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2 172.8 ⋅H 1 ⎪⎧ ⎪⎫ −5 − 691.2 3 −4 S ζ ( ω) = ⋅ω ⋅ exp ⎨ ⋅ ω 4 4 ⎬ (1) T1 ⎪⎩ T1 ⎪⎭ ω p (2001). 2 π = , the modal frequency, T1 = 0. 772 ⋅Tp , transformation from mean to peak period, Journée T p 3. Ship responses in waves Response amplitude operators (RAOs) and response functions for the added resistance due to waves (RFs) were employed for the evaluation of the ship performance in waves. Both have been calculated prior to the optimization by means of the strip theory code SEAWAY, Journée (2001), based on potential theory. Besides RAOs for the center of gravity motions for all six degrees of freedom and RAOs for the motions of selected points also relative to the free surface, two different methods are available to determine the added resistance due to waves: The radiated energy method of Gerritsma and Beukelman and the integrated pressure method of Boese, Journée (2001).The numerical results used within the optimization procedure are: • The RAOs of the translatory motions on the bridge (calculation of the loading on the crew by means of accelerations). • The RAOs of the motion relative to the free surface (calculation of the slamming probability). • The RFs for the added resistance due to waves (preferably according to the integrated pressure method which displays a smoother distribution over the wave frequency ω than its radiated energy counterpart). Fig.1 shows the RAOs of motion on the bridge, relative motion at the bow and the RFs of the added resistance due to waves as computed with SEAWAY. The plots serve to illustrate the input to the response simulations within the route optimization. 3.1. Ship motions Fig.1: RAOs of motion on the bridge, relative motion at the bow and the RFs of the added resistance due to waves The product of the wave spectrum S ζ and a squared RAO of the considered motion yields the response spectrum of the ship motion S s : ( ω) = RAO ⋅S ( ω) S s 2 ζ (2) Taking into account the ship velocity, this operation has to be performed with all involved terms 28
expressed as functions of the wave encounter frequency ω e . Generally the n th moment of the response spectrum is built with: ∞ ∫ ∞ n ( ω e ) ⋅ω e dω e= ∫ Ss( ω ) mn s = Ss ⋅ω e dω (3) 0 0 n The significant amplitude of the acceleration is determined with the following approximate formula provided by probability calculations: & (4) 1 = ⋅ 3 sa 2.0 m4 s This can be applied to determine the acceleration on the bridge for instance. 3.2. Slamming Slamming can be defined as the coincidence of two events: the emergence of the bow and its subsequent dunking above a critical velocity. The critical velocity according to Ochi, Journée (2001), is: s& = 0. 0928 ⋅ g ⋅L (5) cr pp Presuming statistical independence of these events the probability of slamming is calculated from: P { slam} ⎪⎧ −D = exp ⎨ ⎪⎩ 2 m0 2 s rel −s& + 2 m 2 cr 2srel ⎪⎫ ⎬ ⎪⎭ (6) Where m 0srel and m 2srel are the 0 th and 2 nd moment, respectively, of the response spectrum for a point on the keel line 10% behind the forward perpendicular FP, D being the draught 10% behind FP. 3.3. Fuel consumption The added resistance due to waves is calculated from: ∞ ∫ 0 ζ ( ω ) R AW = RF ⋅S dω (7) The determination of the calm water resistance is based on a regression analysis of model tests and full-scale data, following Holtrop and Mennen (1984).The operating point of the propeller was calculated according to the ITTC (1978) power prediction method, using the characteristic of a propeller with the same diameter, number of blades, similar pitch and blade area ratio as given in Yasaki (1962). In a final step the fuel consumption and the compliance with the permitted operating condition was determined in agreement with the project guide available from the producer of the ship's main engine, MAN B&W (2000). 4. Setting up of the optimization task Simply put, automated optimization is the formal process of finding a good (the best) solution from a set of feasible alternatives. It requires a complete mathematical problem formulation in terms of objective functions (what is to be improved), free variables (what shall be consciously changed) and constraints (what restricts the feasibility). 29
Page 1 and 2: 3 rd International Conference on Co
Page 3 and 4: Patrick Hupe, Uwe Langbecker, Mubas
Page 5 and 6: Towards Intelligent Simulation-Base
Page 7 and 8: ectly damage in terms of greenhouse
Page 9 and 10: Fig.7: FEA of a catamaran made of c
Page 11 and 12: Set the small parts fixing the part
Page 13 and 14: main benefit of 3-d design lies in
Page 15 and 16: Applic. Mar. Industries, COMPIT, Ha
Page 17 and 18: Use of Genetic Algorithms in Propel
Page 19 and 20: 3. Fitness Function Formulation The
Page 21 and 22: where µ α and µ θ are the chose
Page 23 and 24: From another point of view and unde
Page 25 and 26: Y X Benchmark First Optimum Fig.8:
Page 27: A Systematic Study on Posing and So
Page 31 and 32: 4.4. Optimization with modeFRONTIER
Page 33 and 34: Fig.5: SIMPLEX optimization and Par
Page 35 and 36: References HOFFSCHILDT, M.; BIDLOT,
Page 37 and 38: 2.2. Tribon Product Information Mod
Page 39 and 40: 3. New Process The new process is b
Page 41 and 42: 4. Conclusions and next step The ne
Page 43 and 44: 2. E-Commerce of goods versus servi
Page 45 and 46: Main steps on ePING’s road-map ar
Page 47 and 48: anon. client new client registered
Page 49 and 50: Preparing an offer can be hierarchi
Page 51 and 52: Acknowledgment This work was partia
Page 53 and 54: The focus within this paper is the
Page 55 and 56: conditions have to be prevented. Fo
Page 57 and 58: Ship 2 LPP 182.390 m B 26.00 m T D
Page 59 and 60: Fig.9: Ship 1; Simulated Crash stop
Page 61 and 62: Using Simulation in Evaluating Bert
Page 63 and 64: ship. To shorten the time spent by
Page 65 and 66: travelled by each SC are totalled t
Page 67 and 68: around time is the highest against
Page 69 and 70: to alternative berths instead of pl
Page 71 and 72: Appendix 1: Data Collected from Con
Page 73 and 74: Abstract Introduction to BALTPORTS-
Page 75 and 76: - at the level of operational plann
Page 77 and 78: - External interoperability - In ad
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5. Setting up of the Baltic Sub-Reg
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Robot Applications in the Field of
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Fig.3: The main components of the D
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The precision of the process depend
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The frame is further divided into 2
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1. Periodicity on the time line, pe
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Quality measures. Let J be the inst
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6.2 Mutation A random number out of
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7.1 Adaptation of Theorem 2 in our
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8. Conclusions and scope for future
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meet the needs of the user. Typical
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2-digit level (e.g., 220 - Engineer
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eviewed in dialogue boxes and on Ex
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Fig.3: Example tanker (HMI BRENTON
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Fig.7: Assigned material tabular en
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Fig.11: Design ship 2-digit SWBS Re
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Communication in Ship Design Networ
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number and volume of communicated i
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The investigated collaborations are
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The four principle communication pa
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6. Information content In design cl
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References ERIKSTAD, S.O., HAGEN, A
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intensive. The terminal's own drive
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A distribution of decision competen
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the order for planning the task to
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3.400.000 Total costs 3.200.000 3.0
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Visualisation of Ship Motions in Wa
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3.3. Panelisation and information e
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5.2. 3D visualisation Fig.4: Refere
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6.2. Examples of the visualisations
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7. Conclusions The presented toolki
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Fig.2: Possibilities for robotic in
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Experiments with the underwater cam
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Fig.13. and 14: Cleaning of the cha
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Acknowledgements The authors want t
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Fig.2: Result of Industrial Enginee
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2. Industrial engineering system fo
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4. Next steps In the next phase, th
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organizations and organizational un
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artifact’s context and extend the
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We take the ship survey process, wh
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device multimedia capabilities: Sur
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4. Future Work The mobile services
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FEM Supported Alignment of Power Tr
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2.2. Causes First researches result
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Fig.5: Sufficient tooth grip patter
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4. Alignment of a RoRo vessel’s p
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4.3. Calibration/Validation of the
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Optimisation of the Survivability o
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Table I: Current UK & US Damage Sta
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Fig.2: Damage Density Distribution,
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An Air-to-Surface Missile (ASM) is
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length according to the existing re
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the use of a stochastic optimizatio
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Each MOGA loop requires approximate
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JIASIONOWSKI, A. (2002), An integra
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Design problems are typically chara
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o planned: systematic; o ad-hoc: op
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o Provide justification for decisio
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o o o o o o Guide the user through
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- for some systems, the initial com
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feasible. The practical implementat
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PARK, J.H.; STORCH, R.L. (2002), "O
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where: a, b - coefficients (weights
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C Fig.2: The fuzzy domain of the bu
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5.2. Ship fuzzy domain in an open a
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PIETRZYKOWSKI, Z. (2003a), Modellin
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means that the number of intersecti
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4. Manipulation of Sets of Data Poi
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Fig.2: The selection function defin
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Let us define the root node of a se
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Fig.4 took up to several minutes on
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Applying Meta-Models to the Probabi
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The assessment of the damage stabil
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Fig.1 shows clearly an important ch
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one is willing to do, the smaller t
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Depending on the number of simulati
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Since none of the points of the lat
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CHEN, S.; WANG, L.; WU, X.; WANG, X
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alance between ship resistance and
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frequent movements of the pitch tha
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"commanding" by itself since a vari
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The numbers shown in the 3 rd row o
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angle of attack of the water flow o
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stationary, i.e. all variables rema
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the engine map runs through the ove
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References GRIMMELIUS, H.T.; STAPER
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their output to be random too. Runn
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simulation runs. It typically takes
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When the system initiates, the star
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The user is guided through various
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• Port Planning & Development •
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Knowledge-based Concurrent Engineer
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or puts components aside to make mo
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Technical specs Make preliminary ca
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ios, and knowledge about the design
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are applied afterwards, they can be
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calculations etc.) The product rela
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For finding the dependency of reque
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GIASSI, A. (2003), Multidisciplinar
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already mentioned. It is based on t
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2.2.2 Geometry Geometry covers the
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2.3 Simulation The simulation engin
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As far as the simulation engine inc
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time results. Table I: Mustering ti
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simulation means. The required time
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design consultants. Starting from a
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different severity, e.g. warning or
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• Execute calculation (including
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and ghostscript, Gnuplot, Ghostscri
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References CASTOR; An open source d
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an accurate description of a densit
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(a) UDS and CDS Schemes (b) Gamma S
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Figure 3: Typical unstructured grid
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(a) 0 degree (b) 5 degrees - Port s
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(a) Computations (b) Experiments Fi
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(a) X/L = +0.10 (b) X/L = +0.20 (c)
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4 Conclusion This paper has describ
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State of the art in climbing and wa
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2.1 REST 1 and REST 2 climbing robo
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Figure 5: ROWER 1 system. The full
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Acknowledgements The REST climbing
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X X X X X X X X Z Z Z Z Z Z Z Z Y Y
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30 25 20 Conjugate gradient 30 25 2
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CARENA is a naval architectural sof
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Fig.6: Cargo vessel carrying “spe
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used especially for shape optimizat
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easily given as simple auto-update
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and mutation concepts for evolving
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govern agents’ interaction with t
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Create generation behaviour Sequent
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Side Casing Hoister Deck Car Deck C
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The selection of the best individua
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Appendix A Table A-I: Optimisation
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2. Project Management tools in ship
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Fig.1: Example of document properti
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Fig.4: Example of query view on doc
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The Product Data Management is comp
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Abstract Applications of Self-Organ
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EMERGENT GLOBAL STRUCTURE LOCAL INT
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dynamically structured, the system
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After a leakage has been detected,
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EXIT door door corridor exit device
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adaptive. Furthermore, from a imple
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The main objective for our approach
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LUCAS, C. (2003), Self-organizing s
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• As a result of the above-mentio
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Table I: Exemplary matching of Refe
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Yard Program time Mile-stone Plan d
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In the following we start with a di
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Material Information Machines Proje
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module (SpaceMan) supports the allo
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ÑÓÖ ÙÖØÐÝ¸ Ö Ó ÓÚÖ
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10 10 Exp ANN Exp ANN 7.5 7.5 Cr [x
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7 Cr [x 1000] 6 5 4 3 2 0.2 0.4 0.6
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Automation Tools in the Design Proc
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Fig.1: Visual LISP integrated devel
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• Bentley’s adoption of VBA •
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To these outstanding features, it h
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4.2.1. Automation The objective of
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• Direction of the start of the c
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• The FDE program processes the p
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Database access The FORAN System us
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A Heuristic for the Container Pre-M
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When they arrive in the terminal ya
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(3) The number of all badly placed
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still greater than zero, the minimu
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• For each dirty stack s exactly
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in the remaining 7 instances no mor
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DOF motion. Then, alter the input f
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learn of any delay that can occur b
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40 20 30 10 x-x0 (m) 20 roll (deg)
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Since, among the velocity component
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Y (m) -1700 -1500 -1300 -1100 -900
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system framework, the details of it
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Real-time Nonlinear Simulation (RNS
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design modifications are made, and
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Evacuation Notation - a New Concept
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• r(t): response time, which acco
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• The time tk: the time correspon
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5.1. Quantitative assessment Quanti
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Table 2: Summary of total and model
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notation: besides an objective asse
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Neural Networks Model for Ship Mane
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&r V G • • r = a = ( uî & & +
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V a Estimating Forces F Calculating
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Fig. 5: Error variation for the net
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Fig 8: Ship's path in Zigzag test 3
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[4] ALMAN, P.R., BERTSCHE, W.R., BO
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2 Numerical Methods RANSE methods l
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As a conclusion of these parameter
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For correlation of propeller data t
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quadratic functions result in littl
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Index by authors Abels 470 Akinfiev
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