Component blending for bitumen production for Indian refineries

UMA CHAKKOTH1, K R KRISHNA2, M RAMKUMAR2, SYED ARIF HUSSAIN3, P V C RAO2,

N V CHOUDARY2, G SRIGANESH2 and J MURALI KRISHNAN1,*

1Department of Civil Engineering, Indian Institute of Technology Madras, Chennai, India2Fuels Research Lab, HP Green R&D Centre (HPGRDC), Bengaluru, India3Hindustan Petroleum Corporation Limited (HPCL), Mumbai Refinery, Mumbai, India

e-mail: umamenon88@gmail.com; krkrishna@hpcl.in; ramkumarm@hpcl.in; arifshussain@hpcl.in;

drpvcrao@hpcl.in; vcnettem@hpcl.in; gandham@hpcl.in; jmk@iitm.ac.in

MS received 28 July 2019; revised 24 November 2019; accepted 27 November 2019

Abstract. This investigation pertains to the bitumen production using component blending. During the

manufacture of blended bitumen, the proportion of the constituents, the temperature during blending, and the

duration of blending are selected to meet the penetration at 25�C and the absolute viscosity at 60�C as per the

Indian specifications. The choices of the blend parameters become challenging when the constituents from

multiple crudes are blended to produce different paving grades. Two constituent and three constituent blends for

four different grades of bitumen were prepared in a laboratory blending facility from four different crude

sources. A design of experiments framework was used to develop prediction models for penetration and vis-

cosity. Simulations were carried out to suggest blending schemes to manufacture all the viscosity grades from

different crude sources. Correspondence between the viscosity grade and high-temperature performance grade

was observed for blend parameters for the crude sources investigated in this study.

Keywords. Component blending; blend parameters; blended bitumen formulations; design of experiments;

viscosity grading; performance grading.

1. Introduction

India has twenty-three refineries processing a wide variety

of crude sources. Out of these, paving grade bitumen is

produced from twelve refineries, and the remaining eleven

refineries do not produce bitumen. The crudes processed by

refineries are mainly of medium American Petroleum

Institute (API) gravity from the Middle East, Mexico,

Venezuela and Canada [1]. Most of the crudes processed

are blends of two or more crudes namely Arab light,

Murban, Das, Iran and Basrah light.

The Indian standard specification for paving bitumen was

based on penetration, and it was formulated in 1950. Sub-

sequent amendments were made to the specifications over

the years by including various empirical test methods [2].

Considering the limitations of the penetration based grad-

ing, viscosity-based grading was incorporated in the year

2006. The latest revision of the Indian standard specifica-

tions for paving grade bitumen IS 73 [3] classify the binders

into four viscosity-based grades, and these are VG10,

VG20, VG30, and VG40.

The refineries in India process crudes through air recti-

fication using patented BITUROX technology and

component blending [4, 5]. In the component blending

process, different constituents obtained from the refinery

units, such as the propane deasphalted (PDA) pitch, low

viscous extract, vacuum gas oils, and vacuum tower bottom

(VTB) are blended in conditioning tanks. PDA process is an

extraction process in which vacuum residue is contacted

with propane to extract heavier oils known as deasphalted

oil [6]. The PDA pitch obtained from the deasphalting

process is a low penetration material (typically less than 12

at 25�C) with a viscosity of around 20,000 Poise at 60�C.The extracts are the residue collected from auxiliary

refinery operations units such as fluid catalytic cracking

(FCC) and solvent extraction.

1.1 Blended bitumen formulations

Various factors influence the quality of bitumen processed

using component blending. These factors are the propor-

tions and the consistency of constituents, processing con-

ditions such as the duration of blending, the temperature

during blending, target grade, and other production aspects

of the refinery. Most of the early investigations on blended

bitumen were mainly focused on the influence of blend

proportions on the properties of the blended bitumen*For correspondence

Sådhanå (2020) 45:48 � Indian Academy of Sciences

https://doi.org/10.1007/s12046-020-1268-9Sadhana(0123456789().,-volV)FT3](0123456789().,-volV)

defined in terms of penetration and softening point [7–11].

These studies focused on developing nomographs relating

the blend properties and the specification-based parameters.

Lopatskii [7] developed the prediction models used for

blended bitumen which includes a graphical and analytical

method for determining the softening point of blended

bitumen. Gun and Biryulina [8] investigated the influence

of the properties of the individual constituents which were

tar and ‘oxidized’ bitumen, on the properties of the blended

bitumen processed using it.

Lopatinskii and Lopatinskii [9] developed a nomograph

for arriving at a specific softening temperature based on the

softening point of the blend constituents. Akhmetova and

Glozman [10] proposed a triangular diagram for the choice

of optimal constituent ratios for preparing the blended

bitumen to meet the required specification criteria. Tabolina

et al [11] proposed an analytical expression for finding the

softening point of the blended bitumen based on the soft-

ening point of the individual constituents. In these studies,

the influence of process conditions on the properties of the

blended bitumen during the blend production was not

adequately quantified.

An extensive characterization of blended bitumen was a

result of research efforts carried out by refineries in Israel to

understand the issues related to using propane precipitated

asphalt (PPA) blends in bituminous mixtures [12]. The

research carried out by Ishai and co-workers in three sig-

nificant publications [12–14] discussed different blending

constituents which could be used for processing blended

bitumen. The paving grade bitumen produced using VTB,

extract, and PPA was used for the investigation. The pro-

cess parameters during blending were the temperature

which was kept constant at 125�C for 75 minutes. Fourteen

blends were produced using different proportions of the

constituents with similar process parameters. The blends

were verified for the compliance with Israel standard for

viscosity-based grading [14]. The studies on blended bitu-

men by Ishai and Yuval [14] indicate that the proportion of

extract in a three constituent blend should be in the range of

5 to 15% when blended with PDA pitch and VTB.

Similar to the penetration and softening point based

nomographs, the viscosity based mixing rules were exten-

sively used for different research applications after the

introduction of viscosity based paving grade specifications.

Chaffin et al [15] used viscosity based mixing rules to make

appropriate choices for recycling agents and modifiers

suggested regression analysis to predict the penetration,

viscosity, and ductility of binary mixtures of oxidized

bitumen and vacuum residue (see also [16–18]). The

underlying assumption of these mixing rules that there

exists a linear relationship between the proportion and the

viscosity of the constituents does not hold good at all

conditions, the details of which are reviewed in Centeno

et al [19]. Chakkoth et al [20] evaluated the use of viscosity

based mixing rules to determine the blended bitumen vis-

cosity and the viscosity predictions were obtained with a

wide range of errors. These simplified viscosity mixing

rules can at best give a rough estimate of the expected blend

viscosity as long as the constituents consist of light to

intermediate hydrocarbons. These rules cannot be used for

blend formulations of paving grade bitumen as the com-

pliance of such blends to the specification limits of other

parameters such as penetration, or softening point is ques-

tionable. In addition to this, complex hydrocarbons such as

bitumen pose a serious challenge due to the possible

chemical interactions.

The design of experiment techniques provides an effi-

cient means to formulate a mixture design as well as to

optimize a process [21]. An effective experimentation plan

includes two steps; one is to find an appropriate formulation

for experimental design and the second is to optimize the

process using factorial or response surface methods. The

implementation of the design of experiments techniques

span across all industries, and engineering application

wherein the response variable depends on multiple input

variables. Very few investigations on bituminous materials

have used the design of experiments approach. Bressi et al

[22] used response surface methodology (RSM) to deter-

mine the influence of percentage of reclaimed asphalt

pavement (RAP) and penetration of virgin bitumen on the

quality of the RAP blend (see also [23, 24]).

Recently, the design of experiments framework was used

by Varanda et al [25] to propose blend formulations for

paving grade bitumen using products such as asphaltic

residue, vacuum residue, and extracts obtained from the

refining processes. The blended bitumen data was used in a

constrained mixture design to develop prediction models

for the response variables. The response variables, the

penetration (at 25�C) and the softening point, were fitted

with Scheffe’s polynomial functions. The experimental

design consisted of different proportions of the compo-

nents, and all the blends were prepared at the same process

conditions.

1.2 Motivation

This investigation was initiated to develop an understand-

ing of the issues related to the production of component

blended bitumen in the Indian refineries. Table 1 shows the

requirements for paving grade bitumen as per IS 73 [3].

Here, the penetration at 25�C and viscosity at 60�C are only

shown. The existing blending scheme followed in one of

the Indian refineries is for a two-constituent blend and uses

86.4% of PDA pitch and 13.6% of extracts to process VG30

grade bitumen. The refinery chooses the proportion of the

blend constituents and the blend parameters (temperature

and duration of blending) such that the resulting blend

complies with a target viscosity and penetration as per IS

73 [3]. Since the design of the blending scheme can become

involved when the constituents of different crudes are to be

processed for different paving grades, a need was felt in

48 Page 2 of 16 Sådhanå (2020) 45:48

rationalizing the whole procedure. Also, the refinery

explored the options of using VTB in processing the three

constituent blends. The VTB is used in other refinery pro-

cesses such as visbreaking, deasphalting, coking and

hydroprocessing [26]. As VTB serves as a material which

could be used as a feedstock to different other units in the

refinery, only a minimum quantity of VTB would be

available for blending purposes. With such constraints on

constituents and with multiple crudes being processed, the

development of a robust blending scheme accounting for

the influence of crude type, process factors, and constituent

properties is necessary. This investigation reports such a

design, and towards this end, a multivariate statistical

technique was used.

This work is aimed towards formulating a scheme of

blending for producing paving grade bitumen by varying

the proportion of the constituents and the process parame-

ters. The main objectives of this investigation are:

1. to develop a process protocol for producing the various

grades of paving bitumen in the laboratory, and

2. to develop and validate the prediction model for

penetration and viscosity of the blends for a given crude

source and blend parameters.

The model would also serve as a tool for determining the

blend parameters for bitumen of a particular viscosity grade

from a given crude source.

1.3 Methodology

The constituents obtained from four crude sources with API

of the crude sources ranging from 30.8 to 37.6�, were usedfor developing a blending scheme for all the viscosity

grades as per IS 73 [3]. The blend parameters were the

process conditions, proportions of the constituents and API

of the parent crude. The two constituent and three con-

stituent blends were processed in a pilot scale arrangement

in the laboratory to meet the two key parameters which are

the penetration at 25�C and the absolute viscosity at 60�Cas per the Indian technical specifications. The blending

scheme for VG10, VG20, VG30 and VG40 grade of bitu-

men was finalized for both the two and three constituent

blends. In order to harmonize the blending scheme devel-

oped, the statistical prediction models were formulated by

using blend parameters as the variables using the design of

experiments framework. The penetration and the absolute

viscosity of the blended bitumen were the response vari-

ables for these models.

The blended bitumen data of one set of the crudes were

used to develop the model. The validation of the model was

carried out using the data of another crude source. The

prediction models were used to simulate the process

parameters for different ranges of the blend parameters. For

every simulation carried out a set of optimal solutions was

generated using the desirability function approach. These

simulations focused on relating the influence of blend

proportions and API gravity of the parent crude on the

process parameters. All the manufactured blends were

measured for their performance grade properties, and it was

seen that a correspondence between the viscosity grade and

high-temperature performance grade could be observed for

blend proportion and process parameters for the crude

sources investigated in this study.

2. Experimental investigation

The procedure followed for the design of blending

scheme is explained in this section. It includes the details

on the materials and the experimental procedures used for

processing the two constituent and three constituent

blends.

2.1 Materials

The details on the crude sources are presented in table 2.

The constituents from the identified crude sources were

received from the refinery. The blend constituents were

PDA pitch, vacuum tower bottom (VTB) and residue or

extract from auxiliary refinery units such as solvent

extraction or fluid catalytic cracking units. The two con-

stituent blends, designated as ‘2C’ in this paper were pro-

cessed using PDA pitch and residue. In the case of three

constituent blends, designated as ‘3C’ here, PDA pitch,

VTB, and the residue were used. The constituents of crude

source 1 were used for producing 2C blends. The con-

stituents of crude source 2, 3 and 4 were used for making

both 2C and 3C blends.

The details on the blend constituents are presented in

table 3. The absolute viscosity of PDA pitch from crude

source 2, 3 and 4 was measured using vacuum capillary

viscometer. Due to the high viscosity of the PDA pitch

Table 1. Requirements for paving grade bitumen as per IS 73 [3].

Test

Paving Grades

VG10 VG20 VG30 VG40

Penetration 25�C, 100g, 5s, 0.1 mm (min.) 80 60 45 35

Absolute Viscosity at 60�C, (Poise) 800–1200 1600–2400 2400–3600 3200–4800

Sådhanå (2020) 45:48 Page 3 of 16 48

sample obtained from crude source 1, there were difficulties

in carrying out absolute viscosity measurements using

vacuum capillary viscometer. Hence, the apparent viscosity

at 60�C of the PDA pitch from crude source 1 was mea-

sured by carrying out steady shear experiments using par-

allel plate geometry of 25 mm diameter at a shear rate of

0.1 s-1, in the dynamic shear rheometer. For the sake of

comparison, the apparent viscosity measurements carried

out using PDA pitch from crude source 2, 3 and 4 are

reported here (see table 3). The absolute viscosity of VTB

samples of all the crude sources was measured using vac-

uum capillary viscometer. The viscosity of the residue was

measured using a rotational viscometer as per the test

procedure specified in ASTM 2015 [27]. The percentages

of asphaltenes were determined by following the test pro-

cedure as per IP 469 [28].

2.2 Design of blending scheme

The pilot scale laboratory blending facility used as part of

the current investigation consists of IKA Eurostar 100

control homogenizer with an anchor stirrer and a container

for blending, placed under controlled conditions of tem-

perature using a heating plate. The blend parameters were

the temperature, duration of blending and angular velocity

of the stirrer during blending. The proportion of the blend

constituents and the blend parameters were chosen such

that the resulting blend complies with a target viscosity

grade as per IS 73 [3]. Two constituent blended bitumen of

VG30 grade, processed in the refinery using constituents

from crude source 1 was used as a benchmark to determine

the blend parameters for the laboratory blends. For a VG30

bitumen (specification details are given in table 1), the

typical blend proportions used in the refinery are 86.8%

PDA pitch and 13.2% extract for a 2C blend. Preliminary

2C laboratory blends, using constituents from crude source

1, were prepared using the blend proportions identical to

that used in the refinery. The refinery process conditions

dictate that the temperature range of the blending operation

should be in the range of 140 to 160�C. The duration of

blending for each blend was varied between 30 to 120

minutes. The angular velocity was varied between 500 and

700 rpm. It was observed that the measured penetration and

viscosity values were identical for both refinery and labo-

ratory blend when the angular velocity of the stirrer during

laboratory blending was 500 rpm at a temperature of

140�C, and the duration of blending was 45 minutes. For

subsequent blending trials, to reduce the variability in the

trials, the angular velocity of the stirrer during blending of

both 2C and 3C blends for all the grades of bitumen was

kept constant as 500 rpm. The blended bitumen data of

these preliminary blends were used as a reference for

subsequent blending trials.

2.2.1 Two constituent blends: The range of the process

parameters obtained from the preliminary blending trials

was used to design the blending scheme for 2C blends.

Trial blends were produced using constituents from the

crude source 1 to determine the blend parameters for all the

grades. For a particular target viscosity grade, the blend

proportions were kept constant, and the blend parameters

Table 2. Crude source details.

Source ID Crude source API (�) Blend constituents

Source 1 66% Basrah and 34% Murban 34 PDA pitch, Residue

Source 2 80% AXL, 10% Basrah and 10% Iran Mix 37.6 PDA pitch, Residue, VTB

Source 3 75% Basrah and 25% Arab Mix 30.8 PDA pitch, Residue, VTB

Source 4 80% Basrah and 20% Das 32.5 PDA pitch, Residue, VTB

Table 3. Properties of the blend constituents.

Constituents Properties

Crude source

Source 1 Source 2 Source 3 Source 4

PDA Pitch Penetration at 25 �C (dmm) 7 12 19 14

Absolute Viscosity at 60�C (Pa.s) – 2171.2 1666.5 1759.2

Apparent Viscosity at 60�C (Pa.s) (shear rate 0.1 s-1) 3387.3 4711.9 3050.2 3109.2

Asphaltenes (%) 14.1 16 14 17

VTB Penetration at 25�C (dmm) – 113 100 95

Absolute Viscosity at 60�C (Pa.s) – 83.6 101.7 108.1

Asphaltenes (%) – 15.4 12.4 10.9

Residue Viscosity at 60�C (mPa.s) 10 100 342 124

Asphaltenes (%) 0.6 1.5 0.4 0.5

48 Page 4 of 16 Sådhanå (2020) 45:48

(temperature and duration of blending) were varied in the

range discussed earlier. The blend parameters were final-

ized based on the penetration, and the viscosity values of

the blend which was closer to the range specified for a

particular grade of bitumen as per IS 73 [3] (see table 4).

Identical to the exercise carried out for crude source 1, the

blend parameters were determined using the constituents of

crude source 2, 3, 4, and the details are presented in table 4.

2.2.2 Three constituent blends: The proportion of VTB

used for producing the 3C blends was kept between 5 and

15% by weight of the blend, and the proportion of PDA

pitch was kept constant at 75%. The temperature of

blending was kept constant at 140�C. The trial blends for

designing the blending scheme for the 3C blends were

produced using constituents from crude source 2. The blend

proportions were finalized for a target viscosity grade, and

the blend parameters were varied. The penetration and

viscosity values of the blends were measured and verified

for the compliance to the specifications as per IS 73 [3].

The data presented in table 5 are the final blend parameters

for the three constituent blends for all the crude sources.

It was observed that the viscosity values of certain blends

of VG10 (a 2C blend of crude source 2 and 3; 3C blends of

crude 2, 3 and 4) deviated slightly from the specification

limits. The production parameters of these blends were not

changed as the penetration values of the blends complied

with the specifications as per IS 73 [3]. Furthermore, the

laboratory blending scheme has to be scaled appropriately

to suit the refinery applications. The process parameters for

the blends with minor deviation from the specification

limits can be revised during this scaling procedure at the

refinery to obtain the penetration and viscosity values

within the required range.

3. Analysis of blended bitumen data

The experimental database of blended bitumen presented

in the earlier section was used to develop a statistical

model for predicting penetration and viscosity of the

blends. A multivariate statistical technique was used here

for the same. The test variables of the current investi-

gation include the proportion of the constituents, the

temperature during blending and the duration of blending.

For model development, the variables were bifurcated

into two sets, and those were the mixture and the process

variables.

The mixture variables were the proportion of each con-

stituent. To capture the influence of crude type on the

properties of the blended bitumen, API gravity of the parent

crude was included as one of the variables. From blended

bitumen data, for a particular viscosity grade, it was

observed that the temperature and duration of blending

were influenced by the API gravity of the parent crude. For

instance, by keeping all the other blend parameters similar,

on comparing the blend parameters of crude source 3 and 4,

the duration of blending for 2C-VG10 blends of crude

source 4 was reduced by 30 minutes to meet the specifi-

cation limits as per IS 73 [3] (see table 4). Similar varia-

tions in the process parameters were applied for three

constituent blends of crude source 2 to process VG10 grade

blend of crude source 3, and for VG40 grade blend of crude

source 3 and 4 (see table 5). Hence, API gravity was

included as a process variable. Thus, the process variables

consisted of temperature during blending, duration of

blending and API gravity of the crude. Each process vari-

able was assigned levels which were the different values of

the variable at which the experiments were carried out. For

instance, the temperature during blending consists of three

Table 4. Details on blending scheme for 2C blends.

Source

Pitch

(%)

Residue

(%)

Temperature

(�C)Duration

(min.)

Penetration

(dmm)

Absolute viscosity

(Poise)

Viscosity Grade (IS 73)

[3]

1 75 25 160 90 148 828 VG10

80 20 160 90 82 1810 VG20

85 15 140 45 60 3489 VG30

85 15 150 90 43 3792 VG40

2 75 25 160 90 88 787 VG10

80 20 160 90 60 1750 VG20

85 15 140 45 48 2514 VG30

85 15 150 90 30 3859 VG40

3 75 25 160 90 88 1286 VG10

80 20 160 90 60 2240 VG20

85 15 140 45 48 3203 VG30

85 15 150 90 41 4076 VG40

4 75 25 160 60 115 940 VG10

80 20 160 60 64 1797 VG20

85 15 140 45 52 2577 VG30

85 15 150 90 42 3809 VG40

Sådhanå (2020) 45:48 Page 5 of 16 48

levels which were 140, 150 and 160�C. Similarly, the

duration of blending consists of values which were 30, 45,

60, 90 and 120 minutes. The API gravity of the parent

crudes was in the range of 30.8 to 37.6�.

3.1 Experimental design

The functionalities of the Stat-Ease Design-Expert (ver-

sion 11.0.5.0) software [29] were used in the experi-

mental design, model validation and estimation of the

model reliability in this study. As both mixture and

process variables are involved, a combined design was

used. In a typical refinery operation, there are process

parameters which are ‘hard to change’ (HTC) such as

temperature during blending, API gravity of the crude

and ‘easy to change’ (ETC) parameters such as duration

of blending. For the model development, the designations

for the mixture and process variables are presented in

table 6. The parameters with an upper-case designation

are the ETC parameters, and the lower-case designations

are the HTC parameters. To account for the influence

HTC and ETC parameters, the algorithm used in the

current research for the experimental design was I-opti-

mal design of split-plot type [30]. I-optimal designs are

used in response surface methods (RSM) where the

prediction is important. The algorithm minimizes the

integral of the prediction variance of the variables across

the design space [25, 31]. A total of 26 blends from

crude source 2 and 3 (details presented in table 7) were

included as part of the experimental design. In addition

to the data presented in table 4 and 5 earlier, the trial

blend data was included in the experimental design. The

analysis of the blended bitumen was carried out by fitting

the responses (penetration and viscosity of the blends) to

a polynomial function. All the parameters were assumed

to be discrete, and the range of each parameter are given

in table 7 (second row, columns 4 – 8).

3.2 Prediction models: Penetration and Viscosity

The response, penetration at 25�C of the blends given in

table 7 were fit with Scheffe’s reduced polynomial function

[32] given by the equation (1) below where y is the

response variable, xi, xj represents the mixture and process

factors, bi are the linear coefficients and bij are the inter-

action coefficients. The P-values of all the model parame-

ters were used to estimate statistical significance.

y ¼Xn

i¼1

bixi þXn�1

i\j

Xn

j

bijxixj ð1Þ

The mixture variables ‘a,’ ‘b,’ and ‘c’ were observed to

be statistically significant. Figure 1(a) shows the normal

plot of residuals for the model (before transformation)

which indicates a deviation from a normal distribution. The

combined effect of the process variables, denoted by the

parameters ‘ad’, ‘aE’, ‘af’, ‘bE’, ‘bf’, ‘cd’, ‘cE’, ‘cf’, were

not statistically significant. The response variable was

transformed using a logarithmic function and based on the

P-values, the parameters which are not significant (P-

value[ 0.05) were removed, and the model was refined.

The analysis of variance (ANOVA) results for the pene-

tration model, before and after the transformation of the

response variable are presented in table 8.

Table 5. Details on blending scheme for 3C blends.

Source

Pitch

(%)

VTB

(%)

Residue

(%)

Duration

(min.)

Penetration

(dmm)

Absolute viscosity

(Poise)

Viscosity Grade (IS 73)

[3]

2 75 5 20 60 85 1224 VG10

10 15 60 60 2114 VG20

15 10 45 45 3248 VG30

15 10 90 35 4615 VG40

3 75 5 20 30 91 1356 VG10

10 15 60 65 2300 VG20

15 10 45 48 3359 VG30

15 10 120 44 4502 VG40

4 75 5 20 60 100 1250 VG10

10 15 60 68 2076 VG20

15 10 45 51 2945 VG30

15 10 120 43 4030 VG40

Table 6. Model parameters.

Variable Variables Designation Parameter type

Mixture PDA pitch a HTC

VTB b

Residue c

Process Temperature d HTC

Duration E ETC

API gravity f HTC

48 Page 6 of 16 Sådhanå (2020) 45:48

Figure 1(b) shows the normal plots after the log trans-

formation of the response after removing the terms which

are not significant. The parameters which were significant

in the revised model were the combined effect of the

proportion of PDA pitch, residue, and the process vari-

ables. The final model for penetration (in dmm) is given

in equation (2) below. The R2 value of this model was

0.9695.

lnðpenetrationÞ ¼ 5:15274aþ 5:73617bþ 11:75827c

� 0:009557aE�0:067418af�0:071748cd

þ 0:035250cE þ 0:2525306cf

ð2Þ

The analysis similar to that of the penetration model was

carried out for developing the viscosity model. The vis-

cosities at 60�C of the blends given in table 7 were fit with

Scheffe’s reduced polynomial function given by the equa-

tion (1). The response variable was transformed, and the

analysis of variance (ANOVA) results for the viscosity

model, before and after the transformation of the response

variable are presented in table 9.

Figure 2 shows the normal probability plots of the vis-

cosity model before and after the transformation of the

response variables. The parameters indicating the combined

effect of the proportion of PDA pitch, residue, and the

process variables were observed to be statistically signifi-

cant after the logarithmic transformation of the response

variable. The final viscosity model is given in equation (3).

The R2 value of this model was 0.9905.

lnðviscosityÞ ¼ 7:57766aþ 6:20796bþ 8:92844c

þ 0:005467aE þ 0:066777af

þ 0:032396cd�0:511549cf

ð3Þ

3.3 Model validation

The validation of the prediction models (penetration and

viscosity) was carried out using the blended bitumen data of

crude source 4 (API gravity of 32.5�). The penetration and

viscosity models were used to estimate the values for

response variables using the blend parameters of 8 blends

(4 grades - 2C blends; 4 grades - 3C blends) of crude source

4 presented earlier in tables 4 and 5. The limits for the

response variables were a minimum value for the penetra-

tion (at 25�C), and upper and lower limit of the viscosity (at

60�C) as per IS 73 [3]. The variations in the measured and

Table 7. Design generated by an I-optimal algorithm.

Group Run Source ID Pitch VTB Residue

Temperature

(�C)Duration

(min.) API

(�)Penetration

(dmm)

Absolute

viscosity

(Poise)Range 0–1 0–1 0–1 140–160 30–120

1 1 3 0.75 0 0.25 160 90 30.8 88 1286

1 2 3 0.80 0 0.20 160 90 30.8 60 2240

2 3 2 0.75 0 0.25 160 90 37.6 88 787

2 4 2 0.8 0 0.20 160 90 37.6 60 1750

3 5 3 0.85 0 0.15 140 45 30.8 48 3248

3 6 3 0.85 0 0.15 150 90 30.8 41 4076

4 7 2 0.85 0 0.15 140 45 37.6 48 2514

4 8 2 0.85 0 0.15 150 90 37.6 30 3859

5 9 2 0.75 0.15 0.10 140 90 37.6 35 4615

5 10 2 0.75 0.15 0.10 140 75 37.6 46 3530

6 11 2 0.75 0.15 0.10 140 60 37.6 42 3563

6 12 2 0.75 0.15 0.10 140 45 37.6 45 3248

7 13 3 0.75 0.05 0.20 140 30 30.8 91 1356

7 14 3 0.75 0.05 0.20 140 45 30.8 89 1435

8 15 2 0.75 0.10 0.15 140 45 37.6 61 1845

8 16 2 0.75 0.10 0.15 140 60 37.6 60 2114

9 17 3 0.75 0.05 0.20 140 60 30.8 85 1604

9 18 3 0.75 0.10 0.15 140 60 30.8 65 2300

10 19 3 0.75 0.15 0.10 140 45 30.8 48 3359

10 20 3 0.75 0.15 0.10 140 120 30.8 44 4502

12 21 2 0.75 0.05 0.20 140 90 37.6 105 1049

12 22 2 0.75 0.05 0.20 140 120 37.6 85 1224

13 23 2 0.75 0.25 0 140 90 37.6 15 12259

13 24 2 0.75 0.20 0.05 140 45 37.6 32 5897

14 25 2 0.75 0.10 0.15 140 90 37.6 55 2311

14 26 2 0.75 0.10 0.15 140 120 37.6 51 2585

Sådhanå (2020) 45:48 Page 7 of 16 48

predicted values of the response variables were estimated.

Figure 3 shows the measured and predicted values of

penetration for both 2C and 3C blends. The measured and

predicted viscosity values for all the eight blends are pre-

sented in figure 4.

The mean absolute percentage error (MAPE) was com-

puted to measure the prediction accuracy using the

expression given in equation (4).

MAPE %ð Þ ¼ 100

N

XN

i¼1

yexpi � y

preij j

yexpi

ð4Þ

where N is the number of blends, yprei is the predicted value

of the response variable and yexpi is the measured value of

the response variable. The obtained MAPE was 10.1% for

penetration, and 10.2% for viscosity. The blending

scheme proposed in this investigation is based on condi-

tions in a laboratory. The blend parameters have to be

scaled to suit the conditions at a refinery, during which this

variability could be considered and the parameters be

refined accordingly.

4. Model simulations

The prediction models were evaluated by carrying out

simulations for different ranges of the blend parameters.

The details of two sets of simulations carried out are dis-

cussed here. The first set of simulations was to estimate the

process parameters for a given set of blend proportions. The

second set of simulations was to estimate the blend

parameters for a particular viscosity grade for crudes of

different API gravity.

4.1 Influence of the process parameters

In the context of current investigation on blended bitu-

men, there exists an increasing demand for the lower-

grade (such as VG10) as well as higher-grade (such as

VG40) bitumen, and the refinery operations have to be

suitably designed to address it. One such revision could be

the use of equal blend proportions for processing different

viscosity grades. Towards this end, the simulations were

carried out to verify the correspondence of the blend

proportions to a particular viscosity grade, and they are

discussed below. Table 10 shows the limits of the process

parameters used for this simulation. The simulations for

the process parameters were carried out for two blend

proportions. Firstly, the blend proportions were kept at

75% of PDA pitch and 25% of residue, which was used to

process VG10-2C blend. A set of 100 solutions were

generated with different blend parameters, and it was

observed that the penetration value was in the range of

83–85 and the viscosity values were in the range of

892–993 Poise. Thus, for the blend proportion of 75%

PDA pitch and 25% of residue, only a VG10 grade blend

could be produced for the process parameters shown in

table 10. The set of four blends presented in table 11 was

used to quantify the influence of the process parameters

on the penetration and viscosity of the blends.

The estimated process parameters for the first three

blends in table 11 indicate that for identical temperature

during the blending, a decrease in the duration of blending

results in a decrease in the penetration and the viscosity

Figure 1. Normal probability plot of the residuals - penetration

model.

48 Page 8 of 16 Sådhanå (2020) 45:48

values of the blends. For temperature during the blending of

160�C, a decrease in the duration of blending by 20 minutes

results in a decrease in penetration by 3 dmm and decrease

in viscosity by 75 Poise (see table 11). Similarly, for a

constant duration of blending of 33 minutes, a 2�C decrease

in the temperature during blending resulted in an increase

in penetration by 3 dmm and decrease in the viscosity by 14

Poise as observed from the estimated process parameters of

the last two blends in table 11.

For the second set of simulations, the blend proportions

were kept at 75% of PDA pitch, 10% of VTB and 15% of

residue, which was the proportion used to process VG20-

3C blends. A set of solutions with different process

parameters (temperature and duration of blending) were

generated. The penetration of the blends was in the range of

48–69 and viscosities were in the range of 1962–3031

Poise. Table 12 shows the set of 6 blends which has the

penetration and viscosity values complaint with VG20 and

VG30 grade bitumen specified as per IS 73 [3].

For a given set of blend proportions an increase in the

temperature during blending by 5�C and duration of

blending by 67 minutes, a VG30 grade could be processed

from a VG20 grade blend (the third and fourth blend data in

table 12). It was observed that for a given set of blend

parameters by varying the duration of blending by 30

minutes, the viscosity of blends varies by 257 Poise. This

Table 8. ANOVA results for penetration model.

Variables Term df Error df F-value P-value

Before transformation Subplot 10 9.33 11.61 0.0004

Mixture 2 9.71 39.33 \0.0001

ad 1 14.62 0.0014 0.9708

aE 1 14.13 0.0219 0.8845

af 1 14.25 0.1217 0.7323

bE 1 14.13 0.0597 0.8106

bf 1 10.40 0.0650 0.8038

cd 1 13.84 0.0366 0.8511

cE 1 14.07 0.0552 0.8176

cf 1 14.99 0.0866 0.7725

After transformation Subplot 7 18.00 81.82 \0.0001

Mixture 2 18.00 190.59 \0.0001

aE 1 18.00 10.06 0.0053

af 1 18.00 7.66 0.0127

cd 1 18.00 21.22 0.0002

cE 1 18.00 4.92 0.0397

cf 1 18.00 4.75 0.0428

Table 9. ANOVA results for viscosity model.

Variables Term df Error df F-value P-value

Before transformation Subplot 10 9.33 11.61 0.0004

Mixture 2 9.71 39.33 \0.0001

ad 1 14.60 2.46 0.1381

aE 1 14.21 4.03 0.0641

af 1 14.22 0.0638 0.8042

bE 1 14.19 0.6079 0.4484

bf 1 10.94 0.7922 0.3926

cd 1 13.97 4.39 0.0549

cE 1 14.24 4.91 0.0535

cf 1 14.94 0.4668 0.5049

After transformation Subplot 6 10.44 201.17 \0.0001

Mixture 2 10.62 424.38 \0.0001

aE 1 18.88 39.16 \0.0001

af 1 11.77 8.14 0.0148

cd 1 9.64 5.28 0.0454

cf 1 12.58 22.49 0.0004

Sådhanå (2020) 45:48 Page 9 of 16 48

observation corresponds to the first two blends of VG20

grade. Similar is the case of the first two blends of VG30

grade (see table 12). There is a combined effect of the

process parameters on the penetration and viscosity of the

blend and a decrease in duration results in a variation of

penetration and viscosity values of the blends. The API

gravity of the crude also influences such variations in the

penetration and viscosity values with the change in the

process parameters, and this is discussed in the following

section.

4.2 Influence of API gravity of the crude

The refineries use multiple crudes to process paving grade

bitumen and, in such scenario, it is paramount to identify

the influence process parameters on API gravity of the

parent crude. The prediction models were used to design

the blending scheme for a particular viscosity grade for

crudes of API gravity used in the current study. The limits

of the parameters for determining the blending scheme for a

VG30 grade binder is given in table 13.

The desirability function approach was used to determine

the optimal set of solutions. Desirability function is

extensively used for multivariable optimization procedures

Figure 2. Normal probability plot of the residuals - viscosity

model.

Figure 3. Comparison of measured and predicted values: Pen-

etration model.

48 Page 10 of 16 Sådhanå (2020) 45:48

[30, 33]. The desirability function can take values from 0 to

1, wherein a value of 1 indicates maximum desirability and

0 is for undesirable solutions. The optimal set of blend

parameters with a desirability value of 1 was identified.

From the set of 100 optimal solutions, the blend parameters

were chosen based on the compliance to the specifications

as per IS 73 [3].

The blend parameters estimated using the prediction

models (penetration and viscosity) are presented in

table 14. It was observed that for identical blend propor-

tions, the process parameters vary with the API gravity of

the parent crude. The temperature during blending was

observed to be lower for blends processed using con-

stituents from the lighter crudes (API[35�), with all other

parameters being similar. The estimated temperature during

blending for the blend with API gravity of crude as 31� was158�C whereas for the blend with API gravity of crude as

37� was 147�C (see table 14). A reduction in the temper-

ature during blending by 11�C resulted in a decrease in

viscosity of the blend by 220 Poise and penetration by 2

dmm. Similar decision tables for blend parameters can be

generated using the prediction models for the other vis-

cosity grades.

For the sake of brevity, the results of VG10, VG20 and

VG40 grade blends of lowest and highest API gravity are

reported in table 15. It was observed that for a particular

viscosity grade, the process parameters were influenced by

the proportion of VTB. For instance, the proportion of

VG10 grade was 70% of PDA pitch, 10% of VTB and 20%

of residue and the temperature during blending was similar

for the blends of both the crudes. However, for the VG20

grade, the blend proportion was 70% of PDA pitch, 17% of

VTB and 13% of residue, the temperature during blending

was observed to decrease with the increase in the API

gravity of the crudes. The blends processed using con-

stituents of heavier crudes require a higher temperature

during blending when compared to lighter crudes. A similar

trend as that of VG30 blends was observed for the blends of

VG40 grade.

4.3 Performance grading of blends

The pass/fail temperatures of the blends were measured,

and the performance grades (PG) of the blends were

determined (see table 16). The range value, which is the

difference between the pass/fail temperature of the blended

bitumen sample in unaged and long term aged condition

was calculated. For a given viscosity grade, the higher

value of the range indicates better performance as per the

performance grade system.

In addition to this, it is worthwhile to see whether the PG

data could be used to identify the viscosity grades as

ascertained from the blends independently. As of now,

Indian refineries do not produce PG bitumen. However, it

will be interesting to see whether a given viscosity grade,

for instance, VG10 from all the crude sources can provide a

unique performance grade. Such investigations have been

carried out in the past [34, 35]. However, these investiga-

tions did not report data on the variability associated with

the production aspects of the viscosity grade bitumen and

Figure 4. Comparison of measured and predicted values: Vis-

cosity model.

Table 10. The limits of the process parameters.

Parameter

Limits

Lower Upper

Temperature (�C) 140 160

Duration (minutes) 30 120

API (�) 32.5

Penetration (dmm) 35 85

Absolute Viscosity (Poise) 800 4800

Sådhanå (2020) 45:48 Page 11 of 16 48

performance grade bitumen. In addition to this, the influ-

ence of production parameters on the grades of the blended

bitumen was not precisely known.

On comparing the pass/fail temperature of the blends of

all the viscosity grades, for a given crude source, the

pass/fail temperature of the 3C blends were observed to be

higher than that of the 2C blends at both unaged (except for

VG20 grade blend of crude source 4) and long-term aged

condition (except for VG40 grade blend of crude source 4).

In the case of the short-term aged blends, the pass/fail

temperature of the 3C blends of crude source 3 were

observed to be identical or lesser than the 2C blends. A

similar trend was observed in the case of blends of VG20

and VG40 grade of crude source 2.

The comparison of the blends of crude source 2 is pre-

sented in figure 5 (a) and (b). For a given viscosity grade,

the 3C blends of crude source 2 were observed to have a

higher range value than the 2C blends. For instance, the

range value of 2C-VG30 blend was 41.4�C and that of 3C-

VG30 blend was 42.8�C. The increase in range value of 3C

blends of crude source 2 could be attributed to the process

Table 11. Estimated process parameters - 2C blend.

Sl.No.

Components

Temperature

(�C)Duration

(min.)

Penetration

(dmm)

Absolute viscosity

(Poise)

Viscosity Grade (IS 73

[3])

Pitch

(%)

Residue

(%)

1 75 25 160 53 85 993 VG10

2 75 25 160 46 84 967 VG10

3 75 25 160 33 82 918 VG10

4 75 25 158 33 85 904 VG10

Table 12. Estimated process parameters - 3C blend.

Sl.

No.

Components

Temperature

(�C)Duration

(min.)

Penetration

(dmm)

Absolute viscosity

(Poise)

Viscosity Grade (IS

73) [3]

Pitch

(%)

VTB

(%)

Residue

(%)

1 75 10 15 140 30 69 1962 VG20

2 75 10 15 140 60 65 2219 VG20

3 75 10 15 150 39 61 2143 VG20

4 75 10 15 155 106 51 2885 VG30

5 75 10 15 160 113 48 3031 VG30

6 75 10 15 160 74 51 2591 VG30

Table 13. The limits of parameters – VG30 grade.

Parameter

Limits

Lower Upper

PDA pitch 0.7 0.85

VTB 0 0.2

Residue 0 0.3

Temperature (�C) 140 160

Duration (minutes) 30 120

API (�) 30.8 37.6

Penetration (dmm) 45 50

Absolute Viscosity (Poise) 2400 3600

Table 14. Decision table for paving bitumen – VG30 grade.

Sl.

No.

Pitch

(%)

VTB

(%)

Residue

(%)

Temperature

(�C)Duration

(min.)

API

(�)Penetration

(dmm)

Absolute viscosity

(Poise)

1 70 20 10 158 69 31 49 3224

2 70 20 10 154 71 32 50 3188

3 70 20 10 156 56 33 50 3014

4 70 20 10 145 78 34 50 3161

5 70 20 10 142 82 35 49 3169

6 70 20 10 142 74 36 49 3043

7 70 20 10 147 67 37 47 3004

48 Page 12 of 16 Sådhanå (2020) 45:48

parameters of 3C blends and also the addition of VTB. For

instance, the 2C-VG20 blend of crude source 2 was pro-

cessed using 80% PDA pitch and 20% residue for 90

minutes at temperature during blending kept constant at

160�C. In the case of 3C-VG20 blend, the blend propor-

tions were 75% of PDA pitch, 10% of VTB and 15% of

residue, and the process parameters were the temperature

during blending kept constant at 140�C for 60 minutes.

In order to quantify the influence of the addition of VTB

on the range value, the blend data corresponding to VG30

grade of all the crude sources was used. The process

parameters of these blends, both 2C and 3C, were identical

(the temperature during blending kept constant at 140�C for

a duration of 45 minutes). It was observed that the reduc-

tion of the proportion of PDA pitch by 5% and the addition

of VTB by 10% of the total weight of the blend resulted in

an increase in the range value of the 3C blends of crude

source 2 for VG30 grade. However, the range value of 2C-

VG30 blends of crude source 3 and 4 was higher than that

of 2C-VG30 grade blends.

Similar trends were observed in the case of blends of

crude source 3 and 4 for all the viscosity grades. The range

value of 3C blends was observed to be identical to or lower

than that of 2C blends (except for VG40 blend of crude

source 4). Figure 6 (a) and (b) show the comparison of the

blends of crude source 3. Thus, for the blends processed

Table 15. Decision table for paving bitumen.

Sl.

No.

Pitch

(%)

VTB

(%)

Residue

(%)

Temperature

(�C)Duration

(min.)

API

(�)Penetration

(dmm)

Absolute viscosity

(Poise)

Viscosity Grade (IS

73) [3]

1 70 10 20 156 36 31 88 1077 VG10

2 70 10 20 159 72 37 92 851

3 70 17 13 152 47 31 65 2189 VG20

4 70 17 13 140 36 37 67 1839

5 80 10 10 157 44 31 39 4231 VG40

6 80 10 10 143 32 37 39 3900

Table 16. Paving grades of the blends.

Viscosity Grade (IS

73) [3]

Crude

source

Blend

type

Pass/fail temperature (�C)

Range

(�C)Intermediate

Temperature (�C)PG Grade ASTM

2016 [36]Unaged

Short-term

aged

Long-term

aged

VG10 2 2C 58.7 60.3 20.9 37.8 22 PG 58-XX

3C 62.4 61.9 21.2 41.2 22 PG 58-XX

3 2C 61.3 62 19.1 42.2 22 PG 58-XX

3C 62.9 62.8 23.3 39.6 25 PG 58-XX

4 2C 60 61 18.4 41.6 19 PG 58-XX

3C 62 62.6 20.7 41.3 22 PG 58-XX

VG20 2 2C 63.8 65 23.2 40.6 25 PG 64-XX

3C 66.5 64.6 23.7 42.8 25 PG 64-XX

3 2C 65.7 67 22.6 43.1 25 PG 64-XX

3C 66.9 65.7 24 42.9 25 PG 64-XX

4 2C 63.4 63.6 20.4 43 22 PG 64-XX

3C 62.5 65.5 22.6 39.9 25 PG 64-XX

VG30 2 2C 67.2 66.3 25.8 41.4 28 PG 64-XX

3C 69.7 67.9 26.9 42.8 28 PG 64-XX

3 2C 68.6 69 24 44.6 25 PG 64-XX

3C 69.6 68.6 26.8 42.8 28 PG 64-XX

4 2C 67.9 66.3 20.4 47.5 22 PG 64-XX

3C 68.2 68.3 26.6 41.6 28 PG 64-XX

VG40 2 2C 69.4 72.3 26 43.4 28 PG 70-XX

3C 72.2 68.9 27.6 44.6 28 PG 70-XX

3 2C 69.8 71 25.8 44 28 PG 70-XX

3C 71.1 71.1 27 44.1 28 PG 64-XX

4 2C 69.6 68.7 27.3 42.3 28 PG 70-XX

3C 70.7 69.5 25.6 45.1 28 PG 64-XX

Sådhanå (2020) 45:48 Page 13 of 16 48

using constituents from the lighter crudes, the addition of

VTB would increase the range value. In the case of blends

processed using constituents from heavier crudes (API

\35�) the appropriate choice of process parameters and the

blend proportions would result in higher range values.

The performance grades are specified based on the

pass/fail temperatures at short term aged and long-term

aged condition. For instance, consider two constituent

blend of crude source 2, VG10 sample (VG10-2C). The

highest pass temperature for VG10-2C at short-term aged

condition is 58�C and that in the long-term aged condition

is 22�C (see table 16). Hence, the PG grade would be

designated as PG 58-XX. From the PG data, it was also

observed that the blends (both 2C and 3C) of crude source

2, have similar high and intermediate temperature grades

for all the viscosity grades. The VG10 blends of all the

crude sources had the same high-temperature performance

grade of PG 58-XX. Similarly, the VG20 and VG30 grades

correspond to a high-temperature grade of PG 64-XX (see

table 16). This observation is in agreement with the trend

observed in the simulation of process parameters discussed

earlier that the blend proportions used to produce VG20

binder could be used to produce a VG30 binder. Using the

same analogy, the blend proportions of VG10 could be used

to process only VG10 grade binders, and the blend pro-

portions of VG30 could be used to process both VG30 and

VG40 grades. However, such trends were not observed for

the blends of VG40 grade. The high-temperature grade of

3C-VG40 blends of crude source 3 and 4 was PG 64-XX,

which is similar to that of VG20 and VG30 grade blends

(see table 16).

The correspondence of two different grading systems

(performance and viscosity based) was established using

the study. The blend parameters used to process viscosity

based blended bitumen can be used to process blended

Figure 5. Comparison of blends - Crude source 2.

Figure 6. Comparison of blends - Crude source 3.

48 Page 14 of 16 Sådhanå (2020) 45:48

bitumen complying to performance grade. However, in

such cases, the blending scheme proposed in the study

would require minor refinements.

5. Summary and discussion

This study facilitated in developing a blending

scheme for viscosity grade binders. The blend formula-

tions for all the four viscosity grades VG10, VG20,

VG30, and VG40 as per IS 73 [3], were carried out in

the laboratory facility. The blended bitumen data was

used in an optimal combined design developed using the

design of experiments framework. A Scheffe’s reduced

linear polynomial function was fit to penetration and

viscosity of the blends to develop a prediction model

using the blended bitumen data. The parameters of the

prediction models were the blend proportions, the process

parameters and API gravity of the parent crude. The

penetration and viscosity of the blends were estimated

using the model and compared with the experimental

data. The variations between the estimated and measured

values were quantified using the error estimate (MAPE),

and it was found to be 10.1% for penetration model and

10.2% for viscosity model.

The prediction models were used to estimate the feasi-

bility of processing bitumen of different viscosity grades

using identical blend proportions. The simulation of the

process parameters helped in identifying that the blend

proportions are unique for a particular viscosity grade. It

was observed that using blend proportions of lower vis-

cosity grades, higher viscosity grade blends could be pro-

cessed (an exception to this being blends of VG10 grade).

From performance grades of the blends, it was observed

that the blend of a particular viscosity grade corresponds to

a high-temperature performance grade. The blends of vis-

cosity grade VG10 corresponds to the high-temperature

performance grade PG 58-XX. The high-temperature

grades of VG20 and VG30 grade blends were observed to

be the same, which was PG 64-XX. In the case of VG40

blends, the performance grades were PG 70-XX and PG

64-XX. The correspondence of the viscosity grades to the

performance grades was observed. Such observations

indicate the amenability of using the viscosity grade-based

blending scheme for processing paving bitumen as per the

performance grade specifications.

The influence of API gravity of the parent crude and

proportion of VTB on the blend parameters was charac-

terized, and it could be used as a yardstick for making the

appropriate choice of the blend parameters. The process

parameters of the blends were observed to vary with the

proportion of VTB and such variations are influenced by

the API gravity of the parent crude. It is, however, essential

to understand that the blend parameters are interdependent

and individual effects of each of the parameters on the

penetration and viscosity of the blends have to be

adequately quantified. The experimental database devel-

oped as part of this investigation could be used for under-

standing such influence of each of the process parameters

on the response variables. The characterization of these

influences is essential to refine the existing blending

schemes for its application in the refineries to obtain paving

bitumen of better quality.

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