Risk of collision between service vessels and offshore wind turbines

Reliability Engineering and System Safety 109 (2013) 18–31

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Risk of collision between service vessels and offshore wind turbines ¨ Lijuan Dai a,n, Soren Ehlers a, Marvin Rausand b, Ingrid Bouwer Utne a a b

Department of Marine Technology, Norwegian University of Science and Technology, NO 7052 Trondheim, Norway Department of Production and Quality Engineering, Norwegian University of Science and Technology, NO 7491 Trondheim, Norway

a r t i c l e i n f o

a b s t r a c t

Article history: Received 30 April 2012 Received in revised form 16 July 2012 Accepted 30 July 2012 Available online 29 August 2012

Offshore wind farms are growing in size and are situated farther and farther away from shore. The demand for service visits to transfer personnel and equipment to the wind turbines is increasing, and safe operation of the vessels is essential. Currently, collisions between service vessels and offshore wind turbines are paid little attention to in the offshore wind energy industry. This paper proposes a risk assessment framework for such collisions and investigates the magnitude of the collision risk and important risk-influencing factors. The paper concludes that collisions between turbines and service vessels even at low speed may cause structural damage to the turbines. There is a need for improved consideration of this kind of collision risk when designing offshore wind turbines and wind farms. & 2012 Elsevier Ltd. All rights reserved.

Keywords: Collision risk Service vessel Offshore wind turbine Risk analysis

1. Introduction Current offshore wind farms are located close to the shore, typically within a distance of 20 km, where the density of shipping lanes and other traffic is relatively high. The maritime safety in the vicinity of offshore wind farms therefore raises concern. Several studies (e.g. [1,2]) focus on the risk of collision between offshore wind turbines (OWTs) and passing vessels, due to maritime transportation, fisheries, and military activities, but limited attention is paid to the risk of collision from service vessels that approach the OWTs, for example, to carry out maintenance. The trend is to move OWTs farther offshore and into deeper water to take advantage of the increased production potential and fewer conflicts with local human and animal populations. The future offshore wind farms may be located away from commercial ship traffic lanes. The need is therefore reduced for the analysis of collision risk between passing vessels and OWTs [3]. On the other hand, the more hostile environment farther offshore requires new and larger types of service vessels, and this increases the need for assessing the risk of collision between the service vessels and the OWTs. The offshore oil and gas industry is much concerned about collisions of visiting vessels on assignment with offshore installations [4,5]. In the last decade, 24 out of 26 reported collisions on the Norwegian Continental Shelf were caused by visiting vessels [6]. The underlying causes of the collisions include complex equipment, inadequately trained crew, and violation of

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Corresponding author. Tel.: þ47 73 59 5839. E-mail address: [email protected] (L. Dai).

0951-8320/$ - see front matter & 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.ress.2012.07.008

procedures [6]. Due to the similarities in operational procedures and environmental conditions, the same causes may lead to collisions between service vessels and OWTs. Offshore wind energy production does not involve hazards on the same level as the process hazards on oil and gas installations, but damage to the OWTs may pose risk to personnel onboard service vessels, increase the need for maintenance and repairs, and lead to costly production outage. To have a thorough understanding of the collision risk and the need for mitigating measures is, therefore, important in order to improve workers’ safety and cost-efficiency. The main objective of this paper is to present a framework for analysis of the collision risk between service vessels and OWTs. For probability estimation and consequence analysis, methods are introduced with examples to illustrate their application. These examples can contribute to new knowledge about the impact of collisions on OWTs, and the importance of taking this kind of collision risk into consideration in the design of OWTs and offshore wind farms. The collision risk may increase when offshore wind farms are moved farther from the coast and into more exposed areas and when, consequently, the service vessels become larger. These wind farms have yet not been designed to the level of detail necessary for enabling a complete risk analysis. The collision risk analysis framework in this paper is proposed for these offshore wind farms, but will need to be adapted to the specific cases. Therefore, the focus of this study is on the introduction of the framework and associated approaches, with simplified examples for illustration. The remainder of this paper is arranged as follows: Section 2 provides an overview of the previous incidents in offshore wind

L. Dai et al. / Reliability Engineering and System Safety 109 (2013) 18–31

energy industry and relevant statistics from the offshore oil and gas industry. The framework for collision risk analysis is presented in Section 3. Section 4 gives a brief introduction on current offshore wind farms and the development trend, as well as the service vessels which are categorized into four groups. Hazards related to collision between service vessels and OWTs are identified in Section 5. Section 6 focuses on causal analysis and presents methods for probability analysis. Section 7 applies a quasi-static simulation approach for collision consequences. The simulation results reveal the magnitude of collision between service vessels and OWTs. Section 8 discusses the strategies for risk reducing measures. Conclusions are drawn in the final section.

2. Previous incidents Public data on accidents and incidents related to offshore wind farms is hard to find, but some brief incident descriptions based on news articles are collected in the Caithness Windfarm Information Forum (CWIF) database [7]. This database contains only one relevant record of a collision between a service vessel and an OWT (up to June 30, 2012): A jack-up barge smashed into one OWT on October 6, 2006 in Scroby Sands wind farm, off the Norfolk coast in England. About 20 cm of the tip was broken off the blade and vital maintenance work was interrupted. In addition, Sharples and Sharples [8] describe another incident: Collision near miss happened on September 21, 2003 in Lolland, Denmark. A float dock broke loose from the tug and threatened the wind farm. It was, however, reconnected in time. The same report [8] also mentions damage caused by service vessels on the appurtenances, such as the boat landing or J-tubes, and claims that such damage may have been underestimated in early OWT tower designs. The low number of reported incidents may indicate a rather low risk, but can also be a sign of negligence to record information about collisions, or that data is not disclosed. Due to the limited availability of reports on collisions with OWTs, it is not possible to base any risk analysis solely on historical data. Several studies in the offshore oil and gas industry, however, provide valuable information on the risk of collision between visiting vessels and oil and gas installations. Among these studies are:

 HSE (2003) records 557 collision incidents between ships and



platforms on the United Kingdom Continental Shelf in the period 1975–2001. Service vessels account for 514 of these incidents, i.e., more than 96% [9]. Most collisions from service vessels are low-energy collisions that cause minor damage, but five supply or standby vessel collisions resulted in severe damage [6]. The Petroleum Safety Authority in Norway indicates that 26 collisions have occurred in the last 10 years on the Norwegian Continental Shelf, and six of the incidents had a very large damage potential [5].

3. Risk analysis framework A risk analysis provides answers to the three questions: (i) What can go wrong?; (ii) What is the likelihood of that happening?; and (iii) What are the consequences?. The OWT structure is normally designed to withstand collisions from

19

dedicated service vessels at low speed. It is more uncertain whether the OWT is able to withstand collisions from the same vessels at high speed, or from larger service vessels. The threshold for damage to the OWT needs to be evaluated in each specific case, based on detailed information about the properties of the OWT structure and the shape, weight, and speed of the relevant service vessels. To determine the collision risk between service vessels and OWTs, all the significant accident scenarios have to be analyzed in a structured manner. The risk analysis framework in this paper resembles a general risk analysis process [10], but the various steps include extensions and adaptations to collision risk. The framework consists of six main steps: (1) initiating analysis; (2) hazard identification; (3) probability analysis; (4) consequence analysis; (5) risk description and evaluation; and (6) risk reduction. 1. Initiating analysis—to establish the objectives and the boundary conditions for the risk analysis. The results from the risk analysis can, for example, be used to modify the design of the OWT structure and/or the service vessels, to improve the operational procedures, to improve the personnel training, and to establish plans for emergency preparedness. Characteristics of offshore wind farms that need to be taken into consideration include location, size, capacity, number of OWTs, distance between OWTs, and the support structure of the OWTs. Site conditions (i.e., environmental conditions) have strong impacts on the reliability of OWTs and the service demand. Wind speed and wave height usually influence the service vessel types and the weather window for operation. The activities of the initiating analysis are described in detail in [10] and are not discussed further in this paper. 2. Hazard identification—to identify all relevant hazardous events related to collisions between a service vessel and an OWT. Only hazardous events that have the potential to result in significant harm to the OWT and/or the service vessel and the personnel should be included. 3. Probability analysis—to provide an estimate of the likelihood of each of the hazardous events that were identified in step 2. The likelihood can be given as a probability related to a specified operation or as a frequency, for example, the expected number of events per year. For collision with OWTs, the historical data is inadequate, and we therefore have to use an indirect approach to estimate the likelihood of the hazardous events, as outlined in Section 6. 4. Consequence analysis—to estimate the impact energy and the harm to the OWT structure and the vessel. In this paper the impact energy is calculated based on finite element modeling. Finite element modeling requires input data about size, shape, stiffness of vessels and OWT structures. The analysis therefore has to be attuned to a specific vessel and a specific OWT structure. 5. Risk description and evaluation—to describe the risk picture related to collision scenarios, combining consequences and likelihoods. If risk acceptance criteria have been established, this step should compare the calculated risk with these acceptance criteria to determine whether or not the situation is ‘‘acceptable’’. 6. Identification and suggestion of risk reducing measures—to propose design, operational, and/or administrative changes that may reduce the collision risk. The results of the risk analysis are often used for decision-making based on costbenefit analysis of the available risk reducing measures. Measures that are associated with low economic costs should be considered even if the estimated risk is low. On the other hand, if the estimated risk is high, even expensive measures

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must be considered. Cost-benefit analysis is outside the scope of this paper.

4. OWTs and types of vessels Currently, there are 1247 OWTs installed and grid connected, totaling 3294 MW in 49 wind farms in nine European countries [11]. Experience from a few offshore wind farms in operation, for example, Tunø Knob, indicates a total number of five service visits to each OWT per year [12]. Tunø Knob consists of only 500 kW OWTs with relatively mature technology and extensive operational experience. Recent OWTs have a rated power of 2–3 MW, with a trend towards 5 MW and higher. These OWTs are developed especially for offshore wind conditions, but there is a significant uncertainty when it comes to future production availability. Besides the increasing power capacity of individual OWTs in offshore wind farms, the number of OWTs in each farm is also growing. The largest offshore wind farm so far—Thanet, was commissioned in 2010 and has a capacity of 300 MW, consisting of 100 OWTs. Dogger Bank, one of the offshore wind farms with consent of Crown Estate Round 3 will have a capacity of 9000 MW. It means that even with 5 MW turbines, 1800 OWTs will need to be installed. Many different types of service vessels are available, and they can be categorized according to their operational patterns and the contact modes with the OWT structure: Type 1 Mooring maneuvers in direct contact with the OWT structure. This kind of vessel is pushed against the OWT structure with a thrust; for example, inflatable rubber boat (Zodiac), Windcat, and SWATH. Minor bumps during operation are expected to occur frequently, but these can be disregarded in the analyses of collision risk.

Table 1 Reference values for Type 1 vessels. Specification

Length Beam Weight Cruising speed Material Person capacity Hs max at transfer V max at transfer Load capacity Mobilization time

Vessel Zodiac

Windcat

SWATH

4–9 m 2–3 m 90–150 kg 36 knots Rubber 5–22 1.5 m 16 m/s 900–1500 kg 1–4 h

15 m 6m 60–70 tonnes 25 knots Aluminium 12 1.5 m 12 m/s 500 kg 1–4 h

25 m 15 m 125 tonnes 15–18 knots Aluminium 12 3.5 m 12 m/s 3 tonnes 1–4 h

Table 1 presents generic data for these vessels, based on sources, such as [13–15]. Type 2 A gangway from the vessel is connected with the OWT structure. An example is the Ampelmann system with a Stewart platform placed on either a seagoing tug or an offshore supply vessel, with lengths varying from 25 to 75 m [16], illustrated in Table 2. It is found that the workability of the Ampelmann depends on the motions of the vessel, so the longer the vessel is, the better workability can be achieved. Type 3 There is no contact between the vessel and the OWT structure, but contact is made through additional facilities, for example, the personal transfer system (PTS), which is a radio controlled two-armed hydraulic boom. The vessel holds position close to the OWT structure with a safety distance of at least 5 m. Type 4 The vessel is used for crane and lifting operations, mostly occurring during installation, but can also be associated with maintenance of larger parts like a nacelle or blades. This type of vessel needs to get close to the OWT for the operation.

5. Hazard identification To identify hazards related to collision risk, it is necessary to know the typical operations of the service vessels. A general procedure for service vessel access is adapted from the RenewableUK guideline [18], and is shown in Fig. 1. The activities in Fig. 1 that may lead to collision impact are:  Service vessel approaches an OWT: J The service vessel fails to stop when it reaches the OWT and hits the OWT at high speed. J The vessel misjudges a turning or maneuvering, and hits the OWT at relatively low speed.  Service vessel remains alongside an OWT to perform a task related to the OWT (usually, to unload maintenance personnel and equipment from the vessel to the OWT, or vice versa): J The vessel loses power or the dynamic positioning system fails, and the vessel drifts into the OWT due to wind and waves. The impact speed depends on the weather and sea conditions. These operational activities give rise to the following categories of collision scenarios: 1. head-on collision, 2. maneuvering collision, 3. drifting collision. Each scenario has to be analyzed separately.

Table 2 The Ampelmann system on different vessels [17]. Specification

Vessel type Dimensions Displacement Max. sea state Workability

Anchor handling tug 24 m  10 m  2.75 m 120 tonnes Hs¼ 2.0 m 85% (S. North Sea)

Multi-purpose vessel 50 m  12 m  3.80 m 900 tonnes Hs ¼2.5 m 93% (S. North Sea)

Offshore support vessel 70 m  16 m  5.60 m 4000 tonnes Hs ¼3.0 m 97% (S. North Sea)

L. Dai et al. / Reliability Engineering and System Safety 109 (2013) 18–31

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Service is required. The access procedure is initiated.

Are current and forecast weather conditions suitable for access and transfer?

No The access operation is terminated.

Yes No

Voyage is planned (incl. weather conditions, site location, target OWTs, vessel routing).

Yes

Vessel sets sail and arrives in field.

Vessel leaves the current OWT.

Vessel approaches towards an OWT.

Do local weather conditions allow safe access from vessel to OWT?

Is service required for another OWT?

Personnel return to vessel from the OWT.

No

Yes

Vessel is maneuvered to a safe position.

Vessel remains in position during service on the OWT.

Personnel access the OWT using established procedures.

Vessel is moored with boat landing on the OWT.

Fig. 1. Flowchart of vessel access procedure to an OWT (adapted from [18]).

6. Collision probability Due to the lack of historical data, it is not feasible to estimate the probability of the hazardous events and/or the consequences of the collision scenarios from data alone. The best alternative is to use a Bayesian approach where the collision probability is interpreted as our degree of belief based on all available knowledge. As part of this approach, it is necessary to identify the risk-influencing factors (RIFs) and evaluate their effects on the hazardous events and/or the development of the collision

incident. In this paper, we propose a procedure where the estimation problem is broken down into six steps: 1. identify the direct causes of the hazardous event by a fault tree or event tree analysis, 2. provide initial data, 3. identify the relevant RIFs for the basic event probabilities of the fault tree, or the barrier failure probabilities in an event tree, 4. establish Bayesian networks with relevant RIFs,

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Collision happens when a service vessel approaches an OWT Head-on collision AND

Detection function of the navigational system on the vessel fails

The vessel is on a collision course

E1

AND

Watchkeeping on the vessel fails

Initiated recovery of the vessel fails

E2

E3

Fig. 2. Fault tree for the service vessel heading towards the OWT.

5. rank the importance of the RIFs, 6. compute the basic event probabilities and the hazardous event probability. qE3 6.1. Causal analysis The direct causes of a hazardous event are commonly identified and assessed by fault tree analysis; as illustrated by the simplified fault tree in Fig. 2, where a head-on collision (called the TOP event) occurs when all the three basic events E1, E2, and E3 occur. When the basic events in Fig. 2 are assumed to be independent, the probability Qhc of the TOP event per approach can be expressed as (e.g., see [10]) Q hc ¼ qE1  qE2  qE3

ð1Þ

where qEi is the probability of basic event i (for i ¼ 1,2,3). The basic events in Fig. 2 represent failures of the three barriers: B1: navigational system, B2: watch keeper, and B 3 : recovery action. If the number of visits to a specified OWT is nA per year and pA is the fraction of these approaches where the vessel is heading straight towards the OWT, the frequency fhc of head-on collisions with the specific OWT per year is f hc ¼ nA  pA  qE1  qE2  qE3

ð2Þ

The frequency of head-on collisions (2) is hence broken down into elements that can be assessed individually: nA The annual number of visits can be estimated based on the demand for maintenance and service of the OWT. pA The probability that the vessel will head straight to the OWT will depend on the procedures for the approach, e.g., if the vessel uses autopilot with the OWT as a way-point. qE1 Failure of the watchkeeping on the vessel is usually related to human and organizational factors, such as the watchkeeper being absorbed in other tasks, but can also be rooted in procedure deficiencies and affected by bad weather conditions. qE2 Failure of the navigation and control system of the vessel may be caused by a technical deficiency or lack of maintenance.

An initial estimate of qE2 may be determined by a reliability analysis of the navigation/control system. It may also be considered independent of time and as a representation of the overall operational standard of the vessel [19]. Failure of the initiated recovery of the vessel is related to how the vessel crews handle emergencies.

Fault tree analysis is a well established method for causal analysis, but has several limitations. The most important is its lack of ability to take the sequence in which the basic events may occur into account. When this sequence is important, event tree analysis may be a better choice. A simplified event tree related to a head-on collision is shown in Fig. 3. The sequence of events is started by the initiating event ‘‘service vessel is approaching the OWT’’. A head-on collision may be avoided by the three barriers B1, B2, and B3. Since one or more of the barriers may fail, we get different end events as shown in Fig. 3. A timeline is drawn beneath the event tree in Fig. 3 where the time available for carrying out the various actions can be indicated. The probabilities in an event tree are always conditional, depending on the events earlier in that particular event path and also on the time between events. The frequency of headon approaches to the OWT is nA  pA , and the total frequency of head-on collisions will be the same as (2) for the fault tree. The event tree, however, provides more information about the sequence of events and the time available, such that the estimation of the various elements may be more accurate. The two other categories of collisions may be analyzed in the same way. 6.2. Initial data Due to the lack of data from offshore wind farms, initial data may be collected for similar collision incidents in the offshore oil and gas industry. According to [20,9], collision frequencies vary with different oil and gas platforms. The frequency for collisions leading to moderate and severe damage is much higher for semisubmersibles than for fixed bottom-standing platforms. This may be due to the semi-submersibles moving in waves, leading to higher impact velocities, and more reported damage. OWTs far off

L. Dai et al. / Reliability Engineering and System Safety 109 (2013) 18–31

Barrier B1 Initiating event

Barrier B2

23

Barrier B3

Navigational system

Watchkeeping on the

fails

vessel fails

Initiated recovery of the vessel fails

End event

qE3 Yes

Head-on qE2

No

collision

qE1

Collision avoided

1-qE3

Collision avoided

1-qE2

Service vessel approaches the

Collision avoided

OWT 1-qE1

t1

t2

t3

Time

Fig. 3. Event tree for service vessel approaching the OWT.

the coast or in deep sea are likely to be floating, such as the Hywind concept [21]. Experience from current OWTs indicates that planned maintenance (expected 1–2 times per year) each takes 2–3 working days and corrective maintenance (expected 2–4 times a year) each takes 2–4 days [22]. This means that the maintenance personnel needs to be transported back and forth to the OWTs several times to finish up the work. Assuming that the number of visits per OWT needed for both planned and corrective maintenance is 3 times a year and that each maintenance job on the average takes 3 days, the total number of visits will be 9 times a year. Further, if the service vessel does not stay alongside the OWT during the maintenance job, the total number of approaches will be 18. The number of approaches is based on the assumption that all equipment for performing the maintenance job is transported along with the personnel. An initial estimate of the frequency for all types of collisions between service vessels and semi-submersible platforms is 1:56  103 per visit [20], or on the average one collision per 641 approaches. This means that the expected number of collisions per OWT according to Eq. (2) would be 2:8  102 per year (assuming that all approaches are head-on, i.e., pA ¼ 1). The expected number of collisions for a large offshore wind farm with 500 OWTs becomes 14 per year. According to [20], about 20% of collisions are on approach, and about 80% due to drifting, corresponding to about 3 collisions on arrival and maneuvering and 11 collisions due to drifting. Of the collisions occurring upon arrival of an oil and gas supply vessel most are of the maneuvering type, i.e., of low speed (between 0–6 knots or on average 0.3–2.8 m/s). Drifting collisions are due to the loss of power or dynamic positioning occurring at the same time as wind and waves move the vessel in the direction towards the OWT with typical speeds of 0.3–1.2 m/s (for a 40 m, 820 tonnes vessel). For these types of collisions, it is necessary to obtain failure data on power and engine loss, as well as knowledge on weather and sea state conditions. In addition, the geometry of the vessel greatly influences the impact velocities [20].

With respect to the failure of technical barriers, e.g., engine breakdown, a number of generic reliability databases are available. A list of some of these databases is provided on the webpage [23]. If a service vessel loses propulsion in a wind farm, there will only be a short time period available for restarting the machinery since there will be OWTs in ‘‘all’’ directions, increasing the probability of collision. Supply vessels approaching oil and gas platforms may drift away from the platform if they lose propulsion. This means that drifting collisions can be assumed to occur more frequently for OWTs than for oil and gas platforms. 6.3. Risk-influencing factors A risk-influencing factor (RIF) is an enduring condition that influences the occurrence of hazardous events and the performance of barriers [10]. For example, the performance of watchkeeping can be influenced by bad weather conditions, personnel competence and workload, and so on. It may be efficient to identify RIFs in specific categories, such as personal characteristics, task characteristics, characteristics of the technical system, administrative control, and organizational factors [24]. Then RIFs represent average conditions that can be improved by certain actions in specific aspects. Identifying RIFs facilitates assessment of conditions that influence the barriers or basic events and contributes to the estimation of probabilities. 6.4. Bayesian networks A large number of RIFs may influence the collision probability. The best approach to model these influences is using a Bayesian network [25–27]. As an example, a Bayesian network for the basic events in Fig. 2 is suggested in Fig. 4. The nodes represent RIFs, which are normally identified with expert judgment and literature review. Fig. 4 is based on input from [28,29,20]. These references mainly focus on the collision between (supply) vessels and offshore oil and gas installations, so the differences from offshore wind energy are discussed briefly.

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Bridge procedures Distracted by other tasks

Asleep

Physical properties of the target Time of the day

Alcohol

Poor bridge design

Illness

Blind angles

Absence from bridge Competence

Bad weather condition Insufficient lookout

Poor visibility

Watchkeeping on the vessel fails

Basic event E1

The vessel is on a collision course Detection function of the navigation system on the vessel fails

Basic event E2

Technical failure of equipment

Equipment not used

Equipment design

Competence Reliability of equipment

Technical condition of equipment

Workload/stress Fatigue

Maintenance of equipment

Humanmachine interface

Distracted by other tasks

System feedback Operational error

Absent from the bridge

Competence Lack of management procedures

Poor decision making

Performance impaired

Poor judgement

Head-on collision Poor communications

Familiarity

Initiated recovery of the vessel fails

Basic event E3

Bad safety culture/work culture

Competence

Bad weather condition

Equipment condition on the vessel

Time pressure

Insufficient manning

Workload/stress

Fig. 4. RIFs for E1, E2, E3.

Supply vessels and service vessels have limitations to weather conditions and operation. In offshore wind farms, service vessels should be assigned when the weather forecast predicts suitable access and transfer conditions (Fig. 1), for example in line with the maximum wave heights as listed in Tables 1 and 2 for different vessel types. The RIF bad weather condition, therefore, only has impact on the barriers if the weather changes during operation or if the vessel operator does not follow procedures. Operation of vessel is still to a large degree based on human– machine control. The human element plays the major role in most accidents involving modern vessels [30]. It is noticeable that the

identified RIFs include a lot of human and organizational factors (Fig. 4). However, it could be expected that the crew on the service vessels have less possibility of drinking alcohol, using drugs, and being asleep than crew sailing with cargo ships, due to shorter operation time. 6.5. Importance of RIFs In a Bayesian network, the influences of the RIFs are given as conditional probability tables. Specific data related to Fig. 4 is hard to obtain for visiting vessels. For passing vessels on collision

L. Dai et al. / Reliability Engineering and System Safety 109 (2013) 18–31

1.2

700

1 Failure strain [-]

Stress [MPa]

Measurements Trendline

1.1

600

25

500 400 300 200

0.9 0.8 0.7 0.6 0.5 0.4

100 0

0.3 0.2 0

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Strain [-]

0

50 100 150 Element length [mm]

200

Fig. 5. (a) Element-length dependent material relation. (b) Corresponding failure strain versus element length.

course with oil and gas installations, when the operational visibility is good, the watchkeeping failure rate without recovery for a vessel is 7:6  103 [20] (roughly corresponding to basic events E2 and E3). However, for visiting vessels, this failure rate should be lower since the vessel operator is more concentrated on the approach to an OWT. An initial estimate of E1 can be determined by reliability analysis of the vessel navigation and control system. To show the influence of RIFs on the basic events or the hazardous events, the RIFs can be ranked according to the conditional probabilities. Three methods are used in [26] for analyzing the influence of Bayesian network model variables (RIFs) on ship collision probability in the Gulf of Finland. It is found that the effect of a variable (RIF) with a path to the ‘‘collision’’ variable typically decreases when the path between them increases. 6.6. Probability estimates To calculate the probability estimates, several approaches have been proposed—although for different applications. The three most relevant approaches are:

relevant for only one of them. This step involves to indicate the relevance and the status of each RIF for each of the two application by a score (e.g., on a five-step scale). 3. Weighing the contribution of the RIFs—This involves to weigh the importance of each RIF relative to the collision probability for each of the two applications. 4. Establishing the collision frequency—This step combines the relevance, the score, and the weight of each RIF in order to obtain a scaling factor that is used to adjust the (known) collision probability for supply vessels in the offshore oil and gas industry, to an estimate of the collision probability between a service vessel and an OWT. The scoring and weighing procedure is similar to [32,31]. All the steps will involve expert judgments, and be supported by a careful comparison between the two applications and recorded collision data from collisions between supply vessels and offshore platforms. When the operational experience from offshore wind farms becomes available, the initial estimates of collision probability can be updated by, for example, a Bayesian procedure [34].

7. Assessment of collision consequences

 Barrier and operational risk analysis (BORA) [31] developed for

 

the Norwegian oil and gas industry. The BORA approach is concerned with the frequency of gas leaks in offshore process system and focuses mainly on human and organizational factors. Failure rate evaluation with influencing factors [32] describes an approach that is similar to BORA, but mainly concerned with failure rates of technical equipment. Unified partial method (UPM) has some similarities with the two first approaches but is concerned with the fraction b of common-cause failures in a technical system [33].

To provide probability estimates involves several steps. A detailed justification and description of each step would require a separate article and is outside the scope of this paper. The approach chosen is, however, in line with the one proposed by Brissaud et al. [32]. The main steps are: 1. Selection of relevant RIFs—This involves to identify and select the relevant RIFs related to service vessels for an OWT and for similar vessels for offshore oil and gas installations. 2. Scoring the effects of each RIF—The effects of the RIFs may be different for the two applications and some RIFs may be

The possible consequences resulting from collisions between service vessels and OWTs include environmental impacts, economic losses, and personnel injuries/fatalities. They are all dependent on the severity of the structural damage to the OWTs and the service vessels. Structural damage can be analyzed based on the principle of energy conservation. The basic formula for calculating the total collision energy E (J) is: E¼

1  a  m  v2vessel 2

ð3Þ

where m is the vessel displacement (kg), a is the added mass coefficient (which is assumed as 1.4 for sideways collision and 1.1 for bow or stern collision) [35], and vvessel is the impact speed (m/s). 7.1. The collision impact approach The choice of collision strength assessment methods for internal mechanics is commonly the non-linear finite element method [36]. However, care has to be taken to enable the finite element method to predict the collision strength to fracture physically correct and accurately. Therefore, this paper utilizes

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Fig. 6. FE-model overview incl. main dimensions and boundary conditions.

a reliable method [37] to predict the energy absorbed until fracture. Reliability of the impact simulation is achieved, because a consistent link between the local material measurements and the discretized finite element model is obtained on the basis of optical measurements [37,38]. This element length-dependent material relationship for the Norske Veritas Grade A (NVA) steel is a commonly used shipbuilding steel and it is assumed to represent the material behavior of the monopile, because the exact material relationship is unknown. The elastic modulus is 206 GPa, the Poisson ratio is 0.3 and the measured yield stress is 349 MPa. The measured failure strain and element length relationship is implemented in the ANSYS parametric design language model generation via material 24 of LS-DYNA (Fig. 5) [39]. Thereby, the possibility of failing elements, which reach the critical strain, can be observed. The collision impact approach in this paper is thus carried out in two main steps: 1. Quasi-static simulation is used to obtain the basic structural behavior of the monopile. The energy absorption capacity of the monopile is assessed when the service vessel is assumed to be rigid and moves along a pre-defined straight penetration path. This assumption is well justified, because the crashworthiness of the monopile is of interest and not the crashworthiness of the service vessel. Hence, from a design point of view this quasi-static simulation approach will result in the maximum energy, respectively, force versus indentation curve, for the defined scenario in a conservative manner. The solver LS-DYNA version 971 is used for the impact simulations. The ANSYS parametric design language is used to build the finite element model for the monopile, as demonstrated in Fig. 6, and the service vessel. The main dimensions, boundary conditions and the characteristic element lengths, Lelement , are given therein. The structure is modeled using primarily four noded, quadrilateral Belytschko-Lin-Tsay shell elements with five integration points through their thickness. The characteristic element-length in the contact region is 24 mm to account for the non-linear structural deformations, such as buckling and folding. Standard LS-DYNA hourglass control and automatic single surface contact (friction coefficient of 0.3) is used for the simulation [39]. The impact simulations are displacementcontrolled. The service vessel is moved into the monopile at a constant velocity, which is slow enough not to cause inertia

Fig. 7. Representative scenarios for simulation.

effects resulting from the vessels’ masses, to obtain the characteristic structural resistance against impact loading for the monopile. 2. Critical collision scenarios are identified based on the energy absorption capacity of the monopile obtained in step 1. These are discussed in the next subsection. 7.2. The results Numerical simulations for seven collision scenarios with a service vessel and a monopile with a boat landing structure have been carried out. The vessel Smit Bronco has been approved as an option for the Ampelmann system [16]. Therefore, the Smit Bronco is a Type 2 service vessel as categorized in Section 4, and is selected for the simulation. The displacement of the Smit Bronco is 230 tonnes, and the overall length and beam are 25.8 m and 10.05 m, respectively. To show the shape of the Smit Bronco, a few illustrations are extracted from the producer and included in the Appendix. The OWT specifications are as shown in Fig. 6. The simulation results are used for analyzing the criticality of different collision scenarios, with respect to the collision location on the OWT structure, as exemplified in Scenario 1–7 (Fig. 7). These scenarios are chosen, because they cover a wide range of possible collision scenarios (head-on, maneuvering, and drifting), which are assumed to be most relevant for the OWT service operations. More specifically, the scenarios are:

 Scenario 1: The service vessel collides with the monopile structure head-on.

 Scenario 2: The service vessel collides with the boat landing structure head-on.

 Scenario 3: The service vessel goes straight forward towards the OWT, but the bow collides with a part of the boat landing structure.

L. Dai et al. / Reliability Engineering and System Safety 109 (2013) 18–31

x 10

14

27

6 Local yield

Global yield

12 Scenario 1

Force (N)

10

8

6

Scenario 3 Scenario 5 Scenario 2 Scenario 7

4

Scenario 4 Scenario 6

2

0 0

0.2

0.4

0.6 Displacement (m)

0.8

1

Fig. 8. Simulation results—the relationship between displacement and force.

7

x 105 Local yield

Global yield

6 Scenario 1

Energy (J)

5 4 Scenario 5 3

Scenario 2 Scenario 7

2 Scenario 3 Scenario 4 Scenario 6

1

0

0

0.2

0.4

0.6 Displacement (m)

0.8

1

Fig. 9. Simulation results—the relationship between displacement and energy.

 Scenario 4: The sharp edge of the vessels bow collides with a   

part of the boat landing structure. Scenario 5: The vessel stern collides with the monopile structure when the service vessel leaves the OWT. Scenario 6: The stern of the vessel collides with the monopile structure when alongside the OWT. Scenario 7: The vessel collides with the monopile structure midships when alongside the OWT.

Figs. 8 and 9 show the relationship between the intrusion of the service vessel into the OWT structure, respectively, displacement (D), and force (F), and the relationship between displacement (D) and energy (E), respectively. For each scenario, two critical values of displacement are identified based on the

numerical results. One is the value of local yield, which causes limited deformation on the structure and is found at a limited number of finite elements only, for example, the boat landing structure in Scenario 2–4. Hence, local yield represents a permanent structural deformation at a very small area, which may be compensated by the residual capacity of the surrounding elements. The other value is the global yield, which leads to more than local plastic strain but a spread of deformation on a larger area of the structure, which cannot be compensated by the surrounding elements. In this case, the monopile may lost its structural integrity. Correspondingly, the relevant parameters for the critical displacements, including force, energy, and vessel speed, are listed in Table 3. The speed values are calculated according to Eq. (3), and specified as the critical speed.

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L. Dai et al. / Reliability Engineering and System Safety 109 (2013) 18–31

Table 3 Simulation results. Local yield

Scenario Scenario Scenario Scenario Scenario Scenario Scenario

1 2 3 4 5 6 7

Global yield

Displacement (m)

Force (MN)

Energy (kJ)

Speed (m/s)

Displacement (m)

Force (MN)

Energy (kJ)

Speed (m/s)

0.09 0.25 0.20 0.25 0.15 0.25 0.25

1982.38 1593.11 828.51 665.86 1130.43 536.66 1055.31

14.42 28.86 11.59 12.02 10.45 9.38 20.14

0.34 0.48 0.30 0.31 0.29 0.24 0.35

0.19 0.50 0.35 0.45 0.3 0.45 0.45

2801.96 3686.07 1134.63 1276.78 2491.33 999.45 2394.76

38.76 88.31 25.98 29.70 37.70 24.54 52.37

0.55 0.84 0.45 0.48 0.55 0.39 0.57

1.4 Local yield

Global yield

1.2 1 Speed (m/s)

125 tons vessel

0.8 230 tons vessel

0.6 0.4 900 tons vessel

0.2 0

0

1

2

3

4

5 Energy (J)

6

7

8

9 x 104

Fig. 10. Comparison on vessel mass and critical speed for certain impact energy.

According to the simulation results, the OWT structure responds with the highest reaction force when the service vessel directly collides with it (i.e., Scenario 1 and 5 in Fig. 8). As a result, this reaction force causes limited deformation on the monopile, with the displacement of 0.09 m and 0.15 m in Scenario 1 and 5, respectively. In the other scenarios, the service vessel first collides and causes deformation of the boat landing structure. With less strength than the monopile, the boat landing structure is deformed by smaller force, but with bigger displacement of 0.20 m or 0.25 m. To discuss the critical scenarios in another way, the values in Table 3 can be considered as the limits to avoid structural deformations. Consequently, Scenario 6 is the most critical. If the service vessel is at a speed of more than 0.24 m/s at the time of the collision, the structure is damaged. In this way, we can rank the different scenarios, for example, Scenario 6–3–4–5–1–7–2 with respect to the loss of the monopile (i.e., the global yield). Furthermore, because it is likely that these scenarios occur during daily operations, it is worthy to note that the speed in any of the seven scenarios is quite low, ranging from 0.24 m/s to 0.48 m/s for the local yield and from 0.39 m/s to 0.84 m/s for the global yield. The operation speed of the reference vessel type is around 5.66 m/s (11 knots), which is significantly higher than the critical speed identified and will thus result in major damage of the OWT. According to Eq. (3), the vessel mass is inversely proportional to the square of the vessel speed. Thus, assuming that the energy value from the simulation results is the limit of the OWT structures, service vessels with less mass can have higher critical

speed. Fig. 10 shows the critical speeds for service vessels of 125 tonnes, 230 tonnes, and 900 tonnes, with respect to certain impact energy. Taking a SWATH as an example, its mass is 125 tonnes. The critical speed in the seven scenarios ranges from 0.37 m/s to 0.65 m/s for the local yield and from 0.60 m/s to 1.13 m/s for the global yield. However, these speeds are still quite low compared to the operation speed of a SWATH, which is 15–18 knots. Therefore, besides paying enough attention during operation, additional measures to mitigate the collision consequences are necessary. Hence, calculating the energy according to Eq. (3) results in a conservative estimation of the energy available for structural deformations, because it neglects eventual vessel motions being excited as a result of the impact. The influence of dynamic effects from the rotor-nacelle mass that may occur during the collision can be incorporated into the presented procedure in the further work.

8. Risk evaluation and risk reduction measures Risk is usually measured and evaluated by the combination of probability and consequence. According to the simulation results, the OWT structure is damaged even when the vessel speed is low. Damage to the boat landing structure or the OWT support structure are costly to repair offshore. In addition, the collisions may lead to loss of human lives if, for example, the service vessel sinks after collision. Risk reduction measures can be grouped into two main categories: probability reducing (proactive) measures

L. Dai et al. / Reliability Engineering and System Safety 109 (2013) 18–31

and consequence mitigation (reactive) measures. With respect to the risk of collision between service vessels and OWTs, the following risk mitigating aspects can be considered:

 OWT structure vulnerability, personnel access and vessel







design. In the development of OWTs, limit state design is used to achieve the prescribed level of safety [40]. Accidental limit states (ALS), in particular, relate to the structural damage caused by accidental loads, such as vessel impacts [3]. There is no standard ALS value or maximum size for the service vessel. The Federal Environmental Agency in Germany proposes a single hull oil-tanker of 160,000 dwt as the design vessel for ALS in the event of total structural failure of an OWT [2]. The ship of this size would not be reasonably expected to be the service vessel involved in a visiting collision with an OWT. In particular, when an offshore wind farm is situated far away from shipping lanes, it may not be necessary to select such a large ship as the design criterion. The simulation results in Section 6 show how much energy the OWT structures can absorb before being damaged for the various scenarios. We may take the conservative one into the design consideration. For example, choosing scenario 2, the global yield occurs when the collision energy reaches 88.31 kJ. If the OWT structures are able to absorb this energy, none of the seven collision scenarios can lead to OWT damage. The choice of vessel size and access system will also impact the risk of visiting collisions. A boat landing structure increases the distance from the service vessel to the OWT and reduces the probability of direct contact and wear between vessel and OWT structure. Vessel capability and manning; crew competence. It is important to ensure that the service vessel crew is capable of executing the work tasks, assessing the field conditions, and for handling severe weather conditions. The environmental conditions should be watched during operation for changes in seastates, wind speed and direction, and so on. The reliability of navigation systems, propulsion systems and control systems should be maintained. It is preferable to have adequate reserve power and sufficient redundancy of these technical systems. In addition, the technical systems can be developed to decrease the effect of human factors in accident causation. Procedures and checklists. In the offshore oil and gas industry, to avoid head-on collisions when a service vessel approaches towards an installation, the vessel usually set the course slightly off the installation [41]. Another risk reduction measure is to establish a safety zone around the OWT with maximum vessel speed. Operational procedures with respect to weather conditions are important to implement. Maintenance strategies. New concepts for maintenance of OWT have to be developed [42]. Large wind farms will be very costly to maintain if





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onshore maintenance concepts are transferred directly to offshore wind farms, for example, due to the very many maintenance visits then needed. In addition to cost reduction, keeping the number of visits to the OWT at a very minimum obviously reduces risk. Contingency plans. Damage to the service vessel from collision is not included in the simulations. However, emergency procedures should be established to guarantee personnel safety. Appropriate facilities and procedures should be in place for evacuation and rescue of personnel. Reporting system, and follow-up analysis. In order to assess the risk of collision and to implement effective controls, a reporting system should be established in the offshore wind energy industry, for recording and followup of incidents and near misses, including visiting collisions. This system can also identify trends and allow further controls to be implemented.

9. Conclusion The offshore wind energy industry continues to grow fast and into more exposed areas which means that the safety of personnel and the structural integrity of the OWTs become more demanding issues. The development into more remote locations and deeper waters may require larger service vessels, increasing the potential impact energy and resultant severity of collisions with OWT structures. To investigate the risk of collision between service vessels and OWTs, the current paper proposes a specific risk analysis framework with relevant analysis methods. Without sufficient incident/accident records in the offshore wind energy industry, the probability analysis in this paper emphasizes extrapolating data and information from similar operations in the offshore oil and gas industry, and updating the probability estimations as more data becomes available. In the paper, collision consequences are analyzed based on numerical simulations of seven possible collision scenarios. A 230-tonne service vessel and an OWT with monopile structure were selected for the simulations. The results show the response of the OWT structures from collision with the service vessel. Critical values of force and energy are identified for structural damage in each scenario. Based on the collision energy equation, the critical vessel speeds in most scenarios are found to be quite low. Therefore, risk reducing measures are essential. Suggestions of risk reducing measures are proposed in five aspects, which cover the design requirements to OWT structures, vessels, and means for access, personnel competence, operation procedures, maintenance strategies, contingency plans, and data collection and recording. The measures are suggested as input to the design of future offshore wind farms and as basis for developing new and updating existing standards, guidelines, and operational procedures.

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Appendix A. General plan Smit Bronco

Extracted from SMIT website: http://www.smit.com/sitefac tor/public/Extras/Brochures/Leaflet_Smit_Bronco_July_2010.pdf.

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