Schooner Brilliant Sail Coefficients and Speed Polars

2001 ◽  
Author(s):  
Howard Grant ◽  
Walter Stubner ◽  
Walter Alwang ◽  
Charles Henry ◽  
John Baird ◽  
...  
Keyword(s):  
Standard Deviation ◽  
Wind Pressure ◽  
Scale Model ◽  
Experimental Program ◽  
Side Force ◽  
Prediction Program ◽  
Wind Speeds ◽  
Velocity Prediction ◽  
Horizontal Side ◽  
Study Performance

The sail coefficients for a schooner rig, as a function of wind angle and heel angle, are presented, based on an experimental program, for historic vessel research, at Mystic Seaport, using the 61'6" schooner Brilliant. The coefficients were determined by full-scale sailing tests and 9- scale model tow-tank tests. Sail coefficients CR and Cttare defined as the drive force and horizontal side force , due to the sails, rigging, and hull above the waterline, per unit of sail area, per unit of wind pressure. These coefficients can be used to study performance of historic schooner­rigged vessels, predict performance of new designs, and compare performance of schooners and sloops. Sail coefficients for sloops have long been available. A velocity prediction program for the schooner was also developed. The predicted and actual ship speeds agree, with standard deviation of0.028 in the ratio. Upwind sail coefficients for the schooner are found to be lower than for historic sloops, and display the expected droop with heel. The schooner velocity made good upwind is largest with the sail plan of four lowers plus fisherman staysail. The schooner and sloop both point higher as wind increases. The sloop outpoints the schooner at all wind speeds, by about 10°. On a beam reach or broad reach, schooner speed is largest with the sail plan of big jib, golliwobbler, and mainsail. This sail plan also produces the largest downwind velocity made good. The polars suggest that the schooner has the advantage over the sloop on a beam reach.

Modeling IACC Sail Forces by Combining Measurements with CFD

1993 ◽  
Author(s):  
Jerome H. Milgram ◽  
Donald B. Peters ◽  
D. Noah Eckhouse
Keyword(s):  
Scale Model ◽  
Force Model ◽  
Actual Performance ◽  
Force Coefficients ◽  
Prediction Program ◽  
Induced Drag ◽  
Load Cells ◽  
Velocity Prediction ◽  
America’S Cup ◽  
Parasitic Components

A sailing dynamometer with a 42% scale model of an International America's Cup Class rig is used to measure sail forces and moments in actual sailing conditions. The sailing dynamometer is a 35-foot boat containing an internal frame connected to the hull by six load cells configured to measure all the forces and moments between the frame and the hull. All sailing rig components are attached to the frame, so that the sail forces are measured. Sail shapes in use are determined by computer-interfaced video. Computational fluid dynamics performed on the measured shapes provides the induced drag. This allows the measured drag to be decomposed into induced and form-and-parasitic components, which is necessary for generating a mathematical sail force model for a velocity prediction program (VPP). It is shown that VPP results using these new sail force coefficients are in better agreement with actual performance than are VPP results based on traditional sail force coefficients.

Approximation of the Calm Water Resistance on a Sailing Yacht Based on the 'Delft Systematic Yacht Hull Series'

1999 ◽  
Author(s):  
J. A. Kenning ◽  
U. B. Sonnenberg
Keyword(s):  
Water Resistance ◽  
Force Production ◽  
Data Set ◽  
Side Force ◽  
Prediction Program ◽  
Resistance Increase ◽  
The Past ◽  
Calm Water ◽  
Velocity Prediction ◽  
Sailing Yacht

Over the past years a considerable extension has been given to the Delft Systematic Yacht Hull Series (DSYHS) The DSYHS data set now contains information about both the bare hull and appended hull resistance in the upright and the heeled condition, the resistance increase due to the longitudinal trimming moment of the sails, the side force production and induced resistance due to side force at various combinations of forward speeds, leeway angles and heeling angles. New formulations for the relevant hydrodynamic forces as function of the hull geometry parameters have been derived to be able to deal with a larger variety of yacht hull shapes and appendage designs. During the past two years some results of this research have already been published. In the present paper an almost complete picture of the relevant expressions which may be used in a Velocity Prediction Program (VPP) will be presented.

Improvement of Sailing Yacht Performance Prediction by Including Force-Moment Equilibrium for the Calculation of Helm Angle in a Velocity Prediction Program

1995 ◽  
Author(s):  
Peter van Oossanen
Keyword(s):  
Mathematical Model ◽  
Performance Prediction ◽  
Model Tests ◽  
Side Force ◽  
Prediction Program ◽  
Moment Equilibrium ◽  
Force Moment ◽  
Velocity Prediction ◽  
Sailing Yacht ◽  
Rudder Angle

Contemporary Velocity Prediction Programs (VPP's) consider the equilibrium of forces acting on a sailing yacht in the thrust direction and in the direction of the developed side force on canoe body and appendages. In addition, force-moment equilibrium is considered in the transverse plane of the yacht. In this way a solution is found for the three main unknowns in performance prediction, viz: boat speed, leeway angle and heel angle. The impact of helm angle on performance is herein ignored. In the velocity prediction program developed by Van Oossanen & Associates, a fourth equilibrium condition is included, viz: force-moment equilibrium in the horizontal plane for the calculation of the helm angle required for the equilibrium sailing condition. In this paper a description is given of some of the main problems that need to be solved when introducing this fourth equilibrium requirement. One of these is associated with the development of accurate mathematical expressions for the calculation of rudder side force and resistance, as influenced by heel angle and the proximity of the free surface. Model tests can be utilized for obtaining insight into the physical phenomena involved in such cases. Model tests were carried out in the context of an optimization study for the design of a yacht according to the International Level Class 40 (ILC40) Rule, under the International Measurement System (IMS). The analysis of some of the results of these tests with respect to improving the mathematical model for rudder side force and resistance, is described in the paper. The effect of including this mathematical model in a VPP is demonstrated in the paper by providing the results of calculations which reveal that a variation in rudder angle causes significant speed differences. It is shown that the IMS VPP that is used to calculate the rating and speed potential of ILC40 and other IMS Class yachts, in not taking into account the significant variations in performance associated with different values of the equilibrium rudder angle (and the associated rudder side force and resistance), is not sufficiently accurate.

A Velocity Prediction Program for a Planning Dinghy

2005 ◽  
Author(s):  
Todd Carrico
Keyword(s):  
Hydrodynamic Resistance ◽  
Side Force ◽  
Prediction Program ◽  
Fundamental Goal ◽  
Velocity Prediction ◽  
Sailing Yacht ◽  
Series Of Experiments ◽  
College Of Engineering ◽  
The University ◽  
Visual Basic 6.0

This paper summarizes the author’s graduate thesis in Naval Architecture accepted by the University of New Orleans, College of Engineering. The author sought to investigate the complicated interactions between the hydrodynamics and aerodynamics of a sailboat. The type of sailboat investigated was the Olympic dinghy class called the Laser. It was the author’s understanding that at that time, no work has been completed in the area of velocity prediction for this type of sailboat. Thus, the fundamental goal of this thesis was to develop a velocity prediction program specific to the Laser. In order to accomplish the goal of creating a velocity prediction program, multiple essential pieces of the data were needed. In particular, the hydrodynamic resistance data, aerodynamic drive and side force data, and hydrodynamic side forces were needed. To determine the dynamic trim of the dinghy, a series of experiments were conducted. In addition, a data acquisition system was developed in which full scale tow testing could be done. Next, a complete tow test series was conducted for the Laser. The aerodynamic sail coefficients were derived from Marchaj’s Aero-Hydrodynamics of Sailing. To determine the hydrodynamic side force, a two dimensional approach was employed. The coding of the velocity prediction program was done using Microsoft’s Visual Basic 6.0 and Excel 2000. The algorithms published in the 15th Chesapeake Sailing Yacht Symposium and Principles of Yacht Design pertaining to velocity prediction were used as a baseline. Finally, validation and verification was performed with the shareware program PCSAIL.

Elements of Resistance of IACC Yachts

1993 ◽  
Author(s):  
Jerome H. Milgram ◽  
Fernando C. Frimm
Keyword(s):  
Numerical Computation ◽  
Frictional Resistance ◽  
Nonlinear Effects ◽  
Model Testing ◽  
Entire System ◽  
Sea Waves ◽  
Side Force ◽  
Prediction Program ◽  
Resistance Components ◽  
Velocity Prediction

Resistances due to hull friction, appendage friction, wavemaking, heel and side force, and sea waves are considered. Comparative values of each of these resis­tance components for four boats, including one with two different sets of appendages, are shown. Most of the resistance components are accurately determined by a combination of theory, numerical computation or model testing. An exception is the resistance due to sea waves for which nonlinear effects not accounted for in present theories appear to be significant. Some de­sign features which increase resistance have associated speed-increasing effects. An example is increasing the vessel beam which increases wetted surface, and there­fore the frictional resistance, but has an associated in­crease in potential sail power. This demonstrates the necessity of evaluating the entire system with a good velocity prediction program rather than using an eval­uation based on a few resistance components.

Mainsail Planform Optimization For IRC 52 Using Fluid Structure Interaction

2013 ◽  
Author(s):  
Robert Ranzenbach ◽  
Dave Armitage ◽  
Adolfo Carrau
Keyword(s):  
Fluid Structure Interaction ◽  
Element Analysis ◽  
Fluid Structure ◽  
Structure Interaction ◽  
Prediction Program ◽  
Wind Speeds ◽  
Wide Range ◽  
Velocity Prediction ◽  
Computational Fluid Dynamics Cfd ◽  
The Cost

Most IRC 52 based upon existing TP52 retain their original rig proportions and mainsail girths to avoid the cost and disruption of a rig change and to not disturb he finely tuned yaw balance. It is not obvious whether the mainsail proportions essentially dictated by the TP52 box rule (aggressively square topped mainsails) are actually optimal under IRC even though IRC 52 with TP52 style mainsails tend to successfully compete under IRC. To determine the answer to this question, a mainsail planform investigation was performed as collaboration between Botin Partners and Quantum Sail Design Group. The mainsail planform investigation utilized a Fluid Structure Interaction (FSI) program developed by Quantum Sail Design Group (QSDG) known as IQ Technology (IQT) that consists of sail geometry definition, inviscid Computational Fluid Dynamics (CFD), Finite Element Analysis (FEA), Velocity Prediction Program (VPP), and shape validation (based upon VSPARS) modules. Applicability of the inviscid CFD was validated by comparison to a limited number of viscous flow solutions, i.e. RANS analysis, performed by Porto Ricerca. Two mainsails were considered, a conventional TP52 style and an alternative that was chosen to be closer to the IRC default girth values. To maintain sail area and yaw balance, the alternative mainsail had a longer P and E. The focus of the study was exclusively on upwind performance, i.e. to maximize upwind Velocity Made Good (VMG). Results from the study suggest that a TP52 style mainsail is not optimal under IRC. The combination of rating reduction and predicted performance advantages over a wide range of wind speeds suggest that an alternative mainsail with larger P and E with girth values closer to the IRC default values is a superior choice for an IRC 52.

The Application of VPPs to Practical Sailing Problems

1987 ◽  
Author(s):  
Kart L. Kirkman
Keyword(s):  
Prediction Program ◽  
Widespread Acceptance ◽  
Velocity Prediction ◽  
Do So

The velocity prediction program, VPP, appeared on the yachting scene about ten years ago and it now dominates design and sailing. Originally implemented as a handicapping tool under the Measurement Handicap System, now accepted internationally as IMS, it has seen widespread acceptance for many other uses, from design to tuning and racing. This capability means that it is productive, even necessary, for the typical sailor interested in good performance to understand how to apply a VPP to his activities. To do so requires an appreciation of how a VPP functions and how it is applied to practical sailing problems, such as sail selection or tactics. The paper presents a review of VPP fundamentals and then treats the following applications: - Sail selection and strategy for offshore yachts. - Tuning and optimization of all boats. It is the goal of the paper to impart a working understand­ing of the VPP to many sailors so that they can take advantage of the technology in their normal activities.

Added Resistance in Seaways and its Impact on Yacht Performance

2007 ◽  
Author(s):  
Kai Graf ◽  
Marcus Pelz ◽  
Volker Bertram ◽  
H. Söding
Keyword(s):  
Strong Impact ◽  
Wave Spectra ◽  
Linear Extensions ◽  
Added Resistance ◽  
Optimum Length ◽  
Prediction Program ◽  
Strip Theory ◽  
Velocity Prediction ◽  
Added Resistance In Waves ◽  
Response Amplitude Operators

A method for the prediction of seakeeping behaviour of sailing yachts has been developed. It is based on linear strip theory with some non-linear extensions. The method is capable to take into account heeling and yawing yacht hulls, yacht appendages and sails. The yacht's response amplitude operators (RAO) and added resistance in waves can be predicted for harmonic waves as well as for natural wave spectra. The method is used to study added resistance in seaways for ACC-V5 yachts of varying beam. Results are used for further VPP investigations. The AVPP velocity prediction program is used to study optimum length to beam ratio of the yachts depending on wind velocity and upwind to downwind weighting. This investigation is carried out for flat water conditions as well as for two typical wave spectra. The results show that taking into account added resistance in seaways has a strong impact on predicted performance of the yacht.

scholarly journals Uncertainties in estimating regional methane emissions from rice paddies due to data scarcity in the modeling approach

2014 ◽  
Vol 7 (3) ◽  
pp. 1211-1224 ◽  
Author(s):  
W. Zhang ◽  
Q. Zhang ◽  
Y. Huang ◽  
T. T. Li ◽  
J. Y. Bian ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Standard Deviation ◽  
Rice Variety ◽  
Scale Up ◽  
Methane Emissions ◽  
Data Availability ◽  
Scale Model ◽  
Anthropogenic Source ◽  
Rice Paddies ◽  
Data Scarcity

Abstract. Rice paddies are a major anthropogenic source of the atmospheric methane. However, because of the high spatial heterogeneity, making accurate estimations of the methane emission from rice paddies is still a big challenge, even with complicated models. Data scarcity is one of the substantial causes of the uncertainties in estimating the methane emissions on regional scales. In the present study, we discussed how data scarcity affected the uncertainties in model estimations of rice paddy methane emissions, from county/provincial scale up to national scale. The uncertainties in methane emissions from the rice paddies of China was calculated with a local-scale model and the Monte Carlo simulation. The data scarcities in five of the most sensitive model variables, field irrigation, organic matter application, soil properties, rice variety and production were included in the analysis. The result showed that in each individual county, the within-cell standard deviation of methane flux, as calculated via Monte Carlo methods, was 13.5–89.3% of the statistical mean. After spatial aggregation, the national total methane emissions were estimated at 6.44–7.32 Tg, depending on the base scale of the modeling and the reliability of the input data. And with the given data availability, the overall aggregated standard deviation was 16.3% of the total emissions, ranging from 18.3–28.0% for early, late and middle rice ecosystems. The 95% confidence interval of the estimation was 4.5–8.7 Tg by assuming a gamma distribution. Improving the data availability of the model input variables is expected to reduce the uncertainties significantly, especially of those factors with high model sensitivities.

scholarly journals Inter-annual variability of wind climates and wind turbine annual energy production

2018 ◽  
Author(s):  
Sara C. Pryor ◽  
Tristan J. Shepherd ◽  
Rebecca J. Barthelmie
Keyword(s):  
Standard Deviation ◽  
Wind Energy ◽  
Wind Turbine ◽  
Energy Production ◽  
Wind Farm ◽  
Wind Farms ◽  
Wind Speeds ◽  
Annual Variability ◽  
Eastern Usa

Abstract. Inter-annual variability (IAV) of expected annual energy production (AEP) from proposed wind farms plays a key role in dictating project financing. IAV in pre-construction projected AEP and the difference in 50th and 90th percentile (P50 and P90) AEP derives in part from variability in wind climates. However, the magnitude of IAV in wind speeds at/close to wind turbine hub-heights is poorly constrained and maybe overestimated by the 6 % standard deviation of annual mean wind speeds that is widely applied within the wind energy industry. Thus there is a need for improved understanding of the long-term wind resource and the inter-annual variability therein in order to generate more robust predictions of the financial value of a wind energy project. Long-term simulations of wind speeds near typical wind turbine hub-heights over the eastern USA indicate median gross capacity factors (computed using 10-minute wind speeds close to wind turbine hub-heights and the power curve of the most common wind turbine deployed in the region) that are in good agreement with values derived from operational wind farms. The IAV of annual mean wind speeds at/near to typical wind turbine hub-heights in these simulations is lower than is implied by assuming a standard deviation of 6 %. Indeed, rather than in 9 in 10 years exhibiting AEP within 0.9 and 1.1 times the long-term mean AEP, results presented herein indicate that over 90 % of the area in the eastern USA that currently has operating wind turbines simulated AEP lies within 0.94 and 1.06 of the long-term average. Further, IAV of estimated AEP is not substantially larger than IAV in mean wind speeds. These results indicate it may be appropriate to reduce the IAV applied to pre-construction AEP estimates to account for variability in wind climates, which would decrease the cost of capital for wind farm developments.

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