, diesel generator control console and main switchboard console to allow trainees to
operate valves and machinery throughout the engine room. Realistic engine room sounds and alarms are also
simulated in the engine control room to provide aural cues. Equipped with twelve (12) student workstations,
the computer workstation laboratory provides trainees access to a wide variety of equipment and controls
associated with the various power plant and auxiliary system and may be used for both individual and team
instruction. Five engine models provide trainees with comprehensive knowledge of major engine makers like
MAN B&W, SEMT Pielstick, Wartsila Sulzer and Kawasaki Heavy Industry. . When interconnected, the
FMSHS will response in accordance with the ERS models, which have been accurately modeled and
validated.
4.3 Liquid Cargo Operation Simulator
These are designed to conform to latest liquid cargo operation system found on modern ship, the Liquid Cargo
Operation Simulator (LICOS) is equipped with twelve (12) student workstations that provide access to a wide
variety of examples of liquid cargo operation functions and may be used for both individual and team training.
Eight (8) of the workstations have two LCD monitors and the other four (4) workstations are fitted with four
LCD monitors which may be configured as an oil terminal when integrated with the VLCC model for team
training.

ALAM`s Liquid Cargo Operation Simulator
The calculations of tanks, hull strength and ship loading in the simulator are carried out by the Load
Calculator System, which is a real on-board Load Calculator. The Graphics User Interface (GUI) is optimized
for familiarization with the entire system operating principles and for acquiring practical skills in equipment
handling. The main tanker units are implemented as 3D objects, showing cross sections of individual
assemblies. Computer animation is used to display the current processes. Since operations by the bridge team
on the main FMSHS will impact team operations of the ERS, and vice versa, the main Full Mission Ship-
handling Simulator will be fully integrated with the Engine Room Simulator (ERS) to provide team training.
When interconnected, the FMSHS response is in accordance with the ERS models, which have been
accurately modeled and validated - making the ALAM Simulation Center a world-class simulator-based
learning environment [10,11].
5. Benefits of simulation
Benefit offer by incorporating simulation in education are further amplified by the following:
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i. Simulation allows us to explore natural events and engineered systems that have long defied analysis,
measurement, and experimental methodologies. In effect, empirical assumptions will be replaced by
science-based computational models.
ii. Simulation also has applications across technologies—from microprocessors to the infrastructure of
cities.
iii. Simulation methods will lay the groundwork for entire technologies that are only now emerging as
possibilities.
iv. Simulation will enable us to design and manufacture materials and products on a more scientific basis
with less trial and error and Shorter design cycles.
v. Simulation improves our ability to predict outcomes and optimize solutions before committing
resources to specific designs and decisions.
vi. Simulation will expand our ability to cope with problems that have been too complex for traditional
methods. Such problems, for example, are those involving multiple scales of length and time, multiple
physical processes, and unknown levels of uncertainties.
vii. Simulation will introduce tools and methods that apply across all engineering disciplines—electrical,
computer, mechanical, civil, chemical, aerospace, nuclear, biomedical, and materials science. For
instance, all engineering disciplines stand to benefit from advances in optimization, control,
uncertainty quantification, verification and validation, design decision-making, and real-time
response.
viii. Simulator certification benefits training institutions seeking assurance on heavy investments result in
optimal training conditions and marketing of simulator training centers services
In addition to this simulation also offer advantage of:
 Protection against Air Contaminants:
 Optimization of Infrastructures:
 Prediction of Long-Term Environmental Impacts
 Optimization of Emergency Responses
 Optimization of Security Infrastructures for Urban Environments
 Planning of countermeasures
 Prediction of treat and countermeasure responses
5.1 Educational strategies of the future for Engineers and Scientists
Our time has seen significant dramatic expansion of the knowledge base required to advance modern
simulation. The expansion ignores the traditional boundaries between academic disciplines, which have long
been compartmentalized in the rigid organizational structures of today‘s universities. The old silo structure of
educational institutions has become an antiquated liability. It discourages innovation, limits the critically
important exchange of knowledge between core disciplines, and discourages the interdisciplinary research,
study, and interaction critical to advances in simulation.
Today‘s demands nonetheless call for:
i. Citadel of learning to change their organizational structures to promote and reward collaborative
research that invigorates and advances multidisciplinary science. It has also become a matter of need
for universities to implement new multidisciplinary programs and organizations that provide rigorous,
multifaceted education for the growing ranks of simulation trainers and researchers.
ii. Simulation need to be incorporated in our educational discipline as a engineering tool and proponent
life-long learning opportunity
iii. Simulation requires a broad range of interdisciplinary knowledge that tomorrow‘s engineers and
scientists with substantial depth of knowledge in computational and applied mathematics, as well as in
their specific engineering or scientific disciplines. Participation in multidisciplinary research teams
and industrial internships will give students the broad scientific and technical perspective, as well as
the communication skills that are necessary for the effective development and deployment of
simulation education.
iv. Integrating simulation into the educational system will broaden the curriculum for undergraduate
students. Undergraduates, moreover, will have access to educational materials that demonstrate
theories and practices that complement the traditional experimental and theoretical approaches to
knowledge acquisition.
v. Simulation will also provide a rich new environment for undergraduate research, in which students
from engineering and science can work together on interdisciplinary teams.
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vi. As in any entrenched culture, change is hard to come by. To change the culture of separate disciplines
in our universities will require well directed, persistent, and innovative government initiatives.
vii. The necessary changes in educational structure will come without strong directives from leaders from
academia, industry, and government laboratories.
viii. And provide funding for multidisciplinary graduate education programs that offer students simulation
integrated approach of team research and career development.
5.2 Challenges
There are challenges, that need to be faced regaining multiscale and multi-physics modeling, real-time
integration of simulation methods with measurement systems, model validation and verification, handling
large data, and visualization for discipline that want to incorporate it for the first time. It is only by these
challenges involved in resolving open problems associated with simulation. Significantly, one of those
challenges is education of the next generation of engineers and scientists in the theory and practices of
simulation in every subject. There is no doubt that a lot of money will be involved, and research will be
required for specific feed where simulations need to be plugged into the program, But the risk worth taken
research to exploit the considerable promise of Simulation in education. Therefore it also necessary to
provide new cyber -infrastructure that will allow teacher and scientists to pursue Competency and
Objective Based Education and research in new ways and with new efficiency‖ by utilizing [12,13]:
i. high-performance, global-scale networking,
ii. middleware,
iii. high-performance computing services,
iv. observation and measurement devices, and
v. improved of interfaces and visualization services.
Building simulation center require serious consideration of feasibility of developing a parallel programs in
simulation that interfaces to multiple divisions of engineering education in concert with cyber infrastructure.
Progress in simulation will also require the creation of interdisciplinary education teams that work together
on leading-edge simulation problems. A sweeping overhaul of our educational system towards simulation and
initiative for change will not likely come from academia alone; it must be encouraged by the engineering and
scientific leadership and throughout the organizational structure of our universities as well as simulation
institution in industry. The payoffs for meeting these challenges are profound. We can expect dramatic
advances on a broad frontier of knowledge and practice.
The following list is a summary of its current limitations:
i. The development of models is very time consuming, particularly for geometries of complex
engineering systems such as ships, automobiles, and aircraft. Moreover, the determination of material
properties often requires extensive small-scale testing before simulation can be started, especially if
statistical properties are needed. This testing also lengthens the time to obtain a simulation and hence
the design cycle.
ii. Methods are needed for linking models at various scales and simulating multi-physics phenomena.
iii. Simulation is often separate from the design optimization process and cannot
iv. Simultaneously deal with factors such as manufacturability, cost, and environmental impact.
5.2 Overcoming the challenges of now
As design processes increasingly rely on computer simulation, validation and verification procedures will
become increasingly important. Although some efforts have been made at providing validation benchmark
problems for linear analysis, nonlinear simulation software has not been subjected to extensive validation
procedures. Clearly, a basic understanding of verification and validation procedures is urgently needed. After
all, to be useful, the simulation tools used by industry and defense agencies must provide reliable results.
Furthermore, since many real-world phenomena are not deterministic, statistical methods that can quantify
uncertainty will be needed. Design optimization is also in its infancy, and it too has many obstacles to
overcome. The constraints on the optimization of a product design relate to manufacturability, robustness, and
a variety of other factors. In order to be effective for engineering design, optimization methods must be
closely coupled with simulation techniques[13,14]. Overcoming the barriers behind simulation will require
challenges and progress in our basic understanding and in the development of powerful new methods. Among
these challenges are the following:
i. Multiscale methods that can deal with large ranges of time and spatial scales and link various types of
physics.
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ii. Methods for computing macroscopic phenomena, such as material properties and manufacturing
processes, in terms of subscale behavior.
iii. Effective optimization methods that can deal with complex integrated systems, account for
uncertainties, and provide robust designs.
iv. Frameworks for validation, verification, and uncertainty qualification.
v. Methods for rapidly generating models of complex geometries and material properties.
vi. Multiscale methods will provide extensive benefits.
The following are a few of the areas requiring development:
i. • Quantitative models of the processes to be simulated must be developed. For many of those
processes, models of some level of fidelity already exist, or they are being developed for narrower
engineering purposes.
ii. • A comprehensive simulation system is required that integrates detailed models of a wide range of
scales. The comprehensiveness of the simulation system is a requirement if simulation in education
applications is to simulate multiscale complex systems. Some of the issues are generic, but others are
problem specific.
iii. • New models of exceptional fidelity are required. The development and validation of such models
entail the acquisition of data of extraordinary detail.
iv. • A better understanding of the role of uncertainty is required. Some degree of uncertainty is
inevitable in the ability of a model to reflect reality and in the data the model uses. We need to find
ways to interpret uncertainty and to characterize its effects on assessments of the probable outcomes.
Generally, however, we still lack a fundamental understanding of what constitutes an optimal design and how
to find it in a complex multi-criteria design environment. Once optimization methods are developed that can
deal with these complexities, we can expect to see chemical plants, automobiles, laptop. Simulation has the
potential to deliver, within a short design period, designs that are optimized for cost performance and total
impact on the environment.The rewards of meeting those challenges are great: enhanced efficiency, security,
safety, and convenience of life in the digital, infrastructure, city and ecosystem, a social infrastructure of
unparalleled efficiency, rational responses to natural events and optimal interactions with natural
environments.
6. Conclusion
The need for Simulation based education is at a crossroads in our global technological development. For
almost half a century, developments in mathematical modeling, computational algorithms, and the technology
of data intensive computing have led to remarkable improvements in the health, security, productivity, quality
of life, and competitiveness of nations. We have now arrived at an historic moment where simulation is the
key elements for achieving progress in engineering and science. The challenges of making progress, however,
are as substantial as the benefits. We must, for example, find methods for linking phenomena in systems that
span large ranges of time and spatial scales. We must be able to describe macroscopic events in terms of
subscale behaviors. We need better optimization procedures for simulating complex systems, procedures that
can account for uncertainties. We need to build frameworks for validation, verification, and uncertainty
quantification.
In today‘s competitive world, in order to b at the frontier of knowledge it has become important to explore the
possibility of incorporating in our engineering educational system to reflect the multidisciplinary nature of
modern engineering and to help students acquire the necessary modeling and simulation skills. Thus
simulation required good computer speed, funding and efficiency. However, this barrier can be solved by
promoting interaction between multiple disciplines that fit naturally and strategically in parallel with or within
the Cyber infrastructure framework. Simulation definitely has the potential to deliver designs that are
optimized for cost performance and their total impact on the environment (from production to disposal or
recycling), all within a short design cycle. This achievement is not possible, however, simply by extending
current research methods and taking small, incremental steps in simulation based education development. The
barriers to the realization of simulation in education relate to our entire way of conducting research
development and educating engineers. Other field of engineering can surely use experience of the shipping
industry as a guide to incorporate simulation in education work.
Reference
1. Down, D.F., and R. Mercer. 1995. ―Applying Marine Simulattion System To Improve Mariner Professional
Development ―. In the proceeding PIANC, Port `95, TAMPA Florida , March 1995
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2. Roger D. Smith: "Simulation: The Engine Behind the Virtual World", eMatter, December, 1999
3. Gynter, J.W., TJ Hammell, J.A. grasso, and V.M. Pittsley. ―Simulator for Marine Training & Licensing:
Guidelines For Deck Officer Training Systes. CAORF, 1948
4. Johnson, C., Moorhead, R., Munzner, T., Pfister, H., Rheingans, P., and Yoo, T. S., (Eds.); NIH-NSF
Visualization Research Challenges Report; IEEE Press, 2006.
5. Hammel, T.J.) . The Training Derive Is More Than A Simulator. Proceeding internatonal coference on marine
simulation, 1981
6. Aldrich, C. (2003). Learning by Doing: A Comprehensive Guide to Simulations, Computer Games, and
Pedagogy in e-Learning and Other Educational Experiences. San Francisco: Pfeifer — John Wiley & Sons
7. STCW 95:STYCW Convention , IMO London
8. Johnson, C.R., ―Top Scientific Visualization Research Problems‖, IEEE Computer Graphics and Applications,
pp. 2-6, July/August 2004
9. Hays, R.T. & Singer , MJ.‖Simulation fidelity in Training System Design – Bridging the gap between reality
and Training ―New York , 1989
10. Percival, F., Lodge, S., Saunders, D. The Simulation and Gaming Yearbook: Developing Transferable Skills in
Education and Training. London: Kogan Page, 1993
11. Deutch, Christian ―From Work Analysis Tool To A Training Simulator: The Realism Of Teaching Tools, 1993
12. Paramore, B and P King, ―Study Of Task Performance In Report Of Collision, Rammings, Grounding In
Harbors And Entrance‖, USACE, 1979
13. P. Humphreys, ―Extending Ourselves: Computational Science, Empiricism, and Scientific Method. Oxford:
Oxford University Press, 2004
14. Wolfe, Joseph & Crookall, David, ―Developing a scientific knowledge of simulation/gaming‖ . Simulation &
Gaming: An International Journal of Theory, Design and Research, 1998

Appendix
Table 3 - Simulation Product Types

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