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A DATABASE MANAGEMENT SYSTEM FOR RAPID VISUALSCREENING AND TWO-DIMENSIONAL SEISMIC

VULNERABILITY CLASSIFICATION OF PUBLIC SCHOOLBUILDINGS

Richerene Y. Caparos1

, Xenia B. Fajardo2

, Harlene Marie M. Ilagan3

, Joemar N.Revelo4,and Andres Winston C. Oreta5

1De La Salle University, Manila, Philippines,[email protected] La Salle University, Manila, Philippines,[email protected]

3De La Salle University, Manila, Philippines,[email protected] La Salle University, Manila, Philippines,[email protected]

5Civil Engineering Department, De La Salle University, Manila, Philippines,[email protected]

ABSTRACT

Prolonging the life of important structures such as public school buildings due to earthquake

hazards requires regular inspection, maintenance and possible retrofitting. Detailed inspection and

retrofitting, however, is costly considering the limited budget. Public school buildings that need detailed

inspection and possible retrofitting must be prioritized using a brief seismic diagnosis.The Department of Public Works and Highways (DPWH) regularly inspects public school

buildings and refers the survey results to the Department of Education for further action. The DPWH

adopts the Rapid Visual Screening (RVS) procedure of FEMA154/ATC21, a methodology based on a

sidewalk survey of a building, where a building is inspected from the exterior in order to quickly

determine if the building is probably adequate for the earthquake forces it is likely to experience, orwhether there may be reasonable doubts as to the bui ldings seismic performance. The RVS yields a

Basic Structural Hazard Score which may be used to identify, inventory, and rank buildings that arepotentially seismically hazardous. Buildings that will be subjected to a more detailed inspection are

usually determined based on cut-off value of the RVS score. To further refine the use of RVS specially inprioritizing public school buildings for a more detailed inspection and possible retrofitting, a two-

dimensional approach is proposed wherein a dual criteria is used to classify buildings based on the RVS

score and second criterion such as non-structural defects, assets importance, population or seismic

hazards. The inspection survey results on school buildings obtained from the Department of Public Worksin Manila were stored in a database to implement the 2D-seismic vulnerability classification and ranking.

Based on the preference of a decision maker, the second criterion can be selected and a classification andranking of the school buildings for a given area (district or city) will be automatically displayed with a

GIS map. Through this approach, decision makers can be guided in prioritizing buildings and identifyingbuildings that require immediate attention for detailed investigation and possible retrofitting.

INTRODUCTION

Having been located within the Pacific Ring of Fire, the Philippines is prone to several

earthquake occurrences. In fact, there are several active fault lines in the Philippines such as the Marikina

Valley Fault, Western Philippine Fault, Eastern Philippine Fault, Southern of Mindanao Fault, andCentral Philippine Fault. Also, the country is surrounded with trenchesManila trench, Philippine trench,

Negros Trench, Sulu Trench, and Cotabato Trench (NSCP, 2010). As of 2008, the Philippine Institute ofVolcanology and Seismology (PHILVOCS) listed 12 destructive earthquakes in the country. The

recorded earthquakes had magnitudes ranging from 5.1 to 7.9.Due to the frequency of earthquakes in the country, essential facilities are of great importance as

most are used for emergency operations during natural disasters. Public School Buildings are classified as

one of the essential facilities (Table 103-1 Occupancy Category, NSCP 2010). In the country, public

school buildings are often used as evacuation centres during calamities.The DPWH conducts the seismic screening of public school buildings in the Philippines.

Conducting a detailed evaluation for each public school buildings would take a lot of time and money. So,the DPWH conducts an initial screening known as the Rapid Visual Screening (RVS), a procedure from

the Federal Emergency Management Agency (FEMA 154) that determines which building must be
mailto:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]:[email protected]

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R. Caparos, X. Fajardo, H.M. Ilagan, J. Revelo, A.W. Oreta

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prioritized for detailed evaluation. Hence, it improves the disaster risk reduction management of the said

structures.Using the RVS scores in prioritizing buildings may not be effective in screening buildings for

detailed inspection since it is only limited to the configuration of the building. Also, there are possibleinstances wherein two or more buildings may have the same RVS score. Due to budget constraints,

detailed evaluation cannot be carried out to all public school buildings. One method in prioritizing

buildings is the Two-Dimensional Analysis which considers another seismic vulnerability parameter asthe second criterion aside from the RVS score. The second criterion could be used to differentiate

buildings with the same RVS score wherein the building with a more critical score in the second criterion

will be prioritized first. Moreover, the addition of such allows decision makers to prioritize the schoolbuildings based on the desired seismic vulnerability parameter. Furthermore, the analysis generates a

score for each building which allows a more precise ranking..

The primary objective of this research is to enhance the structural health monitoring of publicschool buildings in the Philippines. Specifically, the research has the following objectives: (1) To develop

a DBMS with GIS for the seismic vulnerability classification and prioritization of public school buildingsthat can be easily accessed and updated; (2) To include other seismic vulnerability parameters (Non-

Structural Hazards, Asset of the School Building, Population of Users of the School Building, andSeismic Hazard) together with the existing RVS score to analyse and assess the condition of the buildings

using two-dimensional analysis; (3) To provide query tools and graphical outputs that will be useful fordecision makers to determine which buildings must be prioritized for detailed evaluation using two-

dimensional and multidimensional analysis.

FRAMEWORK

The rapid visual screening (RVS) which is a procedure of Federal Emergency Management

Agency (FEMA 154) is a simple method which has been adopted in the US, Canada, and now one of the

tools adopted by the Department of Public Works and Highways in assessing building defects and

determines if a building is required to undergo a detailed inspection. The said method uses a scoringsystem that identify the primary structural lateral loading resisting system, and seismic performance

expected the building to perform. RVS is not intended for structures other than buildings.Two-dimensional seismic vulnerability classification is important in Seismic screening of

buildings to determine which buildings are greatly at risk. The major criterion (x-axis) would be the RVSScore of a building. FEMA 154 suggests 2.0 as the cut-off, classifying whether the building has a seismic

adequacy or none. The second criterion (y-axis) for the two-dimensional seismic vulnerability

classification can be any of the seismic vulnerability parameters of the building (Cammayo, 2009).

METHODOLOGY

Seismic Vulnerability Parameters

Non-Structural Hazards (NS)

The researchers gathered data, which served as the initial contents of the database, from the

DPWH. Name and location of the buildings, date of the last inspection, date of construction, number offloors, building type, FEMA 154 ratings, findings in structural and non-structural hazards, and

recommendations are the available data that can be accessed in the DPWH.The DPWH data for non-structural hazards was utilized. A checklist was developed by the

researchers. A total of ten non-structural hazards are considered: (1) broken/missing window glass; (2)bent/corroded steel window grills; (3) dilapidated ceilings; (4) uncovered electrical panel boads; (5) no

emergency exits; (6) construction along corridors/stairways; (7) possible falling hazards; (8) concretechipping on corridors/stairs; (9) installed water tank; (10) decayed wood/anay infested plywood.The

presence of a single non-structural hazard would yield a score of one.

The cut-off score for the checklist was set to 3.0. Any score equal and greater than the said value

would indicate that the building has poor non-structural condition. This method of scoring was based on

the study of Cammayo (2007). However, in Cammayos study, 7 NS were considered and 2.0 was set as

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the cut-off score. The researchers made 3.0 a cut-off score, instead of 2.0, since a total of 10 NS are being

considered.

Asset of a School Building (BA)

Buildings in a school may have different functions. To determine which of these buildings mustbe prioritized, it is necessary to provide asset values which give the importance of buildings. The higher

the asset value, the higher the importance of a building is. The asset value of each building will be itsscore. The cut off score is set to 5 which means that a score of five or greater are of high priority. The

scoring and cut-off was based from FEMA 428.

Population of Users of the School Building (P)

The population data of schools for school year 2012-2013 were gathered from the Department ofEducation. The data includes the number of students enrolled and the number of classrooms for the entire

school. The Population is denoted by the average number of enrolees per classroom

According to National Statistical Coordination Board, a classroom-student ratio of 50 must be

maintained in the country. The number of students is based on the assumption that whole day classes arebeing conducted. Thus, a cut-off score of 50 was considered. Buildings with population of higher than the

said value would be regarded as high priority.

Seismic Hazard Score (SH)

The seismic hazard score was determined by measuring the approximate distance of the nearest

fault line to the school being considered. The cut off score was set to 5km away from the fault line. This

means that buildings that are 0-5 km away from the fault line are of high priority. A map of active fault

line was collected from the Philippine Institute of Volcanology and Seismology, and incorporated to the

GIS in order to approximate the distance.

Two-Dimensional Analysis

Having the data gathered involving the RVS score and other vulnerability parameters, the

researchers subjected the said data to a two-dimensional analysis. Four two-dimensional analyses were

carried out since there are four other seismic vulnerability parameters being considered. A quantitative

approach was used in this analysis wherein the RVS score was plotted in the X-axis. Since an RVS score

of 2 and below means that the building would require further detailed evaluation, the origin at the X-axis

was set at 2. Building located to the left of the origin would mean that it is highly recommended fordetailed evaluation.

The y-axis served as the axis wherein the desired seismic vulnerability parameter (secondcriteria) is plotted.

Fig. 1: Two-Dimensional Classification According to Priority

Upon the plotting of data, the buildings that fall to quadrant 1 are those that are satisfactory in

both RVS and second criterion. As for those in quadrant 2, these buildings passed the RVS but failed in

the second criterion. In quadrant 3, the buildings had a failing score in the RVS but have satisfied the

second criterion. Buildings in quadrant four are those that failed to meet both criteria. Thus, the buildings

are group based on the quadrants with quadrants 1 and 4 being the very low and high priority group,

respectively.

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The Two-Dimensional Analysis score is computed by using the Pythagorean distance formula to

obtain the hypotenuse distance of two points as shown in equation 1. The derivation of the said formula ispresented in figure 2.

(eq. 1)

Fig. 2: Derivation of 2D Analysis Formula

Where,

The average factors from survey, Fn, were obtained by surveying 25 civil engineers from

DPWH. The respondents were to rate each seismic vulnerability from 1 to 10 with 10 being the highest.

Multidimensional Analysis

The multidimensional analysis formula, as shown in equation 2, is the formula used in obtaining the

overall score of the school building wherein all of the 5 vulnerability parameters are being considered.

(eq. 2)

TWO DIMENSIONAL ANALYSIS RESULTS

Using 2D Analysis with the four seismic vulnerability parameters, pie charts were used as torepresent the results of the analyses, showing the percentage of buildings falling to each quadrant.

(Figures 3-6).

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Fig. 3: 2D Analysis (NS vs. RVS)

Fig. 4: 2D Analysis (P vs. RVS)

Fig. 5: 2D Analysis (BA vs. RVS)

Fig. 6: 2D Analysis (SH vs. RVS)

SOFTWARE

The Database Management System is developed with the aid of Microsoft Visual Studio 2010

for the program and Microsoft Access for the database. It stores information and analyses data to assessthe seismic vulnerability of a structure. Thus, it aids decision makers in the prioritization of school

buildings to be subjected for detailed inspection.The Program is dynamic, data can be changed including information of buildings. The user can

register and add more area such as a city or a region. Values of cut-off scores and factors for eachparameter can be freely changed to suit the users interest in prioritizing. The main graphical user

interface of the software is shown in Figure 7.

Fig. 7: Main Graphical User Interface

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Highlighted Features

Search Box

The Search Box allows the user to filter the data to be shown by region, city, and district in the

GIS window and in the Summary Table. The search box also enables the user to choose the desired

seismic vulnerability parameters to be considered in the 2-Dimensional analysis.GIS Window

The GIS Window displays the school buildings as pins in the virtual map. It incorporates Google

Maps API so features such as zoom, span, and change of map type (satellite, or roadmap) enables the user

to navigate with ease. The Pins that represents each school building varies in color depending on the

condition of the school - green means safe, red means the building is in high risk.

Summary Table

The Summary Table shows and summarizes the scores of all the school buildings. The columns

in the table show the scores in RVS (FEMA Rating), Non-Structural, Building Assets, Population of

Users of the Building, Seismic Hazard, 2-D analysis score of the chosen parameters in the search box, and

the over-all score of each building. The user may also sort the entries in an ascending or descending

manner upon clicking the header of the column to be sorted. (Figure 8).

Fig. 8: Summary Table

Information Box

The Information Box displays information of a specific building that is selected by the user in

the summary table or in the GIS window. Information such as Building ID, Building Name, School,Latitude, Longitude, Year Built, Population, Asset, Gallery link of the photo, RVS score, Number offloors, Vertical Irregularity, Plan Irregularity, Building Type and Soil Type can be seen. It also features

an Automatically Generated Report which summarizes a school building that includes remarks and

comments in a text form that can be easily printed.

2D Classification Summary

The 2D Classification summary window displays a pie chart, which shows the total count of

school buildings categorized by quadrants. The pie chart serves as a brief overview of the status of all thebuildings (Figure 9).

Fig. 9: 2D Classification Summary

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Program Function

Fig. 9: Program Function Flowchart

Figure 9 basically shows the function of the program. First, the program allows user to isolatethe schools based on desired location to be considered. Then, the buildings on that specific location will

be subjected to two featured methods of prioritizationTwo Dimensional Classification and the Multiple

Parameter Analysis. The program outputs 3 scores for each building: (1) it identifies the Quadrant it

belongs by 2D Classification; (2) computes for a score considering two parameters by 2D analysis; (3)

computes for a score considering multiple parameters by multidimensional analysis. The user has the

freedom of choice of which method of analysis to use for prioritizing.

CONCLUSION

The DBMS of DPWH-Inspected Public School Buildings is a tool for seismic vulnerability

classification and prioritization for decision makers. The software can be easily accessed and updated due

to its simple GUI. It has the capability to assess and analyze the condition of the public schools thatshould be given top priority based on the different seismic vulnerability parameters RVS score, non-structural hazards, building assets, population, and seismic hazard.

In assessing the buildings, the two-dimensional analysis of the given seismic vulnerability

parameters can help the DPWH in the decision making to determine which public school building should

be prioritize with the desired specific vulnerability parameters. Moreover, the multidimensional analysisis also incorporated in the software wherein an over-all score ranks the buildings based on all the

parameters given. The said scoring is useful to further filter the ranking of the buildings which makes amuch more efficient allocation of budget.

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REFERENCES

Bautista, M. T., Dizon, A. R. L., &Panaloza, J. M. N. (2000). A program for the inspection andassessment of conditions of existing rc buildings. Unpublished manuscript, De La Salle University,

Manila, Philippines.

Bhatia, S. (2009).Tool for Vulnerability Assessment of a School Building.Vulnerability Assessment ofSchool Building V1.Cammayo, O.M., (2007). Seismic Screening and Condition Evaluation of Public School Buildings in

Quezon City. Manila: De La Salle University.Chua, C. P., Cruz, K. C., & Delos Reyes, F. B. (2007).Rapid visual screening of buildings (dlsu, csb and

vicinity). Unpublished manuscript, Civil Engineering Department, De La Salle Universsity, Manila,Manila, Philipppines.

Clearinghouse for Educational Facilities.(2012). NCEF - Safe Schools. National Clearinghouse for

Educational Facilities. Retrieved June 25, 2012, from http://www.ncef.org/safeschools/index.cfm

FEMA 428, (2003). Primer to design safe school projects in case to terrorist attacks. Retrieved fromwebsite:www.fema.gov

Gerbesioti, A., Delis, V., Yannis, T., &Anagnostopoulos, S. (2001).Developing decision support tools forconfronting seismic hazards.

Hoffer, J. A., Prescott, M. B., &Topi, H. (2009).Modern database management. New Jersey: PearsonPrentice Hall

National Statistical Coordination Board, (2009). Statistical indicators on philippine development.

Retrieved from website: http://www.nscb.gov.ph/stats/statdev/2009/Education/Chapter_Education.asp

The National Building Code of the Philippines ; and, Its revised implementing rules and regulationsapproved by the Department of Public Works and Highways on October 29, 2004 and took effect on

April 30, 2005 after official publication.. Quezon City, Metro Manila, Philippines: Vicente B. FozPublisher-Editor :, 2005. Print.

Oreta, A. W. C., Cammayo, O. M. J., Baluyot, K. S., Ramos, A. J. C., & Suarez, M. C. N. (2012, March).

Rapid visual screening and two-dimensional seismic vulnerability classification of important

buildings. Paper presented at 9th international conference on urban earthquake engineering / 4th asia

conference on earthquake engineering, Tokyo, Japan.

Saitta, S. Data Mining Research, (2007). standardization vs. normalization. Retrieved from website:

http://www.dataminingblog.com/standardization-vs-normalization/Savvaidis, P., Hatzigogos, T., Tziavos, T., Kiratzi, A., Roumelioto, Z., Savvaidis, A., Sotiriadis, A.

(2004).Data base development and evaluation of earthquake damage reports under the

seisimpact-thes system. Bulletin of the Geological Society of Greece, 36, 2004.

Porter, K. A. (2010). Rapid observation of vulnerability and estimation of risk (rover): End-to-end

seismic risk management software.Velasquez, J., Oreta, A. W., Tanhueco, R. M., & Salvador, F. (2010, December). The one million safe

schools and hospitals campaign: Promoting disaster awareness, preparedness and risk reduction. Paperpresented at 3rd asia conference on earthquake engineering (acee), Bangkok, Thailand.

BRIEF BIOGRAPHY OF PRESENTERS

Richerene Y. Caparos and Joemar N. Revelo are currently taking up Bachelor of Science in Civil

Engineering with specialization in Structural Engineering in De La Salle University Manila. Thesestudents are solid supporters of The One Million Safe Schools and Hospitals Campaign of UNISDR.

Andres Winston C. Oreta, D. Eng. is a professor in civil engineering at De La Salle University

Manila. He is one of the key persons who initiated The One Million Safe Schools and HospitalsCampaign of UNISDR. He is a member of the Philippine Institute of Civil Engineers (PICE) and the

Association of Structural Engineers of the Philippines (ASEP).
http://www.fema.gov/http://www.fema.gov/http://www.fema.gov/http://www.fema.gov/

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