Development of a Risk-Based Performance Assessment for Boats_PBS_2024 (3).pdf

SNAME Power Boat Symposium 2024 14 October 2024, Norfolk, VA

Copyright © 2024 Society of Naval Architects and Marine Engineers (SNAME) www.sname.org

Development of a Risk-Based Performance Assessment for Boats

Operating in Heavy Weather

PBS 2024, 14 October, Norfolk, VA 1

Benjamin C. Brainard

Benjamin C. Brainard1 (V), Eric D. Schmid1 (V), Karl A. Stambaugh, Ph.D.2 (F)

1. United States Coast Guard Surface Forces Logistics Center

2. United States Coast Guard, Civilian Naval Architect, Retired

The United States Coast Guard uses various boats for coastal and offshore operations, often in heavy weather, to meet mission requirements such as Search and Rescue (SAR). Traditional assessments based on static stability criteria do not reflect operational environments or seakeeping capabilities. The Coast Guard evaluated cutter boats’ seakeeping and controllability through ship seakeeping methods, comparing model and full-scale tests in wave environments at sub-planing speeds. The evaluation included comparisons with seakeeping programs like SMP, VERES, and LAMP, focusing on motions, accelerations, and control parameters. A risk-based approach combining response probability and consequences is proposed for evaluating operational performance and informing design and in-service capability evaluations. This approach helps develop and validate simplified criteria for quick assessment. Recommendations for further development of the risk-based approach and performance criteria are provided.

The views expressed herein are those of the authors and are not to be construed as official or reflecting the views of the Commandant or of the United States Coast Guard.

Distribution A: Approved for Public Release. Distribution is Unlimited.

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KEY WORDS: coast guard; operations (general);

performance prediction; safety; sea keeping; small craft.

INTRODUCTION

The United States Coast Guard (USCG) operates a variety of boats as support craft and deployed from cutters in coastal and offshore operations. The boats often deploy in coastal and offshore heavy weather wave environments to respond to mission requirements including Search and Rescue (SAR). The assessment of a boat’s ability to meet mission requirements has been based on static stability criteria that do not reflect a specific operational environment nor the required seakeeping and control capabilities. Other assessments are based on empirical analysis of accelerations at high speeds in lower seaway conditions. The

USCG conducted an evaluation and validation effort to assess the seakeeping and control abilities of USCG cutter boats using various seakeeping approaches and criteria developed for boat and ship applications.

The effort included comparisons of model tests and full-scale trials of a seven-meter Rigid Hull Inflatable Boat (RHIB) in wave environments, generally at sub-planing speeds typical of heavy weather operations. The full-scale trials were conducted by

USCG Surface Forces Logistics Center and US Navy (USN)

Naval Surface Warfare Center, Carderock Division (NSWCCD), Combatant Craft Division (CCD) on both the East and West

Coasts of the US. The validation efforts included analytical comparisons with seakeeping programs including SMP, VERES, LAMP, PanShip, and POWERSEA with the model test and full-scale trials data. Response comparisons include motions, accelerations, slamming, freeboard exceedances, and maneuvering control parameters. Results of the comparisons provide a range of utility and applicability for each program for the design and analysis of operational capabilities for boats.

A risk-based approach is proposed for evaluating operational performance that is suitable for both design and in-service capability evaluations. The approach combines the probability of responses and events with the severity of the consequences to determine a value of risk. Limiting criteria are discussed and assigned to levels of risk. High-risk responses such as loss of control and capsize in a seaway are considered. Levels of risk are related to operational decision support within USN and USCG risk standards. This risk-based approach is useful in validating and developing simplified limiting criteria for quick in-service evaluations. It is also applicable to the requirements development process for future boat acquisition programs. Example operator guidance is proposed for cutter boat operations.

Conclusions and recommendations are provided for further development of the risk-based approach and performance criteria.

BACKGROUND

Initial Studies and Framework Debord et al. (2012) provided a framework methodology for assessing crew safety, risk of boat loss, and potential for damage to machinery and structure. The study highlighted the importance of evaluating performance and safety for boats operating in elevated sea states at low speeds by identifying key risk factors and environmental conditions that cause a reduction in capability.

Detailed descriptions of the methodologies used for assessments of structural integrity, maneuverability, flooding, stability, and seakeeping analysis are included. The paper highlights limitations of current analytical tools and the need for more robust design criteria and analytical methodology to ensure boat safety and performance in survival conditions. Key recommendations include the need for empirical data and full-scale trials data to appropriately bound analytical tools for specific evaluation purposes.

In 2016, the USCG initiated a follow-up project to further develop and validate a process to establish safe operating guidance for USCG boats and develop associated technical standards. The following sections discuss the full-scale trials and model test data and its usefulness in efforts to validate existing seakeeping calculations methods, programs, and other tools available to naval architects.

Full-Scale Trials Full-scale trials data is critical for validation of both the model test results and the software-based calculations. Early in the project concept and development phase, it was identified that full-scale testing must be constrained by minimizing risk to personnel and boats while also ensuring the testing program remained within the limitations of the available software tools and analysis methods. Key independent variables were identified, measured, and documented prior to full-scale testing to ensure accuracy of the validation effort and mitigate undesired deviations from the test conditions. Such variables included:

• As-tested geometry of hull and appendages.

• Accurate weight, center of gravity (CG), and mass moments of inertia measurements of the boat load condition, including crew and equipment.

• Running trim angle over a range of speeds in calm water.

• Directional sea spectra including energy versus frequency and energy versus direction, with time series data to supplement portions of each test.

• Speed and direction for current and wind.

• Video recordings of each boat to identify events and data anomalies.

Two sets of full-scale trials were completed, one on the East

Coast of the US and one on the West Coast over a range of four running speeds (6, 12, 15, and 25 knots) and five relative wave headings (head, bow quartering, beam, stern quartering, and following seas). The goal of the trials was to obtain performance data in a variety of calm water and heavy seas conditions. The lower speed runs were of particular interest as boats generally must limit speed as they approach their operational limit to maintain control. Both trials were performed in conditions ranging from Sea State 3 (SS3) through Sea State 5. The trials included accurate measurements of roll decay, mass properties measurements, and six degree-of-freedom motions and accelerations at the bow and longitudinal CG in the trials

PBS 2024, 14 October, Norfolk, VA 3 conditions. An air incline was performed prior to the trials and freeboard measurements were recorded prior to each trial run.

Wave Environment

For the East Coast trials, the full-scale measured directional wave data was obtained from a National Oceanic and Atmospheric

Administration (NOAA) National Data Buoy Center (NDBC) station. All testing was completed near the wave buoy to ensure the measured response data accurately correlated with known sea conditions. In Sea State 3, the measured significant wave height

(Hs) ranged between 3.6 to 4.0 ft (1.1 to 1.2 m) with a wave period

(Tp) between 10.0 and 11.0 seconds. This seaway had wave energy peaks centered around two wave periods coming from two different directions. In Sea State 4, the measured significant wave height ranged between 5.3 to 6.0 ft (1.6 to 1.8 m) with a wave period between 7.0 and 9.0 seconds. This seaway had the majority of the wave energy centered around a single wave period from essentially the same direction. The recorded wave statistics from the East Coast trials are provided in Table 1 and Table 2 representative sea spectra and wave directions are shown in Fig.

1 and Fig. 2.

Table 1. East Coast Trials Wave Statistics, SS3

Time Hs Hs Tp Hdg

(UTC) (ft) (m) (s) (deg T)

1328 4.0 1.2 11 078

1358 3.9 1.2 11 082

1428 4.0 1.2 11 090

1458 3.9 1.2 11 083

1528 3.6 1.1 11 086

1558 3.6 1.1 11 093

1628 3.6 1.1 11 085

1658 3.8 1.2 11 103

1728 3.7 1.1 10 093

1758 3.6 1.1 11 113

1828 3.7 1.1 11 103

Max 4.0 1.2 11 113

Min 3.6 1.1 10 078

Average 3.8 1.2 11 092

Table 2. East Coast Trials Wave Statistics, SS4

(UTC) (ft) (m) (s) (deg T)

1358 5.8 1.8 8 089

1428 5.6 1.7 7 086

1458 5.6 1.7 9 085

1528 5.5 1.7 8 090

1558 5.7 1.7 8 092

1628 5.3 1.6 9 090

1658 5.8 1.8 7 085

1728 5.5 1.7 8 092

1758 5.9 1.8 8 093

1828 5.8 1.8 8 093

1858 6.0 1.8 8 090

Max 6.0 1.8 9 093

Min 5.3 1.6 7 085

Average 5.7 1.7 8 090

Fig. 1. East Coast Trials SS3 Wave Spectrum and Direction

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Fig. 2. East Coast Trials SS4 Wave Spectrum and Direction

For the West Coast trials, a free-drifting wave buoy was deployed to measure the wave environment. All testing was completed near the wave buoy to ensure the measured response data accurately correlated with known sea conditions. In Sea State

4, the measured significant wave height ranged between 4.9 to 5.2 ft (1.5-1.6 m) with a wave period between 8.3 and 11.8 seconds.

This seaway had the majority of the wave energy centered around a single wave period with variable direction. In Sea State 5, the measured significant wave height ranged between 8.9 to 9.0 ft

(2.7 m) with a wave period between 9.0 and 10.0 seconds. This seaway had the majority of the wave energy centered around a single wave period from essentially the same direction. The recorded wave statistics from the West Coast trials are provided in Table 3 and Table 4 and representative sea spectra are shown in Fig. 3 and Fig. 4.

Table 3. West Coast Trials Waves Statistics, SS4

(PDT) (ft) (m) (s) (deg T)

0950 5.15 1.57 8.33 293

1050 5.03 1.53 10.00 290

1150 4.92 1.50 11.76 276

Table 4. West Coast Trials Waves Statistics, SS5

(PDT) (ft) (m) (s) (deg T)

1525 8.93 2.72 9.09 302

1554 9.01 2.75 10.00 314

Fig. 3. West Coast SS4 Wave Spectrum and Direction

Fig. 4. West Coast SS5 Wave Spectrum and Direction

Model Tests Model testing was completed shortly after the conclusion of the full-scale trials. The identification and documentation of independent variables for model testing was similar to the procedure from the full-scale trials. The model tests allowed for data collection in conditions that may not be safe for full-scale testing and special cases to facilitate stepwise validation of the software tools. All model tests were performed with a free-sailing, self-propelled model of the RHIB at 1:6.67 scale.

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The model test program included tests in regular (sinusoidal) and irregular waves with realistic variations of wave heights and periods. Irregular wave tests were conducted in unidirectional seas. Additional runs were completed with a wider range of sea conditions and speeds than the full-scale trials. This included steep waves to model survival conditions. The intent of these conditions was to cause non-linear behavior and potentially induce capsize, broaching, and/or cockpit flooding to help identify critical waves. These types of responses were desired to help assess the ability of the calculation methodologies and seakeeping programs to predict these extreme events. Specific sea conditions measured during full-scale trials were reproduced in the model basin to provide a direct comparison of the boat responses. A summary of the tested irregular wave conditions is provided in Table 5. A summary of the regular wave conditions tested is provided in Table 6. Head seas is a relative wave heading of 180 degrees.

It was observed that the boat began wave jumping in irregular wave Sea State 4 conditions at high speed in head and bow quartering seas. This behavior occurred more frequently in Sea

State 5, which resulted in more extreme acceleration peaks, even at lower speeds. Several capsizes were observed when breaking waves overtook the boat, causing it to broach towards the beam in lower speed conditions of 6 knots. These observations were used to help identify critical waves and incident wave properties that lead to undesirable events such as broaching, capsize, and surf riding in survival conditions.

The critical wave approach is one of the more practical approaches for estimating probability of occurrence for rare and infrequent events, such as capsize. It involves predicting the vessel response and determining the local wave conditions, typically using time domain simulations or model tests. The characteristics of the local waves are then used to infer their probability of occurrence from Joint Probability Density

Functions (JPDF).

Modeling the Full-Scale Trials Wave Spectrum

During the full-scale trials, sea spectrum data was collected to help understand boat responses in a defined seaway. The measured characteristics of the waves, including frequency and direction, were incorporated into the model test plan. These parameters were used to correlate the model test responses with those observed during full-scale trials conducted in an equivalent model-scale seaway.

The model basin Sea State 4 “manual” irregular wave spectrum was calibrated to the measured East Coast SS4 full-scale trials spectrum. This was done by recording the wave height for 30 minutes in the center of the basin. The basin wave maker settings were adjusted until the model basin spectrum resembled the full-scale spectrum for each heading. The spectrum details are shown in Fig. 5.

Fig. 5. Model Test Wave Spectrum for SS4 Full-Scale Trials

Condition

Table 5. Model Test Irregular Wave Conditions

Spectra Type Hs Hs Tp Wave Heading Speeds Comments

(ft) (m) (s) (deg) (knots)

Bretschneider 5.6 1.7 6.9 180, 135, 090, 315, 000 6, 12, 25 Mid SS4

Manual (Bretschneider) 5.5 1.68 7.69 135, 315 6, 12 Measured East Coast Trials SS4

JONSWAP 8.2 2.5 5.2 180, 090, 000 6, 12 Mid SS5, very steep

JONSWAP 9.8 3.0 5.2 135, 315 6, 12 Mid SS5, very steep

Table 6. Model Test Regular Wave Conditions

Load

Condition

Wave

Slope

Wave

Heights

Wave Headings Speeds

(deg) (knots)

Full 1:15 8.0-25.4 ft

(2.44-7.75 m)

180, 135, 090, 315, 330, 345, 000

6, 12, 25

Performance 1:15 8.0-25.4 ft

(2.44-7.75 m)

180, 135, 090, 315, 330, 345, 000

6, 12

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Model Test Wave Train Reconstruction

During the model tests, the wave height was measured by three sonic wave probes attached to the carriage following the model.

One probe was mounted in front of the model, one aft of the model, and one next to the model. The distances between the model and wave probes were most times sufficient to avoid interference from ship radiated waves. The wave spectral densities for each wave spectrum were determined by means of spectral analysis of the wave train signals measured while travelling at very low speed through the basin (without the model present). This yielded an “average” wave spectrum valid anywhere in the basin.

Next, the phase angles were determined for each test run with the model by means of a non-linear minimization procedure. In this procedure, the difference between the measured and reconstructed wave trains was minimized at each time step by varying the phase angles. It is necessary to match the phase angles to ensure that the modeled wave spectrum accurately reflects the measured input frequencies. The object function was minimized using the measurements at the three wave probe positions simultaneously to produce the phase angles. It was assumed that these phase angles were valid for arbitrary positions near the model. Sample plots from the bow quartering wave tests are shown in Fig. 6, Fig. 7, and Fig. 8 below. They provide a comparison between the measured (WavexM) and the reconstructed (WavexP) wave elevation for the three wave probes used during testing.

Fig. 6. Measured Reconstructed Waves Comparison, Probe 1

Fig. 7. Measured Reconstructed Waves Comparison, Probe 2

Fig. 8. Measured Reconstructed Waves Comparison, Probe 3

Critical Wave Approach A key component to the overall determination of risk-based boat operating limits and the associated validation efforts was the critical wave approach. For the purposes of this effort, a critical wave is defined as a wave that causes surf riding, broaching, going airborne, capsize, or other events of interest. Details on the practical application of the critical wave approach are presented by DeKat et. al., (1994), Sheinberg et. al., (2006), and Leadbetter, Rychlik, and Stambaugh (2011). The basic methodology of the critical wave approach can be summarized as follows:

1. Identify the characteristics of critical waves through evaluation of the spatial wave profiles present during a series of simulated capsize events from model tests and analysis tools.

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2. Define a deterministic region of discrete wave characteristics, such as wave height and period, that constitute critical waves.

3. Integrate a JPDF of wave height and wave period for a widely accepted wave spectrum, utilizing the region defined above as limits, to determine the probability that these critical waves occur in a given seaway. The JPDF for wave height and frequency is given by Longuet-Higgins (1983) and Sobey (1992).

The critical waves identified during the model tests were used in further validation efforts of seakeeping programs. The critical wave approach decreases computation and analysis time by reducing the number of simulations required to arrive at a statistically significant representation of an event-based probability. The identification and characterization of the critical wave maximizes the probability that events will occur during the simulation using predetermined adverse conditions. Data from capsizes in both regular and irregular waves was compared to determine if any correlation existed that would allow conclusions to be drawn from the simpler regular wave case.

Low Sea State Significant Wave Heights and

Wave Periods The sea state definitions for ship application are generally developed for significant wave heights greater than 3.28 ft (1 m)

(Campana, 2021). This lower limit is satisfactory for higher seaway conditions where operational risk is highest. However, it is desirable to perform some level of verification for boats and inshore craft that may have lower seaway limitations. The combinations of significant wave height and wave period for seaways lower than 3.28 ft (1.0 m) significant are developed from measured spectra including NDBC and the full-scale trials performed by NSWCCD CCD. The resulting combinations of significant wave height and wave period used for lower seaway conditions are presented in Table 7 along with extrapolations from other data sources. These parameters are typically used in seaway modeling, including the Bretschneider (1959) formulation.

Table 7. Hs and Tp for Low Sea State Evaluations

Sea State Hs Hs Tp

(ft) (m) (s)

SS 2 (Top) 1.6 0.5 3.5

SS 3 (Mid) 3.0 0.9 4.75

SS 3 (Top) 4.1 1.3 5.5

SS 4 (Mid) 6.0 1.8 6.5

VALIDATION

Overview and Scope The data collected during the full-scale trials and model tests was the baseline for the validation efforts of several industry-standard seakeeping programs for ships and/or boats. This process is referred to as validation, rather than verification and validation, because verification, which is the process to confirm that calculations are completed as intended, was assumed to have been completed by the developer. Validation, which is the process to confirm that the models predict actual behavior with sufficient accuracy, was necessary for this project. The overall goal of the validation process was to define ranges of speeds, headings, sea conditions, and types of responses where the calculation methods and related computer programs do or do not produce acceptable results to identify useful tools and approaches for assessing boat performance in heavy weather sea conditions. This was done by comparing the predictions from each program to the full-scale trials and model test data. Accuracy of the appended hullform model, weight distribution, roll decay properties, simulated wave environment, meshing, running trim, and performance characteristics is critical for effective validation of analytical tools. In the words of George E. P. Box, “All models are wrong, but some are useful.”

Evaluation Approach The validation for all candidate calculation methods and related computer programs followed the below sequence:

1. Validate model test results against full-scale trials results.

2. Validate predictions of individual responses (pitch, roll, heave, accelerations, relative motions) from the calculation methods against model test regular wave results.

3. Validate statistical response predictions from the calculation methods against statistical measurements from the model tests and full-scale trials.

4. Validate the capabilities of the calculation methods to predict extreme responses that occur in relatively short time periods such as broaching and capsize.

Model Test Validation to Full-Scale Trials Several comparisons were made between the model test and full-scale data to determine if model test predictions adequately represent full-scale behavior to the extent necessary to meet the objectives of this effort. The model test and full-scale trials sea conditions were not able to be perfectly matched, speed and relative heading varied from test to test, and the behavior of coxswains was represented in the model using an automatic heading control system. In spite of these differences, comparisons of statistical results provide no evidence that the model test results systematically differed from the full-scale trials results. Similar trends are evident in the data sets, and, in general, the ranges of variations in the model results are similar to those in the full-scale trials results. Representative plots showing a comparison of the non-dimensional statistical responses between the model tests and full-scale trials are shown in Fig. 9 and Fig. 10.

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Fig. 9. Non-Dimensional Roll Comparison, Bow Quartering Seas

Fig. 10. Non-Dimensional Pitch Comparison, Bow Quartering

Seas

Three capsizes and numerous broaches occurred during the model test program, in very steep irregular waves (10 ft (3.0 m) significant wave height, 5.2 second wave period) primarily during stern quartering seas. The capsizes occurred when the model was swamped in the presence of a steep 16-foot critical wave.

Although the seaway tested included waves that were much steeper than is typically found in existing operating environments, the model test data provided valuable cases of nonlinear events for the validation of numerical predictions in extreme seaways.

During both sets of full-scale trials, capsize and broaching events were not observed even though significant wave heights up to 9 ft (2.7 m) were tested. These differences are due to the fact that the boats in the full-scale trials were in less steep waves, did not have significant water in the cockpit, and were driven by experienced coxswains rather than an autopilot. Therefore, the fact that the model experienced capsizes and broaches should not be interpreted to mean that the tested condition is beyond the safe operating limit of the boat. Further investigation was required to determine the safe operating limit.

Seakeeping Program Validation Five industry-standard ship and/or boat seakeeping programs were selected for this validation effort: SMP, VERES, LAMP, POWERSEA, and PanShip. The objectives were to determine if each program was useful when evaluating boat operating limits and, if so, determine the ranges of speeds, sea conditions and relative wave headings for valid results. The predictions from each program were compared to the measured statistical responses from the full-scale trials and model tests. The most accurate representation of the boat geometry, boat load condition, and wave environment allowed in each program was used. The hydrostatic properties of the boat model calculated by each program were checked to ensure that they compared favorably to the nominal values for the boat hydrostatics as measured during the testing events. The statistical responses presented in this section are significant single amplitude (SSA), defined as the average of the highest one-third motions, unless otherwise noted.

Head seas is a relative wave heading of 180 degrees.

SMP

SMP (Ship Motions Program) is a linear frequency domain seakeeping code based on strip theory developed by NSWCCD.

Its primary use is to evaluate the seakeeping performance of displacement monohull surface ships operating at constant speeds and headings. Prior to this study, its application to planing craft had not been evaluated by the USCG. Each SMP simulation was run at the average measured speed of the boat during its associated test. The twenty-five knot tests were not simulated due to the speed falling well outside of the applicability range of SMP.

It is not possible to predict short-term extreme events using SMP.

SMP does not allow for the input of a custom sea spectrum, so a theoretical Ochi-Hubble spectrum was fitted to each measured spectrum. The Ochi-Hubble spectrum is a six-parameter spectrum with two separate three parameter component spectra. Having two component spectra allowed for the representation of both swell and wind driven sea components

(Ochi and Hubble, 1976). The parameters of the fitted Ochi-

Hubble spectra used with SMP are provided in Table 8.

Table 8. Fitted Ochi-Hubble Spectra Parameters

Location SS Speeds Hs,1 Hs,1 Tp,1 λ1 Hs,2 Hs,2 Tp,2 λ2

(knots) (ft) (m) (s) (ft) (m) (s)

East Coast 3 6 2.50 0.76 10.50 1.50 2.65 0.81 4.12 3.00

3 12 2.25 0.69 10.60 1.70 2.54 0.77 4.25 1.70

4 6, 12 4.95 1.51 8.05 1.00 2.00 0.61 4.40 1.00

West Coast 4 6, 15 2.60 0.79 15.50 1.00 3.90 1.19 10.70 1.00

5 6 6.35 1.94 12.78 1.02 5.75 1.75 9.60 1.15

0.00

0.50

1.00

1.50

2.00

2.50

3.00

3.50

4.00

4.50

5.00

0.00 0.50 1.00 1.50 2.00 2.50

R o ll

SS

A

W av e S lo p e

Wave Encounter Frequency (rad/sec)

Roll Quasi RAO Bow Qtr. Seas

Model Test 6 knots

Model Test 12 knots

East FS Test 6 knots

East FS Test 12 knots

West FS Trial 6 knots

West FS Trial 15 knots

0.00

0.50

1.00

1.50

2.00

2.50

3.00

0.00 0.50 1.00 1.50 2.00 2.50

P it ch S

SA

W av e S lo p e

Wave Encounter Frequency (rad/sec)

Pitch Quasi RAO Bow Qtr. Seas

Model Test 6 knots

Model Test 12 knots

East FS Test 6 knots

East FS Test 12 knots

West FS Trial 6 knots

West FS Trial 15 knots

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Representative plots comparing the fitted spectra to the observed spectra are provided in Fig. 11, Fig. 12, and Fig. 13. All full-scale simulations were run with shortcrested waves to model the multi-directional behavior of the observed seas.

Fig. 11. East Coast SS3 Fitted Ochi-Hubble Spectrum

Fig. 12. East Coast SS4 Fitted Ochi-Hubble Spectrum

Fig. 13. West Coast SS5 Fitted Ochi-Hubble Spectrum

Representative comparisons of the statistical responses for roll and pitch between the SMP predictions and full-scale trials results are provided in Fig. 14 and Fig. 15. Comparisons between the SMP predictions and model test results are presented in Fig.

16 and Fig. 17.

Fig. 14. Full-Scale Trials vs. SMP Results, East Coast SS4 Roll

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Fig. 15. Full-Scale Trials vs. SMP Results, East Coast SS4 Pitch

Fig. 16. Model Test vs. SMP Results, SS4 Roll

Fig. 17. Model Test vs. SMP Results, SS4 Pitch

Overall, the ability of SMP simulations to accurately predict the motion and acceleration responses from the tests was questionable, with some responses comparing well and some not coming close to the responses measured during the full-scale trials. Its predictions for heave and pitch were close for the full-scale trials, but mostly larger than what those measured during the model tests. Its roll response predictions tended to be much larger than the test data, especially in bow quartering and beam seas, and show less agreement with the higher speed test results.

In general, its surge acceleration predictions were not good, though there was a significant difference in the magnitude of the test results relative to the predictions. Its sway and heave acceleration predictions were largely close, though some noticeable differences at specific headings were present. Also, SMP was more inaccurate when predicting responses for the higher speed tests on average.

Due to its many limitations and tendency to predict larger magnitude motion responses, the recommendation for SMP was to only use it for speeds where the boat does not exhibit planing behavior as a conservative estimator of the boat’s motions. The limited amount of time required to run SMP simulations makes it a useful tool to compare boat motions between various headings in multiple seaways, but its limited accuracy does not support its use in determining specific motion limits.

VERES

VERES is a linear frequency domain seakeeping program based on strip theory developed by Marintek of Norway. VERES has a

2-1/2-dimension approach for predicting the motions and accelerations at semi-displacement speeds. The primary use of

VERES is to predict ship motions and accelerations for displacement and semi-displacement monohull surface ships operating at constant speeds and headings. The ability of VERES to predict relative motion is also useful for estimating freeboard exceedances and slamming loads in a seaway. Prior to this study, the application of VERES to planing craft operating in displacement and semi-displacement speeds had not been fully evaluated by the USCG. Each VERES simulation was run at the average measured speed of the boat during its associated test. The twenty-five knot tests were not simulated due to the speed falling well outside of the known applicability range of VERES. It is not possible to predict short-term extreme events using VERES. The

VERES model included small bilge keels added at the location of the spray chines to model the hydrodynamic roll damping of the hard chine flat.

VERES allows for the input of custom sea spectra wave energy distribution and direction. All full-scale simulations were run with the wave conditions measured during the trials.

Example results are presented here for vertical accelerations in directional seaways and roll and relative motion in a model test seaway simulating full-scale conditions. Vertical accelerations at the CG are shown in Fig. 18. VERES heave acceleration predictions compare well with the tests at both speeds, though it does predict slightly larger magnitude accelerations for the 12-knot tests in head, bow quartering, and beam seas.

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Fig. 18. Full-Scale Trials vs. VERES Results, East Coast SS3, CG Heave Acceleration, 12 knots

A plot comparing the performance load JONSWAP spectrum

(SS5) model test roll statistics to the VERES-calculated statistics is provided in Fig. 19 showing good agreement. VERES predictions were close to those measured during the model tests for all of the 6-knot tests and most of the 12-knot test headings.

However, VERES predictions were slightly higher in stern quartering seas.

Fig. 19. Model Test vs. VERES Results, Steep SS5, Roll

A representative relative wave height prediction comparison is shown in Fig. 20. The locations for relative wave height measurements are aft, bow quarter and bow labeled G1, G2, and

G3, respectively. The VERES predictions are relative SSA and the model test results are maximum for 30-minute tests. The trends in relative wave height predictions were roughly similar.

Fig. 20. Model Test vs. VERES Results, SS5 Relative Wave

Height at the Bow

VERES is a useful tool for predicting ship motion statistics in a given theoretically modeled seaway. Roll motions predicted by VERES are slightly over damped, likely due to the addition of a bilge keel to model the damping effects of the spray chine. The size of the small added bilge keel could be adjusted slightly to reduce roll damping and likely improve the roll motion predictions, even though they were very good for these initial validation predictions. VERES did not predict surge and sway accelerations very well for the boat hullform. VERES was able to predict motions, vertical accelerations, and relative wave height trends for sub-planing speeds for specific evaluation parameters used in operator guidance in terms of limiting combinations of wave height, heading and forward speed.

LAMP

LAMP (Large Amplitude Motions Program) is a numerical, time domain ship motions predictions program based on 3-D potential flow developed by the USN and Science Applications

International Corporation (SAIC). LAMP can calculate and predict the following:

• Linear and nonlinear motions of ships in waves

• Linear and nonlinear hydrodynamic forces

• Linear and nonlinear wave excitation forces

• Time-domain pressure distribution over the hull surface

• Hydrodynamic response to forced or impulsive motion

• Response to impulsive motion or incident waves

LAMP simulations were run for each combination of speed, heading, sea state, and loading condition evaluated during the full-scale trials and model tests. However, it was quickly determined that the 25-knot LAMP simulations were unreliable, so they were not included in the validation effort. Each LAMP simulation was run at the average measured speed of the boat during its associated test. It is possible to simulate and predict short-term extreme events using LAMP by reviewing the simulation results in the LAMP visualization tool.

LAMP allows for the input of a custom sea spectrum. All full-scale simulations were run with the wave energy spectra measured during the trials with shortcrested waves to model the

PBS 2024, 14 October, Norfolk, VA 12 multi-directional behavior of the observed seas.

Sample comparison plots of the full load regular waves model test Response Amplitude Operators (RAOs) to the LAMP-calculated RAOs are shown in Fig. 21 and Fig. 22. All model tests were free running, resulting in varying speeds from test to test.

Rather than speed, the results shown were converted to wave encounter period to ensure more consistent results. LAMP tends to predict larger resonant motions in regular waves.

Fig. 21. Model Test vs. LAMP Results, Roll RAO, Bow

Quartering Seas

Fig. 22. Model Test vs. LAMP Results, Pitch RAO, Head Seas

Representative comparisons of the statistical responses for roll and pitch between the LAMP predictions and the full-scale trials results are provided in Fig. 23 and Fig. 24. Comparisons between the LAMP predictions and the irregular waves model test results are presented in Fig. 25 and Fig. 26. In general, the responses predicted by LAMP were larger than those measured during the tests. Heave and pitch predictions were reasonably close, though the predicted roll response for the full-scale trials conditions were significantly higher. The most noteworthy differences were in bow and stern quartering seas. Results from the low-speed tests showed better agreement than the results from the higher speed tests.

Fig. 23. Full-Scale Trials vs. LAMP Results, East Coast SS4 Roll

Fig. 24. Full-Scale Trials vs. LAMP Results, East Coast SS4 Pitch

Fig. 25. Model Test vs. LAMP Results, SS4 Roll

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PBS 2024, 14 October, Norfolk, VA 13

Fig. 26. Model Test vs. LAMP Results, SS4 Pitch

Several surf riding events and one capsize occurred during the model tests in stern quartering seas with significant wave heights of 8 to 9 ft (2.4 to 2.7 m) at speeds of 6 and 12 knots.

LAMP was able to predict these capsize events. However, LAMP predicted a number of other capsize events that did not occur during the model tests.

LAMP features an autopilot simulation to supplement the input file and provide course correction during test runs. This feature was closely monitored and frequently adjusted to ensure the simulation was realistic for each test run through LAMP’s visual representation tool. The model test autopilot represented a more realistic coxswain than the LAMP autopilot. The LAMP autopilot does not use experience-based intelligence for steering and thrust control and was very sensitive to the input parameters.

During certain heading and speed combinations, extreme motions were observed that resulted in the transom lifting out of the water, which created an unrealistic constant thrust when the thruster was above the water surface. This phenomenon occasionally caused the LAMP model to find resonance with the sea state or otherwise behave erratically. On several occasions the

LAMP model capsized rapidly or unexpectedly. Capsizing and broaching predictions appear to be heavily influenced by steering and thrust control. There are ways to minimize the course correction and better control the thrust and thus minimize irregular boat responses. These were not utilized during the validation runs because they entail limiting certain degrees of freedom and analyzing each motion individually, which results in a loss of real-world simulation.

The model test videos and the visual output from the LAMP simulations were compared to note differences in performance.

The LAMP simulations showed large differences in directional stability and steering control, particularly at higher speeds. The

LAMP visualization tool predicted capsize at least once for all headings at speeds above 12 knots. Capsize events were particularly evident in both bow and stern quartering seas.

LAMP is a useful tool to quickly obtain estimates of ship motion statistics in a seaway. Most of its predictions follow the same trends as the test data (i.e., roll response is greatest at relative headings of bow quartering and beam seas, roll response is smallest in following or head seas). Occasionally, one data point from the LAMP simulation (usually bow or stern quartering seas) skewed the curves in the comparison plots, but, overall, the trends are reasonable. In addition, LAMP predictions at higher speeds are far less accurate than at lower speeds. LAMP documentation does indicate that the program could be used for semi-displacement test configurations. However, it is believed that there is a limitation on the Froude number to achieve accurate results from the program.

Due to its many limitations and tendency to predict larger magnitude motion responses, the recommendation for LAMP was to only use it for speeds where the boat does not exhibit planing behavior as a conservative estimator of the boat’s motions. Based on the results, the Froude number should be limited to 0.4, which corresponds to a speed of 6 knots for the RHIB utilized in this study. Further investigation of adjustments to the autopilot settings and variation of the sea and boat model panel meshes were completed after the validation effort, which resulted in improved accuracy of the simulations.

POWERSEA

POWERSEA is a time-domain seakeeping program based on a low-aspect ratio of strip theory that predicts the vertical-plane motions of planing craft developed by Ship Motion Associates.

Its primary use is to predict the heave and pitch response of planing craft in head and following seas. POWERSEA uses a simplified hullform model that only requires the definition of the keel line, a single chine line, and the nominal boat characteristics.

Each POWERSEA simulation was run at the average measured speed of the boat during its associated test. The six knot tests were not simulated due to the speed falling well outside of the applicability range of POWERSEA. POWERSEA is only capable of simulating motions in head and following seas.

The components of the measured wave spectra were input into POWERSEA without directionality. All simulations of tests in irregular waves were done using longcrested waves.

POWERSEA is not capable of calculating the frequency of certain extreme events (i.e., capsize or broaching), though it is possible to review the time histories to determine if deck wetness events occurred at any point along the centerline of the boat. A preliminary review of this capability revealed that POWERSEA predicted significantly more deck wetness events than what was recorded during the model tests, so this capability requires further investigation.

Representative comparisons of statistical responses predicted by the POWERSEA simulations to those measured during the model tests in irregular waves are shown in Fig. 27 and Fig. 28.

In general, its predictions for these tests were questionable. Its pitch predictions tended to be larger than the tests, especially in higher sea states and head seas, though the predictions did show the same general trends as the test data. POWERSEA vertical acceleration predictions were generally close to the tests in Sea

State 4, but significantly too large in Sea State 5, especially in

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PBS 2024, 14 October, Norfolk, VA 14 head seas and at the bow. However, the predictions did show the same general trends as the test data.

Fig. 27. Model Test vs. POWERSEA Results, Irregular Waves

Pitch

Fig. 28. Model Test vs. POWERSEA Results, Irregular Waves

Bow Vertical Acceleration by the POWERSEA simulations to those measured during the full-scale trials are shown in Fig. 29 and Fig. 30. Due to the limited number of data points, it was difficult to determine the ability of POWERSEA simulations to accurately predict the motion and acceleration responses from the full-scale trials. Its prediction of pitch response was close to the tests, though the predictions tended to be large for all investigated speeds and headings. POWERSEA also tends to predict that the boat will pitch more in following seas than head seas, while the tests show the opposite will occur. At times, POWERSEA heave acceleration predictions were close and the data trends were largely similar, though the predictions were generally worse at higher speeds in head seas.

Fig. 29. Full-Scale Trials vs. POWERSEA Results, East Coast

SS4 Pitch

Fig. 30. Full-Scale Trials vs. POWERSEA Results, East Coast

SS4 Bow Heave Acceleration

Overall, the ability of POWERSEA simulations to predict the motion and acceleration responses from the tests was questionable. Some of its predictions compared well to the test data, specifically the head seas tests in regular waves. However, others did not, especially those run in steep waves. This was a known limitation because the program outputs a warning when the specified wave spectrum exceeds a certain wave slope. In addition, POWERSEA predictions did not always follow the same overall trends as the test data. POWERSEA vertical acceleration predictions also tended to be larger than the tests, especially at the bow. In general, predictions for the regular wave tests compared more favorably than those for the tests in irregular waves. Simulations of tests in head seas were also found to be more accurate than simulations of following seas tests. Variation from the test data was expected at speeds of 12 to 15 knots where the boat was not fully in the planing regime due to the advertised applicability range of POWERSEA.

Due to its performance relative to the test data, the recommendation for POWERSEA was to use it to estimate the motions of planning boats throughout the planing regime in

PBS 2024, 14 October, Norfolk, VA 15 unidirectional seaways that do not have steep waves. Given that each POWERSEA simulation was run for the minimum number of wave encounters, it is possible that its motion statistics would be more reliable from longer simulations. In addition, vertical acceleration predictions should be considered conservative and may suggest a more limited operating envelope than what is practical.

PanShip

PanShip is a time domain panel method seakeeping code developed and maintained by Maritime Research Institute

Netherlands (MARIN). Both the linear and semi-nonlinear

(PanShip(NL)) versions of the simulation tool were evaluated.

PanShip assumes that the motions of the craft are small and, therefore, that the submerged geometry does not change in time.

PanShip(NL) employs the semi-nonlinear body-exact approach.

In PanShip(NL), the motions may be large while the speed and heading are not necessarily constant, as the discretization of the submerged geometry and the computation of the Green function convolution integrals are performed at each time step. More detailed information about the theory and characteristics of

PanShip can be found in de Jong (2011) and Van Walree and

Turner (2013), while the applicability of PanShip for high-speed craft applications is discussed in Van Walree and de Jong (2015).

The comparison includes motion and acceleration responses in regular and irregular waves as well as a comparison of time traces in regular and irregular waves. PanShip utilized the reconstructed model test wave trains to place the PanShip model in similar waves as the model test. The rotations per minute

(RPM) of the PanShip water jet was set to best match the mean speed from each model test, though exact matches were difficult to achieve in the extreme wave conditions.

by the PanShip simulations to those measured during the model tests in regular waves are shown in Fig. 31 and Fig. 32, while representative time history comparisons are provided in Fig. 33 and Fig. 34. The predicted responses for motions, accelerations, and forward speed variations are generally close to the experimental values for both PanShip and PanShip(NL) simulations, with the exception of yaw. The time series acceleration signals show good agreement and the peaks are reasonably well predicted.

Fig. 31. Model Test vs. PanShip Results, Regular Waves with

15.4 ft (4.68 m) Wave Height and 0.94 rad/s Frequency (Full-

Scale), 12 knots, Roll RAO

Fig. 32. Model Test vs. PanShip Results, Regular Waves with

15.4 ft (4.68 m) Wave Height and 0.94 rad/s Frequency (Full-

Scale), 12 knots, Pitch RAO

Fig. 33. Model Test vs. PanShip Time History, Regular Waves with 25.4 ft (7.75 m) Wave Height and 0.73 rad/s Frequency

(Full-Scale), 12 knots, Head Seas, Pitch

PBS 2024, 14 October, Norfolk, VA 16

Fig. 34. Model Test vs. PanShip Time History, Regular Waves with 25.4 ft (7.75 m) Wave Height and 0.73 rad/s Frequency

(Full-Scale), 12 knots, Head Seas, Bow Vertical Acceleration by the PanShip simulations to those measured during the model tests in irregular waves are shown in Fig. 35 and Fig. 36. The predicted responses for motions, accelerations, and forward speed variations are close to the experimental values for both PanShip and PanShip(NL) simulations, with the exception of yaw. Stern quartering seas were not simulated because wave reconstruction was not possible for these tests due to the large surge and sway motions of the model. Sample time series comparisons are provided in Fig. 37 and Fig. 38. There are larger differences between the PanShip predictions and model test time traces than the regular waves, as the peaks predicted by PanShip are generally lower. This was likely due to the imperfect wave reconstruction and difficulties in predicting the yaw motion.

PanShip(NL) was more accurate than linear PanShip. Fig. 37 shows a test where the model was observed to have jumped fully out of the water. The PanShip(NL) simulation predicted similar behavior. The extreme pitch motion that resulted from this event can be seen at 36 seconds, which indicates that PanShip(NL) can capture short-term extreme events that occur during physical testing.

Fig. 35. Model Test vs. PanShip Results, Standard Deviation Roll

Fig. 36. Model Test vs. PanShip Results, Standard Deviation

Pitch

Fig. 37. Model Test vs. PanShip(NL) Time History, Steep SS5

Pitch in Head Seas

PBS 2024, 14 October, Norfolk, VA 17

Fig. 38. Model Test vs. PanShip(NL) Time History, Steep SS5

Roll in Bow Quartering Seas

Overall, the…