Uncertainty of Sea Trials Results Used for Validation of Ship Manoeuvring Simulation Models

2015 ◽  
Author(s):  
Sergey Gavrilin ◽  
Sverre Steen
Keyword(s):  
Simulation Model ◽  
Simulation Models ◽  
Full Scale ◽  
Experimental Uncertainty ◽  
Time Domain Simulation ◽  
Empirical Methods ◽  
Scaled Model ◽  
Monte Carlo Techniques ◽  
Ship Manoeuvring ◽  
Rudder Angle

Increasingly complex marine operations dictate higher need for precise and reliable modelling. For the last decades several different approaches to modelling of ship manoeuvring were developed, including scaled model testing, numerical and empirical methods. Increasingly, time-domain simulation models for ship manoeuvring are developed and used for training and planning of marine operations. Especially when using the simulation models to plan operations, it is essential that the simulation model is properly validated. There is a need for better and more standardized validation methods for such simulation models. A key issue is the uncertainty of the data used in the validation. Typically, the validation will be against full scale trials results. In the study reported in this paper it was found by inspection of repeated tests results that even under relatively calm environmental conditions outcomes of sea trials can be highly uncertain. However, it is very expensive to investigate uncertainty of each type of trial experimentally. Therefore it can be very beneficial to estimate it by means of a simulation model. This paper presents results of analysis of full scale turning circle trials of research vessel “Gunnerus”. Turning circle trials with 20° and 35° rudder angle executed both to starboard and port sides are analyzed. Experimental uncertainty analysis is performed. Effectiveness of IMO correction procedure is discussed. Also paper describes a method for determining uncertainty of trial results due to environmental effects by means of simulation model and compares them with experimental uncertainty. The method is based on Monte-Carlo techniques.

scholarly journals Submarine Autopilot Performance Optimization with System Identification

2018 ◽  
Author(s):  
F Belanger ◽  
D Millan ◽  
X Cyril
Keyword(s):  
System Identification ◽  
Simulation Model ◽  
Performance Optimization ◽  
Full Scale ◽  
Hydrodynamic Coefficients ◽  
Scaled Model ◽  
Towing Tank ◽  
Ship Manoeuvring ◽  
Free Running ◽  
Motion Dynamics

Computer simulation models play a vital role in the assessment of a ship’s autopilot design. A well-tuned autopilot will contribute to reducing rudder activity, thereby minimizing wear on the actuation plant and also generally reducing fuel consumption. The equations that describe the ship motion dynamics contain a large number of hydrodynamic coefficients that must be calculated as accurately as possible to justify the use of a simulation model and its relevance to predicting the ship manoeuvring characteristics. Proper prediction of the ship performance is an essential pre-requisite in the process of tuning the autopilot. The hydrodynamic coefficients can be calculated by using theoretical methods or by carrying out experiments on the actual ship or on a scaled model of the ship. System Identification (SI) is an experiment-based approach and in this paper the authors present an algorithm that can estimate the coefficients with great accuracy. These coefficients can classically be obtained in a towing tank using a captive model, and with a planar motion mechanism and a rotating arm. Generally, these systems are costly and entail expensive trials programs, and SI methods have been developed in an effort to obviate some of those problems and limitations. They typically process ship manoeuvring data obtained from a free-running scaled model or full-scale trials. While similar to a surface ship, the motion dynamics of a submarine introduce additional challenges for SI methods. This is because the submarine manoeuvres in “three dimensions”, which adds complexity and more hydrodynamic coefficients to the equations. The standard submarine simulation model, also referred to as the Gertler and Hagen equations, incorporates over 120 coefficients. To calculated these coefficients, the SI algorithm uses a Square-Root Unscented Kalman filter (SR-UKF). One of its appealing features is that it calculates all the coefficients by processing data from a single submarine manoeuvre that has a repeating sinusoidal pattern in both depth and course. The manoeuvre can be performed in a towing tank by a free-running scaled model of the submarine, or it can be performed at sea on the full-scale submarine as part of the sea trials schedule.

RECURSIVE NEURAL NETWORK MODEL OF CATAMARAN MANOEUVRING

2021 ◽  
Vol 154 (A3) ◽  
Author(s):  
L Moreira ◽  
C Guedes Soares
Keyword(s):  
Neural Network ◽  
Mathematical Models ◽  
Simulation Model ◽  
Network Model ◽  
Neural Network Model ◽  
Full Scale ◽  
Passenger Transport ◽  
Recursive Neural Network ◽  
Rudder Angle ◽  
Scale Data

A neural network model to simulate catamaran manoeuvres is proposed as an alternative to the traditional methodology of developing manoeuvring mathematical models. Data obtained in full-scale trials with a real ship are used to train the model. By recording full-scale trials of catamaran manoeuvres it is possible to generate a neural network model which will allow the prediction of the catamaran manoeuvring performance under different conditions. A Recursive Neural Network (RNN) manoeuvring simulation model is proposed and applied to a catamaran in this specific case. Inputs to the simulation are the orders of rudder angle and ship’s speed and also the recursive outputs velocities of sway and yaw. Two types of manoeuvres are simulated: tactical circles and zigzags. The results between the full-scale data and the simulations are compared in order to analyze and determine the accuracy of the RNN. The study is performed for a catamaran operating in the Tagus estuary for passenger transport to and from Lisbon.

Recursive Neural Network Model Of Catamaran Manoeuvring

2012 ◽  
Vol 154 (A3) ◽  
Keyword(s):  
Neural Network ◽  
Mathematical Models ◽  
Simulation Model ◽  
Network Model ◽  
Neural Network Model ◽  
Full Scale ◽  
Passenger Transport ◽  
Recursive Neural Network ◽  
Rudder Angle ◽  
Scale Data

A neural network model to simulate catamaran manoeuvres is proposed as an alternative to the traditional methodology of developing manoeuvring mathematical models. Data obtained in full-scale trials with a real ship are used to train the model. By recording full-scale trials of catamaran manoeuvres it is possible to generate a neural network model which will allow the prediction of the catamaran manoeuvring performance under different conditions. A Recursive Neural Network (RNN) manoeuvring simulation model is proposed and applied to a catamaran in this specific case. Inputs to the simulation are the orders of rudder angle and ship’s speed and also the recursive outputs velocities of sway and yaw. Two types of manoeuvres are simulated: tactical circles and zigzags. The results between the full-scale data and the simulations are compared in order to analyze and determine the accuracy of the RNN. The study is performed for a catamaran operating in the Tagus estuary for passenger transport to and from Lisbon.

Time Domain Simulation Model for Research Vessel Gunnerus

2015 ◽  
Author(s):  
Vahid Hassani ◽  
Andrew Ross ◽  
Ørjan Selvik ◽  
Dariusz Fathi ◽  
Florian Sprenger ◽  
...  
Keyword(s):  
Simulation Model ◽  
Time Domain ◽  
Trial Data ◽  
Full Scale ◽  
Dynamic Equations ◽  
Scale Model ◽  
Research Vessel ◽  
Oil Exploration ◽  
Time Domain Simulation ◽  
Sea Trial

A research vessel (RV) plays an important role in many fields such as oceanography, fisheries and polar research, hydrographic surveys, and oil exploration. It also has a unique function in maritime research and developments. Full-scale sea trials that require vessels, are usually extremely expensive; however, research vessels are more available than other types of ship. This paper presents the results of a time-domain simulation model of R/V Gunnerus, the research vessel of the Norwegian University of Science and Technology (NTNU), using MARINTEK’s vessel simulator (VeSim). VeSim is a time-domain simulator which solves dynamic equations of vessel motions and takes care of seakeeping and manoeuvring problems simultaneously. In addition to a set of captive and PMM tests on a scale model of Gunnerus, full-scale sea trials are carried out in both calm and harsh weather and the proposed simulation model is validated against sea trial data.

Validating the Vertical Dynamic Performance of a Multi-Wheeled Combat Vehicle Computer Simulation Model

2005 ◽  
Author(s):  
Matthew J. Hillegass ◽  
James G. Faller ◽  
Mark S. Bounds ◽  
Moustafa El-Gindy ◽  
Seokyong Chae
Keyword(s):  
Computer Simulation ◽  
Simulation Model ◽  
Dynamic Performance ◽  
Performance Testing ◽  
Simulation Models ◽  
Simulation Software ◽  
Full Scale ◽  
Computer Simulation Model ◽  
Vehicle Model ◽  
Combat Vehicle

Performance testing is an important step in the development of any vehicle model. Generally, full-scale field tests are conducted to collect the dynamic response characteristics for evaluating the vehicle performance. However, with increases in computational power and the accuracy of simulation models, virtual testing can be extensively used as an alternative to the time consuming and costly full-scale tests, especially for severe maneuvers. Validation of the simulation results is critical for the acceptance of such simulation models. In this paper, a methodology for validating the vertical dynamic performance of a virtual vehicle has been discussed. The dynamic performance of a multi-wheeled combat vehicle model specially developed using a multi-body dynamics code was validated against the measured data obtained on the U.S. Army Aberdeen Test Center’s (ATC) test courses. The multi-wheeled combat vehicle variant computer simulation model was developed in TruckSim, a vehicle dynamic simulation software developed by the Mechanical Simulation Corporation. Prior to validating the model, the vehicle weights, dimensions, tires and suspension characteristics were measured and referenced in the specially developed computer simulation model. The data for the tire and suspension characteristics were acquired from the respective leading manufacturers in the form of look-up tables. The predictions of the vehicle vertical dynamics on different road profiles at various vehicle speeds were compared with the field test results. The time domain data for the vertical acceleration at the vehicle center of gravity, pitching, vehicle speed and the suspension/damper displacement were compared to analyze the feasibility of using the computer simulation models to predict the vertical dynamic performance of the vehicle. Based on the results it was found that the particular combat vehicle computer simulation model is capable of predicting the vertical dynamic performance characteristics.

scholarly journals Guidelines to Calibrate a Multi-Residential Building Simulation Model Addressing Overheating Evaluation and Residents’ Influence

Buildings ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 242
Author(s):  
Christoph Schünemann ◽  
David Schiela ◽  
Regine Ortlepp
Keyword(s):  
Simulation Model ◽  
Time Window ◽  
Residential Building ◽  
Simulation Models ◽  
Building Simulation ◽  
Night Time ◽  
Building Performance Simulation ◽  
Starting Point ◽  
3D Simulation Model ◽  
Building Physics

Can building performance simulation reproduce measured summertime indoor conditions of a multi-residential building in good conformity? This question is answered by calibrating simulated to monitored room temperatures of several rooms of a multi-residential building for an entire summer in two process steps. First, we did a calibration for several days without the residents being present to validate the building physics of the 3D simulation model. Second, the simulations were calibrated for the entire summer period, including the residents’ impact on evolving room temperature and overheating. As a result, a high degree of conformity between simulation and measurement could be achieved for all monitored rooms. The credibility of our results was secured by a detailed sensitivity analysis under varying meteorological conditions, shading situations, and window ventilation or room use in the simulation model. For top floor dwellings, a high overheating intensity was evoked by a combination of insufficient use of night-time window ventilation and non-heat-adapted residential behavior in combination with high solar gains and low heat storage capacities. Finally, the overall findings were merged into a process guideline to describe how a step-by-step calibration of residential building simulation models can be done. This guideline is intended to be a starting point for future discussions about the validity of the simplified boundary conditions which are often used in present-day standard overheating assessment.

Settings, Experimentation and Evaluation of the Simulation Models

2013 ◽  
Vol 309 ◽  
pp. 366-371 ◽  
Author(s):  
František Manlig ◽  
Radek Havlik ◽  
Alena Gottwaldova
Keyword(s):  
Simulation Model ◽  
New Technology ◽  
Simulation Models ◽  
Manufacturing Processes ◽  
Customer Requirements ◽  
Evaluation Functions ◽  
Operational Management ◽  
Minimum Number ◽  
User Friendly ◽  
Setting Parameters

This paper deals with research in computer simulation of manufacturing processes. The paper summarizes the procedures associated with developing the model, experimenting with and evaluating the model results. The key area is of experimentation with the simulation model and evaluation using indicators or multi-criteria functions. With regards to the experiment the crucial variables are the simulation model. The key ideas are to set the number of variables, depending on what a given simulation will be. For example, when introducing new technology into production, modify the type of warehouse, saving workers, thus economizing. The simulation models for the operational management uses simplified models, if possible, a minimum number of variables to obtain the result in shortest possible time. These models are more user friendly and the course will be conducted mostly in the background. An example of a criteria function is the number of parts produced or production time. Multi-criteria function has given us the opportunity to make better quality decisions. It is based on the composition of several parameters, including their weight to one end point. The type of evaluation functions, whether it is an indicator or criteria function is selected and based on customer requirements. In most cases it is recommended to use the multi-dimensional function. It gives us a more comprehensive view of the results from the model and facilitates decision-making. The result of this paper is a display of setting parameters for the experimentation on a sample model. Furthermore, the comparisons of results with a multi-criteria objective function and one-criterion indicator.

A Method to Define the Best Weld Sequence Using a Limited Number of Welding Simulation Analysis

2015 ◽  
Author(s):  
Mahyar Asadi ◽  
Ghazi Alsoruji
Keyword(s):  
Simulation Model ◽  
Surrogate Model ◽  
Simulation Analysis ◽  
Combinatorial Problem ◽  
Fem Analysis ◽  
Simulation Models ◽  
Computational Time ◽  
Optimal Sequence ◽  
Welded Structure ◽  
Welding Sequence

Weld sequence optimization, which is determining the best (and worst) welding sequence for welding work pieces, is a very common problem in welding design. The solution for such a combinatorial problem is limited by available resources. Although there are fast simulation models that support sequencing design, still it takes long because of many possible combinations, e.g. millions in a welded structure involving 10 passes. It is not feasible to choose the optimal sequence by evaluating all possible combinations, therefore this paper employs surrogate modeling that partially explores the design space and constructs an approximation model from some combinations of solutions of the expensive simulation model to mimic the behavior of the simulation model as closely as possible but at a much lower computational time and cost. This surrogate model, then, could be used to approximate the behavior of the other combinations and to find the best (and worst) sequence in terms of distortion. The technique is developed and tested on a simple panel structure with 4 weld passes, but essentially can be generalized to many weld passes. A comparison between the results of the surrogate model and the full transient FEM analysis all possible combinations shows the accuracy of the algorithm/model.

Guidelines for CFD Simulations of Spar VIM

2013 ◽  
Author(s):  
Charles Lefevre ◽  
Yiannis Constantinides ◽  
Jang Whan Kim ◽  
Mike Henneke ◽  
Robert Gordon ◽  
...  
Keyword(s):  
Reynolds Number ◽  
Test Data ◽  
Model Test ◽  
Model Tests ◽  
Full Scale ◽  
Mooring System ◽  
Time Step ◽  
Cfd Simulations ◽  
Scaled Model ◽  
Sway Motion

Vortex-Induced Motion (VIM), which occurs as a consequence of exposure to strong current such as Loop Current eddies in the Gulf of Mexico, is one of the critical factors in the design of the mooring and riser systems for deepwater offshore structures such as Spars and multi-column Deep Draft Floaters (DDFs). The VIM response can have a significant impact on the fatigue life of mooring and riser components. In particular, Steel Catenary Risers (SCRs) suspended from the floater can be sensitive to VIM-induced fatigue at their mudline touchdown points. Industry currently relies on scaled model testing to determine VIM for design. However, scaled model tests are limited in their ability to represent VIM for the full scale structure since they are generally not able to represent the full scale Reynolds number and also cannot fully represent waves effects, nonlinear mooring system behavior or sheared and unsteady currents. The use of Computational Fluid Dynamics (CFD) to simulate VIM can more realistically represent the full scale Reynolds number, waves effects, mooring system, and ocean currents than scaled physical model tests. This paper describes a set of VIM CFD simulations for a Spar hard tank with appurtenances and their comparison against a high quality scaled model test. The test data showed considerable sensitivity to heading angle relative to the incident flow as well as to reduced velocity. The simulated VIM-induced sway motion was compared against the model test data for different reduced velocities (Vm) and Spar headings. Agreement between CFD and model test VIM-induced sway motion was within 9% over the full range of Vm and headings. Use of the Improved Delayed Detached Eddy Simulation (IDDES, Shur et al 2008) turbulence model gives the best agreement with the model test measurements. Guidelines are provided for meshing and time step/solver setting selection.

Rotorcraft Lateral-Directional Oscillations: The Anatomy of a Nuisance Mode

2021 ◽  
Author(s):  
Dheeraj Agarwal ◽  
Linghai Lu ◽  
Gareth D. Padfield ◽  
Mark D. White ◽  
Neil Cameron
Keyword(s):  
Simulation Model ◽  
Simulation Models ◽  
Flight Test ◽  
Flight Simulation ◽  
Stability And Control ◽  
Systems Research ◽  
Control Derivatives ◽  
Research Aircraft ◽  
Level Of Understanding ◽  
And Control

High-fidelity rotorcraft flight simulation relies on the availability of a quality flight model that further demands a good level of understanding of the complexities arising from aerodynamic couplings and interference effects. One such example is the difficulty in the prediction of the characteristics of the rotorcraft lateral-directional oscillation (LDO) mode in simulation. Achieving an acceptable level of the damping of this mode is a design challenge requiring simulation models with sufficient fidelity that reveal sources of destabilizing effects. This paper is focused on using System Identification to highlight such fidelity issues using Liverpool's FLIGHTLAB Bell 412 simulation model and in-flight LDO measurements from the bare airframe National Research Council's (Canada) Advanced Systems Research Aircraft. The simulation model was renovated to improve the fidelity of the model. The results show a close match between the identified models and flight test for the LDO mode frequency and damping. Comparison of identified stability and control derivatives with those predicted by the simulation model highlight areas of good and poor fidelity.

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