Mgr.inz.arch. Makowska Agnieszka
Cracow University of
Technology
COMPUTER AIDING FOR ESTIMATING THE CURVILINEAR
ENGIEERING STRUCTURES
1.Introduction
This paper is the continuation of determining of the curvelinear
objects parameters.
The most of contemporary
building use soft form and irregular shapes.
The base of the cost
calculation is the exact calculation of length or the surface area or the
volume. The new techniques and technology use very expensive materials, hence
it is very important to do the precise calculation to reduce the cost of
investment.
Exact calculation of
the surface or the volume of straight-line forms is easy, in the case of
curvilinear objects it can be controversial.
The attempt of
description of curvilinear objects made with the help of cubic spline
interpolation has been presented in this paper.
2.
Elementary theory of cubic spline
We have got n+1 points in the interval <a,b>
: a= x0 , x1 ,
. . . , xn = b, call this nodes and value function y=f(x) in
this points: f(x0)=y0 , f(x1), ...,f(xn).
Pair (xk, yk) we call data points.
We seek estimate values function f(x) class C2 between nodes as of polynomial of third
degree for x <xi-1, xi>. Let
us mark us:
for i=0,1,2,...,n (1)
from definition of function f(x) to appear that f’’(x) is the continuous
function in interval <a ,b> and
linear for x <xi-1, xi>, so we have:
(2)
where:
Integrating twice (2) we obtain:
(3)
where
(4)
Using function’s
conditions of continuity and first derivative by algebraic conversion we have
linear system of equation :
for i=1,…,n-1 (5)
where:
for
i=1,2,..,n-1 (6)
System (5) has got n-1 equations and n+1 unknown
coefficients: M0, M1,..., Mn .
Often we accept two additional conditions :
M0=0, Mn=0
(f”(x0)=0, f”(xn )=0: Natural cubic Spline).
for i=2,3,...,n-1 (7)
for
i=2,3,...,n-1 (8)
and for symmetric expression :
. (9)
From the first equation of system (5)
we have:
, or
by recurrence end algebraic
conversion we obtain:
, for k=1,...,n-2 (10)
Using principle of mathematical induction easily proof the truth of this
expression.
From the last equation of
system (5) ,we have:
(11)
after calculation coefficients
Mk we construct
function f(x):
(12)
Fig.1 The visual graph of function
f[x]
where fi is the right side of
expression (3).
We define Heaviside’s function:
and then function f(x) is expressed one rule:
(13)
Now we can write in any programming language
the basic procedure named splajnP, in which the input parameters are data
points: (x0,y0) , (x1,y1) , . . . , (xn,yn) ,
and on the exit of that procedure we will get function f(x) and her graph.
Fig.2 Procedure SplajnP written in Mathematica program
3. Application
and estimation of error
Example 1.
In publications or
WEB we can often see graph of function, but we do not know value of this
function. We will show in three steps, how can we find a rule of function.
1. step: we import a
scanned graph of function to the Mathematica program
Fig.3 Graph of unknown function g[x]
2 step: we read and write coordinates of screen witch Fig.3:
Fig.4 Coordinates of screen function g[x]
We read coordinates of beginning (xB, yB) and end (xE,yE) of graph and corresponding them coordinates of screen
are: (xBS,yBS) and (xES,yES).
Now we define a procedure using linear interpolation which will transform
coordinates of screen on coordinates of
real:
Fig.5 ChangeCord procedure
After executing of this procedure with parameters DataScrCord we obtain
real coordinates:
Fig.6 Real coordinates
Step 3: we evaluated procedure SplajnP [DataRealCord] and we obtain
function f[x] and her graph :
Fig.7. f[x] Function graph
The compatibility of Fig.3 and Fig.7 is almost ideal, author knows g
function:
g[x]=x Exp[-x] , therefore we can find estimate error in this method:
Fig 8. Estimate error
Adding graphic and numeric
instructions to procedure SplajnP we can obtain new procedures.
Example 2. In the procedure SplajnTheWall the first parameter are data points, and
the second is height of the wall; output parameters are the graph and area of
the wall surface.
Fig.9 Result of Procedure
SplajnTheWall[data,4]
Example
3. We construct the circle with centre on curve and in normal plane which moves
after curve.
Fig.10 The circle in normal plane
In
the SplajnPipeline procedure the first parameter are data points, and the
second is radius of pipeline; parameters output are graph and area of the
pipeline surface.
Fig.11 Result of Procedure
SplajnPipeline [data,0.7]
Example 4. In the SplajnVolume procedure input parameter are data points, output
parameters are graph and volume of the solid formed by the revolution of the
curve y=f[x] around x-axis.
Fig.12 Result of Procedure
SplajnVolume[DataHeart]
Fig.12 represents the heart of Zygmunt’s bell.
These calculations
were made without taking into account of the handle of the bell heart. The mass
of the handle was estimated as 20 kg.
The density of the heart is unknown, there are some admixtures:
phosphorus, sulphur, etc. According to the accessible data new heart mass is
about 350 kg. Specific mass of the heart is assumpted as 7.7 [g/cm3].
Counted mass of bell:
mass=47371.7[cm3]*7.7[g/cm3]/1000+20[kg]=384.762 [kg],
error of calculations=(384.762 –350)/350*100% = 9.9 %
The heart of Zygmunt Bell is in the Wawel
Cathedral in Cracow.
Conclusion
The presented above method of calculations enables the precise defining
of the necessary object parameters to its optimalization from the engineer’s
point of view, for example the quantity of necessary material to object
construction. The presented method of calculations permits to qualify of object with
engineering point of view permits his optimization necessary parameters. The
method creates the possibility of the objects modelling as well as quick
amendments of parameters in the project process. On the base of support of
prepared procedures in Mathematica program, it permits to calculate the
interesting us parameters.
Literature
[1].Stephen Wolfram
Mathematica 4 book: Cambridge Universuty Press 1999.
[2]. Z. Fortuna D.Macukow. J.Wasowski: Metody
numeryczne WNT Warszawa 1982.
Abstract
The natural cubic splain theory elements apllied to building engineering have been presented in the paper. Coefficients of cubic spline have been determined in recurring form. Graphics and numerical procedures were executed in programme "Mathematica". Application of that theory for estimating of curvilinear objects has been presented on chosen examples.