AQ
A.J. Quast
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1
In offshore operations a trend is forming where vessels are more often required to do multiple short operations within a small-time frame. Traditional mooring systems require execution time far beyond the operation time. Dynamic positioning systems offer great advantages for short time span operations such as crew transfer or lift operations.
Currently operations are planned based on DP capability plots and experience of captain and DPO. DP capability plots have little operational value as this is a static calculation and only provide information for average station keeping capability. During operations, the displacements made by the vessel around the DP set-point, also referred to as DP offset, are of great importance to determine the operability of an operation. Currently, the only way of calculating the DP offset is by conducting extensive time domain simulations, which are hard to integrate in the operational workflow of a DP vessel involved in walk-to-work operations. Therefore, a new approach is developed which predicts the vessel’s DP offset in the frequency domain, which enables a quick and robust calculation of the DP offset which is suited to merge into the on-board workflow. A frequency domain model is per definition a linear model. This leads to the main challenge of this research. A vessel operating on DP is non-linear. Currently there is no insight in what the effect is of non-linear components present in a DP system, on the linear approximation of a frequency domain model.
To investigate the effect of non-linear components onto the DP frequency domain model, a time domain model is developed that is capable of systematically enabling/disabling different non-linear components. The time domain model will serve as the ’truth’ in this research as no actual vessel data is available. Furthermore, this helps identify the effects more easily, as the input for both models are identical. From the time domain model transfer functions can be derived that serve as the basis for the frequency domain model. The transfer function is a linear relation between two variables. In this case, between second order wave drift forces and displacement of the vessel in surge, sway and yaw direction. The following non-linear components are investigated in this research: Thruster ramp up, thruster turning rate, forbidden zones, saturation and thruster allocation. Thruster allocation is present in each model that will be tested, as this is an essential part of a DP system.
Using two methods of determining transfer functions the model and the effects of all non-linear components are tested. The model is subjected to a variety sea-state, with different wave directions. Both methods offer similar results even though different approaches to determine the transfer functions are used. The selected method is capable of accurately predicting vessel offsets, although some extreme offsets are not captured.
It is concluded that the presence of non-linear components have little to no effect on the DP offset as calculated by the time domain model. Because natural frequencies characteristic to these non-linear components are expected to exist at much higher frequencies that naturally present in second order wave drift forces. Thus, making a linear frequency domain model suitable for DP offset forecasting. It is advised to investigate the effect of including 2D input spectra as this is expected to improve the current model.
...
Currently operations are planned based on DP capability plots and experience of captain and DPO. DP capability plots have little operational value as this is a static calculation and only provide information for average station keeping capability. During operations, the displacements made by the vessel around the DP set-point, also referred to as DP offset, are of great importance to determine the operability of an operation. Currently, the only way of calculating the DP offset is by conducting extensive time domain simulations, which are hard to integrate in the operational workflow of a DP vessel involved in walk-to-work operations. Therefore, a new approach is developed which predicts the vessel’s DP offset in the frequency domain, which enables a quick and robust calculation of the DP offset which is suited to merge into the on-board workflow. A frequency domain model is per definition a linear model. This leads to the main challenge of this research. A vessel operating on DP is non-linear. Currently there is no insight in what the effect is of non-linear components present in a DP system, on the linear approximation of a frequency domain model.
To investigate the effect of non-linear components onto the DP frequency domain model, a time domain model is developed that is capable of systematically enabling/disabling different non-linear components. The time domain model will serve as the ’truth’ in this research as no actual vessel data is available. Furthermore, this helps identify the effects more easily, as the input for both models are identical. From the time domain model transfer functions can be derived that serve as the basis for the frequency domain model. The transfer function is a linear relation between two variables. In this case, between second order wave drift forces and displacement of the vessel in surge, sway and yaw direction. The following non-linear components are investigated in this research: Thruster ramp up, thruster turning rate, forbidden zones, saturation and thruster allocation. Thruster allocation is present in each model that will be tested, as this is an essential part of a DP system.
Using two methods of determining transfer functions the model and the effects of all non-linear components are tested. The model is subjected to a variety sea-state, with different wave directions. Both methods offer similar results even though different approaches to determine the transfer functions are used. The selected method is capable of accurately predicting vessel offsets, although some extreme offsets are not captured.
It is concluded that the presence of non-linear components have little to no effect on the DP offset as calculated by the time domain model. Because natural frequencies characteristic to these non-linear components are expected to exist at much higher frequencies that naturally present in second order wave drift forces. Thus, making a linear frequency domain model suitable for DP offset forecasting. It is advised to investigate the effect of including 2D input spectra as this is expected to improve the current model.
...
In offshore operations a trend is forming where vessels are more often required to do multiple short operations within a small-time frame. Traditional mooring systems require execution time far beyond the operation time. Dynamic positioning systems offer great advantages for short time span operations such as crew transfer or lift operations.
Currently operations are planned based on DP capability plots and experience of captain and DPO. DP capability plots have little operational value as this is a static calculation and only provide information for average station keeping capability. During operations, the displacements made by the vessel around the DP set-point, also referred to as DP offset, are of great importance to determine the operability of an operation. Currently, the only way of calculating the DP offset is by conducting extensive time domain simulations, which are hard to integrate in the operational workflow of a DP vessel involved in walk-to-work operations. Therefore, a new approach is developed which predicts the vessel’s DP offset in the frequency domain, which enables a quick and robust calculation of the DP offset which is suited to merge into the on-board workflow. A frequency domain model is per definition a linear model. This leads to the main challenge of this research. A vessel operating on DP is non-linear. Currently there is no insight in what the effect is of non-linear components present in a DP system, on the linear approximation of a frequency domain model.
To investigate the effect of non-linear components onto the DP frequency domain model, a time domain model is developed that is capable of systematically enabling/disabling different non-linear components. The time domain model will serve as the ’truth’ in this research as no actual vessel data is available. Furthermore, this helps identify the effects more easily, as the input for both models are identical. From the time domain model transfer functions can be derived that serve as the basis for the frequency domain model. The transfer function is a linear relation between two variables. In this case, between second order wave drift forces and displacement of the vessel in surge, sway and yaw direction. The following non-linear components are investigated in this research: Thruster ramp up, thruster turning rate, forbidden zones, saturation and thruster allocation. Thruster allocation is present in each model that will be tested, as this is an essential part of a DP system.
Using two methods of determining transfer functions the model and the effects of all non-linear components are tested. The model is subjected to a variety sea-state, with different wave directions. Both methods offer similar results even though different approaches to determine the transfer functions are used. The selected method is capable of accurately predicting vessel offsets, although some extreme offsets are not captured.
It is concluded that the presence of non-linear components have little to no effect on the DP offset as calculated by the time domain model. Because natural frequencies characteristic to these non-linear components are expected to exist at much higher frequencies that naturally present in second order wave drift forces. Thus, making a linear frequency domain model suitable for DP offset forecasting. It is advised to investigate the effect of including 2D input spectra as this is expected to improve the current model.
Currently operations are planned based on DP capability plots and experience of captain and DPO. DP capability plots have little operational value as this is a static calculation and only provide information for average station keeping capability. During operations, the displacements made by the vessel around the DP set-point, also referred to as DP offset, are of great importance to determine the operability of an operation. Currently, the only way of calculating the DP offset is by conducting extensive time domain simulations, which are hard to integrate in the operational workflow of a DP vessel involved in walk-to-work operations. Therefore, a new approach is developed which predicts the vessel’s DP offset in the frequency domain, which enables a quick and robust calculation of the DP offset which is suited to merge into the on-board workflow. A frequency domain model is per definition a linear model. This leads to the main challenge of this research. A vessel operating on DP is non-linear. Currently there is no insight in what the effect is of non-linear components present in a DP system, on the linear approximation of a frequency domain model.
To investigate the effect of non-linear components onto the DP frequency domain model, a time domain model is developed that is capable of systematically enabling/disabling different non-linear components. The time domain model will serve as the ’truth’ in this research as no actual vessel data is available. Furthermore, this helps identify the effects more easily, as the input for both models are identical. From the time domain model transfer functions can be derived that serve as the basis for the frequency domain model. The transfer function is a linear relation between two variables. In this case, between second order wave drift forces and displacement of the vessel in surge, sway and yaw direction. The following non-linear components are investigated in this research: Thruster ramp up, thruster turning rate, forbidden zones, saturation and thruster allocation. Thruster allocation is present in each model that will be tested, as this is an essential part of a DP system.
Using two methods of determining transfer functions the model and the effects of all non-linear components are tested. The model is subjected to a variety sea-state, with different wave directions. Both methods offer similar results even though different approaches to determine the transfer functions are used. The selected method is capable of accurately predicting vessel offsets, although some extreme offsets are not captured.
It is concluded that the presence of non-linear components have little to no effect on the DP offset as calculated by the time domain model. Because natural frequencies characteristic to these non-linear components are expected to exist at much higher frequencies that naturally present in second order wave drift forces. Thus, making a linear frequency domain model suitable for DP offset forecasting. It is advised to investigate the effect of including 2D input spectra as this is expected to improve the current model.
Tasikoki Coastal Protection
A researched based advice into the mitigation of shoreline recession of the beach of the Tasikoki Wildlife Rescue and Education Centre
Student report
(2019)
-
Sander de Jong, Ferdi Knoester, Christian Alferink, Arnout Quast, Misiu Smits, Marian Bosch-Rekveldt, Jan van Overeem, Jeroen Hoving
The beach adjacent to the Tasikoki Wildlife Rescue and Education Centre is one of the many beaches worldwide suffering from coastline recession. This loss of coast has a negative impact on the environment, local society and ecology. In general, shoreline retreat is caused by sea level rise (SLR) and erosion. The main objective of this research is to determine which factors are causing recession at Tasikoki beach and consequently which solution would be best in terms of mitigating coastline recession and protecting the hinterland from flooding. A Building with Nature (BwN) design philosophy has been considered to utilise natural processes instead of traditional ones, creating benefits for society and nature. Additionally, a model will be created in Unibest to substantiate and test the final solution.
The research first aimed to describe the coastal characteristics, ecosystem and societal system of the Tasikoki coast. This mainly consisted of a desk-study which was based on literature, but also of examining the surroundings and talking to locals. This study revealed amongst others the significant contribution of climate change on the shoreline retreat at Tasikoki beach.. Among the stakeholders, a major blocking power is absent. Nevertheless, an engagement plan is written to explain the local fishermen how they will benefit from the potential solution in order to prevent resistance. After gathering this general information to form a first impression, more location specific data was required to draw conclusions and setup the Unibest model. Every part of the required data has their own measurement method or source, using handmade measuring equipment, sonar GPS, sediment sieves and data retrieved from wind and wave models.
After a thorough analysis on the wave and wind climate and the surroundings of the Tasikoki coast, it could be concluded that the dominant wave direction is coming from a direction of 164˚ north. This determines the dominant sediment direction, which is thus propagating northward along the shore. Next, the direct coastal retreat due to SLR was calculated by using the Bruun-rule. Based on calculations and aerial image analyses, it was concluded that the two tidal inlets present at the Tasikoki coast play an important role in the erosion patternThe four main nearshore (CST) processes impacting the Tasikoki coast are wave impact, long waves, turbulence and avalanching/sliding. During the research, multiple possible solutions have been investigated which could mitigate the coastline recession. Based on a multi-criteria analysis, it was decided that a Biorock-based solution would suit the Tasikoki case best. This is a permeable submerged breakwater with a low current running through a steel frame to dampen waves and enhance nature at the same time.. A submerged breakwater was modelled in Unibest at Tasikoki beach. The result was positive. The structure traps sediment and causes more accretion along the coast than the length of the structure itself; functioning like a ‘sand engine’. At last a detailed implementation and monitoring plan was written, multiple scenarios are considered to make the solution more future-proof. ...
The research first aimed to describe the coastal characteristics, ecosystem and societal system of the Tasikoki coast. This mainly consisted of a desk-study which was based on literature, but also of examining the surroundings and talking to locals. This study revealed amongst others the significant contribution of climate change on the shoreline retreat at Tasikoki beach.. Among the stakeholders, a major blocking power is absent. Nevertheless, an engagement plan is written to explain the local fishermen how they will benefit from the potential solution in order to prevent resistance. After gathering this general information to form a first impression, more location specific data was required to draw conclusions and setup the Unibest model. Every part of the required data has their own measurement method or source, using handmade measuring equipment, sonar GPS, sediment sieves and data retrieved from wind and wave models.
After a thorough analysis on the wave and wind climate and the surroundings of the Tasikoki coast, it could be concluded that the dominant wave direction is coming from a direction of 164˚ north. This determines the dominant sediment direction, which is thus propagating northward along the shore. Next, the direct coastal retreat due to SLR was calculated by using the Bruun-rule. Based on calculations and aerial image analyses, it was concluded that the two tidal inlets present at the Tasikoki coast play an important role in the erosion patternThe four main nearshore (CST) processes impacting the Tasikoki coast are wave impact, long waves, turbulence and avalanching/sliding. During the research, multiple possible solutions have been investigated which could mitigate the coastline recession. Based on a multi-criteria analysis, it was decided that a Biorock-based solution would suit the Tasikoki case best. This is a permeable submerged breakwater with a low current running through a steel frame to dampen waves and enhance nature at the same time.. A submerged breakwater was modelled in Unibest at Tasikoki beach. The result was positive. The structure traps sediment and causes more accretion along the coast than the length of the structure itself; functioning like a ‘sand engine’. At last a detailed implementation and monitoring plan was written, multiple scenarios are considered to make the solution more future-proof. ...
The beach adjacent to the Tasikoki Wildlife Rescue and Education Centre is one of the many beaches worldwide suffering from coastline recession. This loss of coast has a negative impact on the environment, local society and ecology. In general, shoreline retreat is caused by sea level rise (SLR) and erosion. The main objective of this research is to determine which factors are causing recession at Tasikoki beach and consequently which solution would be best in terms of mitigating coastline recession and protecting the hinterland from flooding. A Building with Nature (BwN) design philosophy has been considered to utilise natural processes instead of traditional ones, creating benefits for society and nature. Additionally, a model will be created in Unibest to substantiate and test the final solution.
The research first aimed to describe the coastal characteristics, ecosystem and societal system of the Tasikoki coast. This mainly consisted of a desk-study which was based on literature, but also of examining the surroundings and talking to locals. This study revealed amongst others the significant contribution of climate change on the shoreline retreat at Tasikoki beach.. Among the stakeholders, a major blocking power is absent. Nevertheless, an engagement plan is written to explain the local fishermen how they will benefit from the potential solution in order to prevent resistance. After gathering this general information to form a first impression, more location specific data was required to draw conclusions and setup the Unibest model. Every part of the required data has their own measurement method or source, using handmade measuring equipment, sonar GPS, sediment sieves and data retrieved from wind and wave models.
After a thorough analysis on the wave and wind climate and the surroundings of the Tasikoki coast, it could be concluded that the dominant wave direction is coming from a direction of 164˚ north. This determines the dominant sediment direction, which is thus propagating northward along the shore. Next, the direct coastal retreat due to SLR was calculated by using the Bruun-rule. Based on calculations and aerial image analyses, it was concluded that the two tidal inlets present at the Tasikoki coast play an important role in the erosion patternThe four main nearshore (CST) processes impacting the Tasikoki coast are wave impact, long waves, turbulence and avalanching/sliding. During the research, multiple possible solutions have been investigated which could mitigate the coastline recession. Based on a multi-criteria analysis, it was decided that a Biorock-based solution would suit the Tasikoki case best. This is a permeable submerged breakwater with a low current running through a steel frame to dampen waves and enhance nature at the same time.. A submerged breakwater was modelled in Unibest at Tasikoki beach. The result was positive. The structure traps sediment and causes more accretion along the coast than the length of the structure itself; functioning like a ‘sand engine’. At last a detailed implementation and monitoring plan was written, multiple scenarios are considered to make the solution more future-proof.
The research first aimed to describe the coastal characteristics, ecosystem and societal system of the Tasikoki coast. This mainly consisted of a desk-study which was based on literature, but also of examining the surroundings and talking to locals. This study revealed amongst others the significant contribution of climate change on the shoreline retreat at Tasikoki beach.. Among the stakeholders, a major blocking power is absent. Nevertheless, an engagement plan is written to explain the local fishermen how they will benefit from the potential solution in order to prevent resistance. After gathering this general information to form a first impression, more location specific data was required to draw conclusions and setup the Unibest model. Every part of the required data has their own measurement method or source, using handmade measuring equipment, sonar GPS, sediment sieves and data retrieved from wind and wave models.
After a thorough analysis on the wave and wind climate and the surroundings of the Tasikoki coast, it could be concluded that the dominant wave direction is coming from a direction of 164˚ north. This determines the dominant sediment direction, which is thus propagating northward along the shore. Next, the direct coastal retreat due to SLR was calculated by using the Bruun-rule. Based on calculations and aerial image analyses, it was concluded that the two tidal inlets present at the Tasikoki coast play an important role in the erosion patternThe four main nearshore (CST) processes impacting the Tasikoki coast are wave impact, long waves, turbulence and avalanching/sliding. During the research, multiple possible solutions have been investigated which could mitigate the coastline recession. Based on a multi-criteria analysis, it was decided that a Biorock-based solution would suit the Tasikoki case best. This is a permeable submerged breakwater with a low current running through a steel frame to dampen waves and enhance nature at the same time.. A submerged breakwater was modelled in Unibest at Tasikoki beach. The result was positive. The structure traps sediment and causes more accretion along the coast than the length of the structure itself; functioning like a ‘sand engine’. At last a detailed implementation and monitoring plan was written, multiple scenarios are considered to make the solution more future-proof.