Response-Based Design

1. Response-Based Design M. J. Santala ExxonMobil Upstream Research Company

2. Identification of controlling design conditions Failure to identify controlling conditions may impact project schedule or lead to unacceptable performance Design practices that are over-conservative may not be cost effective For floating systems the maximum environment is not always sufficient for design Maximum environment  maximum response Response-based methods provide an approach for identification of controlling design conditions Implementation details key to effectiveness Design Method Effectiveness

3. Traditional procedures and limitations Response-based approach Case study - DDCV riser-stroke response Summary Discussion Outline

4. Fixed Platforms Response = f(Hmax) + secondary contributions (ws, v) Specifying the 100-year wave plus associated parameters leads to the 100-year response approximately. Floaters Response=f(Hs, Tp,, ws, v, ) + secondary contributions Specifying the 100-year wave (or any other single parameter) plus associated parameters DOES NOT necessarily lead to the 100-year response. Example limitations for DDCVs In central GoM where offset can be dominated by Loop Current in a VIV lock-in condition. In western GoM responses can be dominated by wind plus associated conditions Traditional procedures and limitations

5. Common “Patches” • Specify a set of 100-year cases and look for the dominant response. Minimal specification might include: • 100-year significant wave + associated wind and current • Range of associated spectral wave periods • 100-year wind + associated wave and current • 100-year current + associated wind and wave • Develop contours in Hs-Tp, Hs-ws, ws-v space to search for dominant responses. • Multi-dimensional parameter contours —though theoretically possible— are not necessarily practical or sufficient.

6. Response-Based Approach • Methodology • Determine limit state for critical systems • Formulate response functions for each critical system element • Realistic characterization effects of wind, wave, and current • Computationally efficient • Develop long-term characterization of the environment • Simulate long-term response time history • Evaluate extreme response statistics • Identify environments that produced design response • Assess design for controlling environments • Consideration • Factors other than environmental conditions may have comparable contribution

7. Case Study : West Africa DDCV Riser Stroke • Slip joints and well heads on top-tensioned risers designed to accommodate a finite amount of push-up and pull-down. • Factors affecting stroke: • initial hull position with respectto well (push-up or pull-down) • loss of buoyancy (push-up) • mechanical space-out allowance (push-up or pull down) • subsidence (pull-down) • thermal growth (push-up) • riser sag (pull-down) • environmentally-induced stroke due to hull surge, pitch, heave and water level variations (push-up and pull-down)

8. Traditional 100-yr Environments(as per ISO regional annexes) West AfricaGoMcentral N. Sea Hs 3.9 m 12.6 m 13.6 m Tp, associated 15-17 s 14.6 s 15.5-19.4 s ws, 1hr,10m 8 m/s* 46 m/s 35 m/s * 3-second gust is 30m/s. (due to West Africa squall conditions)

9. GOM – 100 YR Wave West Africa - Swell What is the issue for W. Africa? • DDCV heave response is highly resonant near its natural frequency. • In the Gulf of Mexico, which is a semi-enclosed sea, there are no long period waves to excite the heave resonance. • In environments like West Africa where there are long period swells it may be possible to excite this resonance. • This comparison shows a heave response more than 10 times greater in a 1m, 25s swell than in the 100-year GoM hurricane.

10. Lo Riser Stroke Response Function Riser Stroke Model • Consider a simple model (ignoring riser sag) to compute riser stroke. • Using this model, any parameters which cause the keel to move from its zero-offset position cause riser stroke to change. • Mean offsets and dynamic motions in 6 D.O.F due to winds, waves and currents all contribute to stroke requirements. • Motions occur on a variety of time-scales. driving forcemotiontime scale wind mean *** wind dynamic O[100s] wave wave-frequency O[10s] wave slow-drift O[100s] current mean *** • Estimating max stroke in a seastate requires a short-term statistical response model that properly combines mean, low-frequency and wave frequency motions.

11. Long-Term Characterization for Environment 45-Year Wave Hindcast • Assembling a long-term environmental database can be problematic. • Wind and Waves - Hindcast data provided a 45-year time history of continuous 6-hourly “normal” winds and waves. • Squalls – Only one year of measured wind data on the seasonal frequency and intensity. • Currents - A long-term synthetic time-series of current based on a year of measurements. • For this region, squalls and currents have little correlation to the swell dominated wave environment. • Assembling long-term databases would be more straight-forward in mature areas such as the GoM or N. Sea but must still be done with care. 45-Year Squall Distribution

12. Initialize & load environmental database Simulate Long-Term Response Time History Analyze next seastate Compute mean forces & moments Compute offset & resulting mooring stiffness Compute slow-drift, wave-frequency and wind-induced motions at the keel Compute min/max stroke in seastate no Last seastate ? yes Archive results as input to extreme value analysis

13. Extrapolation of Response to Extremes Peak-Over-Threshold Analysis • With a 45-year sequence of responses, extrapolation to a 100-year extreme is straightforward. • If our response functions were perfect we could use the results of the analysis directly. However, the response model used was an approximation and we can only use the analysis as a screening tool to determine input conditions. • In past analyses in the GoM where we have used extremely long synthetic time-series (500 years+), the 100-year response can simply be picked out of the input database. • In this case we need to “back out” conditions which lead to the 100-year response.

14. Determining the 100-Year Stroke Input Condition • To determine the environmental conditions which give rise to the 100-year response we examine the conditions which generated the largest peak responses. • None of the responses occurred in the region of the 100-year Hs plus the “conservative” range on the associated Tp. In fact the 100-year response was more than 50% greater than the response in the worst part of the 100-year Hs and associated Tp range. • In this case the top ten responses were all caused by conditions with long wave periods, modest wave heights and negligible winds and currents. • The environmental conditions driving the 100-year stroke response were backed out of the region of the top ten responses using the response function. • This result could have also been • determined by examining 100-year • Hs-Tp contours. And, for this case with a • known sharp resonance, a prudent design • team would explore this option in the • absence of having performed a response • analysis.

15. Design Cycle Considerations • The conditions determined by the response analysis are dependent on the system configuration. • In a subsequent design cycle where the DDCV geometry and mass distribution was changed the response analysis was re-run. • A case unrelated to swells emerged as the peak case. A large tilt response to extreme wind caused a large pull-down (right). • Here simply using Hs-Tp contours does not yield the critical response. Relying contours requires examining other contour dimensions to ensure identification of other conditions that may govern the extreme response.

16. Summary • Traditional methods based on SPJ experience are clearly dated and most of industry has made some effort to move ahead with specifications of metocean conditions more appropriate for floaters. • Specifying a limited set of cases (e.g. wind-dominated, wave dominated etc) in the absence of any knowledge of the structure to be used is a first step but does not guarantee that the 100-year response of every critical system element has been considered. • Judicious use of environmental contours and careful consideration of system resonance and damping on various components of the system may lead to an acceptable range of design cases. In cases where damping or VIV lock-in are an important part of the response it is not assured that the contour approach will identify the critical cases. • Response-based analyses require designers and metocean specialists work together in a collaborative (rather than sequential) mode to identify critical cases. Success requires : • the appropriate responses being screened, • a good input database, • good response models, • appropriate updates of response analysis as design matures. Satisfying the above conditions is not easy and requires a non-trivial analysis and data gathering effort.