A knowledge base approach to the design of tension leg platforms

A KNOWLEDGE BASE APPROACH TO THE

DESIGN OF TENSION LEG PLATFORMS

o'By Oriol R. Rijken and John M. Niedzwecki

,Cla

OFFSHORE

TECHNOLOGY

rji

r

_RESEARCH

12/91-A-24-100

For more informcdion contact:

Offshore Technology Research Center

Texas A&M University 1200 Mariner Drive

College Station, TX 77845-3400

(409) 845-6000

or,

Center for Offshore Technology

The University of Texas at Austin

WRW 217

ABSTRACT

MINIM UNNERSITST

Laboratorlum vow Scheepshydromethanica Archief &Mohr3g 2, 2628 CD Delft id: 018- 786873 - Far.015- 781338

This study examines the preliminary design of a tension leg platform

(TLP), using a knowledge base approach. A TLP is a floating deep water

compliant structure designed for offshore hydrocarbon production. Only a few

TLP's have actually been built, but these platforms have demonstrated the

feasibility of this new concept. Important field experience about their response

behavior due to the environment is not generally available, although many

technical articles on analysis methods have been published. The use of an expert system approach can be used to compensate for this lack of information through the introduction of expert knowledge and the use of simplified mathematical or empirical models.

The preliminary design model developed in this study focuses on general

aspects of the TLP platform configuration and its

tethers. The tether

characteristics provide three constraints. These constraints and the requirement

of minimum cost are combined in a strategy to identify the optimum TLP

configuration for a given offshore site. The final configuration can be plotted and its engineering details shown in a spreadsheet format. This knowledge base was used to study four different TLP configurations which are comparable with either

existing TLP's or TLP's which will be installed in the near future. These

simulations indicate that it is possible to approach practical design configurations using this methodology.

"1.7 -"J..IZI:ji*i4 "C) f'"7 TABLE OF CONTENTS Page ABSTRACT TABLE OF CONTENTS rn LIST OF FIGURES LIST OF TABLES vi 1 INTRODUCTION

1.1 Tension leg platform 1

1.2 Design strategies 4

1.3 Computer oriented approach 4

2 KNOWLEDGE BASE FOR UP DESIGN 6

2.1 Basics of KB design 6

22

Expert system application 8

2.3 Knowledge, software and hardware requirements 9

3 TLP DESIGN THEORY 3.1 TLP constrained optimization 12 3.2 Expansion of model 21 3.2.1 Buoyancy 23

3.22 Mass

25 32.3 Pontoon diameter 26 3.2.4 Added mass ₂₆

Page

4 IMPLEMENTATION FOR EXPERT SYSTEMS 35

4.1 Knowledge inventory 36

4.1.1 Knowledge smoother 36

4.12 Implementation knowledge 39

42

Knowledge base description 41

ILLUSTRATIVE EXAMPLES 47 5.1 TLP in 150 m of water depth 47 5.2 TLP in 536 m of water depth 47 5.3 UP in 870 in of water depth 48 5.4 MP in 1500 m of water depth 48 6 CONCLUSIONS 53 REFERENCES 57 APPEND! C A NOMENCLATURE 59

APPENDIX B LIST OF OBJECTS 62

APPENDIX C EXPERT SYSTEMS SUGGESTIONS 63

APPENDIX D MP DESCRIPTION SHEET 64

LIST OF FIGURES

Figure _Page

1 Tension Leg Platform Definitions ₂

2 _{Tension Leg Platform Configuration 14}

3 _{Constraints and Optimum 20}

4 TLP Column Configuration ₂₄

5 _{Added Mass of Heaving Column 28}

6 _{Different Approach to Added Mass Calculation}

,30

7 _{.NEXPERT Parameter Selection 38}

8 _{Overall Flow Chart of Knowledge Base 40}

9 Rule Description ₄₂

10 Search Path for Modification ₁₄₅

11 _{Nexpert Screen Boolean Input ,66}

12 Nexpert Screen Numerical Input ₆₆

13 _{Nexpert Screen Selection Input 68}

14 Nexpert Screen Start Application ₆₈

LIST OF TABLES Table Page 1 Description of TLP (Nordgren, 1989) 22 2 TLP in 150 m 49 3 TLP in 536 m 50 4 TLP in 870 m 51 5 TLP in 1500 m 52

1 INTRODUCTION

1.1 Tension leg platform

A Tension Leg Platform (TLP), as illustrated in Fig. 1 is a floating structure

which is designed to produce hydrocarbons from deep water offshore petroleum

fields. The first TLP was constructed for Conoco (Offshore, 1985) and was

eventually installed in the Hutton Field in the British sector of the North Sea in

the early eighties. The Hutton TLP demonstrated the feasibility of this type of

compliant offshore structure even though it was located in a water depth of 150

m. Conceptually a TLP is designed to be an excessively buoyant floating

platform, which is connected to the seafloor by vertical mooring lines called

tendons or tethers. These tethers are designed to adjust the draft of the TLP and to limit the amount of sway and surge.

The objective of building an offshore structure is to create a cost efficient

work area away from shore. In this study only tension leg platforms are

considered for deep water offshore field development. The objective of this study

is to develop a computer tool for use in preliminary design using the latest

computer technology. Of particular interest is the general TLP configuration and their associated cost estimate. One approach is to minimize the cost of building

the TLP with regards to key parameters, each offshore site has different

environmental parameters and requirements, an optimization procedure has to be performed for each location. Ideally one single strategy can be used to handle the optimization for different offshore sites. To be meaningful, the optimization procedure must be subjected to several constraints. The basic constraints in this study are sufficient buoyancy, tether tension, tether stress, heave frequency of the platform and sufficient clearance between the highest wave crest and the bottom of the deck. Several parameters in the optimization are site related and can only be modified within a very small range. These parameters are, for instance, the maximum wave height and the water depth. The type of petroleum reservoir, the

Teas ion

deck

brace

tether riser sub sea base

-. _ pontoon flare 'diaineter

Pi

form

column 4diameter hare height waterdepth column length

Fig. 1. Tension Leg Platform Definitions

maximum wave height and the water depth. The type of petroleum reservoir, the type of petroleum product and the distance to further processing facilities, the

size of the living quarters and the drilling equipment dictate

_{the amount of}

processing equipment. These are site specific parameters, as is the top tension in the riser which depends primarily

_{on the water depth. The other type of}

parameters can be called design parameters and these parameters will _change

throughout the preliminary design process.

One of the problems which arises when trying to develop a 1'LP design is the lack of coherence between the available knowledge in the open literature. For example a lot is known about the behavior of floating structures and tethers

but, there is hardly any information available about the behavior of a floating

structure with tethers. This lack of information can not be compensated by field data because there are only a few TLP's in operation and data on their response in proprietary.

A simple yet robust methodology will be required in order to develop an optimized TLP configuration based upon our sometimes incomplete knowledge about various details of TLP design. It will be expected _{to estimate a variety of} parameters and guide the user to an optimum solution, it should be noted further

that the methodology should be tolerant ofusers with a minimum knowledge about TLP's. The resulting solution should be regarded as a different approach

to obtain a starting point in the design spiral (American Petroleum Institute,

1.2 Design strategies

Designing any structure always requires an iterative design procedure. The

steps in this procedure are well defined when a similar structure has been

previously designed. Guidelines or design codes do exist when several similar

structures have been built before. It is rather easy to design a structure when

these guidelines exist. One studies the steps in the previous design and applies them to their specific problem and it is generally not difficult to develop a similar

structure. The guidelines are designed to avoid known problems or tackle

problems efficiently and make the structure comply with existing norms and

regulations. The significant alteration of an existing structural design into a very

different structure makes the design procedure a lot more complex. The

complexity arises from the fact that one may not know how the various

parameters interact with each other.

Existing guidelines or building codes are completely inadequate for the

development of a new type of structure. A different approach is required to

develop a new design. One must acknowledge that for this kind of structure it is impossible to give an exact description. One can only guess about the design or

describe it more quantitatively. An iterative procedure is again required to

develop a preliminary description of the structure. The typical approach to the

iteration procedure is to estimate the values of key design parameters, then

calculate the structure's characteristics, followed by a check and modification of several of the parameters. The iteration procedure stops when the designer feels that the system is adequate.

1.3 Computer oriented approach

There are many calculations involved in the preliminary design of a TLP and they can be preformed in a variety of computer environments. A common

language like FORTRAN, PASCAL_{or 'C'. Mother possibility would be to use} a spreadsheet which is becoming a common engineering approach. However, the use of a spreadsheet for optimization requires a significant amount of numerical computation and knowledge about the problem by the _{user. In order to find an}

acceptable solution the user has to interpret the

_{spreadsheet computations.} Another possibility is the use of a computer environment which captures not only

the content of the spreadsheet but also captures the knowledge of the

experienced engineer. This type of approach is called Expert System Approach or in it's most general context a Knowledge Base System (ICBS) approach. The

combined knowledge used in the spreadsheet and the experienced user's

knowledge is called a Knowledge Base (KB). Nowadays

_{there are softwre}

environments available whicl3 allow for _{an expert system approach to efficiently} build a knowledge base.

2 KNOWLEDGE BASE FOR TLP DESIGN

2.1 Basics of KB design

The strategy behind problem solving with an expert system approach is a very powerful strategy which can be very complex and sometimes abstract. One of the first facts one must realize when taking this approach is that the solution strategy which is represented in the expert system is very subjective and reflects the interpretation of the person who designed it. However, as one becomes more

adept at using the approach the subjective aspects can be minimal One of the most powerful aspects of the expert system approach is the fact that loosely

organized information can be used (Coyne, 1990). Typically gaps exist in

engineering knowledge and the ICBS strategy can compensate for these gaps.

The first form of analysis in developing an expert system deals with the interpretation of the rules within the problem domain. For instance in the case

of TLP modelling the rules describe how the draft and mass of a TLP are

calculated or that there are no braces when there are no pontoons. The result

of this analysis is called the rule based part of an expert system.

The second type of analysis deals with the analysis of the individual parts

which make up the information. One tries to organize these parts into groups

which have identical features. Each separate part is called an object. Each

feature is called a property. Object in the TLP design is for instance water with the property depth, wave with the properties height, frequency and period. Another

objects is column with the properties shape, length, draft and diameter. When objects have identical features they are grouped into a class. Classes can be

grouped too in other classes. An example of a class in the design of a TLP is the class of the construction materials. A TLP can be made out of steel or concrete.

Hence there are two objects in the class Construction Materials : Steel and

Concrete. Each object has the properties density, stress, maximum stress and

The idea of using an expert system approach implies a good mapping of the available knowledge into the ICBS approach. A key factor to developing an efficient approach is the elimination redundancy in the information. This requires

the effective use of classes. Let's return to the example of the

construction materials. One knows that the stress in the utilized construction material should

not exceed a typical value. This is basic knowledge. It implies that one must

search in the class Constntction Materials for a material for which the value of stress does not exceed the value of maximum stres.s. Now one operateson the

class Construction Materials instead of on all the individual objects within this

class. Concluding : One piece of information (i.e. search for material) is

translated into one operation. The advantage of using classes is that the

operation on the class is not influenced by the content of the class. It is

indifferent to the system whether there is only one object or whether there are

one hundred objects.

One must gather all the information or as much as possible information

before starting the process of analysis. This gathered information is known _as

knowledge. This knowledge is the basis for developinga solution strategy. A poor

knowledge level translates directly into a poor strategy. Knowledge _{can lcie}

gathered from books, journal articles, conference papers etc. and of course the experienced practitioner. The interpretation of a problem by the expert himself has a tremendous impact on the overall strategy.

The development of an expert system, the design of _{a knowledge base,}

starts in this study with an initial description of the final result. Starting at this

description one reasons backwards to locate and determine which _parameters

influence the design. This process is known as backward chaining (Coyne, 1990). This approach moves just in the opposite direction of a normal design procedure and initially might cause some difficulties for an inexperienced designer who tries

to utilize a knowledge base approach. One must define the nature of the final

The final and most important part of the development of a knowledge base is the system validation. One has to be sure that the knowledge base acts properly. This is not generally a simple matter because the knowledge base

generally reflects incomplete knowledge about the problem domain. Even with these limitations one must validate the knowledge base. It is very important to

continuously validate the knowledge base during its development because it allows the user to make corrections before the knowledge base becomes too complex. A good method checking the validity of the knowledge base is to discuss the results with a human expert. An indication of the accuracy of the

knowledge base is the when experts conform the results.

2.2 Expert System Application

Designing a TLP is a very complicated matter, especially because there are so few 'TLP's in operation around the world. It is still very hard to come up

with some design criteria from operational experience. Field data has been

gathered about the behavior of the existing TLY's though most of it is propriety to the oil companies. There is a lot of research activity focused upon the design of TLP's. However, even with API-RP2T (American Petroleum Institute, 1987)

there remains a lot to learn regarding the design of a TLP.

Probably the biggest challenge in design is to find a good starting point

for the design spiral (see American Petroleum Institute, 1987). The better this

point is defined the faster one can obtain a solution and the more accurate

preliminary design will be. Incomplete information about the system being

designed does not facilitate the definition of this point.

Conventional computer programming methods are not really suitable for this problem and hence the use of an expert system approach was selected. This approach allows one to develop a preliminary description of the structure. The expert system approach designs a TLP based only upon a few parameters like the

water depth and the number of columns. In these cases the expert system itself contains enough knowledge so that it is capable of providing suggestions to the

user. The approach also allows the user to specify the structure more precise, as additional knowledge is gained, hence overriding the expert systems suggestions.

The expert system will present the most cost effective configuration for the

specified constraints.

It is possible to solve the TLP problem in a spreadsheet format and

engineers have used this approach for other types of structures. Some of the

features of an expert system can be incorporated into a spreadsheet. The

advantage of the expert system is that it is extremely well equipped for guiding the user towards an answer. The expert system interacts with the user by asking well formulated questions and depending on the case, gives a list of options to

choose from. The presentation of selected questions and options are extremely important factors. This control can deceptively lead the user to assume that the

knowledge base is quite simple. The use of an expert system approach allows unexperienced users to develop a preliminary TLP design hence providing, _a

learning tool.

As users get more experienced with the system they may wish to add and

modify the existing system. The text which follows provides the basis fOr

achieving this objective.

23 Knowledge, software and hardware requirements

The use of an expert system approach to problem solving is a relativenew approach to the filed of engineers. The expert system approach has seen limited

use in engineering because it required special work stations,

_{it was too}

complicated, too slow and very inefficient. More recently, the expert systems werle moved to high end PC's but the software was slow developing adequate power. Only recently with the aid of fast computers, like IBM-PC 486 with a minimum

?1,

of 6 Mbyte RAM, it is possible to use the expert system approach idea as a

method for problem solving. Surprisingly, some software development packages

are transportable to other computer systems

such as a VAX or SUN work

stations. Thus substantial development efforts on small computers does not need

to be lost since it is transportable.

Building a knowledge base can be regarded as writing a computer

program thus, some of the skills learned using higher level languages can be used

to great advantages. The term environment is sometimes used because most

knowledge base software access spreadsheets' or data bases to draw conclusions

or to present results. It is also possible to communicate with other programs, including finite element packages or independently developed software packages.

Several facts have to be taken into account before one maps the

knowledge into the expert system environment. First of all the knowledge must be analyzed and well organized. All redundancies must be removed and one must

have a basic idea of bow to implement the knowledge. Furthermore the

-knowledge must be prepared for a specific -knowledge base environment since

they are not all identical. This preparation contributes extra knowledge to the

knowledge base and is environment specific.

The use of an IBM 486 in this study provided the bare minimum in speed, a slower machine can be used for development but the communication with the user is very slow. When running the knowledgebase on a slower computer it may seem like there is something wrong but the delay is only caused by the lack of

speed. The speed of the execution of a knowledge base has probably a

psychological effect. One may tend to doubt the reliability or the validity of the

knowledge base when one has to wait for a while. When the input is very

straightforward one expects the analysis to be executed quickly and one tends to assume that the computer code is probably quite simple. However as we will see

The expert system environment used for the development of a Tp)

description in this study is called NEXPERT OBJECT commonly called

NEXPERT. It operates under Microsoft Windows environment and was designed

by Neuron Data. NEXPERT allows for both rule based knowledge and object oriented knowledge, often these types of environments are called hybrid expert systems. NEXPERT provides extra facilities for a more powerful knowledge base.

One of these facilities is called the META-SLOT. The META-SLOT can be

regarded as a rule or set of rules which will be evaluated only when an object, related to this META SLOT, is evaluated. The knowledge base in this study v:rlas

developed with using a development version of NEXPERT. Most of the functions

of this version are graphical and provide the user with a very good idea about

what is going on in the complex knowledge _base. This graphical representatiOn is probably the best way to represent the knowledge base and can be used very efficiently to fix programming bugs.

The knowledge base developed during this study is transportable to other

versions of NEXPERT and to other machines There is run-time version Of NEXPERT. This version allows the user only to analyze the knowledge base,

however the knowledge base can not be modified with this version. The run-time

version allows the developer of the knowledge base to distribute his product

without providing the capability of modifying the knowledge base. The knowledge base can alto be encrypted preventing disclosure of the knowledge structure.

3 TLP DESIGN THEORY

Before one maps the available knowledge into a knowledge base one has

to capture and analyze all of the relevant knowledge. The basis for the TLP

design methodology used in this research study is based the work of Nordgren (1989). Following his approach it is assumed that the total cost of a TLP design

can be optimized based upon the column configuration and the tether

characteristics. This optimization procedure presently does not optimize for an efficient deck layout, efficient location of processing equipment or other design constraints which represent aspects of a refined design. A number of new ideas

were generated to make this methodology more applicable to the design of

TLP's.

3.1 TLP Constrained optimization

A TLP design constrained optimization method was recently developed by R.P. Nordgren (1989). His goal was to reduce the weight-based cost of a TLP.

The optimization procedure takes into account the vertical equilibrium of the

platform. The equations presented in this research study differ slightly from the ones presented in his journal article.

Optimization is obtained by imposing three constraints. The first constraint

states that the maximum stress in the tethers is not allowed to exceed a given value. The second constraint requires that the tension in the tethers be above

specified value in order to eliminate the concern about the bucking of the

tethers. The third constrained requires that the response heave frequency of the platform to the sea be significantly smaller than the natural heave frequency of

the platform. This to reduce the stretch of the tethers. Reducing the stretch

reduces the stress tethers hence reducing fatigue damage.

Fig. 2 presents a basic TLP configuration. This figure shows a four-legged platform with flared columns, pontoons and braces. The platform is attached to

the subsea base by means of n, tethers and has n, risers. Though the platform

shown in Fig. 2 has four columns which is consistent with popular designs but for increased versatility of the knowledge base, the platform used in the model for this study has n, columns Thus it is possible to explore a TLP with three, four, five, etc. legs. The riser system is are modelled as a single riser with a combined

top tension. In Fig. 2, h represents the incident wave height, 1 represents the length of the tether, H is the water depth and

a is the platform draft. In this

study we assume that the subsea base doesn't have any height therefore the

tether length plus the draft equals the water depth. The on-center spacing

between the columns is represented by the parameter s. The height of the deck is represented by e while f represents the width of the deck. Further, the height

of the flue-out is represented by b and the column length is represented byc.

The basic column diameter is represented by di, d2 represents the diameter of

the flare-out while di represents the diameter of both the pontoon and the

braces. The fact that the diameter of the braces equals the diameter of tlle

pontoons reduces the number of parameters in the model. In the rest of this paper the word 'diameter' will also be used for a square column. Actually this

word should be replaced by significant width but diameter is more obvious. The first step in modelling the platform is to develop an equation for the vertical equilibrium of the platform. The buoyancy force of the platform must be

equal to the combined riser tension plus the tether tensions plus the gravity

loading of the platform itself and the deck equipment. This can be expressed as

B = g

+ Fd+ 7; + 77,7; ₍₁₎

where B represents the buoyancy force, mp represents the mass of the whole

platform, Fd represents the load of equipment on the deck. The combined riser

top tension is represented by 7., the tension of each separate tether is

The buoyancy force of any partially submerged structure is controlled by its displacement. The columns are either round or square. The displacement of a column can be calculated by the following formula

V-=k-612a

(2)

where V is the displacement,

_{a is the draft of the column and d is either the}

diameter of the round column or the beam of the square column. The parameter

k is a shape factor for the column, k = 1 for a square column and k = 14 for a round column. The cobunns, pontoons and braces, if existing, contribute to the displacement. The contribution to the displacement of _{the braces and pontains}

is constant while the contribution by the columns depends on the

area of the

column at the water line for one type of TLP configuration. Thus the buoyancy force can be approximated by

B = zo + zi

di2

The same idea about the columns, braces and pontoons is used to determine

the mass of the whole platform

mr =

n, d j2 ₍₄₎

This equation describes the mass of the platform and not the weight. There is close relatiottship between the factors nj and z1. They describe the contribution of the column to the buoyancy force and mass of the TLP respectively. Utilizing

Equations (1), (3) and (4), the tether top tension _{can be expressed as}

7; (z0 g no + ?lc (zi _{g ndc112 - Fd - Tr) / ni}

(5')

As the platform responds to the heave motion of the sea, this causes a cyclic tensioning in the tethers. The maximum dynamic tension in the tethers can be

approximated by

D (I, + b1 nc.

) hA

(6)

where D is the tension amplitude, bo and bi are constants relating the effect of the submerged TLP configuration and the wave height to the dynamic tension

amplitude. Both of these constants are determined from hydrodynamic analysis.

The stress in the tethers originates from the axial tension in the tethers

and from bending of the tethers. The bending stress is an important factor but,

for simplicity, it is assumed that the axial stress is domirtant The maximum allowable stress in the tethers is reduced to compensate for this assumption

(Nordgren, 1989). The maximum stress occurs at the top of the tethers where

max [a I = (T, + D) / A

where am represents the reduced maximum allowable stress, max (a] represents

the actual maximum stress and A represents the cross-sectional area of one

tether.

Combining Equations (5),(6),(7) and (8) one obtains the constraint

equation

(z1 - g n1

b1 h) d2 + n a. A >

- g no + b0 h - Fd - T,. (9)

The smallest tension is expected to occur near the subsea structure. The

cause damage to the tether mounts. The minimum tension in the tether can be expressed as

mm. = 7; - g -(1 - p, -1 -A - D (10)

Here min [T] represents the minimum occurring tension, p, represents the mass density of the tether. The term b, represents the buoyancy factor of the tethers;

it ranges from zero to one and takes into _{account the attachment of buoyancy}

tanks or synthetic foam to the tethers. The tether must be kept under adequate tension all the time hence

min [T] >7;

₍₁₁₎

where Tb represents the minimum acceptable tension at the bottom of the tether. Combining Equations (6),(10) and (11) one obtains the second constrained equation

(z3 -bih)d +n, g _{-b,) pi 1A < zo -g no-boh -Fd -Tr -n,Tb (12)}

The final constraint used in this study is specified in order to minimiie the fatigue damage of the tethers. An important contribution to fatigue of

tethers is caused by the heave of the platform. The heave of the platform induces

elongation of the tethers which in turn effects the stress levels _.

_{In order to}

reduce the stress levels in the tethers both the heave of the platform and the

stretch of the tethers must be reduced. This leads to the

_{specification of a}

constrained on the heave frequency of the TLP. The longitudinal

_natural

frequency of the tethers must be far away from the_{response frequency of the}

(13) where

wh = (kh/mh) 1/2 (14)

kh = ni E + ne k, to. 412 (15)

= nip +. Fd/g + ms5 (16)

The parameter kc is the shape factor of the column and wh is the radial frequency

of TLP heave, ws is the dominant wave frequency. The virtual mass of the

heaving platform is represented by mh, m55 is the added mass in the heave mode, pw represents the mass density of the surrounding fluid. The spring constant kh

includes the contribution of the axial stiffness if the tethers as well as the

influence of the columns Similar to the approximation of the buoyancy of the TLP, an approximation can also be made about the form of the added mass

expression

mss = so + Sj nc (17)

Combining Equations (13),(14),(15),(16) and (17) one obtains the final

constrained equation

nc - (nj + Si) wh2Jd2 + (n, E / 1) > (no + .so + Fd/g) wh2 (18)

The cost of building a TLP can be regarded as the sum of the costs of the TLP sub systems i.e. the tethers, deck, columns and subsea base. The cost of the tethers is assumed to be proportional to its combined mass (mt).

1

The cost of the subsea base is considered to be proportional to the mass of the sub sea base. The mass of the subsea base is considered to be proportional to the maximum effective tension at the bottom of the tether (max 1 TbI)

max Tb ]

Tb +D

(20)

With these equations the combined cost of a TLP (Cc) may be written as

Cc Cp m + C, m, Cb nr .max 1 Tb] (21)

Combining (4),(19),(20) and (21) one obtains

= Co + CaA + Cd d 2 ₍₂₂₎

with

Co = Cp no + ct, (z0 - g no -

+ b, h)

₍₂₇₃₎

Ca n, 1 IC, p, - Cb p, (1-b,)]

1Cp g ni + Cb (z1 bi h)]

The combined cost of the TLP has to be reduced as much as possible. In other

Words

c, <_ co + A + Cd d 2 ₍₂₆₎

Comparing (9) with (12) and (18) and (26) we see that the in this case the

minimum cost can be obtained by IninimiAng to the column diameter and the tether cross section area within the given constraints. The number of columns has (25)

0 0 0 0 r 0

constant

cost

Lines

\ \

decrOas\i

g

cost

\ \

feasab

I

e

feasable

V Dr

easab

I

e

or 3

= 3 or 1

optimum

conf I gur'at

Ion

column area

to be specified. As more columns are specified the cost will increase (Equation

(25)). The lines representing the constraints are shown in Fig. 3. The three

constraint equations can be represented by three lines. The equations for these lines are

ci <al d2 + k A

(27)

for i 1, 2, 3.

There is a difference in cost caused by different design philosophies for the North Sea and the Gulf of Mexico (Amold,1989; Roobaert,1989). However, this cost difference is not taken into account in this study.

Some caution is required with the parameter Fd which represents the load

of the equipment on the deck. It should include the living quarters, process

equipment and process fluids. This parameter does not represent the whole topside load. The major part of the whole topside load is included in the mass

of the platform. The parameter Fd is a true site specific parameter which

depends on the water depth, field size and petroleum type (i.e oil, gas, amount of water, amount of sand, chemical contents etc.).

A hydrodynamic analysis was performed on a TLP which had a square deck and has four circular columns (Nordgren, 1989). The distance between the columns (column spacing) was 61 m. The columns were flared at 15.2 m from the bottom, where the flare-out diameter was 19.2 m. The column diameter was 146

m at the water line and the draft of the whole platform was 33.5 m. The total

mass of this platform estimated to be 31.6 106 kg. The platform had braces and

pontoons. Seven tubular members at each column (four in tethers total) had a

combined cross sectional area of 0.143 m2, the maximum allowed stress in the tethers was specified as 155 Nimm2 Additional parameters which describe this TLP are shown in Table 1. With these values Nordgren calculated the most wit efficient l'LP configuration using the three constraint equations.

=4

lip

=4

Ac,k = Ir =

/4

= 14.6 m d2 = 19.2 m d3

= 1.8m

a

= 33.5 m b = 15.2 m c = Unknown s = 61 m pb, = 1025 kg/m3 = 9.81 m/s2

The following values are obtained from the hydrodynamic analysis Table 1. Description of TLP (Noragren, 1989)

zo = 10.14 MN z1 ?lc = 1430 kN/m2 no = 8.33.106 kg n1 nc. = 23.8103 kg/m2 bo = 569 kN b1 nc = 9.33 kNfm2 so = -5.70.10° kg si nc = 69.7.103 kg/m2

3.2 Expansion of model

The objective is to design a knowledge base which can optimize a variety of TLP configurations. The methodology presented by Nordgren (1989) can be expanded to include more types of TLP designs. The original model was not valid for TLP configurations with three or five columns and did not allow for a TLP without pontoons or braces. Further the number of tethers was fixed at four and the column diameter and shape were fixed. These limitations have been removed in the current study.

3.2.1 Buoyancy

Consider the TLP column as shown in Fig. 4. In this study it is assumed that the TLP has n, columns evenly distributed along the perimeter. As a direct result of this assumption it was necessary to reevaluate the parameters zo and.;I.

As presented earlier a new variable in the model is the shape of the columns

(k) The value of lc,. equals 1 if the columns are round, it equals ir/4 if the

columns are round. The parameter kp has the same function for the pontoons.

The parameter k, represents the shape factor of the braces. When kp equals 0, it

indicates that there are no pontoons. It is assumed that the shape and cross

sectional area of both the pontoons and the braces are the same and the,ir

diameters are a function of the column spacing. Now it is possible to calculate the buoyancy force. The flare diameter is assumed to be a function of the column diameter

= k

The contribution of one column

V

d2

The contribution of one pontoon

B2 = 432 (s

- di) g

(30)

A brace connects the top of the column with the center of a pontoon. The length

of a brace, when present, is 1/2 42 bigger than the length of the pontoOn.

There are tvice as much braces as pontoons. The contribution of one brace is

B3 = kb d32 - 1/2 v2 (s - di) g Py, (31)

There are 5, pontoons and columns The total buoyancy force is calculated

accordingly i.e.

B n B1 + np B2 2 71), B3 ₍₃₂₎

and f011ows that

B= fn k d12 [a + b (k2

1)] Is, d32 (1 + 2)-('s k dill g pp, (33)

Note that the variations of the free surface are neglected in these estimates

3.2.2 Mass

Related to the buoyancy of the MP is the mass of the TLP. The

contribution of the columns, braces and pontoons are included in the following estimate of the platform mass as

The contribution of the deck to the total mass is

= (35)

The terms PC, pp _{and P, are the average mass density of the columns, pontoons}

and deck. These terms are the result of the division of the mass and the volume of either the column or the pontoon or the deck. This enables the consideration of columns, braces and pontoons as solid objects.

The total mass of the platform is then obtained as the sum

mp "2/ m2 (36)

3.2.3 Pontoon diameter

The pontoons provide extra buoyancy to the TLP and they also stiffen the

columns. A function for the size of the pontoons is required. This function

describes the diameter of the pontoons when they are round, or the width of the

pontoons when they are square. Assuming that the diameter or width of the

pontoon can be approximated by the following formula

d3 =

s + q

(37)

Where L,, takes into account the influence of the column spacing and q is the

minimum diameter.

Substituting Equation (37) in Equation (33) one obtains the following

expression for the TLP buoyancy

3.2.4 Added Mass

It is rather difficult to specify the theoretical added _{mass for a TLFis of} variable configuration since the added

mass depends on the T'LP's heave

frequency of the TLP. Numerical analyses have been performed on a heaving

structure which crosses the water line (Wybro, 1980). A graphical presentation of the results of Wybro is shown in Fig. 5. This figure clear shows that the added mass coefficient depends on the heave frequency. It is possible to approximate the normalized added mass as a function of the normalized

_{frequency. But 4en}

the normalized frequency is bigger than 0.25 one can estimate the normalized added mass has a value of 1.3. The added mass can now be estimated as 1.3

times the mass of displaced fluid. The mass of the displaced fluid by a column can be obtained from Equation (29).

The values of bo and b1 in Table 1 _{were probably obtained through curve} fitting and hence these values presented by Nordgren (1989) are only valid in a very confined range of column diameter and platform configuration. Therefore the values of the parameters bo and b., are calculated differently for this study. A comparison of the present approach with that of Nordgren (1989) is shown in

Fig. 6. One can see that the values of the added _{mass don't differ significantly}

when the column diameter ranges from 18 to 25 _{m. For diameters smaller than} 20 m the present theoretical approximation approach _{overestimates the added} mass predicted by the Nordgren (1989) model. For bigger diameters the opposite is true.

The approximation calculations of the added mass is as follows. First, the contribution of the columns to the added mass is

mssj=1.3.n.k.dj2fa+b(k21)J.p,,,

₍₀₎

2D

Normalized added mass for waterline crossing and heaving structure 2.5 2 normalized 1.5 added mass rn33/pV 1 0.5 0 0 0.5 1 1.5 frequency parameter (w^2*d/g) 2d

mss, np kp d32 (s - ) 1:) (40)

The contribution due to the braces is

mssj = 2- kb - d32. 1/2 ,r2

(s. - (41)

There are n3, pontoons and; columns The total added mass is then calculated

accordingly

mss = mss

m2

55, + M55,3 (42)

or substituting the appropriate equations

mss = [ 1.3 n, di2 [a + b (k2 1)] + ni, lcp d32 (1 +,(2)-(s - k )1 A, (43)

Comparing Equations (43) with Equation (17) one obtains the following

approximation for the coefficients in Equation (17)

so = d32 (1 + v2)-(s

k ddi

-= [ 1.3lc [a +

(k 2 - 1 )11 13,,

3.3 Assessment of expert .system's knowledge

The next objective is to find values for the different parameters used in

the previous equations. An existing TLP or model is required to lay a basis. The

TLP as described by Nordgren (1989) is the basis to calculate the parameters.

The values of these parameters are used to describe the TLP initially, when the user doesn't know these values the knowledge base will use these values. Later

added mass [106 kg] 50 T 40 30 20 -10 0

different added mass calculations

14 15.6 17.2 18.8 20.4 22 23.6 252 26.8

diameter [m]

-=. Nordgren.. Expert System error %

Fig. 6. Different Approach to Added Mass Calculation

10 5 0 error -5 -10 -15 -20

on in the design phase these values can be modified. It is easy to calculate k, see Equation (28)

k = d2/d1

03)

k = 19.2 / 14.6

k = 1.31

Calculating the parameters and q, see Equation (37)

s = 1.8

Or

61 + q = 1.8

q Represents the initial diameter of the pontoon. A reasonable value for q is 1.2.2 m or 48". More slender pontoons are prone to bend or buckle easily. This results

in a value for is. l equals 9.5.104.

Substituting these values into Equation (38)

B =Pre112[33.5 + 15.2(1.31 2-1)] + irl.8 (1+,12)(61-1.31 d1)J-9.81-1025 (44) and B = zo zrn, d12 hence 77, = w [33.5+15.2 (1.31 2-1)1 9.81 1025 Zo = IT -1.8 -(1 + 12) (s - 1.31 - 9.81 1025

Notice that there is a term in zo which depends on the column diameter. This term is left in zo, its influence is rather small

Calculating the value of zo and z1

zo 10.31 MN

n, =

1402 IcN/m2

These values are within 2 percent of the ones provided by Nordgren

(1989). The fact that these parameters describe Nordgren's 'TLP model well

allows for continuation with his model.

The next step is to calculate the mass parameters. The displacement of the platform is 14263 m3, the mass of the TLP of equals 32.2-106 kg. The length of the column (c) is not yet defined. Assuming that the column length equals the column spacing, then

C = 61 m

The contribution of the deck mass to the mass of the platform is a

function of the deck height (e) and the deck width (f). The deck

height is

assumed to be a linear function of the deck width. The deck width

is also assumed to be a linear function of the column spacing. The deck mass can

be

expressed as

m2=

(45)

where pd is the mass density of the deck.

Combining Equations (34),(36) and (45) one obtains the following

expression for the platform mass

no

n n=

c

8.33106 kg 23.8-103 kg/m 2

These values imply a value of the column mass density of

pc = 105 keth3

This value is smaller than 1025 kg/m 3, the mass density of the

surrounding fluid and therefore the structure will float. This value is about 10% of the mass density of the surrounding fluid and implies that the columns provide a vast amount of buoyancy.

=Ir (112161 +15.2(1.31 2-1)13c+g 1.82 (1 +v2)(61-1.31 di)Pp+61 Pd (46)

compare Equation (46) with form of Equation (4) which is

Mp = no + ncn, (4)

one can deduce the coefficients no and nj to be as follows

no = IT 1.82(1 + v2)(61 - 1.31 aid Pp + 6i3 Pd

n n=ir 161 + 15.2 (1.31 2-1). pc

The next step is to find some acceptable values for the densities. Based upon the values presented in Table 1 one obtains the following values for no and

Assuming that the mass density of the pontoons equals the mass density of the colnmns, i e.

= Pc (47)

This assumption is allowed because the pontoons and braces don't contribute a

huge enough factor to the overall design of the TLP. This allows us now to

calculate the deck mass density.

Pd = 36 kg/m3

This value is smaller than

k

and this can be explained on the basis that

there more equipment is located in the cohimns than in the deck structure.

Another reason is that the prime function of the deck is to provide a work floor

and not to house equipment.

At this stage most of the basic parameters in the TLP model are defined

and one can proceed with the application of the model in the expert system

4 IMPLEMENTATION FOR EXPERT SYSTEM

The objective of the knowledge base is to allow the design of a TLP from

a minimum of available information. A theory has been developed which

optimizes a TLP design. The optimization procedure has been implemented

utilizing a spreadsheet accessed from the expert system environment. The first

step in the implementation process requires the available information to be

organized and analyzed by the knowledge base developer. This is probably the most important part of the process because from this process one develops the

knowledge base. In the case of TLF' design the knowledge analysis, i.e. the optimized description, has already been performed. This knowledge is now

mapped onto a knowledge base. Knowledge preparation is _{the next step. This} primarily implies the development of the object based knowledge base. Objects

and properties are defined. Several classes are defined which enable easy

manipulation of the objects.

The final product prompts the user for different values of water depth aid

column spacing, this is the Minimum required amount of information. Other

aspects can be user specified. From this point on the knowledge

_{base will} calculate an optimized TLP configuration. The knowledge base keeps track of it's own suggestions and provides a list of all parameters and suggestions to the user. A graphical representation is available to provide _{a different view point to the} TLP configuration. It is possible to modify parameters. The knowledge base will

check for a logical combination of numbers of tethers and the amount of

columns It can also check whether the_{waves will hit the bottom of the deck.}

The questions the knowledge base asks the user must be formulated well.

A nicely formulated question enhances the validity and accuracy of the final

4.1 Knowledge inventory

Before describing the implementation of the available knowledge it is

worthwhile to list the present types of knowledge. There are five basic types of

knowledge which contribute to the TLP design. The core knowledge is the information about the three equations which describe the effects of platform

configurations and constraints on the column diameter and the tether area. This type of knowledge is covered by Nordgren (1989). A second type of knowledge can be described as the hidden erpert's knowledge. This knowledge contains the suggestions the system makes when the user's own knowledge is insufficient. A third type of knowledge represents the compatibility of the model. This type of knowledge is inherent to all systems. It imposes basic conditions to the design.

In the case of a TLP design it checks whether the waves hit the bottom of the

deck or whether there is a logical relation between the number of columns and

number of tethers. The fourth and fifth type of knowledge can be called the

knowledge smoother and the implementation knowledge. The last two types of knowledge will be explained in more detail.

4.1.1 Knowledge smoother

One of the basic tasks of an expert design system is guiding the user to a possible design configuration. This implies that when the user may not be

familiar with a problem or doesn't want to define a parameter, the expert system itself will provide a value for the parameter or the system will reprompt the user

for a value when the knowledge base cannot provide this value. This happens

quite often in the knowledge base. The knowledge smoother invokes other types Of knowledge, like the hidden expert's knowledge or the compatibility knowledge. The knowledge base is capable of providing values for several parameters. These

shape of the deck and columns. For further information about all suggestions see appendix C.

Providing a good user interface is an important part of the expert system approach. One of the ways this is achieved is to keep track of all the parameters

which describe the TLP. This is done in a spreadsheet which runs concurrent

with the knowledge base. This spreadsheet can be made visible all the time. is also possible to make a print out of the spreadsheet. The use of a spreadsheet

has no influence on the knowledge base itself though the idea of using a

spreadsheet is a part of the knowledge smoother.

The user of the knowledge base does not notice on a direct basis the

effect of the system's advice. Programming this is rather complicated though. The system asks the user to make a decision or to provide a value. One of the

option on the selection menu is the NOTKVOWN function, see Fig. 7. The value Of the current parameter is now NOTICNOWN. This value must be transformed

into a system's suggestion. At this point the META SLOT is the right tool to

tackle this problem. The META SLOT is specific to NEXPERT. It enables the user to perform specific tasks when a parameter is evaluated. Examine the case when the value of a parameter is NOTKNOWN. The META SLOT contains an instruction which invokes the analysis of a rule. This rule contains the specific

information about the current parameter. When the value of the parameter is

NOTICNOWN, the rule will asses a value (expert system's advice) to the

parameter. The rule also writes to a spreadsheet the fact that this value of the parameter was specified by the expert system. (The instructions in the META

SLOT are invoked again but the parameter has a value unequal to NOTKNOWN hence the rule will not be executed).

Another location where the META SLOT is used is to define the tether length. The expert system is designed to prompt the user early on for the water depth and the platform draft. The META SLOT of both parameters refer to one

rule where the tether length is calculated. The tether length is calculated

--si.ON1.F10.1::.

immediately when both parameters are known. This also allows the user ' to

modify the water depth; the expert system immediately modifies the tether length accordingly

The META SLOT also allows the developer of the knowledge base to

define the questions which will be asked. For instance, when the expert system

prompts the user for the value of the water depth it asks : "WHAT IS THE DEPTH OF

WATER" because the water depth is represented by the object water with the property depth. An experienced user knows that the system likes to obtain, value for the water depth. The META SLOT for the parameter water.depth

contains an option for the prompt line. The prompt line contains "'WHAT is TIM

WATER DEPTH" which is quite straightforward.

4.1.2 Implementation knowledge

The theoretical

analysis which has been presented describes an

optimization for a TLP design. However,

it

doesn't describe how this

optimization process should proceed in an expert system environment. The

optimization process is typical engineering knowledge, it can be described as a tool which allows the designer to perform his task. The optimization is one part Of the knowledge base, the knowledge base is also capable of modifying values of specific parameters. How, when and where the modifications occur depends

on the designer, all these aspects are not included in the theoretical analysis.

They are the engine of the knowledge base.

One of the aspects of a rule based knowledge base system is that thie

system analyzes the rules. Initially there is no order in the rules, all are of equal importance. The expert system environment links the rules together depending on their hypotheses. The analysis of the rules is achieved by both forward and backward chaining through these hypothesis. It is the task of the knowledge base

' Spreadsheet TLP description Optimization User. specified va ues descriptlon Desired resuit Expert SyStem specified values

MOdificatiOn

Of values &

I/O actions

developer to prepare these rules for the linking and to have an initial idea of how the overall flow, see Fig. 8. The basic idea is to obtain all the parameters which describe a TLP. Then the optimum of column diameter and tether area is calculated. From this point on the knowledge base allows for alterations Of

values of specific parameters or provides the user with a description of the T'Lf,

either in the form of a table or schematic diagram.

4.2 Knowledge Base Description

The one of the main hypothesis in the knowledge base is platform defined.

When this hypothesis is true, the optimization process can start and later on

values can be modified. The hypothesis platform defined is related to a rule with the following conditions: Mass jactors, Buoyancy _factors and Added jactors, see Fig. 9. These conditions are hypotheses themselves. All these hypotheses have io be true in order to define the TLP. These hypotheses require the user to describe the TLP so that respectively the mass, the buoyancy and added mass 'TLP can be

calculated. The _factors hypotheses will force the user to define a TLp

configuration. When the hypothesis platform _defined is true several actions follow. First of all the three constrained equations (Equation (27)) are defined by means of their coefficients, i.e. al, a2, a3, b1, b2, b3, c1, c2 and c3. The next action is to find the optimum, followed by writing the TLP description to a file which allows

the TLP to be plotted.

The optimization procedure can be done very efficiently in NEXPER'T.

It prevents using too many rules and is easily expandable. Let's analyze the

optimization procedure. There are three equations which have to be satisfied. As

can be seen from Fig. 3 (page 20) there are three points where lines intersect. Only at one of these three points the three equations are valid. Therefore the

objective is to calculate these three points and check whether it complies withthe

... 6.1

si

....:!..:.,....,,.:!..::::...::::.:.]:::::::..::::.:T.i.:jiLj....;;::.,;::.::::;::i.E..::::;::1..ti:::fr:.:2J'AIL '...;fv:III,,....-E.i:12.:!:::::!::..,:

Fig. 9. Rule Description

Ir`u

Yes cokrntshaps?\

.)Do pontoon_present pont ?.. .,. .Do flare_exists flare exisb? ....,::,...,

.>Do Won shape braces.? 1.. r.:?

II!'

ii

=>Do shape cokortslcolur ? -';,".;1

\

.>Do (IcsPlYwicolurnn.spac?.1,.: '

.>Do belcalunn.re/4 bel9? ,

_\

4!!.

e

_{Yes colurnn_shape?.,} . .

steel?

.Ii.

s>Do pontecr_presert pail ? '

Yes rears factors? ... _I"'

.

...

1... ,..

s>Do braces_shape braces.? r) .>Do Rare_esists flare watt?

Do shace_coeurnnslcolur ?1 `,./

..."?

Yes bussercy factors ?--.=4

/Y02 addeci_factors? "

...

- - II-platforrs_defined ? ...-..

soDo POWUrcolumn.spaci?/ ..' ,,i.

. Ir

Yes csissetshape? .,.

-,Do portocri_shape panto?, -,\'::, 1.

r,

. ,

-)Do brazes share braces.?..-i!tt.' ? i

...)Do1.7shape column:1c? -:;/' ;ii

1 and 2 is calculated, yielding a value for the column diameter (resultdiam) and a value for the tether area (result area). There is a rule which checks the values

of resultarea and result.diam. When the values are correct, i.e. the values of

resultdiam and resultarea comply with the three constrained equations, the action of the rule implies that the value of result area is copied onto tetherarea and the value of resultdiam is copied onto column.diam. This procedure is repeated for

the intersections of lines 2 and 3 and lines 3 and 1.

A good knowledge base contains no redundancy. This optimization

procedure provides a good example of how to avoid redundancy. As stated before one must check the results of the different lines. The most efficient method (LI!. no redundancy) is the following. The initial value of i is 1 and the initial value

off is 2. CONDITIONS= <= HYPOTHESIS= eeleet_optinniin ACTIONS= Reset (define __j) Do (define jidefine _j) Do (('sAj\m"cAi\m-'a'\i\.1,0"e\j\.*)/('sAj\.vsib'\i\.v-'sAiVir""bAj\.v)) .(reiult.area)

Do (SQR.T(CbAj \ m'c'\)\.v)/Ca'\i\ .sonbAj \ .v-'sAj\.ronbAi\.v) \ ) (result.diam)

Reset (vsilid_tlp_selection)).

Do (valid_tlp_selectio(ajalid_tlp__seleetion)

Do (i+I) (i)

Do (j+1) (j) Reset (select optimum)

CONDITIONS=

3

HYPOTHESIS= define...) ACTIONS=

The rule define j controls the value of j. It allows the value of j to cycle in the following order : 2,3,1. The string 'alji.v defines the parameters al, a2 and a3.

There are some programming requirements like the single quotes and the

addition of a property but this does not influence the performance of this rule. The hypothesis valid tlp selection checks whether the current values of diameter

and area are the optimum ones. The Reset function enables the user to

re-evaluate that hypothesis. The Do (hypothesis narne) (hypothesis name) function allows the user to evaluate the hypothesis immediately. The Do

(j+1) (j)

function assess the value of j+/ to value off. The function Reset select_optimum

enables a loop until the value of i is greater than three.

The second major loop in the knowledge base allows for modifications

of values. The user can choose for a parameter to change a value when the TIP

is defined and the optimization procedure is completed. The whole new

optimization process will be executed. The idea to make this work is as follows. The user selects an item to be modified, e.g. the columns Then the knowledge

base reasons backwards and prompts the user to select which part (of the

column) will be modified. This can be the amount of columns or the shape of the columns, etc. When a new value is submitted to the system, all the hypotheses which govern the calculations are reset. The knowledge base gets the command to re-evaluate the hypothesis platform defined. A good visual feed back enhances

the effectiveness of the knowledge base. Therefore, the old value of the

parameter to be modified is presented to the user before this value is modified. This can be achieved by using the META SLOT. The META SLOT allows for variables to be displayed on the screen. Fig. 10 shows how the modifications can be made and where they can be found.

The knowledge base also allows for more information about TLP design.

A graphical representation of a TLP can be brought directly to the screen

showing the TLP definitions. There is the capability to plot the designed TIP on

flare exist

fixed ,.. flare height

iwarlabieLl.h.flare diameter amoUnt eilaPe presence dfctffiete flare presence /diameter> pontoons emOvnt shape presence braces amount max stress young tethers PuoYancY density wateroepth

wave height ,\>eiTte parameters

Wave period

coiumns

Fig. 10. Search Path for Modification

spacing and wave height. The knowledge base can execute an external program.

This program reads the significant information about the TLP form a file and

plots a TLP configuration. The plot program had to be developed, there was no program available which could perform this task. This program is written in the 'C' language and utilizes a data file generated by NEXPERT. The plot program is executed from within the NEXPERT environment.

One of the questions the knowledge base will ask the user is to make a

choice of tether material. This feature is a good example of how easy it the use of an expert system is. This question is prompted through the META SLOT of either the Young's modulus or maximum allowable stress of a tether. When one

of these two parameters become current the previous question will be shown.

When a choice is made about the material the knowledge base will immediately assigns values to both the Young's modulus and maximum allowable stress. The

different values of Young's modulus and the maximum allowable stress for

different materials are captured in the knowledge base. When the answer to the material question is NOTKVOWN, the knowledge base will prompt the user for

both values. Another feature from this example is the fact that it is rather easy to add a new material type to the knowledge base. One rule is enough to add

one material type and one doesn't have to take into account where this rule will

be located, as long as the rule has the same hypothesis as the other two.

There is nothing really fancy about the development of a knowledge base.

The basics are very simple though the implementation is a very complicated

because of the backward reasoning which occurs in the expert system

environment. Most of the work was done to make the knowledge base more user

friendly and to provide good communication with the user. Debugging the

knowledge base is very time consuming because one is not really aware of what is going on inside.

5 ILLUSTRATIVE EXAMPLES

The knowledge base was used to develop several TLP configurations. It should be noted that it is possible to adjust values of several parameters in order

to obtain the desired result, and that certain values were assumed because tlie actual data was not available.

5.1 TLP for 150 m water depth

Table 2 shows an overview of a TLP in a water depth 150 m. The

description in the right column is obtained by using most of the available

knowledge form the knowledge base. The Hutton TLP in the British sector ofthle

North Sea is installed in the same water depth (Niedzwecki, 1989). A big

difference in configuration is the number of columns The Hutton TLP has six

while the suggested configuration has only four. The suggested TLP has flared columns, braces and pontoons. The Hutton TLP has just pontoons. There is a big difference in column diameter. One of the most significant reasons for this is the difference in the number of columns Note the slender pontoon of thesuggested TLP.

Another 'TLP configuration was created. This configuration is an approach

to the Hutton configuration and can be used to check the model used

fnr

calculations. The middle column of Table 2 lists the parameters of this

configuration. This configuration has thick pontoons, no braces and straight

columns. The calculated column diameter is 16.64 m. This value is bigger than

the smallest diameter (inner columns) but is smaller than the diameter of the

outer columns

5.2 TLP for 536 m water depth

Table 3 shows an overview of a 'TLP in a water depth 536 m. The right

column shows a TLP configuration created by using as much as possible the build-in knowledge. The middle column represents a TIP configuration which

resembles the Jolliet TLP. The Jolliet TLP is located in the Gulf of Mexico in a water depth of 536 m (Offshore, 1990). It is used as a well head platform, therefore the deck load is rather small compared to other TLP configurations. A lot of relevant data was not available about the Jolliet TIP. This example is used to develop some numbers about a TlY in this water depth.

5.3 TLP for 870 m water depth

The third water depth for an example configuration was chosen to be 870 m. The knowledge base generated description of this configuration is shown in

Table 4. The TLP has four round and flared collimns It also has slender

pontoons and braces. The calculated column diameter is 1834 m. This

configuration resembles Shell's Auger TLP which starts producing in the Gulf of Mexico in 1993 (Offshore, 1990). Like the Jolliet TLP there was no data readily

available about the column diameter though notice that the knowledge base suggests a diameter of 17.64 m for a water depth of 536 m and a diameter of

18.54 m for a water depth of 870 m.

5.4 TLP for 1500 m water depth

The last example describes a TLP configuration in a water depth of

1.524 m. The description of such a TLP can be found in Table 5. The values for

the tether area and the column diameter seem to be too large. This optimum

is controlled by the minimum bottom tension and the maximum top stress in the tether.

FONTS bold calculatedby knowledgebase

normal suggestedby user

italic suggestedby knowledgebase BRACES

amount n/a n/a 8

shape n/a n/a round

PONTOONS

amount 4 4 4

shape square square round

diameter ? 8 1.33

TETHERS

amount 16 16 4

area ? 0.09 0.26 m"2

length ? 116.8 117.5 m

material Steel pipe Solid Steel Solid Steel

-buoyancfactor ? 0 0

density ? 7900 7900 kg/m 3

max.stress ? 155.106 155.106 Pa

min.tension ? 9.2 -106 9.2 .106 N

young'smod. ? 2.1E+11 2.1E+11 Pa

MISCELLANEOUS

waterdepth 150 150 150 m

min waveperiod 13.9 13.9 13.9 S

max waveheight 16.6 16.6 16.6 m

topsideload ? 2.20E+08 2.20E+08 N

riser top tens. ? 1.43E+07 1.43E+07 N

Table 2. 112 IN 150 m

Item calculated suggested Unit

Hutton TLP in 150m TLP in 150m

COLUMNS

shape ? square round

amount 6 _§ 4 distance ? 65 65 draft 33.2 33.2 32.5 diameter 17.7& 14.5 16.64 19.27 length 69 69 65 flarediameter n/a 16.64 25.63 flareheight n/a 0 16.25

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Table 3. TLP IN 536 m

Item calculated suggested Unit

Jolliet TLPiñ536m TLP in 536 m

COLUMNS

shape square square round

amount 4 5 4 distance 42.7&54.8 48.8 42 m draft 24.1 24.1 21 m diameter ? 1723 13.1 m length ? 42.1 44.4 m flarediameter n/a 17.23 23.46 m

flare height n/a 0 10.52 m

BRACES amount shape round 8 round PONTOONS amount 4 4 4

shape square square round

diameter ? 1.32 1.52

TETHERS

amount 4 4 4.

area 0.23 0:23 mA2

length ? 511.9 514.95 m

material Solid Steel Solid Steel Solid Steel

-buoyancfactor ? 0 0

density ? 7900 7900 kg/niA3

maximunstress ? 155.106 155i0 Pa

minim umte nsio n ? 9.97 405 9.97 405 N

young'smodulus ? 2.1 .1011 2.1 i0' Pa MISCELLANEOUS waterdepth 536 536 536 m min waveperiod ? 13.9 13.9 S max Waveheight ? 12 12 m topsicleload 5.28 .10 5.28-106 5.28 .10 N

Table 4. TLP IN 870 m

Item calculated suggested Unit

Auger TLP in 871m TLP in 871 m

COLUMNS

shape round round round

amount 4 4 4 distance 65 65 65 m draft 27 27 32.5 m diameter ? 19.76 18.54 m length ? 50 65 m flarediameter n/a 19.76 24.66 m flareheight n/a 0 16.25 m BRACES amount shape PONTOONS amount shape diameter TETHERS amount area length material buoyancfactor density maximunstress minimuntension young'smodulus 4 square ? 51 MISCELLANEOUS water depth 871 min waveperiod ? max waveheight ? topsideload

riser top tension

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8 round 4 4 square round 10.4 1.62 4 4 0.36 0.3 m^2 843 837.5 m

Solid Steel Solid Steel

-0 0 -7900 7900 kg/m^3 155 .106 155.106 Pa 1O.641 1O.641 N 2.1E+11 2.1E+11 Pa 870 870 m 12.9 12.9 S 33.5 33.5 m 1.00E+08 1.00E+08 N 4.06 407 4.06 407 N

Item Unit COLUMNS shape round amount 4 -distance 65 m draft 32.5 m diameter 44.26 m length 65 m flare diameter 58.86 m flareheight 16.25 m BRACES amount 8 shape round PONTOONS amount 4 shape round diameter 1.62 TETHERS amount 4 area 3.74 mA2 length 1491.5 m

material Solid Steel

buoyancfactor 0.9 -density 7900 kg/m"3 maximunstress 155.106 Pa minimumtension 11.948.1d N young'snodulus 2.1 -1011 Pa MISCELLANEOUS waterdepth 1524 m min waveperiod 13.9 S max waveheight 15 m topsicleload 1.004 O. N

riser top tension 6.44 -107 N

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