thesis on sustainable site management for construction

1. M. Ruchith Rao
SPA/NS/BEM - 845
THESIS
DEPARTMENT OF BUILDING ENGINEERING & MANAGEMENT
SCHOOL OF PLANNING AND ARCHITECTURE, NEW DELHI – 110002
JUNE - 2023

2. Need of Study
In order to make an existing Building resilient to the disaster
vulnerabilities in an effective and economical way, the existing capacity of the
building has to be known and then the interventions can be proposed.
Therefore, there is need of identifying the resilience of the existing
building with respect to multiple hazards approach, from the literature it is
identified that there are various models to quantify resilience capacity of a
building in respect of individual disasters such as seismic, flood, cyclone etc.

3. Research Gap
Several models exist for calculating the seismic resilience index (SRI) of buildings, including
the Functionality Curve Method, the Weightage-based Performance Level Method, the Fuzzy
Inference Systems (FIS) Method, and the Dependency Diagram Method.
Similarly, in flood Model (Gourbesville, 2014) quantifies qualitative data and only
considers flood resilience, lacking historical data and recovery parameters. Model (Leandro,
2019) is based on physical, social, and economic indicators, including recovery time and cost,
but is limited to buildings and does not account for loss of life or cascading effects.
Therefore, the existing models for calculating resilience index have different
drawbacks, and none of them can calculate resilience capacity in a holistic manner for
multiple disaster approaches, considering all the necessary factors.

4. AIM:
To formulate a comprehensive indexing model to measure the resilience
capacity of the existing buildings
Objectives:
1. To assess the Impacts of various Multi-Hazard Disaster on the Existing Building.
2. To analyses the Existing models for calculation of Resilience in existing Buildings.
3. To identify the parameters and their correlation for various disasters resilience.
4. Validation of the formulated model to identify the resilience of the existing building.

5. Research Methodology
S
No.
Objective Methodology Outcome
1 Assess the
Impacts of Multi-
hazard Disaster
Through Literature
review and case
study
Impact of various
disaster on existing
buildings.
2 Analyzing
Existing Models
for Resilience
Through the
Literature study of
existing methods
Method details to
calculate resilience
of Building
3 Identify the
parameters and
their correlation
Through Literature,
Case study &
Expert Interview
Parameters to
Include in the model
& Correlation
4 Validate the
formulated
Model
Using the Model
which is developed
on a building
Validation of
building resilience
Indexing method

6. Research Design
3.1 Objective 1: To assess the Impacts of various Disasters that on the Existing Building.
Objective -1.1
a. Study of the Multi-hazard
impacts (Cascading effects
)of the disaster.
b. Building level Impacts of
Disaster
Objective -1.2
• Existing Building Disaster
Vulnerability calculation
methods analysis
Through Literature Study of Post
disaster impact assessment on
Secondary Case examples
Through literature study of
cascading impacts of the hazards Impact potential and
Probability of individual
hazards on triggering
other Hazards.
Through Literature Study - Identify
& analyse calculation procedure of
various Existing Building
Vulnerability Assessment Methods
Selection of the
methods which are
suitable for Quantification
of Resilience Indexing
HAZUS & RVS for
Assessing – Validate using
expert Judgement

7. Research Design
3.1 Objective-2:To analyses the Existing models for calculation of Resilience in existing Buildings
Objective -2.1
Analyze various existing
resilience indexing models
Objective -2.2
Validation of proposed method
for Quantifying Comprehensive
Resilience Indexing Model.
Analyse the methods & Input data
used for quantifying Resilience in
Existing Models Index
Identify Various existing
Resilience Indexing Methods for
Individual Disasters through
Literature Study
Seismic Resilience Index,
Flood Resilience Index,
Cyclone Resilience Index,
SRI, FRI, CRI, etc.
Validation of the method through
Secondary case examples Details of Input Data &
Methods for calculation of
Building Resilience Index
Selection of the method
which is suitable for
Quantification of
Comprehensive Building
Resilience Indexing
Validation of the selected method
through Questioner Survey

8. Research Design
3.1 Objective 3: Identify the parameters and their correlation for various disasters Resilience
Objective -3.1
Identification of Parameters
which are used to calculate
individual resilience index
Objective -2.2
Analyzing the relation between
those reduced parameters to
reduce the Categories
List of all Parameters used in
Calculating all different disaster
resilience index such as
SRI, FRI, CRI, etc.
Using Textual narrative
analysis reduce the
common parameters by
merging into common
category.
Using Partial Correlation to identify
the relation among the parameters
which are in different hazard category
based on Primary data collected by
Expert Survey of Parameter Impact
Reduction of the
categories whose
parameters having higher
correlation.
Validation of the Partial correlation
Data fit using ANOVA Test.
Objective -2.3
Formulate a comprehensive
Disaster Resilience Index
Using Multiple Regression Equation
formulate the Comprehensive Building
Disaster Resilience Index
Validation of the Regression Data fit
using R Square test.
Multiple Regression
Equation with
Independent variables &
Coefficients based on
Inference from obj -1

9. Research Design
3.1 Objective 4: Validate the formulated Model for Comprehensive Building Disaster Resilience.
Objective -4.1
Application on simulation to
measure the resilience
Not Clear:
Any simulation of case example
for Structural Integrity & Loss
estimation. Or Negative impact
on any live case example data.
Results of the simulation
and Errors in Model
Objective -4.2
Improve the Model equation
based on Results of simulation
Reframing the Coefficients
calculation of multiple regression
equation model.
Comprehensive Building
disaster Resilience Index
model
Conclusion &
Way forward

10. Research Design Detail
3.1 Objective 1: To assess the Impacts of various Disasters that on the Existing Building.
Objective 1 can be divided in to two
parts according to the data which is to
be studied and the output data which
is required for the further study and
analysis of the collected data to create
a resilience indexing model.
i. Study of the Multi-disaster impacts (Cascading & Compounding) effects of the disaster from the Literature.
a. This includes the study of Multi-disaster impact from literature &
b. Secondary case examples of (building level) impacts of any disaster on existing buildings from reports
after the disaster.
ii. Existing Building Disaster Vulnerability calculation methods through Literature study.
a. This involves analysis of vulnerability calculation techniques used to quantify deterioration &
contextual features in existing buildings.

11. Research Design
Outcome of Objective 1.1 a: Multi-Disaster Cascading Effect Impact Study analysis through Literature.
Figure 11: Multi-Disaster probability & Impact study; Source: (Gill & Malamud, 2016)
Major disaster which are increasing
the probability of causing another
cascading effect and also the impact
are:
i. Earthquake
ii. Landslide
iii. Flood
iv. Cyclone (Storm)
v. Hail Storm
vi. Extreme Weather Events
(majorly Heat wave)
vii.Volcanic Eruption

12. Research Design
Outcome of Objective 1.1b: Impacts of these disasters in the Building level:
Depending on the type of disaster and the severity of the incident, disasters can have a substantial influence on
existing buildings. Disasters can have the following effects on buildings based of the reports of post disaster
assessment. (J Shanmugasundaram, 2000), (Luka Luli´c, 2021), (Tu & Wen, 2021).
Structural Damage: Earthquakes, hurricanes, tornadoes, floods, and other natural calamities can inflict major
structural damage to buildings. This damage can weaken the foundation, walls, and roof of the building, causing it to
collapse or partially collapse.
Water Impact: Flooding or severe rain can cause water damage to structures, which can lead to mould and
mildew growth, structural damage, and electrical problems.
Impact of Fire: Fires can cause considerable damage to buildings, including structural damage, electrical system
damage, and smoke damage. In extreme situations, fires can completely destroy a structure.
Contamination: Natural disasters such as chemical spills, radiation breaches, and other hazardous material
releases can contaminate buildings and render them unfit for habitation.
Utilities Disruption: Natural disasters can disrupt basic utilities such as power, water, and gas, making it
difficult or impossible for building occupants to stay.

13. Research Design
Outcome of Objective 1.2: Existing Disaster Vulnerability calculation methods through Literature
Vulnerability assessments for buildings are essential to identify and prioritize potential
hazards and risks that may affect the structure and its occupants. Some of the methods used
to quantify the building vulnerability are:
1. FEMA P-58 Method: Uses building Characteristics such as age, construction, location, Now Merged in HAZUS
2. ATC-45 Method: The method evaluates the potential seismic hazards and risks that could affect the building
3. HAZUS Method: assess the vulnerability of buildings to natural hazards such as earthquakes, floods, and hurricanes.
4. Rapid Visual Screening (RVS) Method: Involves a quick visual inspection of a building to identify potential structural
weaknesses and hazards
5. Expert Judgement Method: Experts evaluate the building's design, construction, and maintenance to identify
potential hazard
6. Building Code Analysis: The analysis evaluates whether the building meets the minimum safety requirements
Selected Method:
• From the above methods, HAZUS method & Rapid Visual Screening (RVS) are chosen for assessing the
vulnerability of the existing buildings since they include most of hazards like earthquake, flood, cyclone, fire etc.
• Expert Judgement method can be further used to validate the data assessed by the above methods.

14. Research Design
3.2 Objective 2: To analyses the Existing model to for calculation of Resilience in existing Buildings.
Research Method:
Objective 2 can be achieved in 2 steps,
i. Analyze various existing resilience indexing methods through Literature.
ii. Validating the proposed method through secondary case study & Questioner.

15. Research Design
Outcome of Objective 2.1 : Analyze various existing resilience indexing methods through Literature
After analyzing the existing methods which are used for calculation the resilience indexing of
the existing buildings for individual disaster like Earthquake & Flood, it is identified that the
resilience calculation method is based on the defining the resilience.
So, the best method to define the resilience is Time varying Resilience Index.
It can be used to quantify a combined resilience index since the recovery function & other
thing can be made common for more realistic output. Along with this loss estimation in terms of
economic loss and human days loss can also be added.
Types of methods identified to calculate Seismic Resilience Index of a building are described as follows:
Functionality Curve method: It is a graphical representation of the building's functionality in relation to the intensity(PGA)
Fuzzy Inference Systems (FIS): Use of intuitive values may impact accuracy and complicate decision-making.
Dependency Curve Method: Uses the MMI Intensity scale to quantify the resilience of a building with given strc. System.
Resilience Deficit Index: Based on 1st it also includes the economical and human days losses based on hysterical data
Types of methods identified to calculate Flood Resilience Index of a building are described as follows:
Performance based FRI: Works on the data obtained by quantitative marking of qualitative data based on a Scale.
Time-Varying Flood Resilience Index: Quantifies negative impacts of flooding and their capacity to recover quickly
from them over time.

16. Research Design
Outcome of Objective 2.2: Validation of proposed method
 All the methods are used in some case studies are proven appropriate so the validation
through secondary case study is verified.
 A questioner survey can be floated to validate selected method to calculate the resilience
is applicable for multi-hazard comprehensive resilience Index or not.

17. Research Design
Outcome of Objective 2.2: Validation of proposed method
Analysis of Result: Expected results to Validate selected model.
1. Functional ability followed by Faster recovery are more Accurate terms which defines
resilience.
2. Vulnerability Assessment based Resilience Index is more suitable for Buildings
3. Economic loss should be Included – Yes ( % ) >50%
4. Human working days loss should be Included – Yes (%) >50%
5. Time should be a parameter – Yes (%) >50%

18. Research Design
3.3 Objective 3: Identify the parameters and their correlation for various disasters resilience
i. It includes Identification of Parameters which are used to calculate individual resilience index
like SRI, FRI, CRI or similar from the analysis of Obj - 2.
ii. Analyzing relation between those parameters using to reduce the parameters in the final model
using suitable tool which give more accurate correlation.
iii.Formulate a comprehensive Disaster Resilience Index using the final parameter are their
coefficients.
Research Method:
Objective 3 can be
achieved in 3 steps

19. Research Design
Outcome of Objective 3.1: Identifying Parameters – Textual Narrative Analysis & Objective 2
Parameter
Hazard
P1 P2 P3 P4
Earthquake PGA (Intensity) Stoery Drift Stiffness Zone
Flood Indentation Line Impact Area % Height of GF
Cyclone (Storm) Wind Speed Rain Impact Hails, Other Context
Landslide Slope of land Building Strength Distance Context
EWE Temperature Rain Impact Snow/other
FIRE Codal Provisions Fire Rating Hr.
Other Proximity Impact Scale
Table 2: Important Parameters as per the major disasters; Source: Author
Note: P1 – P4 are the parameters in the order of higher to lower as per their impact on resilience of building in most of the cases

20. Research Design
Outcome of Objective 3.2: Identifying Correlation among the Parameters to reduce them.
Possible Methods and Tools: The following methods identified from literature are the most suitable
methods. They have been critically analysed by illustrating some parameters
1. Textual Narrative Analysis: Uses literature to categorize research into more homogeneous categories.
2. Delphi Technique: Using Pooled Intelligence to get the answer by opinions on a particular research question
3. Pearson’s Correlation: It uses the values instead of rank as in Kendall’s coefficient to quantify the Correlation.
4. Kendall’s Coefficient of Correlation: Uses ranks to quantify correlation by quantifying concordant pairs.
5. Partial Correlation: Measure of the strength and direction of a linear relationship between two continuous variables.
Its Calculation is Based on Pearson’s Correlation .
There is (+)Positive Correlation between Stiffness of building (EQ) & Building Strength (LS)
As per Pearson’s Correlation the correlation value is 0.558
As per Kendall’s Correlation the correlation value is 0.475
As per Partial Correlation the correlation value is 0.569. => Using this the Landslide can be merged into EQ.
This shows partial correlation analysis is giving more accurate & true value of correlation since in real building
strength & stiffness have high positive correlation

21. Research Design
Outcome of Objective 3.2: Identifying Correlation among the Parameters to reduce them.
Applying this to the current study, we filter data based on textual analysis as follows Assuming that we are
trying to establish a point of commonality between the following parameters: Repair cost, Repair time, Delay
time and replacement cost in SRI, FRI, Etc.
From the literature it is identified that all the recovery function parameters are common for any resilience
indexing, whether it be SRI, FRI or CRI.
They all can be categorized as Recovery Function Parameters.
When the process is significantly similar, the parameters present a strong relationship with one another. In this
case, they can be merged together to form a single parameter.
i. Repair cost & Replacement cost can be merged into Recovery Cost as a single Parameter
ii. Delay time & Repair time can be merged into Recovery Time parameter
Parameters before
Analysis
Categorization of
parameters
No. of Final
Parameters
Reduced
parameters
4 1 2 2

22. Research Design
Outcome of Objective 3.3: Formulate a comprehensive Disaster Resilience Index.
Possible Methods and Tools: The following methods identified from literature are the most suitable methods. Data
analysis for the research needs to establish if there is any causal relationship between the issues. There are two
methods for this as observed in literature
1.Multiple Regression Analysis:
Multiple regression is a statistical technique that can be used to analyze the relationship between a single
dependent variable and several independent variables. The objective of multiple regression analysis is to use the
independent variables whose values are known to predict the value of the single dependent value.
Y = a + b1x1 +b2x2 + …… + bnxn
Here Y is the dependent variable, and X1,…,Xn are the n independent variables.
2.SEM
Structural equation modelling is a multivariate statistical analysis technique that is used to analyse structural
relationships. This technique is the combination of factor analysis and multiple regression analysis, and it is
used to analyse the structural relationship between measured variables and latent constructs.
Factor analysis is a technique that is used to reduce a large number of variables into fewer numbers of
factors. This technique extracts maximum common variance from all variables and puts them into a common
score. As an index of all variables, we can use this score for further analysis.

23. Research Design
Outcome of Objective 3.3: Formulate a comprehensive Disaster Resilience Index.
Selected Methods for Modeling Equation: I. Multiple regression equation.
Since we have the Parameters with already filtered by partial correlation (Factor analysis
step in SEM) and only the parameters which are independent are selected for the modeling,
multiple regression equation can be used to identify the final Comprehensive Building
disaster Resilience Index by multiplying the individual resilience index with its coefficients as
per various variables.
Formulating the regression equation from the existing methods for quantifying resilience
indexing in the form of time vs function graph.
Comprehensive Building disaster
Resilience Index (CBRI) = X1Y1(SRI) + X2Y2(FRI) + X3Y3(CRI) + X4Y4(Etc.,)
= X1Y1(Seismic Impact+ Recovery Cost& Time )
+ X2Y2(Flood Resistance + Recovery Cost& Time)
+ X3Y3(Cyclone Resistance + Recovery Cost& time)
+ X4Y4(Etc.,)

24. Research Design
Outcome of Objective 3.3: Formulate a comprehensive Disaster Resilience Index.
Comprehensive Building disaster
Resilience Index (CBRI) = X1Y1(SRI) + X2Y2(FRI) + X3Y3(CRI) + X4Y4(Etc.,)
CBRI = X1Y1(Seismic Impact) + X2Y2(Floor Resistance)
+ X3Y3(Cyclone Resistance) + X4Y4(Etc.,)
+ M1M2(Recovery Time & Cost)
X = Can be Probability of occurrence; Values of X are 1 for Max probability
& 0 for Non-Occurrence (Volcano, tsunami in land locked regions etc.,)
Y = Can be Cascading effect probability; Values of Y are 1 for Max triggered due another
hazard & 0 if no other hazard is triggering this hazard.
M1 = Can be the Cumulative Coefficient for the Recovery Time Function
M2 = Can be the Cumulative Coefficient for the Recovery Cost Function

25. Research Design
Outcome of Objective 3.3: Formulate a comprehensive Disaster Resilience Index.
Comprehensive Building disaster
Resilience Index (CBRI) = X1Y1(SRI) + X2Y2(FRI) + X3Y3(CRI) + X4Y4(Etc.,)
CBRI = X1Y1(Seismic Impact) + X2Y2(Floor Resistance)
+ X3Y3(Cyclone Resistance) + X4Y4(Etc.,)
+ M1M2(Recovery Time & Cost)
Where X = Probability of occurrence; Y = Cascading effect probability
Seismic Impact = Calculated using PGA & Building Stiffness as per condition (using RVS)
Flood Resistance = Calculated using FMEA - HAZUS method (Hysterical data) (Obj-1) similar.
X is calculated using the past data of Hazard Frequency & Zoning by codes (Obj-1)
Y is calculated using the Literature study of Disasters trigger& Impact probability (Obj-1).
M1 is calculated by using the recovery time of previous case examples.
M2 is calculated by measuring Loss estimation by using HAZUS method. (Obj -1)

26. Thank You