S. Rahesh conducted a study to optimize the use of plastic waste aggregates (PWAs) as a partial replacement for normal aggregates in concrete. Response surface methodology (RSM) and absolute volume method (AVM) were used to design mixes with up to 30% aggregate replacement by two types of PWAs. Results showed PWAs can be used to produce concrete with acceptable properties, with the highest compressive strength achieved at 0% replacement by one PWA type and 24% replacement by the other PWA type. This approach helps utilize plastic waste while maintaining good engineering properties in concrete.

1. SUBJECTIVE ASSIGNMENT 2
NAME: S.RAHESH
MAIL.ID.:rockrahesh97@gmail.com
APPLICATION NO.: 9fa79694ee4511e984742df5d4dbdca6
COLLEGE: SASTRA DEEMED TO BE
UNIVERSITY,THANJAVUR

2. ACKNOWLEDGEMENT
I am greatly indebted to express my deep sense of
gratitude to the academic writing course which
taught me how to write a research article and how to
publish an article without plagiarism .

3. Presented by
S.RAHESH
120049014
M.Tech (Structural Engineering)

4. ABSTRACT OF THIS PAPER
An ideal experimental design based on the response
surface methodology (RSM) and the absolute volume
method (AVM) to investigate the potential of plastic
waste aggregates (PWAs) as a partial aggregate
replacement on properties of normal concrete (NC), in
which 30% of the total aggregate volume contains
PWAs.
Results confirmed that RSM prediction showed
satisfactory results in optimizing the amount of PWAs in
NC production. Moreover, PWAs can be used as
aggregates for the production of NC with acceptable
engineering properties. This approach could lead to the
significant utilization of PWAs in concrete, which could,
thus, help in protecting the environment by minimizing
the volume of waste disposal.

5. . INTRODUCTION
• As the world's population grows, plastic consumption
increases due to rapid urbanization and economic
development .Generally, the main sources of plastic
waste can be categorized into household wastes, health
and Medicare wastes, as well as hotel and catering
wastes.
• The most sensible solution to replace significant portions
of the aggregates in concrete with recycled plastic
wastes as an alternative aggregate while maintaining its
mechanical properties.

6. • Several studies on the effects of recycled plastic wastes on
fresh and hardened concrete properties have been
conducted.
• Increasing the plastic content in concrete decreases the
latter's density and compressive strength.
• Bayasi and Zeng verified that air content increased with the
inclusion of plastic fiber.
• Soroushian confirmed reduction in slump with the use of
recycled plastic in concrete due to the shape of plastic
particles, i.e., plastic particles have sharper edges compared
with fine aggregates.
• In addition, the mechanical strengths of concrete decrease
as the plastic content increases in concrete, i.e., splitting
tensile strength, modulus of elasticity, impact resistance,
andcompressive strength.

7. • Several ways to engineer concrete to find a reasonable
solution to these problems are available.
• One way is by optimizing the mix proportions using
mathematical or statistical methods.
• De Larrard and Sedran optimized the ultra high strength
concrete proportions using a statistical method with a
packing model, and studied the effect of paper mill residue
content in the properties of normal concrete using the
response surface methodology (RSM).
• Aldahdooh evaluated the ultra-high performance fiber
reinforced concrete binder content using the RSM.
Moreover, the RSM has been used in developing green
ultra-high-performance-fiber reinforced concrete containing
ultrafine palm oil fuel ash which is applied as a new
retrofitting material for improving the flexural behavior of
damaged concrete beams .

8. The recommended procedures for using RSM as
an optimization tool are summarized as follows :
i) The most important independent variables and their level
on the system through screening studies should be
selected first.
ii) The choice of the experimental design and experimental
procedure are according to the selected experimental
matrix.
iii) The mathematical-statistical treatment of the obtained
experimental data through the fit of polynomial function.
iv) The evaluation of the modes and fitness.
v) The verification of the necessity and possibility of
performing a displacement in a direction toward the
optimal region, and vi) Obtaining optimum values for
each variable.

9. RSM
• As outlined earlier, an ideal strategy is needed for
improving the normal concrete (NC) mechanical
properties relative to ingredient contents.
• Majority of mix design processes of concrete are
multi-variables; moreover, concrete mixture
proportions optimization through the classical
method is inflexible, unreliable, and time consuming.
• Thus, RSM is an efficient and widely used in various
fields, such as in chemical industry and
environmental engineering for optimization and
processing purposes (Table 1).

10. MATERIALS
• The constituent materials include ordinary Portland
cement (OPC) , crushed coarse aggregates, fine
aggregates, two types of PWAs, and water.
• Crushed coarse aggregates with a maximum size of
20mm and a specific gravity of 2.66 were used, whereas
natural sand was used with 2.7 specific gravity and 3.32
fine modulus.
• Two types of PWAs (1.03 assumed specific gravity) were
used as a partial substitute of aggregates in the
production of GNC, which are PWAI (irregular particles)
and PWAR (regular particles) .
• PWAR and PWAI have the same chemical natural
source given that the former is a recycled plastic waste
obtained from the latter. The maximum particle size for
both types was up to 5mm (passing from sieve size of
5mm).

11. MIX PROPORTIONS AND DESIGN
• As mentioned earlier, this study deals with two types of
concrete, which are NC and GNC. The mix proportions
of NC were derived based on the international standard.
• By contrast, the mix proportions GNC mixtures were
designed using RSM and AVM to achieve the optimum
mix with acceptable compressive strength and
workability.

13. AVM
• According to ACI-211.1 [34], the absolute
volume of a granular material defined as the
volume of the solid matter in the particles; it
does not include the volume of the voids
between the particles, as given in Eq. (1).
• The absolute volume of a concrete mix can be
determined if the weight and bulk specific gravity
of the components are known. (Table 2 gives an
example on AVM, determining of total volume for
the given concrete mix design in Table 3).

15. PWAR (regular particle) PWAI (irregular particle)

16. ANALYSIS PROCESS.
• ANOVA was used to obtain the interaction and relationship
between the process factors ([FA-PWAR]% and [FAPWAI]%)
and the responses (workability and compressive strength).
• In order to check the terms statistical significance; the
coefficient of determination R2, probability (P-value), and t-
test have been determined.
• In this study, the actual values were used for generating the
model. The diagnostic plots, such as the normal residual and
predicted plot versus actual value plot for slump and
compressive strength were obtained to determine model
satisfactoriness.
• Diagnostic plots aid in judging the model's adequacy and
satisfactoriness. Moreover, perturbation and 3D response
surface plots were obtained.

18. . SAMPLE PREPARATION
• Concrete sample preparations should refer to BS 1881:
Part 131: 1998. The materials were manually mixed in
the following order: coarse aggregate, OPC, FA and PW.
• The materials were mixed for a few minutes in dry
condition to produce a homogeneous mixture of dry
material.
• Afterward, water was added to the mixed materials, and
the mixing process was continued for a few minutes until
the constituents were thoroughly mixed and wetted.
• The cubical moulds were filled in three equal layers [40].
On the following day after casting, the samples were
removed from the moulds and were subsequently
cleaned and then cured in water at 27±2°C until the
testing date.

20. WORKABILITY
• The workability of GNC mixtures was assessed through a slump
test. Evidently, the inclusion of PWA notably reduced the workability
of GNC.
• Moreover, the slump is prone to sharply decreasing with increasing
the waste–plastic ratio. Where the improvement in workability
increases at a low PWA content, low workability is invariably
associated with high PWAR.
• The effect of PWAI is less significant on the reduction of mix
workability than that of PWAR. This scenario could be attributed to
the lubrication among aggregate particles. When PWAI aggregates
are characterized by better particle grading compared with PWAR
aggregates low void and high cement paste contents occur.
Therefore, the lubrication provided by PWAI is better than that by
PWAR.
• Obla concluded that the cementitious paste should completely fill the
voids among the aggregate particles and that a certain amount of
excess must be left to provide the lubrication required for a given
workability.

21. Experimental results and discussions
• Workability

22. Compressive strength

23. PROCESS ANALYSIS
• The perturbation and the response surface plots
for slump and compressive strength are shown
in Fig. 5I and II, respectively. The comparative
effect of ([FA-PWAR]%, A) and ([FA-PWAI]%, B)
on enhancing the slump and compressive
strength are clarified by the

25. CONCLUSIONS
• The inclusion of the PWA tends to increase the water
demand of GNC, which leads to a lower workability at a
constant water content. The decrease in workability by
replacing the FA with PWAR more significant than
replacing with PWAI.
• The highest compressive strength of GNC was found at
0.0% of [FAPWAR] and at 0.0% of [FA-PWAR]. The
lowest compressive strength was at 30% [FA-PWAR]
and 30% [FA-PWAI]. iii) At the optimum condition, the
RSM predicted that [FA-PWAR]% was 0.0%, and the
[FA-PWAI]% was 24%.
• The optimum mix properties of GNC as following: OPC
content of 380kg/m3; FA content of 670kg/m3; PWAR
content of 0.0kg/m3; PWAI content of 63kg/m3; slump of
26mm and compressive strength of 20MPa at 28 days.

26. MOCK PRESENTATION
• Myself
• M.Loganaganadan
• S.Rahesh

27. THANK YOU