Integrating Seakeeping Analysis into the Design of Floating Systems
Figure 1: Traditional Hull Design Process Based on an Interactive Computer-aided Design System
Edits hull surface Checks hull properties Seakeeping analysis Assesses performance Feasible design Reviews design
Figure 2: Hydrodynamic Hull Shape Optimisation Based on a Form-parameter-driven Computer-aided Design System
Changes required
Casting complex design tasks and decision processes into computer algorithms is, at first, a daunting task. However, selection and implementation of objective functions creates a basis for rational design decisions. It tends to emphasise important and desirable performance characteristics. Constraints allow the control of additional properties such as stability, cost, production, etc. Initially, time savings resulting from better utilisation of computational resources will be lost in formulating the design problem. However, once the problem formulation is completed, large numbers of design alternatives can be evaluated at no additional cost. Over time a library of optimisation problems is created that can be re-used for similar projects. The problem formulation also stores best practices because it records procedural information along with technical content. The fact that the results of the hydrodynamic shape optimisation process represent optima is especially valuable during the development of new platform concepts when solutions cannot be based on prior design experience. Formal optimisation becomes an increasingly popular design tool, but applications to hull design of offshore structures are rarely reported. A summary of work by others is given in articles by Birk.1,2
Specifies hull properties and optimisation problem
The reported optimisation procedures are restricted to very narrowly defined classes of geometries, either by the applied hydrodynamic analysis or by the method used to generate and modify hull shapes. The current work employs a form-parameter-driven system derived from Huang3
and Birk.1,2
Form-parameter-driven Hull Design
Hull surface generation Seakeeping analysis
Optimisation loop Optimised design
Reviews design
Figure 3 illustrates the automated hull generation process. For each design a set of free variables is obtained from the optimisation algorithm. In a pre-processing step, dependent variables are calculated based on the implemented rules (step one). The rules are stored in a Python script4
and
Figure 3: Form-parameter-driven Hull Design
Automated shape generation
Free variables
1. Pre-processing
Interpret free variables and compute form parameters for all components
2. Creating components
Derive vertices, knot vectors and weights for NURBS surfaces
3. Merging components
Approximate surface–surface intersections and trim away superfluous parts
Hull surface
4. Post-processing
Output filter, e.g.
generate panels and write WAMIT geometry file
can be re-used for similar design problems. Typically, a script for a semi- submersible is only a few pages of code long. We exploit that individual hull components (e.g. pontoons and columns) feature rather simple shapes. Cross-sections of components are commonly circular or rectangular with rounded corners. For the definition of most components we only specify the cross-section area and shape at both ends as well as the end-point locations. More complicated shapes are readily available using additional form parameters. From cross-sections and end-points, control net vertices and weights are derived for a B-spline or NURBS representation of the component surface (step two). For details see articles by Birk.5,6
Components are merged by computing surface–surface intersections. Surface parts that lie inside the completed hull are eliminated (step three). Finally, the NURBS surfaces are converted into the format required for further analysis, for instance panels for a potential theory-based flow solver (step four).
Optimisation Algorithms
Non-linear-programming algorithms, also known as optimisation algorithms, are readily available. Over the years we have tested a number of different algorithms and generally they all worked. Most practical are methods that only require objective function values. Gradients are never explicitly known and in cases with several free
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EXPLORATION & PRODUCTION – VOLUME 8 ISSUE 1
Performance assessment
The capabilities of a form-parameter-driven hull design system represent the creativity of the system. Obviously, if a shape generation procedure would solely create spheres, every optimisation would yield a sphere as a result; therefore, it is essential that the shape generation supplies the optimisation with a large variety of hull forms.
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