International Journal of Traffic and Transportation Engineering

2012;  1(3): 40-45

doi: 10.5923/j.ijtte.20120103.02

Operations of Winter Maintenance of Airport

Peter Koščák 1, Štefan Berežný 2, Ján Ferenc 1

1Department of Aviation Engineering Faculty of Aeronautics Technical university of Kosice, 041 21, Slovakia, Airports Operation

2Department of Mathematics and Theoretical Informatics of Electrical Engineering and Informatics Faculty Technical university of Kosice, 041 21, Slovakia, Mathematics

Correspondence to: Peter Koščák , Department of Aviation Engineering Faculty of Aeronautics Technical university of Kosice, 041 21, Slovakia, Airports Operation.


Copyright © 2012 Scientific & Academic Publishing. All Rights Reserved.


The direct ensuring process of air transport by airport operators means to provide all components for safety landings, movements and clearance of particular flights. The mentioned factors depend on the quality and quantity of airport personnel and technical resources. Financial turnover of the airport depends on the number of flights and passengers. The higher the frequency, the higher profit items, whether it is the airport taxes or business of the company. However, to ensure regular income, the airport company has to ensure safe and regular air travel, especially without long-term and frequent limitations. These tasks are of particular importance in the winter, when the weather - snow and ice limit the effects of airfield serviceability.

Keywords: Winter Maintenance of Airport, the Optimal Deployment of Technical Means, Regression Analysism

Cite this paper: Peter Koščák , Štefan Berežný , Ján Ferenc , "Operations of Winter Maintenance of Airport", International Journal of Traffic and Transportation Engineering, Vol. 1 No. 3, 2012, pp. 40-45. doi: 10.5923/j.ijtte.20120103.02.

1. Introduction

Winter maintenance of airport (WMA) must be organized and carried out in order to maintain the all weather operational capability of airport operating areas in a comprehensive, cost-effective and expedient use of people and equipment intended for winter maintenance.
Composition of the WMA group must ensure continuity of the winter maintenance of the airport. Group WMA consists of a shift and the master (head) and drivers – mechanists of a single technique .

2. Snow Properties

Formation of snow must be seen as a part of the hydrological cycle which happens in the atmosphere. Evaporation of water from the earth gets a large amount of water vapour into the atmosphere. If atmosphere is overloaded or water vapours decrease the temperature to so-called dew point, water vapours in the atmosphere condense and there is rain. If temperature is below 0 ℃, the gaseous state of water change right in the solid, recrystallization occurs. This process is linked to so-called crystallisation centres, which are ice cores or dust. Because of valence forces huge number of water molecules creates the formations of a crystal system resulting to snow crystals. The whole process can be represented as follows: saturation of water vapour + centres of crystallization + temperature < 0℃
Snow is hydroscopic and quite quickly depending on the temperature rise and its density increases. Snow density can be determined by sampling a certain volume of snow and measuring a volume of water after it melted.[1][2]
Figure 1. Snow at the Apron
Snow density ranges from 80 kg.m-3 of fresh dry snow up to 800 kg.m-3 slush, i.e. mass, which consists of ice crystals and water. Both these components may be represented in varying proportions in slush, which affects the resulting density and thus the size of the resistance to acceleration of the aircraft.[3]
The amount of snow, the height of the water column on the Runway and snow on load-bearing surfaces and a fuselage of the aircraft may have the effect of extending the total length of take off about 70 %.
The relationship of weight of snow and temperature is determined:
where m is weight of snow, φ - is the density of snow and V - volume of a snow layer
With dry snow the value of density is rapidly variable, because snow raises its density by its own weight. The weight of snow is an important variable that determines the quantity and type of equipment deployed. Deployment of working mechanisms and speed of work must be adapted to the total time devoted to the maintenance of a movement area.[4][5]
Table 1. Density of snow
1dry350 kg/m³
2wet500 kg/m³
3slush.800 kg/m³
A layer of snow on the surface gives:
●resistance exerted on the wheels of the landing gear for the acceleration, the size of the resistance depends on the specific weight and thickness of a snow layer, the characteristics of the landing gear, weight and speed of aircraft movement,
●deterioration of the aerodynamic characteristics of aircraft during acceleration as a result of pollution of bearing surfaces and a fuselage of aircraft by splattering snow from the front bogie wheel,
●reduce braking action of the runway surface (mainly due to the coverage of surface by ice) creates a risk of extension of run down for landing or interrupted take-off.[6]

3. The Analysis of Technological Practices of Winter Maintenance of Airports

Enforcement of activities associated with WMA depends on:
●a size of the airport - the maintenance area → runway, taxiway, apron and service communications,
●density of air traffic for the airport → number of movements of aviation technology for the assessment period,
●an average amount of snowfall and snow under a year.
Following two factors determine the staffing and technical support WMA:
●whereby more movements of aviation technology, thereby reducing the time devoted to the maintenance of airport,
●more snowfalls with the higher volume of snow and extensive areas of maintenance, the more frequent changes of WMA.
For purposes of calculating the optimal deployment of technology to the winter maintenance of airports and the subsequent determination of the dimensions of the model airport, the following size of the airfield is used:
●Runway (RWY) 3000 x 45 meters
●Taxiways (TWY) - parallel taxiway with runway 3000 x 23 m + coupling paths 2 x 300 x 23 m,
●Apron (APN) 200 x 100 m.
Total area is 237,800 m²
Figure 2. Airport sweepers
The size of the model airport movement areas is given by a variable that can be changed in the process of calculating for each of the results depending on the actual values of the airport.
To ensure WMA, considering the density of air traffic is important at the airport - especially the number of movements of air technique on movement areas. These values are important in determining the movement of aviation technology during the one hour on one RWY, TWY and APN - it means time which is available for the WMA shift to dispose snow and make rated airport movement areas operative. An important factor emphasizing the seriousness of time of the maintenance is decreasing the time for aircraft waiting to land - inability of a movement area to take the flight.[7]
Figure 3. Airport’s area

3.1. The Performance Characteristics of Technology

Despite the technological process of disposal of snow in the movement area of airport, the performance characteristics of snow surfaces are primary rated, as the performance of airport sweeper motor is necessary to count with respect to amount and weight of removed snow. This quantity is given by the ability of snow blades to draw aside snow to the weight limits of the snow, which is affected by the technical design of airport snow blades.
Table 2. The values of snow on the model airport due to its size and density
Snow Depth in m
obj. v m³4 0508 10012 15016 20020 25024 300
I. DryWeighta) kg1 417 5002 835 0004 252 5005 670 0007 087 5008 505 000
b) kg2 025 0004 050 0006 075 0008 100 00010 125 00012 150 000
c) kg3 240 0006 480 0009 720 00012 960 00016 200 00019 440 000
TWY2 4844 9687 4529 93612 42014 904
II. WetWeighta) kg869 4001 738 8002 608 2003 477 6004 347 0005 216 400
b) kg1 242 0002 484 0003 726 0004 968 0006 210 0007 452 000
c) kg1 987 2003 974 4005 961 6007 948 8009 936 00011 923 200
APN6001 2001 8002 4003 0003 600
III. SlushWeighta) kg180 000360 000540 000720 000900 0001 080 000
b) kg300 000600 000900 0001 200 0001 500 0001 800 000
c) kg480 000960 0001 440 0001 920 0002 400 0002 880 000
∑ Area7 13414 26821 40228 53635 67042 804
Weighta) kg2 496 9004 993 8007 490 7009 987 60012 484 50014 981 400
b) kg3 567 0007 134 00010 701 00014 268 00017 835 00021 402 000
With a width of snow ploughs of five and more meters, when the weight of snow is more than 350 kg to 1 meter width of the cleaned surface there is a real threat of damage to the plough mount or its parts.[8][9]

3.2. The Performance Characteristics of Equipment

Despite the technological procedure of liquidation of snow on the movement areas in order to evaluate first the performance characteristics of snow blowers, since the motor performance of airport sweepers should be counted with respect to sweep and number and weight of snow. This amount is the possibility of snow ploughs snow pushed back into the weight limits of snow, which is influenced by the technical design of airport snow ploughs. The width of snow plough of 5 or more meters in the weight of snow above 350 kg per 1 meter of purified surface width is a real threat of damage to the handle or blade or its parts.
To approximate the distribution of basic snow blowers it is necessary to take into consideration their performance characteristics and engine performance, operating speed and overall performance. The techniques are divided into three performance groups listed in the Table No. 3.
Table 3. The resulting three values
Performance group123
Engine powerto 100 kWto 600 kWto 900 kW
Cutting Width2000 mm2500 mm3000 mm
Put the snow away30 m40 ÷ 50 m50 ÷ 60 m
Operating performance for throwing the dry snowto 1 500 t.h-1to 5 000 t.h-1to 10 000 t.h-1
Similar to the distribution of snow blowers, the division of motor sweepers at the airport is as follows:.
Table 4. Performance characteristics of airport sweepers
Performance. group123
Engine power260 kW315 kW315 kW
Cutting width Brushes3400 mm3500 – 4500 mm3600 – 5500 mm
Working speed25 – 45 km/h.35 – 50 km/h35 – 60 km/h
Sweeper’s Performanceto 180 000 m2/hto 220 000 m2/hto 260 000 m2/h
We used the performance characteristics and engine performance, operating speed and overall performance of the airport surfaces and sweepers to converge their basic ranking. That technique is divided into three performance groups.
Based on auxiliary calculations of equipment performance there are processed the resulting values of time needed for the maintenance movement area of the model airport based on height and density of snow and performance of equipment.[10]
Currently, for the assessment of the effectiveness of deployment and variation of technical means an information technology can be widely use. The design of optimal set of means of WMA can be solved according to specified input and output for a specific period such as five years. Then we can compare the actual cost and the solution of proposal of techniques to WMA for the two largest Slovak airports with mathematical model outputs of the winter airport maintenance.[11][12]
Table 5. The resulting three values – length of maintenance of the entire airport area based on the performance of technique
DryWetSlushtype of snow, according to its density
0,030,060,030,060,030,06Snow Depth in m
11,0951,2451,2451,2451,2451,395RWYlowest performance of technique
20,9381,0881,0881,0881,0881,238RWYmedium performance of technique
30,8490,9990,9990,9990,9991,149RWYthe highest performance of technique

4. Optimization of Employment of Means WMA

As a means to solve the tasks of optimization of airport maintenance we can use fictional model of employment of proposed technique using the standard size of the international airport.
We assume that we are cleaning constant size of airfields:
Cleaning of the airport area can only be done by whole sets of airport technique, which is intended to winter maintenance of the airport (a kit consists of two airport motor snow blowers and one sweeper).[13]
Figure 4. Cache regression line and residues detected values
We expect that performance of technique can have three performance levels (1,2 and 3), these values may take the variables that we denote V
The snow itself, we monitor the quality and quantity. The quality of the snow is marked K and it will be the type of snow.
The amount of snow we watch as its height and denote it by the letter S.
On the basis of technical parameters of technologies designed to maintenance of airport area, we calculated the base table that contains time information (T).
These data correspond to the time needed to clear the airport if previously defined variables take values:
V {1;2;3},
K {1;2;3}, and
S {0,03;0,06}.
We created a table, which corresponds to 18 theoretical measurements for the WMA at Kosice airport by given technique.
Under these assumptions and given numeric data, which are clearly shown in Table 2, we can establish a multiple linear model using the method of least squares.[14]
Figure 5. The graph of the least square method for linear dependence
Table 6. Table of values of observations
This model has the form:
where α, β, γ are unknown coefficients of the model (α, β, γ R) V, K, S are independent variables defined above and T is the dependent variable, which represents the time needed for WMA of the airport in determined parameters of the model.[15]
The method of least squares estimate the parameters α, β, γ, δ and denote them as the value of a, b, c and d.
Then the values of i (1,2, ... , 18) we get the calculated model, which has the form:
Let us mark: a vector →
are column vectors of the size of 18x1, the vector is a vector of the counted quantity, and vectors and the vectors are broken down above the table.
With this designation, we can then write the model described above in the form:
Then, for the unknown vector is:
We calculate these values:
Specifically, we can write that
a = 1.929853
b = -0.2565
c = 0.17875
d = 5.944444
We get a model that has the form:
ti = 1,929853 – 0, + 0, + 5,
At first glance it may seem that this model does not describe our situation properly, because the parameter value is not zero.
We could assume that if we have no snow, so WMA is the zero-time. This is not possible, because this would be contrary to the assumptions which we put to our model. In them it is stated that the variables v and k do not have zero values, i.e. if we have the snow height of 0, then maintenance takes place in non-zero time, because technique would be idle.[15]
Table 7. Time needed to maintenance of areas of a model airport by one set of techniques depending on the amount of snow
Performance of technique111222333
Type of snow123123123
Maintenance time in hours
Snow height in meters0,011,91152,09032,26901,65501,83382,01251,39851,57731,7560
Figure 6. The graph of the dependence on performance techniques 2
So it is logical to assume that WMA is not made only at non-zero value of the parameter s, so the maintenance is not carried out, which means zero time, but not by the regression model, but upon the definition of the situation.
We have yet to determine credibility of the given calculated regression model .
The coefficient of multiple correlations
rT, VKS = 0,992938835
shows strong relationship between the variable T and the independent variables V, K and S. The strong relationship is between independent variables and the time T.[15]

5. Conclusions

Currently, for assessment of the effectiveness of deployment and variation of technical means, information technology can be widely used. The design of optimal set of means of WMA can be solved according to specified input and output for a specific period of such as five years. Then we can compare the actual cost and the solution of proposal of techniques to WMA for the two largest Slovak airports with outputs of a mathematical model of the winter maintenance of the airport.
The designed model to optimize the use of technical means of winter maintenance of the airport and to establish the optimal time depends on the capacity of airfields. For the established technique, also envisaged economic benefits, particularly in connection with the setting of input parameters of the airport in increasing density of air traffic, the management of airport can find an optimized set of techniques to airport maintenance and conversely of existing airport maintenance.


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