Results from the Guam/ Chuuk/ Puluwat 2012 Leeway Field Tests

Transcription

1 Results from the Guam/ Chuuk/ Puluwat 2012 Leeway Field Tests Author Allen, Arthur, Brushett, Ben, Futch, LT Victoria Published 2013 Copyright Statement 2012 Centre for Infrastructure Engineering and Management. To the extent permitted by law, all rights are reserved and no part of this publication covered by copyright may be reproduced or copied in any form or by any means except with the written permission of Griffith University (GU) (or organisation based on lead author). Downloaded from Link to published version Griffith Research Online

2 Results from the Guam/ Chuuk/ Puluwat 2012 Leeway Field Tests Technical Report Arthur A Allen (US Coast Guard, CG-SAR-1) Ben Amon Brushett (Griffith University, Asia-Pacific ASA) LT Victoria Futch (US Coast Guard Academy) April 2013 Field Tests to Determine the Leeway Drift Coefficients of Common Tropical Pacific Water Craft Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07

3 The mission of the Centre for Infrastructure Engineering and Management (CIEM) is to optimise the life cycle performance of civil infrastructure systems through product innovation and process integration. The primary aim of the Centre is to capitalise on the collective expertise of a highly qualified group of engineers so as to provide practical solutions and answers to the diverse challenges associated with the creation and operation of civil infrastructure systems. Enquiries can be addressed to: Centre for Infrastructure Engineering and Management Gold Coast campus Griffith University QLD 4222 AUSTRALIA This report and other Technical Reports published by the Centre for Infrastructure Engineering and Management are available at Citation Allen, A. A., Brushett, B. A., Futch, V. C. (2013). Results from the Guam/ Chuuk/ Puluwat 2012 Leeway Field Tests Technical Report CIEM/2013/R07, Griffith University. Copyright To the extent permitted by law, all rights are reserved and no part of this publication covered by copyright may be reproduced or copied in any form or by any means except with the written permission of Griffith University (GU) (or organisation based on lead author). Disclaimer CIEM advise that the information contained in this publication comprises general statements based on scientific research and does not warrant or represent the accuracy, currency and completeness of any information or material in this publication. The reader is advised and needs to be aware that such information may be incomplete or unable to be used in any specific situation. No action shall be made in reliance on that information without seeking prior expert professional, scientific and technical advice. To the extent permitted by law, CIEM (including its Partner s employees and consultants) excludes all liability to any person for any consequences, including but not limited to all losses, damages, costs, expenses and any other compensation, arising directly or indirectly from using this publication (in part or in whole) and any information or material contained in it Cover Image Image shows the three pacific island craft studied in this project, 2.7 m Personal Water Craft (top), 5.8 m Panga skiff (middle) and 5.97 m outrigger canoe (bottom) GU (and Ben Brushett) Acknowledgements This work was financially supported by: US Coast Guard Office of Search and Rescue; US Coast Guard Academy, US Coast Guard District Fourteen, Griffith University and the Australian Research Council s Linkage Projects funding scheme LP We would like to acknowledge the assistance we received from the Coast Guard Academy waterfront personnel, especially RJ Burns; Cadets Arnold, Kennedy, and Byrd in preparation of the PWC; the personnel at Coast Guard Sector Guam who provided space, purchasing and shipping support for two weeks prior to the cruise. We would like to thank the officers and crew of the USCGC SEQUOIA for their outstanding professionalism and good humour throughout the three week cruise. We would also like to acknowledge the assistance and support of Assoc. Prof. Charles Lemckert from Griffith School of Engineering and Centre for Infrastructure and Engineering Management, Griffith University, and Dr Brian King from Asia-Pacific ASA. Centre for Infrastructure Engineering and Management Technical Report ISSN (Online) Centre for Infrastructure Engineering and Management Technical Report ISSN X (Print)

4 TABLE OF CONTENTS LIST OF ABBREVIATIONS... 2 LIST OF FIGURES... 3 LIST OF TABLES Introduction The Drift Objects For Field Experiments Fibreglass skiffs Outrigger Canoe Personal Water Craft (PWC) Preparation Of The Drift Objects For Field Experiments Current Meters and Meteorological Instruments Results Summary of the Drift Runs Results for the 5.8 Meter Fiberglass Panga Skiffs Results for the 5.8 Meter Fiberglass Panga Skiffs - with 1 POB equivalent loading (136 kg total loading) Results for the 5.8 Meter Fiberglass Panga Skiffs - with 2 POB equivalent loading (204 kg total loading) Results for the 5.8 Meter Fiberglass Panga Skiffs - with 4 POB equivalent loading (340 kg total loading) Results for the 5.8 Meter Fiberglass Panga Skiffs - with 13 POB equivalent loading (950 kg total loading) Results from the Combination of Panga Drift Runs - Separated by Loading Results for the 5.97 m Fiberglass Outrigger Canoe Results for the 2.70 m 2-person Personal Water Craft Jibing Frequency Search and Rescue Case 3-6 June Summary and Recommendations References Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 1

5 LIST OF ABBREVIATIONS ADCP Acoustic Doppler Current Profiler CWL Crosswind Leeway DWL Downwind Leeway GPS Global Positioning System HAZMAT Hazardous Materials POB Person on Board PVD Progressive Vector Diagram PWC Personal Water Craft SAR Search and Rescue SAREX Search and Rescue Exercise SAROPS Search and Rescue Optimal Planning System USCG United States Coast Guard USCGC United States Coast Guard Cutter Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 2

6 LIST OF FIGURES Figure 1. Guam, Chuuk, Puluwat leeway experiment drift area Figure 2. Panga fiberglass skiffs at Chuuk Island FSM, predominately 19-footers, and few 23-footers Figure 3. Line drawing of the 19-ft (5.80 m) skiffs used during this experiment. Dimensions in cm Figure 4. Line drawing of 23-ft (7.01 m) Panga skiff. Dimensions in cm Figure 5. The 5.80 m fiberglass Panga Skiff One. Arrows: (1) Carmanah M704-5 marine lantern, (2) Gill ultrasonic anemometer, (3) WeatherPak, (4) floatation bag, (5) WeatherPak battery canister with pitch and roll sensors, (6) NovaTech Combination flasher/rdf beacon (RF-700C1), (7) GPS\Iridium beacons, (8) sand-filled ballast bags (34kg each) some underneath floatation bag, (9) AquaDopp ADCP Figure 6. The 5.80 m fiberglass Panga Skiff Two. Arrows: (1) Carmanah M704-5 marine lantern, (2) Gill ultrasonic anemometer, (3) WeatherPak, (4) floatation bag, (5)WeatherPak battery canister with pitch and roll sensors, (6) NovaTech Combination flasher/rdf beacon (RF-700C1), (7) GPS\Iridium beacons, (8) sand-filled ballast bags (34 kg each), and (9) AquaDopp ADCP Figure 7. In the foreground; a 1-person dug-out outrigger canoe and a 19-ft fiberglass South Pacific panga. In the background, six 1- person dug-out outrigger canoes returning from fishing, Puluwat Atoll Figure 8. The 5.97 m fiberglass Outrigger Canoe used in this experiment Figure 9. The 5.97 m fiberglass Outrigger Canoe. Arrows: (1) GPS\Iridium beacon, (2) sand-filled ballast bags (34 kg each), (3) AquaDopp ADCP, and (4) Carmanah M704-5 marine lantern Figure 10. Line drawing of 5.97 m (19.6 ft) fiberglass outrigger canoe. Dimensions in cm Figure 11. Line drawing of 2.70 m (8.86 ft) two-person personal water craft. Dimensions in cm; Draft: ~8 cm, height above waterline: ~66 cm. Dimensions in cm Figure 12. The RDI Workhorse Monitor 1200 khz ADCP mounted in the gimbals inside the Personal Water Craft (aft left, bow right) Figure 13. Two-person Personal Water Craft with mannequin in upright seated position Figure 14. The 2 person Personal Water Craft (1) NovaTech Combination flasher/rdf beacon (RF-700C1, (2) GPS/Iridium beacon, and (3) external battery for RDI ADCP Figure 15. The Nortek AquaDopp 2 MHz ADCP (hull for a single battery pack) Figure 16. Drift Runs off Chuuk, FSM, 28 May June Figure 17. Drift Runs off Puluwat, FSM, 8-9 June Figure 18. Drift Runs off Guam, 12 June Figure 19. Pressure time-series records from Skiff One (red), Skiff Two (blue) AquaDopp current meters, and atmospheric pressure 1030 mb from Skiff Two WeatherPak Figure 20. Time series of the AquaDopp pressure sensor on Skiff Two adjusted for start and end atmospheric pressure. Pressure averages were taken during the periods marked by horizontal dashed lines. Total loading (kg) are labeled above the averaging periods Figure 21. Skiff Two with 8 persons on board, plus sand bags; total loading 820kg Figure 22. Linear regression of draft (cm) against total loading (kg) for Skiff Two. 95% confidence limits are shown Figure 23. Leeway Speed (cm/s) versus Wind Speed adjusted to 10-meter height for the 5.8 m fiberglass panga skiff with 1 POB equivalent loading (blue circles). Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its confidence limits are plotted in red Figure 24. Downwind Component of Leeway (cm/s) versus Wind Speed adjusted to m fiberglass panga skiff with 1 POB equivalent loading (blue squares). Unconstrained linear regression mean (solid green) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its 95% confidence limits are plotted in red Figure 25. Progressive Vector Diagram (PVD) of the Down and Crosswind components of Leeway Displacement, for the 5.8 m fiberglass panga skiff with 1 POB equivalent loading. Downwind is up (solid black line), and positive Crosswind is to the right. Displacement is in kilometers. Hourly intervals are indicated by a black square point every 6 th point Figure 26. Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10-meter height for the 5.8 m fiberglass panga skiff with 1 POB equivalent loading (blue + positive crosswind components), Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its 95% confidence limits are plotted in red Figure 27. Leeway Speed (cm/s) versus Wind Speed adjusted to 10-meter height for the 5.8 m fiberglass panga skiff with 2 POB equivalent loading. The three Skiff One drift runs are plotted in blue, while two Skiff Two runs are plotted in black. Unconstrained linear regression mean for both craft (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression for both craft and its confidence limits are plotted in red Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 3

7 Figure 28. Downwind Component of Leeway (cm/s) versus Wind Speed adjusted to m fiberglass panga skiff with 2 POB equivalent loading. The three Skiff One drift runs are plotted in blue, while two Skiff Two runs are plotted in black. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression (solid) and its confidence limits (dashed) are plotted in red Figure 29. Progressive Vector Diagram (PVD) of the Down and Crosswind components of Leeway Displacement, for the five drift runs of the 5.8 m fiberglass panga skiffs with 2 POB equivalent loading. Downwind is up (solid black line), and positive Crosswind is to the right. Displacement is in kilometers. Hourly intervals indicated by a larger marker every 6 th point and are restarted each drift run; from left to right (Skiff One - Run 1 / Skiff Two - Run 1 / Skiff One - Run 3 / Skiff One - Run 2 / Skiff Two - Run 2) Figure 30. Zoomed in view of the PVD for the Skiff One, Run 1 (red dots with black squares) with 2 POB equivalent loading. Arrows indicate 4 of the 6 switches (jibes) between negative and positive CWL Figure 31. Positive Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10-meter height for the 5.8 m fiberglass panga skiff with 2 POB equivalent loading (blue + Skiff One, black + Skiff Two). Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its 95% confidence limits are plotted in red Figure 32. Negative Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10-meter height for the 5.8 m fiberglass panga skiff with 2 POB equivalent loading (blue + Skiff One, black + Skiff Two), Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its 95% confidence limits are plotted in red Figure 33. Positive and minus one times Negative Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10-meter height for the 5.8 m fiberglass panga skiff with 2 POB equivalent loading (blue markers Skiff One, black markers Skiff Two), are positive crosswind whilst are -1 multiplied by negative crosswind Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its 95% confidence limits are plotted in red Figure 34. Leeway Speed (cm/s) versus Wind Speed adjusted to 10-meter height for the 5.8 m fiberglass panga skiff with 4 POB equivalent loading, Skiff Two plotted in black. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its confidence limits are plotted in red Figure 35. Downwind Component of Leeway (cm/s) versus Wind Speed adjusted to m fiberglass panga skiff with 4 POB equivalent loading. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its confidence limits are plotted in red Figure 36. Progressive Vector Diagram (PVD) of the Down and Crosswind components of Leeway Displacement, for the three drift runs of the 5.8 m fiberglass panga skiffs with 4 POB equivalent loading. Downwind is up (solid black line), and positive Crosswind is to the right. Displacement is in kilometers. Hourly intervals are indicated by a larger marker every 6 th point and are restarted each drift run; from left to right (Skiff Two - Run 3 / Skiff Two - Run 2 (4-POB portion) / Skiff Two - Run 4) Figure 37. Positive Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10-meter height for the 5.8 m fiberglass panga skiff with 4 POB equivalent loading. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its 95% confidence limits are plotted in red Figure 38. Leeway Speed (cm/s) versus Wind Speed adjusted to 10-meter height for the 5.8 m fiberglass panga skiff with 13 POB equivalent loading. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its confidence limits are plotted in red Figure 39. Downwind Component of Leeway (cm/s) versus Wind Speed adjusted to m fiberglass panga skiff with 13 POB equivalent loading. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its confidence limits are plotted in red Figure 40. Progressive Vector Diagram (PVD) of the Down and Crosswind components of Leeway Displacement, for the drift run of the 5.8 m fiberglass panga skiff with 13 POB equivalent loading. Downwind is up (solid black line), and positive Crosswind is to the right Displacement is in kilometers. Hourly intervals are indicated by a larger marker every 6 th point and are restarted each drift run; (Skiff One - Run 1, 13-POB portion) Figure 41. Negative Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10-meter height for the 5.8 m fiberglass panga skiff with 13 POB equivalent loading (Blue ). Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its 95% confidence limits are plotted in red Figure 42. Downwind Component of Leeway Rate (% of 10-m Wind Speed) averaged by drift run versus total loading (kg) of the 5.8 m fiberglass panga skiffs. Unconstrained linear regression mean (solid) and 68% confidence levels (dash) are plotted in green. 40 Figure 43. Absolute value of Crosswind Component of Leeway Rate (% of 10-m Wind Speed) averaged by drift run versus total loading (kg) of the 5.8 m fiberglass panga skiffs. Unconstrained linear regression mean (solid) and 68% confidence levels (dash) are plotted in green Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 4

8 Figure 44. Leeway Rate (% of 10-m Wind Speed) averaged by drift run versus total loading (kg) of the 5.8 m fiberglass panga skiffs. Unconstrained linear regression mean (solid) and 68% confidence levels (dash) are plotted in green Figure 45. Absolute value of Divergence Angle (degrees) averaged by drift run versus total loading (kg) of the 5.8 m fiberglass panga skiffs. Unconstrained linear regression mean (solid) and 68% confidence levels (dash) are plotted in green Figure 46. Leeway Speed (cm/s) versus Wind Speed adjusted to 10-meter height for the 5.97 m fiberglass Outrigger Canoe. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and corresponding 95% confidence intervals are plotted in red Figure 47. Downwind Component of Leeway (cm/s) versus Wind Speed adjusted to 10-meter for the 5.97 m fiberglass Outrigger Canoe. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and corresponding 95% confidence intervals are plotted in red Figure 48. Progressive Vector Diagram (PVD) of Down and Crosswind components of Leeway Displacement, for the 5.97 m fiberglass Outrigger Canoe with 1 POB equivalent loading. Downwind is up, and positive Crosswind is to the right. Displacement is in kilometers. Hourly intervals indicated by larger marker every 6 th point. Ratio of crosswind to downwind displacement is 1 to 1. Run 1 blue diamonds and magenta circles; Run 2 green diamonds and blue circles; Run 3 red diamonds and black diamonds; Run 4 black diamonds and green circles, Run 5 black diamonds and red squares) Figure 49. PVD for the for the 5.97 m fiberglass Outrigger Canoe with 2 POB equivalent loading showing 2 to 1 ratio of crosswind to downwind displacement. Arrows indicate the changes between negative and positive CWL (jibes) Figure 50. Positive Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10-meter height for the 5.97 m fiberglass Outrigger Canoe. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and corresponding 95% confidence intervals are plotted in red Figure 51. Negative Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10-meter height for the 5.97 m fiberglass Outrigger Canoe. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and corresponding 95% confidence intervals are plotted in red Figure 52. Positive and minus one times Negative Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10-meter height for the 5.97 m fiberglass Outrigger Canoe ( (positive crosswind components); (-1 x negative crosswind component)) Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and corresponding 95% confidence intervals are plotted in red Figure 53. Figure 1. Leeway Speed (cm/s) versus Wind Speed adjusted to 10-meter height for the 2.70 m 2-person Personal Water Craft. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and corresponding 95% confidence intervals are plotted in red Figure 54. Figure 2. Downwind Component of Leeway (cm/s) versus Wind Speed adjusted to 10-meter for the 2.70 m 2-person Personal Water Craft. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and corresponding 95% confidence intervals are plotted in red Figure 55. Progressive Vector Diagram (PVD) of the Down and Crosswind components of Leeway Displacement, for the 2.70 m 2- person Personal Water Craft. Downwind is up, and positive Crosswind is to the right. Displacement is in kilometers. Hourly intervals are indicated by a larger marker every 6 th point. Ratio of crosswind to downwind displacement is 1 to 1. (Run 1 red; Run 3 blue; Run 5 black) Figure 56. Positive Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10-meter height for the 2.70 m 2-person Personal Water Craft. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and corresponding 95% confidence intervals are plotted in red Figure 57. Negative Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10-meter height for the 2.70 m 2-person Personal Water Craft. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and corresponding 95% confidence intervals are plotted in red Figure 58. Positive and minus one times Negative Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10-meter height for the 2.70 m 2-person Personal Water Craft ( (positive crosswind components); (-1 x negative crosswind component)) Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and corresponding 95% confidence intervals are plotted in red Figure 59. Probability distribution from the 3-6 June 2012 SAR case at the time the 23-Panga with two person on board was located. The distressed Panga model particles started from the green line which was the intended voyage track of the Panga traveling southward at average speed of 10 knots. The plan track line of the HC-130 is shown as the blue line, starting from the bottom right of the search area Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 5

9 LIST OF TABLES Table 1. Center Depth (cm) of the AquaDopp ADCP vertical bins Table 2. Center Depth (cm) of the RDI ADCP vertical bins Table 3. Summary of Drift Runs (Strike through did not return useful data) Table 4. Summary of 5.8 meter Fiberglass Pacific Island Panga Skiff Drift Runs (Start and End Time of useable data) Table 5. Total weights of common fluids in a 55-gallon drum (35lbs, 16 kg empty) Table 6. Average Rates (% of 10-m wind speed) of: Leeway Speed, DWL, CWL; and Divergence Angle (degrees) for 5.8 m Fiberglass Panga Skiff Drift Runs Table 7. User Defined Leeway Parameters for 19-23ft Panga with a 68 kg 40 Hp motor (where one POB = 68 kg, 150 lbs) Table 8. Down wind and Cross wind components of leeway for 5.8 m Panga with a 40 Hp motor for SAROPS / SARMAP (Where one POB = 150 lbs or 68 kg; DWL Syx (cm/s) = 11.1 cm/s; CWL Syx (cm/s) = 6.5 cm/s) Table 9. Summary of the 5.97 m fiberglass Outrigger Canoe Leeway Drift Runs Table 10. Summary of the 2.70 m 2-person Personal Water Craft Leeway Drift Runs Table 11. Unconstrained Linear Regression of Leeway Speed and Downwind Leeway Parameters Table 12. Constrained through zero, Linear Regression of Leeway Speed and Downwind Leeway Parameters Table 13. Unconstrained Linear Regression of Crosswind Leeway Parameters Table 14. Table 1. Constrained through zero, Linear Regression of Crosswind Leeway Parameters Table 15. Table 2Significant changes between positive and negative Crosswind component of leeway Jibing Frequency Table 16. User Defined Leeway Parameters for Outrigger Canoe and PWC Table 17. Down (DWL) and Crosswind (CWL) components of leeway parameters for Outrigger Canoe and PWC for SAROPS / SARMAP Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 6

10 1 INTRODUCTION Search and Rescue (SAR), and hazardous material (HAZMAT) operational models include modules for predicting the drift of common SAR objects and HAZMAT materials and objects, as well as modules for planning the appropriate resource response. To predict an objects drift, these models require forecast winds and currents, as well as algorithms of the wind and wave component of drift for the objects of interest. A review of the SAR and HAZMAT objects that has been studied by field experimentation before 1999 is presented by Allen and Plourde (1999). They made recommendation for 63 categories of objects to be included in SAR planning tools. Allen and Plourde provided the parameters for leeway speed as function of wind speed and a leeway divergence angle for all 63-leeway categories. Further work by Allen (2005) provided equations in the downwind and crosswind frame of reference for these same 63 categories. The predominance of operational SAR planning tools (Breivik and Allen 2008, Davidson et al. 2010) now uses either the equations from Allen and Plourde (1999) or Allen (2005). Breivik et al. (2011) used an operational definition of leeway defined as: Leeway is the motion of the object induced by wind (10 m reference height) and waves relative to the ambient current (between 0.3 and 1.0 m depth). This definition standardizes the reference levels for the measurements of leeway for SAR drift objects. Estimates of the velocity fields at both of these levels are readily available to the operational SAR planner. Allen and Plourde (1999) organized the previously studied leeway objects into a hierarchical taxonomy based upon their leeway characteristics. This allowed the operator to select a class of object that best matches the search object for that particular case. They also clarified what objects have been studied, and by inference which objects have not been studied. It is the purpose of this particular work to conduct leeway field drift studies and add three additional objects to the existing list. Since Allen (2005) there have been additional leeway field studies providing results in the manner as described by Allen and Plourde (1999) and Allen (2005). These include: Allen et al. (2010), Allen et al. (2011), Breivik et al. (2011), and Breivik et al. (in press). During this experimental field study, direct leeway measurements were made on two fiberglass 19-ft (5.8 m) skiffs; a 19.6-ft (5.97 m) outrigger canoe common to the South Pacific Islands; and a 2-person Personal Water Craft (PWC). This report summarizes the results from this field study from a cruise between Chuuk, Puluwat atoll, and Guam in May-June of Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 7

11 Figure 1. Guam, Chuuk, Puluwat leeway experiment drift area Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 8

12 Results from the Guam/Chuuk/Puluwat Leeway Field Tests 2 THE DRIFT OBJECTS FOR FO FIELD EXPERIMENTS 2.1 Fibreglass skiffs Flat-bottom fiberglass skiffs are very common throughout hroughout the tropical Pacific Ocean. Ocean There are several names for these skiffs: Panga, Banana Boat, Yamaha, and Fiber. The most common in the Federated ederated States of Micronesia (FSM) (F are 19-ft and 23-ft ft versions, version powered by a 40 Hp outboard motor;; see Figure 2 (Chuuk). (Chuuk The 19-ft ft version is most commonly used for transport within the atolls,, and the 23-ft 23 ft version is used for transport between atolls. In May/June 2012 a leeway drift experiment was conducted on two 1919-ft fiberglass Panga skiffs (Figure 3). ). The skiffs were outfitted with WeatherPak wind monitoring systems; Nortek AquaDopp ADCP current meters, GPS/Iridium beacons, and sand bags to simulate the loading of the 150 lb 40 Hp motor, along with additional sand bags to simulate the loading of Persons On Board (POBs) at 150 lbs per POB. The ADCP current meter was located at the stern, where the outboard motor would normally be, therefore all drift runs were conducted with the the motor in the up or stored position. Figure 2. Panga fiberglass berglass skiffs at Chuuk Island FSM, predominately 19-footers, 19 footers, and few 2323 footers. Centre for Infrastructure Engineering and nd Management Technical Report CIEM/2013/R07 Page 9

13 Figure 3. Line drawing of the 19-ft (5.80 m) skiffs used during this experiment. Dimensions in cm. Figure 4. Line drawing of 23-ft (7.01 m) Panga skiff. Dimensions in cm. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 10

14 Figure 5. The 5.80 m fiberglass Panga Skiff One. Arrows: (1) Carmanah M704-5 marine lantern, (2) Gill ultrasonic anemometer, (3) WeatherPak, (4) floatation bag, (5) WeatherPak battery canister with pitch and roll sensors, (6) NovaTech Combination flasher/rdf beacon (RF- 700C1), (7) GPS\Iridium beacons, (8) sand-filled ballast bags (34kg each) some underneath floatation bag, (9) AquaDopp ADCP Figure 6. The 5.80 m fiberglass Panga Skiff Two. Arrows: (1) Carmanah M704-5 marine lantern, (2) Gill ultrasonic anemometer, (3) WeatherPak, (4) floatation bag, (5)WeatherPak battery canister with pitch and roll sensors, (6) NovaTech Combination flasher/rdf beacon (RF- 700C1), (7) GPS\Iridium beacons, (8) sand-filled ballast bags (34 kg each), and (9) AquaDopp ADCP. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 11

15 2.2 Outrigger Canoe Outrigger canoes are commonly used in the South Pacific, and there are a variety of different versions in use. On the more remote atolls, small 1-person outrigger canoes are constructed in the traditional fashion from dugout tree trunks. These canoes are typically used during the day for local fishing, Figure 7. Larger outrigger canoes (6-9 m or ft) rigged with sails and a mast that can be erected at either end of the canoe are used for between island transportation. The fiberglass version of these larger outrigger canoes was purchased for this experiment, Figures Figure 7. In the foreground; a 1-person dug-out outrigger canoe and a 19-ft fiberglass South Pacific panga. In the background, six 1-person dug-out outrigger canoes returning from fishing, Puluwat Atoll. Figure 8. The 5.97 m fiberglass Outrigger Canoe used in this experiment. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 12

16 Figure 9. The 5.97 m fiberglass Outrigger Canoe. Arrows: (1) GPS\Iridium beacon, (2) sandfilled ballast bags (34 kg each), (3) AquaDopp ADCP, and (4) Carmanah M704-5 marine lantern. Figure 10. Line drawing of 5.97 m (19.6 ft) fiberglass outrigger canoe. Dimensions in cm. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 13

17 2.3 Personal Water Craft (PWC) PWC are commonly found along coastal and in-land waterways, primarily used for recreation. The operator either rides on or stands on the craft, rather than inside as in a boat. PWC have an inboard engine driving a jet pump for propulsion and steering. They are often referred by the trademarked brand names Jet Ski, WaveRunner, or Sea-Doo. The US Coast Guard defines a personal watercraft, amongst other criteria, as a jet drive boat less than 13' (3.96 m) in length, in order to exclude from that definition, more conventional sized jet boats. Most are designed for two or three people, though four-passenger models exist. The stand-up model is for one person only. For this experiment a used 2-person sit down style Yamaha PWC was purchased and outfitted with instrumentation, Figures Figure 11. Line drawing of 2.70 m (8.86 ft) two-person personal water craft. Dimensions in cm; Draft: ~8 cm, height above waterline: ~66 cm. Dimensions in cm. Figure 12. The RDI Workhorse Monitor 1200 khz ADCP mounted in the gimbals inside the Personal Water Craft (aft left, bow right). Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 14

18 Results from the Guam/Chuuk/Puluwat Leeway Field Tests Figure 13. Two-person Personal Water Craft with mannequin in upright seated position Figure 14. The 2 person Personal Water Craft (1) NovaTech Combination flasher/rdf beacon (RF-700C1, (2) GPS/Iridium beacon, and (3) external battery for RDI ADCP. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 15

19 3 PREPARATION OF THE DRIFT OBJECTS FOR FIELD EXPERIMENTS Each drift object was outfitted with equipment and gear for deployment, drift and recovery and data collection purposes. The drift objects were ballasted and augmented with extra floatation to mimic the un-equipped distress configuration as closely as possible. GPS/Iridium beacons and strobe-flashers were used to aid in the tracking and recovery of these four drift objects. During this experiment, Clearwater Instrumentation GPS/Iridium beacons were used to track the drift objects. A Clearwater Iridium receiver was located in the chart room of the US Coast Guard vessel SEQUOIA and its antenna was mounted on the flying bridge. The Iridium receiver was connected to a laptop computer to display and capture the Iridium data. Each GPS/Iridium beacon has a unique IMEI number, and captures its GPS position on the 10:00 minute:second cycle, along with internal temperature and battery voltage. Typically, these data are received by the Iridium receiver through the Iridium system within 35 to 45 seconds after the 10:00 minute mark. The GPS / Iridium beacons were self-contained, battery powered, and were turned on by the removal of exterior magnet. Large extra capacity external battery packs allowed for the deployment of the skiffs without having to recharge the battery pack throughout the experiment period. 4 CURRENT METERS AND METEOROLOGICAL INSTRUMENTS The Skiffs and Outrigger canoe each contained a downward looking Nortek AquaDopp 2- MHz Acoustic Doppler Current Profiler (ADCP). The ADCPs were configured with 10 bins of 10 cm bin depth, a blanking range of 10 cm, and a transmit distance of 10 cm, pinging at 1.0 Hz. Compass, tilt and roll corrections were internally applied at 1.0 Hz. The AquaDopp ADCPs also contain a pressure sensor which can be used to measure the depth of the current meter head. The pressure sensor at the head provides nominal depth of cm for the skiffs and 5-10 cm for the Outrigger Canoe. The nominal center-depths of the AquaDopp vertical bins are listed in Table 1. Data was then averaged over the top 6 or 8 bins. The one-minute averages were rotated for magnetic variation (+3.7 o to 4.0 o off Chuuk, +3.6 o off Puluwat and o off Guam) and leeway (180 o ) coordinates systems, and then 1-minute samples were averaged to 10-minute samples. The 10-minute samples were trimmed at both ends to eliminate any effects of deployment and recovery. Figure 15. The Nortek AquaDopp 2 MHz ADCP (hull for a single battery pack). Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 16

20 Table 1. Center Depth (cm) of the AquaDopp ADCP vertical bins. Bin # (top to bottom) Skiff AquaDopps Bin center depth (cm) Outrigger Canoe AquaDopp Bin center depth (cm) Not used Not used The Personal Water Craft contained a downward looking RD Instrument (RDI) Workhorse Monitor khz Acoustic Doppler Current Profiler (ADCP) located 10 cm below the water line, Figure 11. For the first deployment, the RDI ADCP was programmed for 5 cm bin size, with a blanking range of 50 cm, pinging at 1.0 Hz, and averaging over 1:00 minutes. Data was then averaged over the top 6 bins and 10-minute intervals on the 10 minutes. Averages were rotated for magnetic variation (+4.0 o ) and leeway (180 o ) coordinates systems. The first bin was centered 72 cm below the head and last bin was 97 cm below, Table 2. For the remaining deployments, the RDI was programmed with a 25 cm blanking range and 10 cm bins, averaged over the top 5 bins, so data was collected centered at 47 cm to 87 cm depths by 10 cm intervals, Table 2. Averages were rotated for the local magnetic declination and for leeway coordinate system. The 10-minute samples were then trimmed at both ends to eliminate any affects of deployment and recovery. Table 2. Center Depth (cm) of the RDI ADCP vertical bins. Bin # (top to bottom) PWC Run 1 Bin center depth (cm) PWC Run 3 and 5 Bin center depth (cm) Not used Each of the two skiffs were outfitted with a Coastal Environmental System WeatherPak 2000 with a Gill ultrasonic anemometer which were used to collect the winds during their deployment. The Gill ultrasonic anemometer has a threshold and resolution of 0.01 m/s (0.02 knots) for wind speed, with a response time of 0.25 seconds, and a range between 0 and 60 m/s (116 knots). Directional accuracy is +/- 3 and resolution is 1 with no dead band. The height of the sonic anemometer on Skiff One was 179 cm above water line and Skiff Two Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 17

21 was 183 cm. The anemometers sampled at 1 Hz and were averaged over 10-minute samples on the 10:00 (mm:ss). GPS positions were collected by both the WeatherPak and the GPS/Iridium beacons on board the skiffs. The positions closest to the 10:00 (mm:ss) were used to determine the over the ground drift rate of the skiffs. These drift rate values were then use to convert the winds from relative winds to absolute winds at the height of the anemometer. Following Smith (1988) absolute wind speeds were adjusted under neutral conditions to a height of 10-meters. The WeatherPaks also measured: mean and standard deviation of pitch and roll at the battery canister, compass heading, wind direction, scalar wind speed, and vector wind speed. In addition, the WeatherPaks sampled once per sampling period: wind gust, air temperature 8 cm below the anemometer height, GPS position, internal temperature, and battery voltage. The WeatherPak (s/n 2961) which was mounted on Skiff Two also measured once per sampling period the relative humidity and barometric pressure at the level of air temperature sensor (175 cm above water line). Records were then matched in time, for analysis on the 10-minute samples. The leeway was decomposed in components aligned with the downwind direction (DWL) and orthogonal (crosswind) (CWL) to the downwind direction for every 10-minute sample. The leeway speed and the downwind components were linearly regressed against the 10-meter wind speed. The linear regression was undertaken both unconstrained (Eq. 1) and constrained through the origin (Eq 2). The slope, y-intercept (for the unconstrained regression), Standard Error term (S yx ) and the r 2 term were reported (Neter et al., 1996). For the crosswind components of leeway, the values were separated along runs or portions of runs indicated by the progressive vector diagrams to be consistently left (negative) or right (positive) of the downwind direction. Then the positive crosswind components were combined with minus-one multiplied by the negative crosswind components and were linearly regressed against the 10- meter wind speed, again both unconstrained and constrained through the origin. Leeway component (cm/s) = Slope (%) x Wind Speed Adjust to 10-m height + y-intercept (cm/s) Leeway component (cm/s) = Slope (%) x Wind Speed Adjust to 10-m height (Eq. 1) (Eq. 2) Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 18

22 5 RESULTS 5.1 Summary of the Drift Runs Drift runs were conducted on the four drift objects from 28 May to 12 June 2012 by the US Coast Guard vessel SEQUOIA off Chuuk FSM, Puluwat Atoll FSM and Guam. (Figures 16, 17 and 18) The first portion of this experiment was supporting a Search and Rescue exercise (SAREX), so the focus was on establishing a 5-day continuous drift run of a 5.8 m fiberglass Panga skiff with a loading of 2 Persons On Board (POB). After the conclusion of the SAREX (28 May 2 June) SEQUOIA made a port call in Chuuk, FSM. During this time a real Search and Rescue case occurred. A 23-ft (7 m) fiberglass Panga skiff with 2 POB was overdue from Nomwin atoll 60 nm north of Chuuk, en route back to Chuuk. Leeway data from the first SAREX portion was used to successfully predict the location of the missing skiff. However, this somewhat shifted the focus away from only the 19-ft skiff with 2 POB, to also include other loadings of the 5.8 m skiffs, as well as the 23-ft (7.0 m) skiffs. It also outlined the need to investigate the variety and relative number of the Pangas, at least for Chuuk. To this end, an informal survey of the skiffs in Chuuk harbor was undertaken, which facilitated the location and measurement of a 23-ft fiberglass Panga skiff. A draft vs. loading test of Skiff Two was conducted alongside the SEQUOIA whilst it was dockside in Chuuk, whereby weight was progressively added to the 19-ft skiff and its draft was recorded by the pressure sensor in the Aquadopp ADCP mounted on the stern. The drift runs that successfully returned concurrent leeway and wind data are summarized in Table 3. Figure 16. Drift Runs off Chuuk, FSM, 28 May June 2012 Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 19

23 Figure 17. Drift Runs off Puluwat, FSM, 8-9 June 2012 Figure 18. Drift Runs off Guam, 12 June 2012 Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 20

24 Table 3. Summary of Drift Runs (Strike through did not return useful data) Drift Object Run # POB Deployment (clear of boat) Date Time UTC Retrieval (clear of boat) Time Date Duration 10 m Wind Speed Range UTC hh:mm m/s Skiff /28/2012 0:48 5/28/ :32 22: PWC 1 0 5/28/2012 1:00 5/28/2012 6:02 05: Canoe 1 1 5/28/ :06 5/29/2012 6:20 07: PWC /28/ :19 5/29/2012 6:00 06:41 n/a Skiff /28/ :45 5/29/ :59 24: Skiff /29/ :30 5/30/ :22 22: Canoe 2 1 5/30/2012 0:28 5/30/2012 5:52 05: Skiff /30/ :14 5/31/ :15 25: Canoe 3 1 5/31/ :52 6/1/2012 5:46 06: Skiff /31/ :32 6/2/2012 2:26 27: PWC 3 1 6/1/ :16 6/2/2012 2:05 03: Skiff /8/ :17 6/9/2012 8:02 10: Skiff /8/ :11 6/9/2012 8:23 11: Canoe 4 1 6/8/ :25 6/9/2012 8:55 11: PWC /8/ :28 6/9/2012 8:36 11:08 n/a Skiff /12/2012 0:24 6/12/2012 0:41 0:17 n/a Skiff /12/2012 0:19 6/12/ :12 21: Canoe 5 1 6/12/2012 0:29 6/12/ :21 22: PWC 5 1 6/12/2012 0:33 6/12/ :37 22: Battery failed. 2 ADCP hung up on gimbals during deployment, tilt exceeded tolerances. 3 Skiff was overloaded (much greater than 6 POB), unsuccessful recovery, resulted in loss of run and anemometer. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 21

25 5.2 Results for the 5.8 Meter Fiberglass Panga Skiffs Results from the Guam/Chuuk/Puluwat Leeway Field Tests The first five skiff runs were loaded with 204 kg (450 lbs, or the equivalent loading of two POB plus a 40 Hp motor. Successful drift runs were also collected with 1 and 4 POB loading plus 40 Hp motor. Table 4. Summary of 5.8 meter Fiberglass Pacific Island Panga Skiff Drift Runs (Start and End Time of useable data) Drift Object Run # POB Start Date Time UTC End Time Date UTC Duration hh:mm 10 m Wind Speed Range Skiff-1 1a 2 5/28/ :50 5/28/ :30 16: Skiff-1 1b 13 5/28/ :40 5/28/ :30 02: Skiff /28/ :00 5/29/ :50 23: Skiff /29/ :30 5/30/ :20 22: Skiff-2 2a 2 5/30/ :20 5/31/ :40 18: Skiff-2 2b 4 5/31/ :10 5/31/ :10 5: Skiff /31/ :50 6/2/ :20 27: Skiff /8/ :20 6/9/ :00 10: Skiff /8/ :20 6/9/ :20 11: Skiff /12/2012 0:20 6/12/ :10 21: m/s The AquaDopp current meters were mounted on the transoms of the skiffs in the same locations. Each AquaDopp recorded the pressure at the level of the sensor head at the sampling interval of once per minute. The WeatherPak fitted to Skiff Two was equipped with barometer. The AquaDopps started and ended sampling whilst on board the vessel, so there was an initial and final atmospheric offset which was used for Skiff One as it did not have a barometer on board. For Skiff Two, a time series of atmospheric offsets were applied using the barometric readings from the WeatherPak fitted to it. The one minute pressure adjusted for initial and final atmospheric pressure are shown in red (Skiff One) and blue (Skiff Two) in Figure 19. Also shown is the (atmospheric pressure 1030 mb) from Skiff Two (black line). When Skiff One - Run 1, and Skiff Two - Run 2 were recovered they contained rain water from overnight storms. Thus Skiff One - Run 1 was able to be split into two sections, the first portion with its normal 2 POB loading, and second portion with a much higher loading. An estimated 10 cm of rain fell between 17:20 and 17:50z, 5/28/2012, and during this time the leeway rate records suggest either a problem with the sonic anemometer or the ADCP. Skiff Two - Run 2, was trimmed to eliminate the portion with the extra loading, since it was unclear exactly when the rain (extra loading) occurred. Drift Run 1 of the Skiff One was split into two sections dependent on the loading. Skiff One was not weighed at the end of Run 1, with its load of rain water. The information in Figure 19 alone is insufficient to estimate the extra loading of Skiff One, at the end of Run 1. While it is interesting to note that the pressure sensors are measuring a combination of nominal draft of the skiff, atmospheric pressure, and extra draft due to rain loading, the pressure sensors became a sort of draft, barometric pressure, and rain gauge all rolled into one sensor. Dockside in Chuuk, a static loading test of Skiff Two was conducted. Skiff Two was loaded with the nominal two-person loading of 204 kg (450 lbs or 2 POB + 40 Hp motor), Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 22

26 adding two additional persons after 5 minute periods. Figure 20 shows the pressure of the AquaDopp adjusted for start and end atmospheric pressure as loading was increased in 2 person increments from 2 to 10 person-loading. The linear regression of draft against total loading (kg) is presented in Figure 22 Figure 19. Pressure time-series records from Skiff One (red), Skiff Two (blue) AquaDopp current meters, and atmospheric pressure 1030 mb from Skiff Two WeatherPak. Figure 20. Time series of the AquaDopp pressure sensor on Skiff Two adjusted for start and end atmospheric pressure. Pressure averages were taken during the periods marked by horizontal dashed lines. Total loading (kg) are labeled above the averaging periods. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 23

27 Figure 21. Skiff Two with 8 persons on board, plus sand bags; total loading 820kg. Figure 22. Linear regression of draft (cm) against total loading (kg) for Skiff Two. 95% confidence limits are shown. Draft (cm) = cm/kg x (loading kg) cm; r 2 = 0.996, S yx = 0.23 (Eq. 3) Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 24

28 Returning to Figure 19, the time series of pressure records from the skiff s ADCPs, during Run 1 of Skiff One near the end of the record there was approximately a 10 cm increase in the draft of the skiff from 22 cm to 32 cm. Using the relationship found in Equation 3, 10 cm draft / cm/kg = 746 kg extra mass of rain water on board Skiff One - Run 1 during the end portion of its drift run. Thus the skiff contained an estimated total loading of 950 kg, since it already had 204 kg on board simulating 2 POB and a 40 Hp motor. This is the equivalent of 13 POB loading plus 40 Hp motor. Therefore, Skiff One - Run 1 was split into two sections: a 2 POB loading section before the drastic increase in draft and a 13 POB section after, as shown in Table 4, Skiff One - Runs 1a and 1b. The leeway of panga skiffs was measured with the loading of a 40 Hp motor (68 kg) and various loadings equivalent to additional Person-On-Board, assuming one adult POB is 68 kg. Therefore the results were expressed in terms of POB equivalents, meaning the additional loading in 68 kg increments above beyond the weight of the skiff itself and a 40 Hp motor. Children or cargo should be considered in terms of their weight of a standard adult POB (68 kg). Common cargo is a 55-gallon barrel holding cubic meters of liquid. The empty weight of a 55-gallon (0.208 m 3 ) barrel is approximately 35 lbs (16 kg). The density (mass/volume) of common fluids transported in these barrels can be found on-line, usually in kg/m 3. To determine the total mass (weight) of a partial or full 55-gallon barrel the following equations can be used: Total mass = mass of container + density of fluid x volume of container x percent full/100 Full 55-gallon drum (lbs) = 35 lbs + density of fluid (kg/m 3 ) x Partially full 55-gallon drum (lbs) = 35 lbs + density of fluid (kg/m 3 ) x x percent full/100 Full 55-gallon drum (kg) = 16 kg + density of fluid (kg/m 3 ) x Partially full 55-gallon drum (kg) = 16 kg + density of fluid (kg/m 3 ) x x percent full/100 (Eq. 4) (Eq. 5) (Eq. 6) (Eq. 7) (Eq. 8) The weight of 90% and 100% full 55-gallon drums with a few common liquids are listed in Table 5, along with their equivalent additional POB loading. Table 5. Total weights of common fluids in a 55-gallon drum (35lbs, 16 kg empty) Fluid 90% full (total lbs) 100% full (total lbs) 90% full (total kg) 100% full (total kg) POB equivalent Fresh water Gasoline Diesel fuel Fuel oil Kerosene Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 25

29 5.2.1 Results for the 5.8 Meter Fiberglass Panga Skiffs - with 1 POB equivalent loading (136 kg total loading) Skiff One - Run 4 was drifted for 10:40 hh:mm off Puluwat Atoll with 136 kg of sand bags on board to simulate 1 POB and a 40 Hp motor. Wind speeds (10-m) ranged from m/s. The leeway speed, downwind component of leeway and the crosswind components of leeway 10-minute data for 5.8 m fiberglass panga skiff with 1 POB equivalent loading at the measured loadings versus the wind speed adjusted to 10-meter height are shown in Figures 23, 24, and 26 along with the unconstrained and constrained linear regressions and their respective 95% prediction limits. Tables summarize the linear regression slope, y- intercept terms, r 2 and standard error (S yx ) terms for the leeway speed, downwind component of leeway and crosswind components of leeway. The progressive vector diagram (PVD) for the downwind and crosswind components of leeway relative to water is shown in Figure 25. To construct this diagram, the 10-minute leeway vectors are decomposed into a downwind and crosswind component. These components are then converted from velocity vectors to displacement vectors and are plotted head to tail. This illustrates the overall displacement of the skiff relative to the sea surface due to its leeway. A straight-downwind drift would follow the black center line; here it can be seen that the skiff drifted to the right of the downwind direction for the entire 10 hour and 40 min drift run, without switching from positive CWL to negative CWL values, hence no jibes were observed. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 26

30 Figure 23. Leeway Speed (cm/s) versus Wind Speed adjusted to 10-meter height for the 5.8 m fiberglass panga skiff with 1 POB equivalent loading (blue circles). Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its confidence limits are plotted in red. Figure 24. Downwind Component of Leeway (cm/s) versus Wind Speed adjusted to m fiberglass panga skiff with 1 POB equivalent loading (blue squares). Unconstrained linear regression mean (solid green) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its 95% confidence limits are plotted in red. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 27

31 Figure 25. Progressive Vector Diagram (PVD) of the Down and Crosswind components of Leeway Displacement, for the 5.8 m fiberglass panga skiff with 1 POB equivalent loading. Downwind is up (solid black line), and positive Crosswind is to the right. Displacement is in kilometers. Hourly intervals are indicated by a black square point every 6 th point. Figure 26. Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10-meter height for the 5.8 m fiberglass panga skiff with 1 POB equivalent loading (blue + positive crosswind components), Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its 95% confidence limits are plotted in red. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 28

32 5.2.2 Results for the 5.8 Meter Fiberglass Panga Skiffs - with 2 POB equivalent loading (204 kg total loading) Skiff One - Runs 1a, 2 and 3, and Skiff Two - Runs 1 and 2a were drifted for a total of 109:10 hh:mm off Chuuk FSM with 204 kg of sand bags on board to simulate 2 POB and a 40 Hp motor. Wind speeds (10-m) ranged from m/s. The leeway speed, downwind component of leeway and the crosswind components of leeway 10-minute data for 5.8 m fiberglass panga skiff with 2 POB equivalent loading at the measured loadings versus the wind speed adjusted to 10-meter height are shown in Figures 27, 28, 31, 32, and 33 along with the unconstrained and constrained linear regressions and their respective 95% prediction limits. Tables summarize the linear regression slope, y- intercept terms, r 2 and standard error (S yx ) terms for the leeway speed, downwind component of leeway and crosswind components of leeway. The Progressive vector diagrams (PVD) for the downwind and crosswind components of leeway relative to water is shown in Figure 29 and 30 for the five drift runs with 2 POB loading. A straight-downwind drift would follow the black center line; here the results show that the first two drift runs drifted to the left of the downwind direction (negative CWL). However on closer inspection, during Skiff One -Run 1a, three (3) pairs of switches from negative CWL to positive CWL values and back were observed. No jibes (change in CWL signs from positive to negative or vice versa) were observed during the other four drift runs. Figure 27. Leeway Speed (cm/s) versus Wind Speed adjusted to 10-meter height for the 5.8 m fiberglass panga skiff with 2 POB equivalent loading. The three Skiff One drift runs are plotted in blue, while two Skiff Two runs are plotted in black. Unconstrained linear regression mean for both craft (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression for both craft and its confidence limits are plotted in red. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 29

33 Figure 28. Downwind Component of Leeway (cm/s) versus Wind Speed adjusted to m fiberglass panga skiff with 2 POB equivalent loading. The three Skiff One drift runs are plotted in blue, while two Skiff Two runs are plotted in black. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression (solid) and its confidence limits (dashed) are plotted in red. Figure 29. Progressive Vector Diagram (PVD) of the Down and Crosswind components of Leeway Displacement, for the five drift runs of the 5.8 m fiberglass panga skiffs with 2 POB equivalent loading. Downwind is up (solid black line), and positive Crosswind is to the right. Displacement is in kilometers. Hourly intervals indicated by a larger marker every 6 th point and are restarted each drift run; from left to right (Skiff One - Run 1 / Skiff Two - Run 1 / Skiff One - Run 3 / Skiff One - Run 2 / Skiff Two - Run 2). Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 30

34 Figure 30. Zoomed in view of the PVD for the Skiff One, Run 1 (red dots with black squares) with 2 POB equivalent loading. Arrows indicate 4 of the 6 switches (jibes) between negative and positive CWL. Figure 31. Positive Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10- meter height for the 5.8 m fiberglass panga skiff with 2 POB equivalent loading (blue + Skiff One, black + Skiff Two). Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its 95% confidence limits are plotted in red. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 31

35 Figure 32. Negative Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10- meter height for the 5.8 m fiberglass panga skiff with 2 POB equivalent loading (blue + Skiff One, black + Skiff Two), Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its 95% confidence limits are plotted in red. Figure 33. Positive and minus one times Negative Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10-meter height for the 5.8 m fiberglass panga skiff with 2 POB equivalent loading (blue markers Skiff One, black markers Skiff Two), are positive crosswind whilst are -1 multiplied by negative crosswind Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its 95% confidence limits are plotted in red. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 32

36 5.2.3 Results for the 5.8 Meter Fiberglass Panga Skiffs - with 4 POB equivalent loading (340 kg total loading) Skiff Two - Runs 3 and 4 were drifted for 32:50 hh:mm off Puluwat and Guam with 340 kg of sand bags on board to simulate a loading of 4 POB and a 40 Hp motor. Another 5:00 hh:mm at the end of Skiff Two - Run 2 had rain water on board making the total loading for that portion of the run equivalent to 4 POB. Wind speeds (10-m) ranged from m/s over the 37:50 hh:mm total drift periods. The leeway speed, downwind component of leeway and the crosswind components of leeway 10-minute data for 5.8 m fiberglass panga skiff with 4 POB equivalent loading at the measured loadings versus the wind speed adjusted to 10-meter height are shown in Figures 34, 35, and 37 along with the unconstrained and constrained linear regressions and their respective 95% prediction limits. Tables summarize the linear regression slope, y- intercept terms, r 2 and standard error (S yx ) terms for the leeway speed, downwind component of leeway and crosswind components of leeway. The progressive vector diagrams (PVD) for the downwind and crosswind components of leeway relative to water is shown in Figure 36 for the three drift runs with 4 POB loading. A straight-downwind drift would follow the black center line; here all three runs drifted to the right of the wind (positive CWL). No changes in CWL sign (jibes) were observed during the drift runs. Figure 34. Leeway Speed (cm/s) versus Wind Speed adjusted to 10-meter height for the 5.8 m fiberglass panga skiff with 4 POB equivalent loading, Skiff Two plotted in black. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its confidence limits are plotted in red. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 33

37 Figure 35. Downwind Component of Leeway (cm/s) versus Wind Speed adjusted to m fiberglass panga skiff with 4 POB equivalent loading. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its confidence limits are plotted in red. Figure 36. Progressive Vector Diagram (PVD) of the Down and Crosswind components of Leeway Displacement, for the three drift runs of the 5.8 m fiberglass panga skiffs with 4 POB equivalent loading. Downwind is up (solid black line), and positive Crosswind is to the right. Displacement is in kilometers. Hourly intervals are indicated by a larger marker every 6 th point and are restarted each drift run; from left to right (Skiff Two - Run 3 / Skiff Two - Run 2 (4-POB portion) / Skiff Two - Run 4). Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 34

38 Figure 37. Positive Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10- meter height for the 5.8 m fiberglass panga skiff with 4 POB equivalent loading. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its 95% confidence limits are plotted in red. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 35

39 5.2.4 Results for the 5.8 Meter Fiberglass Panga Skiffs - with 13 POB equivalent loading (950 kg total loading) Skiff One - Run 1 started its drift off Chuuk with 204 kg of sand bags on board to simulate a loading of 2 POB and a 40 Hp motor. However, between 16:40 and 20:40z 05/28/2012 nearly 10 cm of rain fell into the skiff, Figure 19. Therefore, at the end of Run 1, Skiff One included rain water making the loading for that portion of the run equivalent to 13 POB. Wind speeds for this portion of the run (10-m) ranged from m/s over this 2:50 hh:mm drift period. The leeway speed, downwind component of leeway and the crosswind components of leeway 10-minute data for 5.8 m fiberglass panga skiff with 13 POB equivalent loading at the measured loadings versus the wind speed adjusted to 10-meter height are shown in Figures 38, 39, and 41 along with the unconstrained and constrained linear regressions and their respective 95% prediction limits. Tables summarizes the linear regression slope, y- intercept terms, r 2 and standard error (S yx ) terms for the leeway speed, downwind component of leeway and crosswind components of leeway. The progressive vector diagrams (PVD) for the downwind and crosswind components of leeway relative to water is shown in Figure 40 for the Skiff One - Run 1, 13-POB portion A straight-downwind drift would follow the black center line; during the 13-POB portion of Skiff One - Run 1 drifted to the left of the wind (negative CWL). No changes in CWL sign (jibes) were observed during the drift run. Figure 38. Leeway Speed (cm/s) versus Wind Speed adjusted to 10-meter height for the 5.8 m fiberglass panga skiff with 13 POB equivalent loading. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its confidence limits are plotted in red. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 36

40 Figure 39. Downwind Component of Leeway (cm/s) versus Wind Speed adjusted to m fiberglass panga skiff with 13 POB equivalent loading. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its confidence limits are plotted in red. Figure 40. Progressive Vector Diagram (PVD) of the Down and Crosswind components of Leeway Displacement, for the drift run of the 5.8 m fiberglass panga skiff with 13 POB equivalent loading. Downwind is up (solid black line), and positive Crosswind is to the right. Displacement is in kilometers. Hourly intervals are indicated by a larger marker every 6 th point and are restarted each drift run; (Skiff One - Run 1, 13-POB portion). Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 37

41 Figure 41. Negative Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10- meter height for the 5.8 m fiberglass panga skiff with 13 POB equivalent loading (Blue ). Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and its 95% confidence limits are plotted in red. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 38

42 5.2.5 Results from the Combination of Panga Drift Runs - Separated by Loading The initial focus of this experiment was in support of the SAREX, where the primary search object was a 19-ft panga with 2 POB. At the conclusion of that initial portion of the cruise, leeway data was gathered on 19-ft panga skiffs with other loadings. Here the combined data set was analyzed to interpolate leeway values for the intermediate loadings. Because of the disparity in the number of samples at the different loadings and the variance of the leeway drifts from run to run, the combined data set was analyzed at the run level. The average 10-minute DWL and CWL rates (DWL / wind speed; and CWL/Wind Speed) were first determined for each drift run. Then the average DWL and CWL rates were then used to calculate the average leeway rate and divergence angle by drift run, using equations 9 and 10. Ave leeway rate = (avedwlrate 2 + avecwlrate 2 ) Ave Divergence Angle = arctan(avecwlrate / avedwlrate) (Eq. 9) (Eq. 10) Table 6. Average Rates (% of 10-m wind speed) of: Leeway Speed, DWL, CWL; and Divergence Angle (degrees) for 5.8 m Fiberglass Panga Skiff Drift Runs Skiff Run Total loading (kg) [POB] # of 10-min Sample s Ave 10-m Wind Speed (m/s) Ave DWL Rate (%) Ave CWL Rate (%) Ave Leeway rate (%) Ave Divergence Angle (deg) Skiff [1] Skiff-1 1a 204 [2] Skiff [2] Skiff [2] Skiff-2 2a 204 [2] Skiff [2] Skiff-2 2b 340 [4] Skiff [4] Skiff [4] Skiff-1 1b 950 [13] Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 39

43 Figure 42. Downwind Component of Leeway Rate (% of 10-m Wind Speed) averaged by drift run versus total loading (kg) of the 5.8 m fiberglass panga skiffs. Unconstrained linear regression mean (solid) and 68% confidence levels (dash) are plotted in green. Figure 43. Absolute value of Crosswind Component of Leeway Rate (% of 10-m Wind Speed) averaged by drift run versus total loading (kg) of the 5.8 m fiberglass panga skiffs. Unconstrained linear regression mean (solid) and 68% confidence levels (dash) are plotted in green. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 40

44 Figure 44. Leeway Rate (% of 10-m Wind Speed) averaged by drift run versus total loading (kg) of the 5.8 m fiberglass panga skiffs. Unconstrained linear regression mean (solid) and 68% confidence levels (dash) are plotted in green. Figure 45. Absolute value of Divergence Angle (degrees) averaged by drift run versus total loading (kg) of the 5.8 m fiberglass panga skiffs. Unconstrained linear regression mean (solid) and 68% confidence levels (dash) are plotted in green. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 41

45 DWL (%) = (% / kg) x total loading (kg) % (Eq. 11) Where: S yx (%) = 1.11 r 2 = 0.46 CWL (%) = (% / kg) x total loading (kg) % (Eq. 12) Where: S yx (%) = 0.65 r 2 = 0.33 Leeway Rate (%) = (% / kg) x total loading (kg) % (Eq. 13) Where: S yx (%) = 1.08 r 2 = 0.52 Divergence Angle (deg) = (deg / kg) x total loading (kg) deg (Eq. 14) Where: S yx (deg) = 7.90 r 2 = 0.11 Equations can be implemented into SAR planning tools to determine leeway as function of total loading for 5.8m Panga. Assuming, a standard 68 kg outboard motor and 68 kg per adult POB, Table 7 provides the inputs for SAROPS User Define Leeway and Table 8 provides inputs for SAR planning tools at 68kg (1 POB) loading increments. SAR planning tools that use the S yx term to generate a spread of DWL and CWL slope terms will need to convert the above S yx term (in %) to equivalent term presently used in the SAR Planning tools (S yx in cm/s), see Equation 15. S yx (cm/s) = S yx (% or cm/s / m/s) x 10m/s (Eq. 15) Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 42

46 SAROPS uses Equation 2 and following Allen (2005), the S yx term is used to generate new slope terms for both DWL and CWL for each particle in the ensemble. However, negative DWL slope terms are un-realistic; the particle would drift upwind faster as the wind blew harder. SAROPS draws from a normal distribution truncated at 3.0 standard deviations about the mean, Equation 16. Equations 17 (metric) and 18 (Imperial units and SAROPS) follow Allen (2005) for generating new DWL slope terms. However, in User Defined Search Objects within SAROPS, the standard error term is given as knots (12 cm/s), Equation 19. Therefore, Equation 20 provides the threshold for using Normal Distributions vs Rayleigh Distributions for User Defined DWL values, and Equation 21 defines the threshold for all other DWL constrained slope terms and their associated S yx (cm/s) terms. Normal_dist_truncated = abs (normal random (zero mean, 1.0 Standard deviation)) < 3.0 (Eq. 16) DWL_slope_terms = DWL_slope (%) + [Normal_dist_truncated x S yx (cm/s)] / (10.29 m/s) (Eq. 17) DWL_slope_terms = DWL_slope + [Normal_dist_truncated x S yx (kts)] / (20 kts) (Eq. 18) DWL_slope_terms = DWL_slope + [Normal_dist_truncated x 0.24 kts] / (20 kts) (Eq. 19) UserDefined_DWL_slope_requiring_Rayleigh < 3 x kts / (20 kts) = or 3.50% (Eq. 20) DWL_slope_requiring_Rayleigh < 3 x S yx (cm/s)/10.29 m/s (Eq. 21) e.g. 3 x 11.1 cm/s/10.29 m/s = 3.236% DWL_slope_from_UserDefined = Leeway_rate x cosine(divergence_angle) (Eq. 22) Therefore we use Equation 20 and Equation 22 for User Defined, and use Equation 21 when SAROPS used the DWL and DWL s S yx terms. Results are presented in Tables 7 and 8. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 43

47 Table 7. User Defined Leeway Parameters for 19-23ft Panga with a 68 kg 40 Hp motor (where one POB = 68 kg, 150 lbs). Loading (POB + motor) Total Loading (kg) / (lbs) Leeway Rate (%) Divergence Angle (deg) Use Rayleigh Distribution / No 2 204/ No / No / No / No / No / No / No / No / Yes / Yes / Yes Table 8. Down wind and Cross wind components of leeway for 5.8 m Panga with a 40 Hp motor for SAROPS / SARMAP (Where one POB = 150 lbs or 68 kg; DWL Syx (cm/s) = 11.1 cm/s; CWL Syx (cm/s) = 6.5 cm/s) Loading (POB + motor) Total Loading (kg) DWL (% 10-m wind speed ) +/- CWL (% 10-m wind speed ) Use Normal or Rayleigh Distribution Normal Normal Normal Normal Normal Normal Normal Normal Normal Rayleigh Rayleigh Rayleigh Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 44

48 5.3 Results for the 5.97 m Fiberglass Outrigger Canoe Results from the Guam/Chuuk/Puluwat Leeway Field Tests There were five drift runs of the 5.97 m fiberglass Outrigger Canoe, Table 9. Leeway drift runs were matched at the ten minute sampling period to 10-m winds from the 5.8 m skiffs. Run 1 was divided into two parts, as there was some interference to the drift as a result of changing out the GPS/Iridium beacon early in the drift. A total of 51:10 hh:mm of leeway data was collected on the 5.97 m fiberglass Outrigger Canoe. Table 9. Summary of the 5.97 m fiberglass Outrigger Canoe Leeway Drift Runs Drift Object Run # POB Start Date Time UTC End Time Date UTC Duration hh:mm 10 m Wind Speed Range Canoe 1a 1 5/28/ :30 5/29/2012 0:50 01: Canoe 1b 1 5/29/ :00 5/29/2012 6:20 05: Canoe 2 1 5/30/2012 0:30 5/30/2012 5:50 05: Canoe 3 1 5/31/ :00 6/1/2012 5:40 06: Canoe 4 1 6/8/ :30 6/9/2012 8:20 10: Canoe 5 1 6/12/2012 0:30 6/12/ :10 21: m/s The 10-minute data for leeway speed, downwind component of leeway and the crosswind components of leeway for 5.97 m fiberglass Outrigger Canoe versus the wind speed adjusted to the 10-meter height are shown in Figures 46, 47, 50, 51, and 52 along with the unconstrained and constrained linear regressions and their respective 95% prediction limits. Tables summarize the linear regression slope, y-intercept terms, r 2 and standard error (S yx ) terms for the leeway speed, downwind component of leeway and crosswind components of leeway. The unconstrained linear regression of the crosswind components were disregarded due to the lack of a reasonable data set for unconstrained regressions. The progressive vector diagram shows that the outrigger canoe drifted generally downwind or slightly to the right of downwind for most of the drift runs, Figure 48. When the crosswind displacement is expanded by a factor of two (Figure 49), four changes in sign of CWL were observed (jibing), marked by arrows. The average leeway rate for the outrigger canoe was % of the 10-m Wind Speed (Table 12), and the average divergence angle was arctan (0.536/2.302) = 13.1 o. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 45

49 Figure 46. Leeway Speed (cm/s) versus Wind Speed adjusted to 10-meter height for the 5.97 m fiberglass Outrigger Canoe. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and corresponding 95% confidence intervals are plotted in red. Figure 47. Downwind Component of Leeway (cm/s) versus Wind Speed adjusted to 10-meter for the 5.97 m fiberglass Outrigger Canoe. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and corresponding 95% confidence intervals are plotted in red. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 46

50 Figure 48. Progressive Vector Diagram (PVD) of Down and Crosswind components of Leeway Displacement, for the 5.97 m fiberglass Outrigger Canoe with 1 POB equivalent loading. Downwind is up, and positive Crosswind is to the right. Displacement is in kilometers. Hourly intervals indicated by larger marker every 6 th point. Ratio of crosswind to downwind displacement is 1 to 1. Run 1 blue diamonds and magenta circles; Run 2 green diamonds and blue circles; Run 3 red diamonds and black diamonds; Run 4 black diamonds and green circles, Run 5 black diamonds and red squares). Figure 49. PVD for the for the 5.97 m fiberglass Outrigger Canoe with 2 POB equivalent loading showing 2 to 1 ratio of crosswind to downwind displacement. Arrows indicate the changes between negative and positive CWL (jibes). Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 47

51 Figure 50. Positive Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10- meter height for the 5.97 m fiberglass Outrigger Canoe. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and corresponding 95% confidence intervals are plotted in red. Figure 51. Negative Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10- meter height for the 5.97 m fiberglass Outrigger Canoe. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and corresponding 95% confidence intervals are plotted in red. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 48

52 Figure 52. Positive and minus one times Negative Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10-meter height for the 5.97 m fiberglass Outrigger Canoe ( (positive crosswind components); (-1 x negative crosswind component)) Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and corresponding 95% confidence intervals are plotted in red. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 49

53 5.4 Results for the 2.70 m 2-person Personal Water Craft There were three successful drift runs of the 2.70 m 2-person Personal Water Craft, Table 10. Leeway drift runs were matched at the ten minute sampling period to 10-m winds from the 5.8 m skiffs. A total of 30:10 hh:mm of leeway data was collected on the 2.70 m 2-person Personal Water Craft. Table 10. Summary of the 2.70 m 2-person Personal Water Craft Leeway Drift Runs Drift Object Run # POB Start Date Time UTC End Time Date UTC Duration hh:mm 10 m Wind Speed Range PWC 1 0 5/28/ :00 5/28/2012 6:00 05: PWC 3 1 6/1/ :20 6/2/ :00 03: PWC 5 1 6/12/ :40 6/12/ :10 21: m/s The leeway speed, downwind component of leeway and the crosswind components of leeway 10-minute data for 2.70 m 2-person Personal Water Craft versus the wind speed adjusted to the 10-meter height are shown in Figures 53, 54, 56, 57, and 58 along with the unconstrained and constrained linear regressions and their respective 95% prediction limits. Tables summarize the linear regression slope, y-intercept terms, r 2 and standard error (S yx ) terms for the leeway speed, downwind component of leeway and crosswind components of leeway. The unconstrained linear regression of the crosswind components were disregarded due to the lack of a reasonable data set for unconstrained regressions. The progressive vector diagram shows that the Personal Water Craft did not jibe during any of its drift runs, Figure 55. The average leeway rate for the outrigger canoe was 4.244% of the 10-m Wind Speed (Table 12), and the average divergence angle was arctan (0.855/4.124) = 11.7 o. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 50

54 Figure 53. Figure 1. Leeway Speed (cm/s) versus Wind Speed adjusted to 10-meter height for the 2.70 m 2-person Personal Water Craft. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and corresponding 95% confidence intervals are plotted in red. Figure 54. Figure 2. Downwind Component of Leeway (cm/s) versus Wind Speed adjusted to 10- meter for the 2.70 m 2-person Personal Water Craft. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and corresponding 95% confidence intervals are plotted in red. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 51

55 Figure 55. Progressive Vector Diagram (PVD) of the Down and Crosswind components of Leeway Displacement, for the 2.70 m 2-person Personal Water Craft. Downwind is up, and positive Crosswind is to the right. Displacement is in kilometers. Hourly intervals are indicated by a larger marker every 6 th point. Ratio of crosswind to downwind displacement is 1 to 1. (Run 1 red; Run 3 blue; Run 5 black). Figure 56. Positive Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10- meter height for the 2.70 m 2-person Personal Water Craft. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and corresponding 95% confidence intervals are plotted in red. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 52

56 Figure 57. Negative Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10- meter height for the 2.70 m 2-person Personal Water Craft. Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and corresponding 95% confidence intervals are plotted in red. Figure 58. Positive and minus one times Negative Crosswind Component of Leeway (cm/s) versus Wind Speed adjusted to 10-meter height for the 2.70 m 2-person Personal Water Craft ( (positive crosswind components); (-1 x negative crosswind component)) Unconstrained linear regression mean (solid) and 95% confidence levels (dash) are plotted in green. Constrained linear regression and corresponding 95% confidence intervals are plotted in red. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 53

57 Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 54 Table 11. Unconstrained Linear Regression of Leeway Speed and Downwind Leeway Parameters Drift Object Slope (%) Leeway Speed Y (cm/s) Syx (cm/s) r 2 Slope (%) Y (cm/s) DWL Syx (cm/s) Panga w/1 POB Panga w/2 POB Panga w/4 POB Panga w/13 POB Outrigger canoe PWC Table 12. Constrained through zero, Linear Regression of Leeway Speed and Downwind Leeway Parameters Drift Object Range of 10m Wind Speed (m/s) # of 10- minute samples Slope (%) Leeway Speed Syx (cm/s) r 2 Slope (%) DWL Syx (cm/s) Panga w/1 POB Panga w/2 POB Panga w/4 POB Panga w/13 POB Outrigger canoe PWC r 2 r 2 Results from the Guam/Chuuk/Puluwat Leeway Field Tests

58 Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 55 Table 13. Unconstrained Linear Regression of Crosswind Leeway Parameters +CWL -CWL +CWL (-CWL) Drift Object Slope Y Syx (%) (cm/s) (cm/s) r 2 Slope Y Syx (%) (cm/s) (cm/s) r 2 Slope Y Syx (%) (cm/s) (cm/s) Panga w/1 POB n/a n/a n/a n/a n/a n/a n/a n/a Panga w/2 POB Panga w/4 POB n/a n/a n/a n/a n/a n/a n/a n/a Panga w/13 POB n/a n/a n/a n/a n/a n/a n/a n/a Outrigger canoe n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a PWC n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a Table 14. Table 1. Constrained through zero, Linear Regression of Crosswind Leeway Parameters +CWL -CWL +CWL (-CWL) Drift Object Slope Syx (%) (cm/s) r 2 Slope Syx (%) (cm/s) r 2 Slope Syx (%) (cm/s) Panga w/1 POB n/a n/a n/a n/a n/a n/a Panga w/2 POB Panga w/4 POB n/a n/a n/a n/a n/a n/a Panga w/13 POB n/a n/a n/a n/a n/a n/a Outrigger canoe PWC r 2 r 2 Results from the Guam/Chuuk/Puluwat Leeway Field Tests

59 5.5 Jibing Frequency Allen (2005) introduces the concept of jibing of the drift objects. Jibing is a term associated with sailing, referring the sailboat changing its tack relative to the downwind direction by passing s its stern through the wind or jibing. Jibing is observed in leeway drifts as significant and prolonged changes in sign changes of the crosswind component of leeway (CWL). The frequency of these changes in CWL is an important element for modeling search areas. With no changes in CWL sign, the initial Monte Carlo probability distribution will eventually separate into left and right distributions about the downwind direction over time. However, with jibing, replications will eventually switch from either the left to right or vice versa generating a more central distribution. The more frequent the jibbing, the more a central distribution will occur at the expense of the two left and right distributions. Jibes or changes in CWL sign occur either abruptly from one ten-minute sample to the next or gradually over a several sampling periods where the CWL value remains within our ability to distinguish CWL from zero. The second method doesn t lend itself to straightforward mathematical definition, and therefore more subjective methods of inspection of the time series were used to splitting the records into either negative or positive segments. Allen (2005) was unable to describe either the dynamics of jibing or provide a statistical model of jibing as function of wind speed or the object shape. Allen (2005) provides a simple averaged value of between 3 and 7% per hour. The frequency of jibing per hour for from this experiment is summarized in Table 15. Table 15. Table 2Significant changes between positive and negative Crosswind component of leeway Jibing Frequency Drift Object # of 10-minute samples Hours:Minutes of Samples CWL switches (jibes) Frequency Per hour Panga w/1 POB 64 10: Panga w/2 POB : Panga w/4 POB : Panga w/13 POB 17 02: Panga total : Outrigger canoe : PWC : (%) Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 56

60 6 SEARCH AND RESCUE CASE 3-6 JUNE 2012 Results from the Guam/Chuuk/Puluwat Leeway Field Tests On 3 June 2012 at about 11:00 local (UTC+10), two persons in a 23-ft Panga left Nomwin Atoll bound for the north entrance to Chuuk atoll (FSM), 60 nm to the south, Figure 59. They were reported overdue to the local SAR authorities in Chuuk at 13:00 (local) 5 June, who immediately contacted the USCG SAR authorities who were in Chuuk with the USCGC SEQUOIA and USCG Sector Guam. The preliminary results from the 5 days of drift of the 19-ft Pangas used during the SAREX was available and passed to Sector Guam for inclusion into SAROPS as a User Define Search Object. A US Marine Corp HC-130 aircraft was available in Guam for searching on 6 June. The drift from a voyage originating in Nomwin Atoll bound for Chuuk (green line) was used to plan the HC-130 search on 6 June. Figure 59. Probability distribution from the 3-6 June 2012 SAR case at the time the 23-Panga with two persons on board was located. The distressed Panga model particles started from the green line which was the intended voyage track of the Panga travelling southward at average speed of 10 knots. The plan track line of the HC-130 is shown as the blue line, starting from the bottom right of the search area. At approximately 14:45 local on the 6 th of June the HC-130 located the Panga and remained on scene until a local coastal freighter was able to rescue the two persons on board the Panga, sunburned, thirsty and hungry, but otherwise in good health. During the de-brief of the Marine Corp pilots, the fact that this Panga was painted orange was significant in detecting the craft and re-acquiring detection as they circled above the Panga awaiting the arrival of the coastal freighter. The two persons were then returned to Chuuk, where their de-brief indicated that about 2 hours after leaving Nomwin Atoll, their engine would not re-start after they had switched out fuel tanks. It was at that point they started drifting. They had some water and provisions on board that lasted until the morning of 6 June. Centre for Infrastructure Engineering and Management Technical Report CIEM/2013/R07 Page 57