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SimFWD is a research, development and application company, providing engineering services in the transport and construction industries. The company focuses on computer aided engineering technologies such as CFD and FEM applied to Ship Design. SimFWD can provide turnkey solutions to complicated generic problems in a cost effective manner, eliminating the overheads normally associated with a dedicated engineering analysis group or department. SimFWD aims at helping customers develop product designs and processes by supplying them with customized engineering analysis and software solutions, www.simfwd.com.
Ioannis Andreou is currently finalizing his internship at SimFWD for his studies in ENSTA-Bretagne University and his Master of Research in Advanced Hydrodynamics. Main task of his internship was to develop further the company’s series of Ropax hullforms. SimFWD has been developing modular Ropax designs to address a range of ship sizes for various operational needs. The first part of the project is the validation of fully parametric Ropax hullform for the range of 120-140m.
Objective 1: to calculate the calm water resistance of a modern Ropax hullform (140m overall length). The hullform is part of SimFWD’s series of Ropax hull specifically designed to combine low environmental footprint with enhanced safety standards. Listed below are the main dimensions:
L.O.A.: 140.00 (m)
Breadth: 23.00 (m)
Service Speed: 26.00 (kn)
Draught: 5.700 (m)
Block Coefficient (T=5.70): 0.57
Objective 2: for the intern engineer at SimFWD to get familiar with the use of FINE™/Marine in an UberCloud application software container and compare the cost benefit in to in-house resources currently in use. The benchmark was analyzed on the bare-metal cloud solution offered by CPU 24/7 and UberCloud. All simulations were run using version 5.1 of NUMECA’s FINE™/Marine software. SimFWD has carried out the set-up of the FINE™/Marine model and simulation parameters, with the goal to generate an initial Power Curve in short time as well as retrieving the effect of small changes on the ship’s bulb design.
CHALLENGES AND BENEFITS
This case study was completed without facing any difficulties whatsoever. The entire process right from the access to files in the UberCloud container, running the jobs in the CPU 24/7 cloud, up to the retrieval of results to a local workstation was very convenient and without any delays. The userfriendliness of the interface was a major advantage!
SIMULATION PROCESS AND RESULTS
Computations on the hullform were performed for 4 different speeds – 20kts, 22kts, 24kts and 26kts. All computations were performed using a fluid domain consisting of approximately 1.8 million cells except for a speed of 22kts, where a finer mesh containing approximately 2.5 million cells was additionally computed.
Fig. 1 Automatic Mesh Set-Up through C-Wizard Shown
Fig. 2 Travelling shot at 26knots: Wetted Surface 1919.96 m²
|Parameters | Speeds||26.0 kts|
|FINE™/Marine global, Resistance||Units|
Fig. 3 Wave Elevation along hull length X
Fig. 4 Streamlines colored by the relative velocity
HULL PRESSURE EFFECTS
The bow hull pressure has a normal distribution over the most affected regions, bow front, and stem near the waterline entrance.
Fig. 5 Overall Hull Pressure
Fig. 6 Flow streamlines on the hull
Following are some details regarding the simulation setup:
Number of time steps: 1500
Number of non-linear iterations: 5
UberCloud has provided a 16-core container, the average computation time on 16-cores for each speed was approximately 4hours, however most of the computations at lower speeds converged faster. This proved that FINE™/Marine is also efficient from a scalability point of view.
As a next step we utilized the parametric geometry model to make small feasible changes on the Bulbous Bow shape in order to assess the performance effect on the ship’s most prominent operational speed throughout the year at around 22 knots. Below is a comparison of wave elevation on the front area after altering the bulb design. At the left side of Figure 7 is the case of the revised bulb and on the right for the standard case, and we see that the results are almost the same, except for the revised bulb case where the waves that are presented on the mass fraction are smoother. A small change in the bulb shape and the corresponding volume present a decrease of almost 5% for the operational speed of 22 knots while decrease for the higher speeds is marginal.
Fig. 7 Wave Elevation Comparison after Bulb alternation
Fig. 8 Wave Elevation Comparison at 22Knots View from Below
The range of computations converged well for all speeds and the overall result was deemed as reliable prediction for the range of bare hull resistance also compared to empirical results and similar designs. This allows the user to set the boundaries on their Initial design process and work towards the next steps with exploring hull modifications by formal or even automated optimization processes. Results have also given valuable insight into available margin to optimize wave resistance at the bow and streamlines in the after part.
UberCloud Application Containers for NUMECA FINE™/Marine UberCloud Containers are ready-to-execute packages of software. These packages are designed to deliver the tools that an engineer needs to complete his task in hand. In this cloud experiment, the FINE™/Marine software has been pre-installed, configured, and tested, in a container running on CPU 24/7 bare metal servers, without loss of performance. The software was ready to execute literally in an instant with no need to install software, deal with complex OS commands, or configure. UberCloud Containers allow a wide variety and selection of resources for the engineers because the containers are portable from workstation to server to Cloud. The Cloud operators or IT departments no longer need to limit the variety, since they no longer have to install, tune and maintain the underlying software. They can rely on the UberCloud Containers to cut through this complexity. This technology also provides hardware abstraction, where the container is not tightly coupled with the hardware. Abstraction between the hardware and software stacks provides the ease of use and agility that bare metal environments usually lack.
Case Study Authors: Vassilios Zagkas and Ioannis Andreou