LH
L.J.G. Huijgens
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1
The interaction between ship propulsion machinery, propellers and the highly dynamic environment which is the sea is a complex yet highly relevant subject. During a storm, for example, waves and ship motions may cause the propeller to draw air, or ventilate, resulting in rapid changes in propeller thrust and load torque. These fluctuations propagate through the propulsion system, potentially causing excessive loads on propulsion machinery, while also reducing the ship's manoeuvrability. A profound understanding of these complex interactions still lacks. One result of this knowledge gap is the limited acceptance of new technologies for ship propulsion, especially those technologies known to have limited transient capabilities. In this paper, hardware in the loop (HIL) is proposed as a solution to this knowledge gap. Paying specific attention to propeller ventilation, HIL is used to identify new aspects of interaction between engine and propeller, thus demonstrating the added value of HIL for ventilation studies.
...
The interaction between ship propulsion machinery, propellers and the highly dynamic environment which is the sea is a complex yet highly relevant subject. During a storm, for example, waves and ship motions may cause the propeller to draw air, or ventilate, resulting in rapid changes in propeller thrust and load torque. These fluctuations propagate through the propulsion system, potentially causing excessive loads on propulsion machinery, while also reducing the ship's manoeuvrability. A profound understanding of these complex interactions still lacks. One result of this knowledge gap is the limited acceptance of new technologies for ship propulsion, especially those technologies known to have limited transient capabilities. In this paper, hardware in the loop (HIL) is proposed as a solution to this knowledge gap. Paying specific attention to propeller ventilation, HIL is used to identify new aspects of interaction between engine and propeller, thus demonstrating the added value of HIL for ventilation studies.
Requirements on ships are rapidly increasing. In particular, safety and environmental impact are under increasing scrutiny. At the same time, cost and profitability remain as important as they have ever been. These increasingly stringent constraints are beginning to pose problems during the design process. For example, the energy efficiency design index (EEDI) aims to reduce emissions of carbon dioxide by progressively limiting engine power installed on board. However, these reductions in propulsive power raise concerns about the ship's manoeuvrability in rough seas. Moreover, the expected introduction of novel power and propulsion systems based on, for example, fuel cell technology, further raises uncertainty regarding the performance of future ships and propulsion systems in dynamic environments. Considering these developments, detailed predictions of manoeuvrability and propulsion plant behaviour are becoming increasingly important in the ship design process. Yet, present prediction methods are insu_cient to evaluate manoeuvrability and behaviour of ship propulsion systems in complex, dynamic environments such as heavy seas. Fully numerical methods based on computational fluid dynamics (CFD) and first principles are inherently uncertain and compute-intensive. As such, these methods are presently unsuitable to assess the dynamic interaction between machinery and hydrodynamics over prolonged periods of time. As an alternative to numerical methods, experiments with scale model ships can be conducted. However, such experiments are subject to hydrodynamic scale effects: viscous friction, spray formation and propeller cavitation are not the same as at full scale. Moreover, these model ships are powered by considerably simplified propulsion systems, causing entirely different propulsion plant dynamics than at full scale. Ideally, scale model experiments would be conducted with, for example, a perfectly downscaled diesel engine, gearbox and propeller; in practice, however, this is generally not feasible. As such, existing prediction methods leave great uncertainty how future ship designs can simultaneously meet all requirements regarding operational performance, safety and compliance with environmental regulations. A possible way to bridge this knowledge gap is by conducting hardware in the loop (HIL) experiments in the ship model basin. Such experiments combine numerical simulations with a physical test setup. During HIL experiments with free sailing ship models, the propulsion engine and other machinery are simulated by a computer. These simulations are then used to control an electric motor, powering the propeller of a physical scale model ship. As such, the complex interaction between engine, propeller, hull and environment can be physically reproduced, allowing to assess design choices early on in the ship design process.
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Requirements on ships are rapidly increasing. In particular, safety and environmental impact are under increasing scrutiny. At the same time, cost and profitability remain as important as they have ever been. These increasingly stringent constraints are beginning to pose problems during the design process. For example, the energy efficiency design index (EEDI) aims to reduce emissions of carbon dioxide by progressively limiting engine power installed on board. However, these reductions in propulsive power raise concerns about the ship's manoeuvrability in rough seas. Moreover, the expected introduction of novel power and propulsion systems based on, for example, fuel cell technology, further raises uncertainty regarding the performance of future ships and propulsion systems in dynamic environments. Considering these developments, detailed predictions of manoeuvrability and propulsion plant behaviour are becoming increasingly important in the ship design process. Yet, present prediction methods are insu_cient to evaluate manoeuvrability and behaviour of ship propulsion systems in complex, dynamic environments such as heavy seas. Fully numerical methods based on computational fluid dynamics (CFD) and first principles are inherently uncertain and compute-intensive. As such, these methods are presently unsuitable to assess the dynamic interaction between machinery and hydrodynamics over prolonged periods of time. As an alternative to numerical methods, experiments with scale model ships can be conducted. However, such experiments are subject to hydrodynamic scale effects: viscous friction, spray formation and propeller cavitation are not the same as at full scale. Moreover, these model ships are powered by considerably simplified propulsion systems, causing entirely different propulsion plant dynamics than at full scale. Ideally, scale model experiments would be conducted with, for example, a perfectly downscaled diesel engine, gearbox and propeller; in practice, however, this is generally not feasible. As such, existing prediction methods leave great uncertainty how future ship designs can simultaneously meet all requirements regarding operational performance, safety and compliance with environmental regulations. A possible way to bridge this knowledge gap is by conducting hardware in the loop (HIL) experiments in the ship model basin. Such experiments combine numerical simulations with a physical test setup. During HIL experiments with free sailing ship models, the propulsion engine and other machinery are simulated by a computer. These simulations are then used to control an electric motor, powering the propeller of a physical scale model ship. As such, the complex interaction between engine, propeller, hull and environment can be physically reproduced, allowing to assess design choices early on in the ship design process.
Hardware in the loop experiments with ship propulsion systems in the towing tank
Scale effects, corrections and demonstration
Standards for environmental impact, safety and operational performance of ships are becoming increasingly strict. In order to meet these standards, the performance of new ship designs must be predicted with an increasing level of detail and confidence. As present prediction methods lack realistic, dynamic behaviour of the ship's propulsion plant, there is a need for more advanced methods. In this paper, an open water test with Hardware in the Loop (HIL) functionality is proposed. HIL open water tests combine software and hardware components to emulate realistic behaviour of the ship's propulsion plant in the towing tank. It is known, however, that experiments in the towing tank are subject to viscous scale effects. In addition to this, shaft dynamics are distorted by a number of scale effects occurring inside the scale model propulsion system. In this paper, it is demonstrated with measurements that if corrections for these scale effects are applied, the dynamic interaction between the propeller and simulated engine system can be accurately emulated in the ship model basin.
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Standards for environmental impact, safety and operational performance of ships are becoming increasingly strict. In order to meet these standards, the performance of new ship designs must be predicted with an increasing level of detail and confidence. As present prediction methods lack realistic, dynamic behaviour of the ship's propulsion plant, there is a need for more advanced methods. In this paper, an open water test with Hardware in the Loop (HIL) functionality is proposed. HIL open water tests combine software and hardware components to emulate realistic behaviour of the ship's propulsion plant in the towing tank. It is known, however, that experiments in the towing tank are subject to viscous scale effects. In addition to this, shaft dynamics are distorted by a number of scale effects occurring inside the scale model propulsion system. In this paper, it is demonstrated with measurements that if corrections for these scale effects are applied, the dynamic interaction between the propeller and simulated engine system can be accurately emulated in the ship model basin.
Regulatory demands on ship designs, such as emission and manoeuvrability requirements, are becoming increasingly stringent, raising the need for advanced methods to predict and assess dynamic propulsion plant behaviour of a new design. At present, model scale experiments and numerical simulations are not able to predict this behaviour in full detail. To fill the resulting knowledge gap, this paper proposes to further develop existing scale model tests into so-called dynamic model basin tests. These tests aim to predict dynamic behaviour of the ship propulsion plant in complex, dynamic environments in more detail, leading to improved propulsion systems and controls and ultimately, lower emissions, lower fuel consumption and increased manoeuvrability.
...
Regulatory demands on ship designs, such as emission and manoeuvrability requirements, are becoming increasingly stringent, raising the need for advanced methods to predict and assess dynamic propulsion plant behaviour of a new design. At present, model scale experiments and numerical simulations are not able to predict this behaviour in full detail. To fill the resulting knowledge gap, this paper proposes to further develop existing scale model tests into so-called dynamic model basin tests. These tests aim to predict dynamic behaviour of the ship propulsion plant in complex, dynamic environments in more detail, leading to improved propulsion systems and controls and ultimately, lower emissions, lower fuel consumption and increased manoeuvrability.
A method to quantify manufacturing activities for shipbuilding projects is devised, based on extrapolation of historical projects. Extrapolation rules are based on first principles and fine-tuned using empirical data. A 4-tier hierarchical system structure is proposed, incorporating different types of interrelations. Subsequently, it is investigated how design principles can be used to mathematically define these relations, resulting in a substantiated work content estimation model. Several shipbuilding projects, some of which recently executed, were used as data source to support the proposed theory.
It is demonstrated that detailed production man hour estimations can be made using limited sets of input data.
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A method to quantify manufacturing activities for shipbuilding projects is devised, based on extrapolation of historical projects. Extrapolation rules are based on first principles and fine-tuned using empirical data. A 4-tier hierarchical system structure is proposed, incorporating different types of interrelations. Subsequently, it is investigated how design principles can be used to mathematically define these relations, resulting in a substantiated work content estimation model. Several shipbuilding projects, some of which recently executed, were used as data source to support the proposed theory.
It is demonstrated that detailed production man hour estimations can be made using limited sets of input data.