1 / 21

Statistical Properties of Wave Kinematics and Related Forces

Statistical Properties of Wave Kinematics and Related Forces. Carl Trygve Stansberg MARINTEK/CeSOS , Trondheim, Norway. CeSOS Workshop on Research Challenges in Probabilistic Load and Response Modelling, Trondheim, Norway, 19 December 2005.

renee
Download Presentation

Statistical Properties of Wave Kinematics and Related Forces

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Statistical Properties of Wave Kinematics and Related Forces Carl Trygve Stansberg MARINTEK/CeSOS , Trondheim, Norway CeSOS Workshop on Research Challenges in Probabilistic Load and Response Modelling,Trondheim, Norway, 19 December 2005

  2. Contents- Linear and second-order random wave kinematics modelling- Case study, storm wave- Simplified distribution model for free-surface velocity peaks- Effects on forces CeSOS Workshop on Research Challenges in Probabilistic Load and Response Modelling,Trondheim, Norway, 19 December 2005

  3. Linear and second-order random wave kinematics modelling:- Here: Focus on horizontal particle velocities u(t,z) at a given vertical level z, for long-crested irregular waves on deep water(for simplicity)- Linear: u0(t,z) =  i A(it) exp(jit) exp(kiz) z ≤ 0i- Second-Order: utot(t,z) = u0(t,z) + u(2 sum)(t,z) + u(2 diff)(t,z) z ≤ 0 utot(t,z) = u0(t,z) +(∂u0/∂z│z=0)∙z + u(2 sum)(t,0) + u(2 diff)(t,0) z > 0 (light blue: in finite water only)Here, u(2 sum) and u(2 diff) are given by their quadratic transfer functions (QTFs). We shall in particular consider the free-surface velocity u(z=(t)) at the crest peaks Ac. CeSOS Workshop on Research Challenges in Probabilistic Load and Response Modelling,Trondheim, Norway, 19 December 2005

  4. Examples from numerical simulation, extreme events in random records:from Stansberg et al. (OMAE 2006) CeSOS Workshop on Research Challenges in Probabilistic Load and Response Modelling,Trondheim, Norway, 19 December 2005

  5. Present case study- Hs=16m, Tp=14s, Gamma=2.5 (steep 100-year storm sea state)- Full-duration 3-hours storm record (1 realisation only, with  1000 wave cycles)- Simulate linear and second-order- Study probability distribution of crest heights Ac & velocity peaksUc CeSOS Workshop on Research Challenges in Probabilistic Load and Response Modelling,Trondheim, Norway, 19 December 2005

  6. Sample time series, linear and second-order elevation CeSOS Workshop on Research Challenges in Probabilistic Load and Response Modelling,Trondheim, Norway, 19 December 2005

  7. Sample time series, linear and second-order free-surface velocity CeSOS Workshop on Research Challenges in Probabilistic Load and Response Modelling,Trondheim, Norway, 19 December 2005

  8. Sample time series, linear and second-order velocityat z=0 CeSOS Workshop on Research Challenges in Probabilistic Load and Response Modelling,Trondheim, Norway, 19 December 2005

  9. Probability distributions from simulations, linear and second-order crest heights CeSOS Workshop on Research Challenges in Probabilistic Load and Response Modelling,Trondheim, Norway, 19 December 2005

  10. Probability distributions from simulations, linear and second-order velocity peaks CeSOS Workshop on Research Challenges in Probabilistic Load and Response Modelling,Trondheim, Norway, 19 December 2005

  11. Simplified second-order formula for maximum crest height:E[Amax] = AR (1 + ½ kp AR )(fromStansberg, (1998), based on Kriebel & Dawson (1993), Tayfun (1980))whereAR [ (2 ln (M)) + 0.577/ (2 ln (M))]kp = wave number = (2fp)2/gThis follows from modified Rayleigh distribution model for short-time statistics of nonlinear peaks a’:P[A < a’] = 1 -exp [-a2/22] where a = a’(1- ½ kpa) are the linear crestsThis formulation is based on second-order regular wave theory. CeSOS Workshop on Research Challenges in Probabilistic Load and Response Modelling,Trondheim, Norway, 19 December 2005

  12. Simplified second-order formula for maximum crest height(cont.):The simple formula compares surprisingly well with full second-order simulations, see e.g. Stansberg (1998): although the negative difference-frequency effects are neglected.Likely reason: Use of the spectral peak frequency fpprobably leads to too long wave periods for the highest crests: Forristall (2000) suggests fAmax = 1.05fp for the highest crests. We think it should be even shorter, because in a random simulation it is locally shorter at a high peak than over the whole cyclus (found from Hilbert transform analysis of linear records). Thus we have found fAmax 1.15fp CeSOS Workshop on Research Challenges in Probabilistic Load and Response Modelling,Trondheim, Norway, 19 December 2005

  13. Similarly, we use the same approach in suggesting a simplified second-order formula for high velocity peaks Uc at the free surfaceAssume regular waves:utot(t,z) = u0(t,z) +(∂u0/∂z│z=0)∙z which can be written, under the crest z=Ac: uC = u0(1 + kp Ac ) and the peak value distribution function becomes:P[u < uC] = 1 - exp [- u02/2u2] = 1 - exp [- uc2(1- kp Ac )2/2u2] (As for the crest heights before, we choose to use kp here, to compensate for the neglecting of difference-frequency terms).Notice: Nonlinear term is twice as important as for crests CeSOS Workshop on Research Challenges in Probabilistic Load and Response Modelling,Trondheim, Norway, 19 December 2005

  14. Check of simplified crest height distribution(thin line), vs. simulations CeSOS Workshop on Research Challenges in Probabilistic Load and Response Modelling,Trondheim, Norway, 19 December 2005

  15. Check of simplified velocity peak distribution(thin line), vs. simulations CeSOS Workshop on Research Challenges in Probabilistic Load and Response Modelling,Trondheim, Norway, 19 December 2005

  16. Effect on velocity-determined wave forces (introductory study)Type 1: Wave slammingF  ½ Cs A Uc2(slamming coefficient Cs  3 – 6, depending on relative angle)Type 2: Drag forcesF = ½  D CD u |u| (and then integrated up to the free surface)Here we limit our study to look at properties of the peaks of free-surface velocity squared – indicates the statistical properties of local forces CeSOS Workshop on Research Challenges in Probabilistic Load and Response Modelling,Trondheim, Norway, 19 December 2005

  17. Sample record of u2, linear and second-order kinematics CeSOS Workshop on Research Challenges in Probabilistic Load and Response Modelling,Trondheim, Norway, 19 December 2005

  18. Total 3-hour record of u2, with linear and second-order kinematics (u > 6.5m/s) Number of “events” increased by several 100%! CeSOS Workshop on Research Challenges in Probabilistic Load and Response Modelling,Trondheim, Norway, 19 December 2005

  19. Probability distributions of u2, linear and second-order kinematics, including comparison to exponential model CeSOS Workshop on Research Challenges in Probabilistic Load and Response Modelling,Trondheim, Norway, 19 December 2005

  20. Probability distribution of u2, with second-order kinematics,compared to simplified distribution based on:P[Y < y’] = 1 - exp[-y2/y2]where y = u02 (from linear velocity)y’ = y(1 + kpAc)2(from nonlinear velocity)(simplified distribution shown with dashed line) CeSOS Workshop on Research Challenges in Probabilistic Load and Response Modelling,Trondheim, Norway, 19 December 2005

  21. Summary with conclusions- Statistical properties of particle velocity peaks in steep random waves have been investigated. - Second-order contributions lead to 30% increased maximum free-surface velocities (while crest heights are increased 15%)- A simple distribution model, similar to Kriebel & Dawson’s for crests, compares well with the simulated results- Preliminary studies of effects on resulting wave forces have been made by considering velocity squared.- The results show considerable contributions from second-order kinematics on forces – almost 100% increase. A simplified, modified exponential distribution model compares well with simulations- Further work recommended on statistical properties of integrated drag forces, and on related moments around z=0 CeSOS Workshop on Research Challenges in Probabilistic Load and Response Modelling,Trondheim, Norway, 19 December 2005

More Related