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IRIS FP7-NMP-2007-LARGE-1

IRIS WP6 Technology Report page 1 of 19

D6 DELIVERABLE

PROJECT INFORMATION:

Project Title: INTEGRATED EUROPEAN INDUSTRIAL RISK

REDUCTION SYSTEM

Acronym: IRIS Contract N°: CP-IP 213968-2 Project N°: FP7-NMP-2007-LARGE-1

Project Start: 01 October 2008 Project End: 31 March 2012

REPORT INFORMATION:

Report Title: WP6 TECHNOLOGY REPORT, THE IRIS RISK PARADIGM

Date of Issue: 8 September 2009

Rep. Period: 01 October 2008 – 30 September 2009

Prepared by: Aristotle University of Thessaloniki

Author: Demos Angelides

coordinating person:

organisation:

e-mail:

fax:

telephone:

Dr. Helmut Wenzel

VCE Holding GmbH

[email protected]

+43-1-893 86 71

+43-1-897 53 39



1 Table of Contents

1 Table of Contents ..................................................................................................................... 2

2 DEVELOPMENT OF A NEW RISK PARADIGM: CONCEPT – APPROACH –

REQUIREMENTS – OUTCOME.............................................................................................. 3

2.1 INTRODUCTION .............................................................................................................. 3

2.2 CONCEPT OF THE RISK PARADIGM ............................................................................ 3

2.3 METHODOLOGY APPROACH FOR THE DEVELOPMENT OF THE RISK

PARADIGM....................................................................................................................... 5

2.4 REQUIREMENTS FOR THE DEVELOPMENT OF THE RISK PARADIGM.................. 10

2.4.1 THE OFFSHORE WIND TURBINE SYSTEM CASE STUDY ........................... 13

2.5 PLANNING FOR THE DEVELOPMENT OF THE RISK PARADIGM ............................ 19



2 DEVELOPMENT OF A NEW RISK PARADIGM: CONCEPT –

APPROACH – REQUIREMENTS – OUTCOME

Demos Angelides

Professor of Marine Structures, Department of Civil Engineering, School of Engineering, Aristotle

University of Thessaloniki, Thessaloniki, Greece

2.1 INTRODUCTION

Risk management approaches currently adopted in the European industries differ because of various

reasons. This represents a roadblock in the establishment of an Integrated European Industrial Risk

Reduction System that would allow for: a) greater synergies between the industries, b) reduction of

the production-cost of the European industrial product, and c) advanced safety conditions and

standards for production, maintenance and use of the industrial product. The overcoming of the

abovementioned fragmentation and the consequent constraints is the main goal of the IRIS project.

A core part of this project is the development of a new risk paradigm that will constitute the platform for

the integration between the various risk management approaches of all project partners in the

IRIS project. This paradigm shall be standardized and, therefore, become a best practice framework to

manage risks from risk identification to response to risk for the European industry. The development of

this paradigm is the outcome of the WP6, a work package assigned to a research group headed by

Professor Demos Angelides who is the scientific coordinator of the research team from the Aristotle

University of Thessaloniki, Greece.

This report aims at:

1. Highlighting the critical outcome of the WP6 content,

2. Presenting, in brief, the approach of implementation and the related requirements, and

3. Presenting the next steps of development of the main WP6 outcomes.

All these are explicitly presented in the following sections.

2.2 CONCEPT OF THE RISK PARADIGM

The paradigm as an overall end product shall be a comprehensive framework acting as an interface

that will allow the processing of risk management by the use of several interconnected tools. Therefore

it shall comprise various sub-products, all developed in the WP6 with the synergy of all project

partners. The sub-products are:

1. Risk Identification Methodology (RIM). The methodology shall introduce a systematic way to

identify risk factors (i.e., contributors to risk), risk components and attributes (i.e., constituents and

exhibitors of risks) and risk occurrence mechanisms (i.e., modes of risk occurrence). This

methodology shall be of the appropriate structure to be applicable in various industries and cases



of applications. Therefore, the paradigm upon application shall become the common approach for

European industries to perceive and identify risks.

2. Risk Inventory (RI). The inventory shall include generally applied in all industries risks of different

nature (e.g. technical, financial, legal, etc.). This shall facilitate the risk analysis in practice because

it will minimize the extent of the risk identification process for the risk analyst. Specifically, a readily

available for the risk analyst list of generally applied risks in all cases shall allow the analyst to

focus only on the identification of the case-specific risks. The RI shall constitute a generally applied

list of risks for all European industries that will set a minimum level of risk management require-

ments in European industrial processes and products.

3. Risk Assessment Tool (RAT). The tool shall quantify and rank in terms of significance the risks

identified after analyzing the input through appropriate algorithms. These algorithms shall provide

with results ready-to-use for risk communication and decision-making (an example of a type of

results is a threshold for early warning systems). The tool shall address the elaboration of data and

information drawn through a real-time monitoring and control system to allow for a dynamic risk

analysis, i.e. a real-time assessment and response to risks. The tool shall become the common

instrument for European industries to assess risks and produce results to decide upon various

performance quantifications, including expected operation conditions, reliability or life-cycle cost,

etc.

4. Risk Monitoring and Control System (RIMOCOS). As already mentioned, the RAT sub-product

shall allow a dynamic risk analysis. To achieve that, a prototype of a risk monitoring and control

system is timely required. RIMOCOS is the sub-product that shall respond to this requirement. This

system shall be defined in terms of: a) elements (e.g. what is monitored), b) devices (e.g. types of

sensors), c) networking (e.g. plan of sensors arrangements) and d) methodology for combined

analysis of data from networking of sensors. This integrated system shall: a) broaden the level and

enhance the quality of conclusions of risk monitoring and control of several industries and b) allow

for refinement of existing devices to extend their field of application.

5. Risk Prevention and Mitigation Strategy (RIPREMIS). The strategy shall be tailored to the

output of RAT and RIMOCOS sub-products to achieve compliance with real situations and best

relate to performance requirements. In this way, the European industry shall adopt a risk preven-

tion and mitigation strategy that is not static but, instead, responds to specific risk-based perform-

ance requirements.

6. Risk Management Standard for the European industry (RMS). The standard shall describe

comprehensively and explicitly the risk paradigm in a manner of best practice of application for the

European industries. The standard shall intend to constitute the specifications for managing risks

in the European industry; the credit for the project partners as developers of such a standard will

be significant.

The abovementioned sub-products along with other potential sub-products that may be essential for

the development of the risk paradigm (e.g. databases and knowledge bases, etc.) shall be developed

in the framework of WP6 and shall be compatible to the products of other WPs (e.g. the Decision

Support System from WP7 and the Database from WP8) to allow integration in the context of the IRIS

project. The WP6 leading organization (Aristotle University of Thessaloniki - AUTh) addresses all the



required expertise in Risk Management and Information Technology (IT) to develop all the necessary

sub-products that will form the risk paradigm.

2.3 METHODOLOGY APPROACH FOR THE DEVELOPMENT OF THE RISK PARADIGM

A graphical outline of the Risk Paradigm is shown in Figure 1. From this presentation it is easy to

identify three different stages for the development of the final outcome:

Figure 1. Graphical outline of the Risk Paradigm

1. The first stage comprises the development of the first two sub-products, namely the RIM sub-

product and the RI sub-product. At this stage, the main sources of knowledge and information for

the development of both sub-products will be: a) the input from project partners, b) the review of

the respective literature from the WP6 team, and c) the analysis of specific case studies from the

industries. To facilitate the investigation of risk management practices an appropriate question-

naire that has already been developed in the context of WP6 may be completed by recipients both

inside and outside the IRIS project team. The methodology approach at this stage is rather

generic, since it is based on review and analysis of the state of the art in risk management in the

European industry without any reference to specific cases of application.

2. The second stage comprises the development of the three next sub-products, namely the RAT

sub-product, the RIPREMIS sub-product, and the RIMOCOS sub-product. At this stage, the

approach becomes rather case based, in order to achieve the modeling, validation and fine-tuning

of these sub-products in relation to real problems. This shifting in the methodology approach from

generic and theory-based to a more practical and case-based is essential since the Risk Paradigm

is oriented for industrial use and therefore its development is expected to be based on real

industrial problems. The development of the appropriate case studies is a core task of the WP6

and more detail on that issue is provided in the section 2.4.

3. The third stage comprises the integration of the developed in the previous stage sub-products to

the Risk Paradigm and the standardization of it (RMS sub-product). This is the last stage where



practically the final outcomes are presented after having been validated and tested. At this stage,

the approach is rather technical since the objective is to develop and present the final tool and a

standard based on the methodology of use of this tool.

Figure 2 provides a more advanced and detailed first approach to the Risk Paradigm’s architecture that

the graphical outline presented in Figure 1.

Figure 2. Risk Paradigm’s architecture (F: Factors, C: Components, A: Attributes, UI: User Interface)

As shown in this figure there is a very close synergy between the several tools (sub-products) that

comprise the Risk Paradigm, which is continuous and cyclical, in the same way that risk management

processes must be conducted in any real case. This architecture allows for a dynamic upgrade through

time of the Risk Paradigm, because it enables the update of core tools such as the RAT, the RI, the

RIMOCOS and the RIPREMIS. This update is achieved by: a) the knowledge and information

produced in the RIMOCOS tool through the elaboration of new data collected from a system of sensors

and other monitoring devices and b) the operation of an ontology server that is a core part of the Risk

Paradigm for the integration of the sub-products. A rough graphical presentation of the architecture of

the ontology server is presented in Figure 3.

The ontology server shall be consisted of:

• Domain Ontologies that shall store domain specific concepts and properties for each type of

industry and case study,

• A Reasoner to infer subsumed knowledge from the ontologies,

• A Risk Core Ontology to store risk concepts and properties for the risk assessment problem, and

• An Interface that will serve as the mediator between the reasoner and the rest of the system’s

components for querying purposes.



Figure 3. Ontology server’s architecture

While the ontology server provides the basis for the integration of the Risk Paradigm’s various tools,

the heart of the system is the RAT, which receives all the input and returns with the assessments of

specific risks per case, thus facilitating the risk response decisions. Figure 4 presents an outline of the

operation of RAT.

Values for

Risk F.C.A.Risk

Assessment

Risk Assessment Tool

Industry data

Meta Reasoner

Risk Identification

Methodology

Risk Management

Standard

Case Based Reasoner

DB (Past Cases)

Model Based Reasoner

KB (Risk Assessment

Models)

Values for

Risk F.C.A.Risk

Assessment

Risk Assessment Tool

Industry dataIndustry data

Meta Reasoner

Meta Reasoner

Risk Identification

Methodology

Risk Management

Standard

Case Based Reasoner

DB (Past Cases)

Model Based Reasoner

KB (Risk Assessment

Models)

Figure 4. A graphical outline of the operation of the Risk Assessment Tool

As presented in Figure 4, the RAT shall be theoretically based on the RIM tool and shall comply with

the specifications set in the RMS tool. The RIM tool shall provide a solid approach for defining and

identifying risks, while on the other hand, the RMS tool shall describe comprehensively and explicitly

the Risk Paradigm in a manner of best practice of application for the European industries.



While these sub-products offer the overall framework of operation, the key input shall be the values for

the variables (e.g. Factors, Components, and Attributes) that describe each specific risk and the

relative data from the industry. The components of the RAT that will store and elaborate all the

incoming data and information will be “Case Based Reasoner”, “Model Based Reasoner”, and “Meta

Reasoner”:

• A Meta Reasoner (MR) or decision support system that will enable the automatic selection of the

most appropriate reasoner between a Case Based Reasoner and a Model Based Reasoner for

each specific case of application. This selection will be achieved based on the industry data that

will be provided as input by the user.

• Case Based Reasoner (CBR) that will enable the detection of risks and their assessment through

the examination of existing similar cases to a specific case of application. CBR shall allow the

matching of the incoming data and information with the respective data and information of already

stored cases in a data base connected to the reasoner. The main components of the CBR will be

(see Figure 5):

a. The Interface that will receive the values for the various risk factors, components and

attributes and will transform them in a concrete structure (new case).

b. The Matching System that will query the database in order to find records (cases) with

similar values in the appropriate fields (i.e., risk factors, components and attributes).

c. The Filter that will filter out a number of similar cases, based on various criteria.

d. The Aggregator that will calculate the value of the risk based on the stored values of the

selected past cases.

CBR will apply in cases where there will be plenty of available data and information from which,

however, it will be difficult for various reasons to analyze them by the use of models.

CASE BASED REASONERCASE BASED REASONER

DB (Past Cases)

New CaseValues for

Risk F.C.A.

Matching

System

INTERFACE

Filter

Nearest Cases

AGGREGATOR

Risk

AssesmentIndustry data

CASE BASED REASONERCASE BASED REASONERCASE BASED REASONERCASE BASED REASONER

DB (Past Cases)

New CaseValues for

Risk F.C.A.

Matching

System

INTERFACE

Filter

Nearest Cases

AGGREGATOR

Risk

AssesmentIndustry dataIndustry data

Figure 5. A graphical outline of the operation of the Case Based Reasoner

• Model Based Reasoner (MBR) that will enable the detection of risks and their assessment

through the analysis provided by certain knowledge models integrated within RAT. These models

may be stored in knowledge bases and shall be able to allow the handling of knowledge from

different sources and of different nature. Therefore, several types of models are required including:



a) mathematical models (e.g. Matlab, Mathematica) to handle analytic scientific knowledge

expressed through mathematical equations, b) expert models (e.g. CLIPS, CLIPS-OWL, JESS,

JENA) to handle heuristic knowledge expressed through rules, frames, etc., and c) machine

learning models (e.g. WEKA) to handle knowledge induced from past data expressed through

neural networks, decision trees, etc. The main components of the MBR will be (see Figure 6):

a. The Interface that will receive the values for the various risk factors, components and

attributes and will formulate a new incident for further analysis.

b. The Model Wrapper that will select the appropriate model simulator according to the case

of application and will homogenize the results.

c. The Model Simulator that will apply the modeli on the data from the specific case of appli-

cation.

The MBR will apply in cases where the available data and information will be appropriate for

analysis through the various available models.

MODEL BASED REASONERMODEL BASED REASONER

New IncidentValues for

Risk F.C.A.

INTERFACE

Risk

Assessment

KB

Model

Simulator

Industry data

MODEL BASED REASONERMODEL BASED REASONERMODEL BASED REASONERMODEL BASED REASONER

New IncidentValues for

Risk F.C.A.

INTERFACE

Risk

Assessment

KB

Model

Simulator

Industry data

Figure 6. A graphical outline of the operation of the Model Based Reasoner

The RIMOCOS and the RIPREMIS tools will be modeled, tested and validated on the same case

studies that will be used for the development of the RAT. This is necessary in order to facilitate the

integration between these tools, which is the objective towards the development of the Risk Paradigm.

The RIMOCOS tool will exploit the RAT results to determine those key risk variables that when

monitored will provide with timely input for new estimations of risks. The RIMOCOS tool will also

identify how these variables can be monitored, incorporate the risk monitoring networks in RAT and

then use RAT to assess the performance and optimize the monitoring network characteristics. The

RIPREMIS tool will exploit the results from the RAT and the RIMOCOS tool to: a) determine both the

key risk variables and the strategies that can be developed to influence these variables, and b) assess

the impact of the risk factors and select the optimal response strategy to each one of them.

The same sources of knowledge and information as in the case of the RIM tool – i.e. input from project

partners and review of the literature and current practices – shall be explored for modeling purposes.



RIMOCOS shall be replaceable upon completion of the respective products of WP7 to achieve

integration in the context of the IRIS project.

2.4 REQUIREMENTS FOR THE DEVELOPMENT OF THE RISK PARADIGM

The implementation of the methodology approach mentioned in section 2.3 requires certain synergies

and input for the development of the several sub-products and the Risk Paradigm. Tables 1- 7 present

in brief those requirements in association with the respective inputs and outputs for each step of the

development process.

Table 1. Inputs, outputs and requirements for the development of the RIM tool

INPUT INPUT REQUIREMENTS OUTPUT OUTPUT REQUIREMENTS

Literature

review Books, Papers, Reports

Data base to include risk

factors, components and

attributes

Feedback from

the industry

Reports, Case studies,

Methods

Information management

framework that will re-structure

and consolidate data to obtain

homogeneity and facilitate

integrated management

Case studies

analysis Case studies, Reports

Risk Identification

Methodology (RIM)

Data mining algorithms and

ontologies to identify new

knowledge on risk occurrence

mechanisms through data

exploitation

Table 2. Inputs, outputs and requirements for the development of the RI tool


Literature

review Books, Papers, Reports

Feedback from

the industry


Methods

Case studies

analysis Case studies, Reports

Risk Inventory (RI)

Data base that will store the

industry risks

Table 3. Inputs, outputs and requirements for the development of the RAT tool


Risk

assessment

tools and

techniques


Literature review

Risk Assessment

Tool (RAT)

Tool architecture that will

include:

a) determination of key

variables and their

interdependencies,

b) incorporation of

assumptions and modelling of

parameters, and

c) design of the tool’s



mechanisms and algorithms of

receiving inputs, performing

the risk evaluation and

delivering outputs

Risk Variables

from the Risk

Inventory

Knowledge base Algorithms

Case studies

All necessary items to

define the case study’s

parameters (e.g.

meteorological data,

spatial conditions,

materials, operation

specifications, etc.).

Numerical models (e.g.

FAST, FLOW-3D, WAMIT

(with ANSYS or

MICROSAS and

MOORSIM), etc)

Machine-learning techniques

Risk and

performance

evaluation

models

Numerical models (e.g.

MULTISIM)

Risk

assessments

from the

RIMOCOS

RIMOCOS

Software programming

Table 4. Inputs, outputs and requirements for the development of the RIMOCOS tool


Elements of

Monitoring

Results drawn from RI,

RAT

Identification of

appropriate types of

monitoring devices (e.g.

sensors, transducers,

cables, etc.)

Existing real-time

monitoring devices

Selection of the appropriate: (i)

monitoring devices (i.e.

sensors),

(ii) sensor configuration and (iii)

network design depending on

type, accuracy, location,

frequency of data required, and

on critical conditions to be

measured

Monitoring

Equipment

Available GIS applications

Results

integration

models

Appropriate algorithms

(Kriging, splines, time

series, etc.)

Networking Current digital or audio

signals processing

methodologies

(verification/calibration and

Risk Monitoring

and Control System

(RIMOCOS)

Selection of the appropriate

approach/method for data

processing



integration methodologies)

Image processing

Type of networks (e.g.

wireless)

Results of network of

monitoring devices

Table 5. Inputs, outputs and requirements for the development of the RIPREMIS tool


Industry input on risk

prevention and mitigation

requirements

Existing Risk

Prevention

and Mitigation

Requirements Literature review

Industry input on risk


strategies

Reports over existing risk


practices

Existing Risk

Prevention

and Mitigation

Strategies Literature review

Risk

assessments Results drawn from RAT

Guidelines for a cost-effective

implementation

Risk

monitoring

and control

system

Results drawn from

RIMOCOS

Risk Prevention

and Mitigation

Strategy

(RIPREMIS)

Industry input for strategies

validation

Table 6. Inputs, outputs and requirements for the development of the Risk Paradigm


Apply changes to

RIM, RAT,

RIMOCOS and

RIPREMIS

Industry input

Software programming

Information agents and

appropriate protocols that will

ensure accuracy in the

registration of new information

and data and ease of

transmission

Evaluation of

RIM, RAT,

RIMOCOS

and

RIPREMIS

Industry input

Development of

Risk Paradigm

Integration of all WP6

intermediate products and

tools



Table 7. Inputs, outputs and requirements for the development of the RMS


Risk

Management

Processes and

Tools of the

Risk Paradigm

Risk Paradigm

Existing Risk

Management

Standards

Current standards,

reports, reviews

Risk Management

Standards (RMS)

Appropriate approvals by

stakeholders and relevant

authorities

A major input for the development of the Risk Paradigm as presented in Figure 1 and referred in

section 2.3 is the case studies that will be used for the modeling, initial validation, and fine-tuning of the

RAT, RIMOCOS and RIPREMIS tools. Considering the integrative nature of the IRIS project, the case

studies should be selected in order to: a) enable the development of synergies between most of the

WPs and b) take full advantage of the expertise of the corresponding partners, as well as of the

expertise and the available resources in the WP6 leading organization team (AUTh). Following this

approach, a case study has been selected regarding an Offshore Wind Turbine System (OWTS). The

following sub-section refers in more details to this case study. A second case study will be a bridge

with data to be provided by VCE.

2.4.1 THE OFFSHORE WIND TURBINE SYSTEM CASE STUDY

According to Henderson et al. (2003)1: ‘Onshore wind energy has grown enormously over the last

decade to the point where it generates more than 10% of all electricity in certain regions (such as

Denmark, Schleswig-Holstein in Germany and Gotland in Sweden). However, this expansion has not

been without problems. The resistance by some members of the public and planning procedures to

wind farm developments experienced in Britain since the mid-1990s is now present in several other

countries. One solution to this problem is to move the developments offshore, where land use disputes

are avoided and noise and visual impacts are greatly reduced. There are also a number of other

advantages:

1. Availability of large continuous areas suitable for major projects;

2. Higher wind speeds, which generally increase with distance from the shore (Britain is an exception

to this, as the speed-up factor over hills means that the best wind resources are where the turbines

are also most visible);

3. Less turbulence, which allows the turbines to harvest the available energy more effectively and

reduces the fatigue loads on the turbine.’

1 Henderson, A.R., Morgan, C., Smith, B., Sorensen, H.C., Barthelmie, R.J. and Boesmans, B. (2003). ’Offshore

Wind Energy in Europe – A Review of the State-of-the-Art’. Wind Energy, Vol. 6, p.p. 35-52.



As Henderson et al. (2003) mention: ‘Offshore wind farms are more and more becoming an important

source of energy. Especially in Europe there are expectations that by the end of this decade, wind

farms with a total capacity of thousands of megawatts will be installed in European seas. This will be

equivalent to several large traditional coal-fired power stations. Plans are currently advancing for such

large-scale wind farms in Swedish, Danish, German, Dutch, Belgian, British and Irish waters and the

first such parks are currently being constructed at Horns Rev, off Denmark’s western coast, and

Rødsand, in the Danish part of the Baltic coast.‘ Figure 7 presents a mapping of the existing and

planned wind farms in North-West Europe up to September 2008.

Figure 7. Map of existing and planned wind farms in North-West Europe: Red stars = (built large wind

turbines), Purple stars = (built small wind turbines), Blue stars = (wind turbines under construction)

Grey stars = (planned wind turbines) (Source: Offshore Wind Energy Europe:

www.offshorewindenergy.org/ [accessed 26/08/2009]).

Offshore wind has the potential to deliver substantial quantities of energy more cheaply than many

other renewable energies, but more expensive than onshore wind. It also has the added attraction that

it has minimal environmental effects and, broadly speaking, the best European resources are

reasonably well located relative to the centers of electricity demand. Wind speeds are generally higher

than onshore and with reduced turbulence. Experience from early installations is already bringing down

energy costs and so the prospects for large-scale exploitation of Europe’s large resource at modest

cost are becoming increasingly attractive.



Currently there are two main design concepts for offshore wind turbine systems (OWTS), namely: a)

bottom founded OWTS and b) floating OWTS. Figure 8 presents schematically these two types of

design.

Figure 8. The two design concepts for OWTS: to the left a bottom founded OWTS and to the right a

floating OWTS (Source: InTech, International Society of Automation (2006): http://www.isa.org/InTech

Template.cfm?Section=Industry_News&template=/ContentManagement/ContentDisplay.cfm&Content

ID=56612 [accessed 26/08/2009])

As shown in Figure 8 the two design alternatives have in their turn a number of other alternatives

depending mainly on the site conditions and especially on the water depth. Different types of support

structures need to be studied to select and design based on the most appropriate. Figure 9 provides

with an indicative suggestion of different support structures for various water depths and electricity

production capacity.

Figure 9. Different types of support structures for OWTS in relation to water depth and electricity

production capacity (Source: OffshoreWind.net:http://offshorewind.net/Other_Pages/Turbine-Foundat

ions.html [accessed 26/08/2009])



However, the water depth and the expected productivity of an OWTS are not the only issues of

investigation for the construction of an OWTS. Despite the significant technological progress that has

been achieved so far, research and development is still needed, especially with regard to larger turbine

designs, for future projects of large scale. Table 8 presents a number of research topics as identified in

the context of the European Commission funded project (contract no. NNE5-1999-00562) under the

title ‘Concerted Action on Offshore Wind Energy in Europe (CA-OWEE)’.

Table 8. Open research topics with regard to OWTS (Source: Concerted Action on Offshore Wind

Energy in Europe (2001). Offshore Wind Energy: Ready to Power a Sustainable Europe, Final Report).

FIELD GROUP TOPIC

Conceptual design of large wind turbines and wind

farms

Design for alternative rotor blade numbers and hub

configuration

Design: Size and

configuration

Combined wind/wave/tidal energy devices

Higher blade tip velocities

Evaluation of the impact of site conditions to the

variable speed

Development and validation of models for reliable

prediction of fatigue and extreme loads

Assessment of the reliability of existing spectral wave

models

Assessment of the importance of wave-driven fatigue

on offshore wind structures

Review of safety factors

Reduction of fatigue loading by introduction of inherent

flexibility, e.g. flexible towers, compliant couplings, etc.

Design: Power

performance and

improvement

Reduction of fatigue loading through more

sophisticated control. (Benefits of greater sophistica-

tion to be balanced against potential reliability

problems.)

Improvement of corrosion protection systems

Reduction of need for floating cranes by development

of internal cranage capability for lifting all, including

largest, components

Enhanced lightning protection systems

Reduction in overall number of components

Development of low maintenance/high reliability

components

Design for

reliability and

maintainability

Modular design approach to facilitate change outs

Consideration of transport and installation loads Design for

installation Sectional components to facilitate ease of

transportation and lifting

Investigation of breaking waves, shallow water effects

and resulting loads

Improvement in understanding of the interaction

of seabed/soil characteristics with system dynamics -

sensitivity of resonant frequencies, fatigue loading etc.

‘Smart tower’ which can alter natural frequencies

Design for future re-use

Offshore Technology

Support structure

and tower

Ice loading



Optimal design of interface between tower and support

structure

Reduction of sensitivity to wave / wind conditions

Reduction of time for offshore working

Minimization of offshore lifting operations

Control costs of overall installation process

Design for decommissioning

Installation and

decommissioning

Review of occupational health & safety standards for

offshore work

Development of mooring systems

Provision of safety to personnel

Development of remote control facilities to allow

manual over-ride of turbine control system from an

onshore base

Development of O&M models

Operation and

Maintenance

(O&M) reliability

Development of condition monitoring via SCADA

systems

High voltage grid link designs

Offshore substation design development

Development of methods to allow Large Scale

Offshore Wind Energy (LSOWE) plants to withstand

transient external faults without disconnecting from the

network

Development of offshore converter designs

Wind farm control

Development of methods to decrease currently

required safety distances between sea cables

Electrical

transmission &

grid connection

Power storage systems development and cost

reduction

Evaluation of effect of early LSOWE projects on grid

operation

System analysis based on future LSOWE plans, taking

account of spatial correlation of supply, existing system

characteristics, future plans for cross-border links, etc.

Analysis of the economical effect (cost) of requiring

LSOWE plants to contribute to primary and secondary

control

Harmonization of electrical protection and reactive

power requirements

Study of the impact of grid limitations on offshore wind

energy potential ; study of the relationship between

technical-economical off-shore wind energy potential

and cost of required grid reinforcements

Grid integration

and electrical

transmission

Grid Integration

& Energy Supply

Development of suitable wind turbine (generator)

models for dynamic grid simulation codes

Improvements in methods for estimating wind resource

in coastal areas, Mean wind speeds

Development of forecasting methods for wind energy

production up to several days ahead

Development & validation of inshore joint wind/wave

simulations

Resources &

Economics Wind resource

Evaluation and prediction of wake effects and

turbulence on power output of large wind farms



Quantification of uncertainty in energy yield estimates

Cost reduction and reliability improvement for methods

for offshore wind data collection

Generic evaluation of LSOWE investment costs taking

into account cost influencing factors

Risk assessment (construction cost, delay risk, energy

production, operating costs, availability)

Economics

Joint wind/wave loading on short time scales for

weather forecasting, power output and improved

maintenance and scheduling

Layout design to accommodate flight paths, where

these are defined

Avoidance of sensitive habitats

Avoidance of site works during sensitive time periods

Management of public awareness of "stunned" fish

during construction (pile driving)

Fauna and Flora

Minimization of the effect of structures and cabling on

stocks

Validation of visual assessment

Promotion of openness and local involvement

Maintenance of good standards of noise emission

despite increases in turbine size and tip speed

Minimization of atmospheric and subsea noise levels

during construction and operation

Studies of disturbance to radars

Environmental

Aspects

General issues

Ensuring of safety of air traffic

All research topics referred in Table 8 are related directly to the risk management process of an OWTS

because they include a great number of risk factors or risks. While it is not possible for a case study to

include all the above mentioned topics, it is expected that the major case study items will be those

included in Table 9.

Table 9. Case study definition items

ITEM PARAMETERS TO CONSIDER

Energy requirements

Energy transfer

OWTS operability

Offshore field uses

OWTS Area

Location

Spatial constraints (e.g. navigation)

Spatial constraints (e.g. seismicity, weather conditions, sea depth, etc.) OWTS Type

and Feasibility Alternative types of OWTS

OWTS Material Material properties

Construction methods

Transportation OWTS

Construction Installation

Operation conditions

Performance requirements and standards

OWTS

Operability and

Maintenance Maintenance requirements and standards

These definition items and the parameters to consider are in direct or indirect compliance with the

research topics mentioned in Table 8.



2.5 PLANNING FOR THE DEVELOPMENT OF THE RISK PARADIGM

The whole planning for the development of the Risk Paradigm based on the approach and

requirements identified this far is presented in Table 10.

Table 10. Planning of future work for the development of the Risk Paradigm

Contribution

Product Sub-Products Developer

Who How

Delivery

Risk

Identification

Methodology

(RIM)

WP6 team All

partners

Provide input on

current practices Project Year 1

Risk Inventory

(RI) WP6 team Project Year 1

All

partners

Provide input on

current practices Risk

Assessment

Tool (RAT)

WP6 team

WP5 team

WP4 team

WP3 team

WP1

team

WP2

team

Provide case

studies for

validation and fine-

tuning

Project Year 3

Risk Monitoring

and Control

System

(RIMOCOS)

WP6 team All

partners

Provide input on

current practices Project Year 3

Risk Prevention

and Mitigation

Strategy

(RIPREMIS)

WP6 team All

partners

Provide input on

current practices,

validate and refine

Project Year 3

Risk

Paradigm

for the

European

Industry

Risk

Management

Standard (RMS)

WP6 team All

partners

Fine-tuning and

promoting the RMS

to audience beyond

IRIS partners

Project Year 3

As presented in this Table, the input from the IRIS project partners to the WP6 is essential as: a) it will

ensure integration of current practices in risk management, b) it will early identify the requirements and

expectations of each industry from the Risk Paradigm, and c) it will give more credibility to IRIS.

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