KR20130093567A - Stochastic estimating model for calculating duration of super-tall building project using vertical climate factors - Google Patents

Abstract

PURPOSE: A skyscraper construction project construction duration predicting system considering a weather factor's vertical changes quantitatively predicts a weather factor's possible influence on construction activities based on weather information in a database and generates quantitative data by predicting possible changes of the weather factor due to increases in altitude. CONSTITUTION: A climatological data processing module (A1) generates weather distribution data of a reference weather value using weather values in a weather database (D1). A climatological data simulation module (A2) generates a set of weather values regarding a specific schedule. An altitude-specific weather data generation module (A3) generates another set of weather values regarding a specific altitude. A non-workable day calculation module (B1) compares the altitude-specific set of weather values with a pre-determined non-workable day standard. A process simulation module (B2) successively carries out a simulation process on the entire processes. A construction duration analysis module (B3) analyzes data about process-specific duration for each process and the entire duration of a construction project transmitted by the process simulation module. [Reference numerals] (A) Weather data generating module; (A1) Weather data processing module; (A2) Weather simulation module; (A3) Weather data by altitude generation module; (B) Air calculation simulation module; (B1) Non-working day calculation module; (B2) Process simulation module; (B3) Construction duration analysis module; (D1) Weather database; (D2) Process database; (D3) Workability standard database

Description

Estimating Model for Calculating Duration of Super-tall Building Project using Vertical Climate Factors

The present invention relates to a system for predicting the construction period of a skyscraper construction project in the field of construction management. The present invention relates to climate factors such as temperature, wind speed, and rainfall, which are factors influencing the process planning of a skyscraper construction project. Through this, we establish a database that can predict the current climate, and analyze the effect on the height work of the skyscraper construction project by estimating the amount of climate change due to the high increase.

In addition, it relates to a system that predicts the construction period reflecting the influence of climate factors by type and altitude by linking the analyzed altitude climate information with the unworkable standard.

In general, construction projects are affected by the construction period depending on the climatic environment of the performing region. In particular, climate factors such as temperature, wind speed, and rainfall have different ways of influencing the nature of the work, and the frequency of occurrence of a specific climatic environment varies by region and time, and therefore, due to the difficulty of quantitative prediction and management in practice, Air delays occur frequently, such as reduced productivity or interruption of work, and problems occur in terms of safety management of employees.

For this reason, in the planning and management of construction projects, various studies on the development of a system that can quantitatively analyze such climate factors and reflect them in the project's process plan ("Probabilistic Air Estimation for Tall Building Frame Construction Using Climate Information"). Model ”-Korean Institute of Architecture (2007)), but the following problems occur in the case of high-rise projects.

High-rise building construction projects are performed at higher altitudes than the construction of general buildings, and these work is affected by climatic environments that are different from the climatic environment on the ground. Consideration should be given to changes. However, since the change of climate factors due to the increase of altitude is not quantitatively estimated and reflected in the process plan, problems such as productivity decrease and construction delay during construction are more frequent than general projects.

In addition, the contractor establishes inoperable standards due to climatic factors such as temperature, wind speed, rainfall, and humidity according to the nature of each work and utilizes it as a guide for process planning and management. However, despite the complex linkage between climate factors and methods affected by work, it is not necessary to consider the exact work and the relationship between work and climate when reflecting this in the process plan. It is difficult, especially for long-term construction such as high-rise projects, which reduces the reliability of process planning. In addition, high-rise projects in regions with different climate environments, such as those carried out overseas, have a greater error rate due to less experience. Therefore, it is necessary to develop a system that can accurately calculate the dead date by linking the quantifiable data on the climate environment and the dead standard.

Finally, even if the data are generated by analyzing the air delay risk due to climate factors, it is not easy to apply them in connection with the process planning techniques currently used by the contractor. Since deadlines can vary depending on the type, timing, duration, and altitude of the work, these are combined with current process planning techniques, such as CPM / PERT, in order to reflect the risk for each work in the process. You need a system.

Therefore, it is necessary to develop a system that can be reflected in the process plan by quantifying the data on the climate environment by climate factor and altitude and linking it with the impossibility criteria reflecting the characteristics of each work.

As described above, the object of the present invention created according to the necessity of developing a new system is as follows.

First, it is an object of the present invention to establish a database of past climate values and to provide a system that can quantitatively predict climate factors affecting activities by using information stored in these databases.

Secondly, another object of the present invention is to provide a system for generating quantitative data by predicting the amount of change in climate factors due to an increase in altitude.

Third, another object of the present invention is to provide a system for estimating whether work incapacity occurs (calculation of work inactivity) by linking work / work impossible criteria by work type / climate factor with a corresponding climate value.

Fourth, it is another object of the present invention to provide a construction period prediction system reflecting the climate factor according to the altitude by linking the date and the process table impossible work.

Technical features of the present invention are as follows.

The present invention provides a climate database (D1) in which the regional climate values measured for many years are classified and stored by date and time measured according to climate factors; By calling the climate value of the climate database (D1), the representative climate value of the corresponding date is generated from the hourly climate value of the predetermined date of a specific region, and the climate distribution of the representative climate value is collected by collecting the representative climate value for several years for each predetermined period. A climate data processing module A1 for generating data; The schedule simulation and location information for each activity of the analysis target are received from the process simulation module B2, and the climate distribution data of the corresponding section to which the schedule of the activity belongs is received from the climate data processing module A1. A climate simulation module A2 for generating a variable to generate a climate value for the schedule; Altitude-specific climate data generation module (A3) for generating a climate value of the corresponding altitude based on the climate value and location information on the schedule received from the climate simulation module (A2); An incompetent work calculation module (B1) for determining whether work incompetence occurs by comparing a corresponding climate value of a corresponding schedule received from the altitude-specific climate data generation module (A3) with a preset work impossibility standard; A process database D2 for storing schedule information, location information, and work type information for each activity to be analyzed; The schedule information and location information among the schedule information, location information, and work information for each activity called from the process database (D2) are transferred to the climate simulation module (A2), and the schedule information and work information are included in the work inability calculation module ( A process simulation module (B2) which transmits to B1) and sequentially performs the simulation from the preceding process to the following process by reflecting the determination result value of whether the work incompetence calculation module (B1) has occurred; And a construction period analysis module B3 for calculating a probability distribution or an average value by analyzing data related to the construction period and the total construction period received from the process simulation module B2.

According to the configuration of the present invention, it is possible to quantitatively predict the impact on activities by building a database of past climate values and using the information stored in these databases, and to predict the amount of change in climate factors according to the increase in altitude You can generate data. In addition, it is possible to calculate whether work incapacity occurred (calculation of work inactivity date) by linking the work inability standard by work type / climate factor with the climate value of the schedule, and reflecting the climate factor according to the altitude by linking the work inability date and the process table. The construction period can be predicted.

1 is a block diagram showing the overall configuration of the present invention.
2 is an exemplary diagram of information stored in the climate database D1.
FIG. 3 is a diagram illustrating climate distribution data (frequency, relative frequency, cumulative frequency) of representative climate values generated by collecting representative climate values for several years by period (by section).
4 is a screen exemplifying contents stored in the task impossible reference database.
5 is a screen illustrating the contents stored in the process database D2.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Reference will now be made in detail to the preferred embodiments of the present invention, examples of which are illustrated in the accompanying drawings.

As shown in FIG. 1, the database includes a climate database D1, a process database D2, and a non-workable reference database D3. The climate data generation module A includes a climate data processing module A1. ), A climate simulation module (A2), and altitude-specific climate data generation module (A3), and the air calculation simulation module (B) includes a work failure calculation module (B1), a process simulation module (B2), and a construction period. It consists of analysis module (B3), each module calls information from another module or database according to the built-in program and performs the corresponding function.

The climate database (D1) stores historical regional climate values measured over many years, classified by date and time, measured according to climate factors.

Here, climate factors stored in the climate database (D1) refer to temperature, wind speed, and rainfall that can affect the activity schedule of the target of the analysis. Depending on the impact of the unworkable days, climate factors such as humidity may be added. have.

Attributes of climate database D1 include area, area code, climate measurement time (year, month, day, time), interval, interval code, climate factor, climate code, unit, climate value, etc. as illustrated in FIG. Include.

Areas are information on the areas where climate information is measured. Climate data measured in areas such as Seoul, Incheon, Daejeon, Daegu, Busan, and Jeju, where high-rise projects are currently in progress, can be used. Can also be used by the Meteorological Administration.

Climate measurement time is the year, month, day and time at which the climate value was observed.

Climate factors include factors such as temperature, wind speed and rainfall. The climate code may be arbitrarily set by the user as a code for identifying a climate factor. In a specific embodiment of the present invention, a climate code is given with "TP".

The interval is set to define the range of data for generating the distribution value, and the interval and interval symbol set by the user are used. For example, 1st to 15th of each month is defined as the first half (FH) and 16th or later is defined as the second half (SH), so that one year and 12 months can be divided into a total of 24 sections.

Climate data can use climate data measured by the Meteorological Administration, and can also input observations on temperature, wind speed, and precipitation measured in hours. The time range of the climate data can be set according to the user's needs. For example, you can use information from the past 10 years from 1 January 2001 to 14:00 on December 31, 2010, and you can add up-to-date observations as needed. The unit is ° C for air temperature, m / s for wind speed, and mm for rainfall.

The climate data processing module A1 calls the climate value of the climate database D1 and generates a representative climate value of the corresponding date from the hourly climate value of a predetermined date of a specific region, which is generated by the climate data processing module A1. Representative climate values are defined as the maximum and minimum values of the day's temperature in the case of temperature, the average value of the wind speed in the day in the case of wind speed, and the daily cumulative value of the day in the case of rainfall.

The reason for extracting and using only specific information (maximum value, minimum value or average value) from the data of climate factors is set in consideration of the relationship between the climate affecting factor and the condition that causes the work failure. Therefore, the average value of the air temperature may be extracted and used according to the setting criteria of the working days, or the maximum value of the wind speed may be extracted and used.

When the representative climate value is generated in this way, the climate data of the representative climate value is generated by collecting the representative climate values for a predetermined period (by section). For example, a climate distribution such as the frequency, relative frequency, and cumulative frequency of representative climate values, as shown in FIG. You can generate data.

Climate distribution data generated by the climate data processing module (A1) is stored separately in the climate data processing module (A1), and the climate distribution data of the corresponding section to the climate simulation module (A2) at the request of the climate simulation module (A2). To pass.

The climate simulation module A2 receives schedule information and location information for each activity of the analysis target from the process simulation module B2, and receives climate distribution data from the climate data processing module A1 of the corresponding section to which the schedule for the activity is performed. Generates a random variable and generates a climate value for the schedule.

Monte Carlo simulation is performed while the climate simulation module (A2) generates climate values for the schedule. Monte Carlo simulation, as is commonly known, is a procedure used to simulate stochastic systems for decision making under uncertain circumstances. Say. The core of Monte Carlo simulation is the experiment on the probabilistic elements of the model, which is performed using a tool that generates stochastic or right-linked results. random numbers) or pseudo-random numbers generated by a computer.

Scheduled climate values (data on temperature, wind speed, and rainfall) generated through Monte Carlo simulations are separately stored in the climate simulation module A2.

In addition, the climate simulation module A2 transmits the generated climate value and location information to the altitude-specific climate data generation module A3.

Altitude-specific climate data generation module (A3) generates the corresponding altitude climate value based on the climate value and location information on the schedule received from the climate simulation module (A2) in the following way, the climate data processing module (A1) Assuming that the climate distribution data generated from) is measured at the reference altitude of 10m, the vertical distribution for each climate factor is calculated to generate distribution data for each elevation.

In the case of air temperature, the change in temperature by altitude is calculated according to the adiabatic reduction rate formula (-6.5 ℃ / 1000m) of the standard atmosphere.

The dry thermal insulation rate is -9.8 / km and the wet thermal insulation rate is -4.5 / km (AD McNaught and A. Wilkinson. 1997), and the actual atmospheric condition sees an average temperature reduction rate of 6.5 on average. It is affected by humidity, so you can use the value adjusted according to the humidity.

In the case of wind speed, the vertical distribution of wind speed is calculated according to the formula of Claes Dyrbye & Svend Ole Hansen.

Z = height from the ground

Vz = wind speed at height (Z)

Vg = wind speed at reference height (0m)

1 / α = distribution decision index according to surface condition (1/3 of urban center)

In the vertical distribution equation of wind speed, the distribution determination index (1 / α) according to the ground surface condition is set in consideration of the height and density of buildings around the construction site, generally 1/3 of the city center and 1 / 4.5 of the city suburbs. For example, the countryside can be set to 1/7.

In the case of rainfall, the vertical distribution is assumed to be the same.

The inoperable standard database (D3) includes work codes for each work type and work type, climate factors (temperature, wind speed, and rainfall), inoperability period by activity, inoperability period (period) in which work is suspended when an inoperability condition by activity occurs. In the event of an impossible condition, an inability criterion is stored that includes an item indicating whether the work can be interrupted and resumed (whether it is interrupted) in the middle of the activity.

The non-operational standard database D3 includes a large work type, a large work code (code 1), a hollow work code, a hollow work code (code 2), a small work type, a small work code (code 3), and climate factors, as illustrated in FIG. It is composed of the condition of occurrence of inoperable condition (condition 1, condition 2), inoperable period (period), work interruption or not, and each piece of information can be set by the contractor. The same applies to the sub-model code of. The work code uses the work code of the WBS classification system used in the process planning. Climatic factors can be selected multiplely for the temperature, wind speed and rainfall used in the climate database (D1). Non-workable occurrence conditions are set to "less than" or "greater than" certain climate values. The period of inoperability (period) is the period during which work is suspended when the climate factor satisfies the inoperability condition. Whether or not to interrupt work is the item that distinguishes the work (activity) that can be resumed even if work is interrupted due to the inoperable condition and the work that cannot be resumed if work is interrupted in the middle. For example, in the case of formwork (B0102), if the wind speed exceeds 10m / s, the work is stopped for one day due to the unworkable condition, and work can be resumed after one day even if the work is stopped. B0103) indicates that if the temperature is less than 5 ℃, the work is stopped for one day due to the unworkable condition, and if it is stopped during the work, it is impossible to resume work due to the nature of the concrete placing work.

The work inability calculation module (B1) compares the climate value of the corresponding altitude received from the altitude-specific climate data generation module (A3) with a preset work disable criterion to determine whether work incapability occurs. The reference is called from the inoperable reference database D3.

The process database D2 stores schedule information, location information, and work type information for each activity of the analysis target. A specific example is shown in FIG. 5.

According to Fig. 5, a job ID, a job start date and time (ES), a job end date and time (EF), a work code, a job height, a predecessor job ID, and a following job ID according to the activity name are stored.

Process simulation module (B2) transfers schedule information and location information among schedule information, location information, and work information by activity called from process database (D2) to climate simulation module (A2), and schedule information and work information are not available. Transfer to Ilsan calculation module (B1).

The process simulation module B2 performs simulation sequentially from the preceding process to the following process by reflecting the determination result value of whether the job failure calculation module B1 has occurred. The job failure calculation module B1 performs the simulation. If it is judged that the inoperability has occurred (satisfaction of the inoperability condition), the process simulation module B2 is capable of stopping and resuming the work in the middle of performing the work (for example, the formwork B0102). If one), add one day to the schedule of the activity and rerun the simulation. If work is interrupted in the middle of performing work (for example, in the case of concrete casting (B0103)), the activity starts from the day after the inability to work. The activity is rescheduled and the simulation is executed again.

If there is no work failure in the schedule of the activity, the simulation of the post process is performed sequentially.

In this way, when the simulation for all activities is completed, the simulation is performed once, and the simulation is repeated as many times as the preset simulation iterations.

The construction period analysis module B3 analyzes data related to the construction period and the total construction period for each type of work received from the process simulation module B2 to calculate and present a probability distribution or an average value.

As described above, the technical contents of the present invention have been described with reference to specific embodiments of the present invention, but the protection scope of the present invention is not necessarily limited to these embodiments, and various designs may be made without changing the technical spirit of the present invention. Changes, additions or deletions of well-known technology, and simple numerical limitations also make it clear that they belong to the protection scope of the present invention.

D1: Climate Database
D2: Process Database
D3: Inoperable Criteria Database
A1: climate data processing module
A2: Climate Simulation Module
A3: Advanced Climate Data Generation Module
B1: Job Failure Estimation Module
B2: Process Simulation Module
B3: Construction Period Analysis Module

Claims (8)

A climate database (D1) in which the regional climate values measured for many years are classified and stored according to the date and time measured according to the climate factor;
By calling the climate value of the climate database (D1), the representative climate value of the corresponding date is generated from the hourly climate value of the predetermined date of a specific region, and the climate distribution of the representative climate value is collected by collecting the representative climate value for several years for each predetermined period. A climate data processing module A1 for generating data;
By receiving the schedule information and location information for each activity of the analysis target from the following process simulation module (B2), and receives the climate distribution data of the corresponding section belonging to the schedule of the activity from the climate data processing module (A1) to generate a random variable A climate simulation module A2 for generating climate values for the schedule;
Altitude-specific climate data generation module (A3) for generating a climate value of the corresponding altitude based on the climate value and location information on the schedule received from the climate simulation module (A2);
An incompetent work calculation module (B1) for determining whether work incompetence occurs by comparing a corresponding climate value of a corresponding schedule received from the altitude-specific climate data generation module (A3) with a preset work impossibility standard;
A process database D2 for storing schedule information, location information, and work type information for each activity to be analyzed;
The schedule information and location information among the schedule information, location information, and work information for each activity called from the process database (D2) are transferred to the climate simulation module (A2), and the schedule information and work information are included in the work inability calculation module ( A process simulation module (B2) which transmits to B1) and sequentially performs the simulation from the preceding process to the following process by reflecting the determination result value of whether the work incompetence calculation module (B1) has occurred; And
A construction period analysis module (B3) for calculating probability distributions or average values by analyzing data related to the construction period and the total construction period received from the process simulation module (B2);
Prediction system construction period of a high-rise building construction project considering the vertical change of the climate factor, characterized in that comprises a. In claim 1,
Climate factor stored in the climate database (D1) is a construction period prediction system of a high-rise building construction project considering the vertical change amount of the climate factor, characterized in that including the temperature, wind speed and rainfall. In claim 1,
Representative climate value generated by the climate data processing module (A1) is a high-rise building construction project considering the vertical change of the climate factor, characterized in that the maximum value and minimum value for the temperature, the average value for the wind speed, the daily cumulative value for the rainfall. Construction period prediction system. In claim 1,
Monte Carlo simulation is carried out in the process of the climate simulation module (A2) to generate a climate value for the schedule, the construction period prediction system of a high-rise building construction project considering the vertical change of the climate factor. In claim 1,
The altitude climate value generated by the altitude-specific climate data generation module A3 is
In the case of air temperature, the vertical distribution of air temperature is calculated according to the insulation reduction ratio of the standard atmosphere.
In the case of wind speed, the vertical distribution of wind speed is calculated according to the formula of Claes Dyrbye & Svend Ole Hansen.
Prediction system for the construction of a high-rise building construction project considering the vertical change of climate factors, characterized in that the vertical distribution of rainfall is the same. In claim 1,
Work code and work code,
Climate factors, including temperature, wind speed, and rainfall
Inability to work by activity,
An inoperable period in which work is suspended when an inoperable condition for each activity occurs, and,
An inoperable criterion database (D3) in which an inoperable criterion is stored, wherein an inoperable criterion including an item indicating whether work is interrupted and resumed in the middle of performing an activity when an inoperable condition occurs;
Lt; / RTI >
The work inability calculation module (B1) is a high-rise building construction project construction period prediction system in consideration of the vertical change of the climate factor, characterized in that for calling the work inability standard from the work inability reference database (D3). The method of claim 6,
If the work failure calculation module B1 determines that work failure has occurred,
The process simulation module (B2) adds one-day to the schedule of the activity and re-executes the simulation if the activity in which the work is not possible is interrupted and resumed in the middle of execution. If it is impossible to resume the activity, the activity starts from the day after the inability to operate.The system predicts the construction period of the skyscraper construction project considering the vertical change of the climate factor, by adjusting the schedule of the activity and then performing the simulation again. In claim 7,
The process simulation module (B2),
When the simulation of the entire activity is completed, the simulation is performed once, and the construction period prediction system considering the vertical change of the climate factor, characterized in that the simulation is repeated by a predetermined number of simulation iterations.

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