Optimization of ultrasonic waves application in municipal wastewater sludge treatment using response surface method

Accepted Manuscript Optimization of Ultrasonic Waves Application in Municipal Wastewater Sludge Treatment Using Response Surface Method

Mahdi Ghafarzadeh, Rezvan Abedini, Rohollah Rajabi PII:

S0959-6526(17)30385-2

DOI:

10.1016/j.jclepro.2017.02.159

Reference:

JCLP 9085

To appear in:

Journal of Cleaner Production

Received Date:

07 May 2016

Revised Date:

09 January 2017

Accepted Date:

22 February 2017

Please cite this article as: Mahdi Ghafarzadeh, Rezvan Abedini, Rohollah Rajabi, Optimization of Ultrasonic Waves Application in Municipal Wastewater Sludge Treatment Using Response Surface Method, Journal of Cleaner Production (2017), doi: 10.1016/j.jclepro.2017.02.159

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ACCEPTED MANUSCRIPT

Optimization of Ultrasonic Waves Application in Municipal Wastewater Sludge Treatment Using Response Surface Method Mahdi Ghafarzadeh1, Rezvan Abedini*2, Rohollah Rajabi3 1- Sharif University of Technology, Tehran, Iran, [email protected] 2- Amirkabir University of Technology, Tehran, Iran, [email protected] 3- K. N. Toosi University of Technology, Tehran, Iran, [email protected]

Abstract Today, many limitations are faced in sludge treatment and disposal. Therefore evaluation of different approaches to reduce sludge production in the activated sludge process has attracted great attention. Application of ultrasonic waves in sludge treatment caused to reduce sludge volume and accelerate sludge digestion. This research intended to study the efficiency of ultrasound in dewatering biological sludge in wastewater treatment plants under different conditions. In this study, response surface method was used to investigate results and optimum conditions were determined. Sludge was treated in different conditions as follows: 330 to 920 watts ultrasound power, 1.5 to 3.9 liters sample volume and 6 to 20 minutes ultrasonic exposure duration. Then, the effect of waves was studied in terms of SRF (specific resistance to filtration). Results of the experiments showed that, the ultrasonic method significantly increases the SRF. Also based on response surface method, the best performance of ultrasonic application in sludge treatment is achievable at the following conditions: 625 watts ultrasound power, 2.7 liters sample volume and 13 minutes ultrasonic exposure duration. A mathematical model for accurate prediction of SRF changes of the sludge was derived using statistical data. Keyword: Sludge Treatment, Response Surface Method, Ultrasonic.

1

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Abbreviations that are used in this paper: CST: Capillary Suction Times, is a quality parameter for sludge. SRF: Specific Resistance to Filtration, is a quality parameter for sludge. VSS: Volatile Suspended Solids, is a quality parameter for sludge. VDSS: Volatile Dissolved Suspended Solids, is a quality parameter for sludge and wastewater. SCOD: Soluble Chemical Oxygen Demand, is a quality parameter for sludge and wastewater. TCOD: Total Chemical Oxygen Demand, is a quality parameter for sludge and wastewater. MLVSS: Mixed Liquor Volatile Suspended Solids, is a quality parameter for sludge and wastewater.

1. Introduction Biological treatment of wastewater produces a large amount of sludge (bio solids) that is very putrescible. This problem caused using of new technologies. Primary sludge is very putrescible, foul smelling, grey, and 60-70% of it consists of volatile solids. Secondary sludge is brown and odorless and is mostly a microbial mass that 70-80% of its volume consists of volatile organic solids (He et al., 2011, Qaderi et al., 2011). Sludge produced with such characteristics causes no fewer problems than the original wastewater itself. A large volume of sludge is produced in large wastewater treatment plants. Therefore, different treatments should be applied on this sludge prior to its disposal, it must be dewatered as much as possible, and its content of volatile solids must be reduced. Sludge condensation for dewatering, and sludge stabilization for reducing volatile organic substances are among the pre-disposal processes carried out on sludge (Dong-Qin He et al., 2015; Sahinkaya, 2015; Skinner et al., 2015). Currently, treatment and disposal of excess sludge is one of the most important challenges. More than fifty percent of the total of costs associated with construction and operation of wastewater treatment plans is related to treatment and disposal of excess sludge (Zhao et al., 2015). Sludge digestion, which is carried out by biological digesters and is used to stabilize it, can be practiced in one of two ways: aerobic and anaerobic. Anaerobic digestion has wider application as it costs less in digestion of large volumes of sludge, but it is a slow process due to different limitations that usually takes 20 days or more to be completed (Yuan et al., 2016). Methods such as thermal pre-treatment, chemical materials consumption, mechanical disintegration of sludge, and ultrasonic disintegration of bio solids are among methods used to improve hydrolysis in the process of anaerobic digestion. Sludge dewatering increases sludge treatment efficiency, reduces volume of sludge, and decreases costs of sludge transportation and disposal (Liu et al., 2009; Saha et al., 2011; Sahinkaya, 2015). 2

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Numerous sewage-related problems are the driving force for using new technologies instead of older and conventional methods. Mechanical vibration and ultrasound are of the methods that can be used to improve and accelerate the sludge treatment process. Since 1954, empirical and laboratory studies have shown that the propagation of ultrasonic waves in water and wastewater eliminates organic pollutants (Lifka. j et al., 2003). Sludge disintegration is the break-up of cell walls freeing nutrients stored within cells which reduces sludge volume and helps its biodegradation (Le et al., 2013). Ultrasound, which accelerates sludge digestion, promotes microbial activities and improves the dewatering process, is used at different energy levels. Variations in microbial activities and dewatering capacity depend on the degree of sludge disintegration during ultrasonic treatment. If the degree of sludge disintegration is less than 20%, low-density ultrasound of longer duration has greater effect compared to high-density ultrasound of shorter duration (Li Huan et al., 2009). Experiments have shown that production rate of hydroxyl radicals at the frequency of 817 kHz is 20 to 25 times higher than of 20 kHz (Vajenhandl S and Le Marechal AM, 2007). Other experiments showed that, at the intensity of 0.5 W/ml, 30% of the sludge mass was disintegrated in 30 minutes, its dry solids content was lowered by 24%, and its biodegradability was increased by 95% (Panyue Zhang et al., 2007). Sludge mass decreases as the energy applied on sludge increases. However, when the energy level exceeds 35,000 kJ/kg VSS, it has a negative effect on decreasing sludge mass. In addition, use of higher energy levels than 35000 kJ/kg VSS to achieve higher specific energy per unit mass of sludge, has the more negative impact on sludge mass reduction (Mohammadi et al., 2011). Dual frequency ultrasound (28-48 kHz) had greater effect than single frequency ultrasound (28 or 40 kHz) on Soluble Chemical Oxygen Demand (SCOD) elimination rate. Single frequency ultrasound effect on disintegration at 28 kHz is more effective compared to 40 kHz (Jung et al., 2011). Ultrasonic pre-treatment decreases the retention time in thermophilic aerobic digestion required to achieve VSS removal efficiency of 55% from 15 days to 3 days (Chang et al., 2011). Capillary Suction Times (CST) decreases as ultrasound energy increases, while VDSS/VSS (Volatile Dissolved Suspended Solids / Volatile Suspended Solids) and SCOD/TCOD (Soluble Chemical Oxygen Demand/Total Chemical Oxygen Demand) turbidities increase by ultrasonic pre-treatment. In addition, dewatering capacity also varies with ultrasonic pre-treatment, whereas sludge mass and volume decrease by this pre-treatment. In addition, it was found that application of the specific energy of 2,000-3,000 kJ/l rapidly changes the characteristics of the treated sludge. Therefore, ultrasonic pre-treatment is a proper tool for the enhancement of sludge dewatering capacity and reduces the volume of sludge produced in biological treatment of wastewater (Seungmin Na et al., 2007). 1.1. Ultrasonic Waves Ultrasonic waves are a simple form of sound that human cannot hear, and oscillations with frequencies of 3

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more than 20 kHz are called ultrasonic waves. Any wave, whether ultrasound or hearable wave, is a kind of mechanical vibration in a gas, liquid or solid environment moving outside sound source with a constant speed. Ultrasound waves have broad applications in chemistry known as Sonochemistry, which is a very interesting research field for experts in environmental and chemical sciences (Le et al., 2013; Mason .T.J, 2003). Applications of ultrasonic waves go back to the year 1880 when Pierre Curie discovered piezoelectric effect (Lesko. T.M, 2004; Mason .T.J, 2003). The cavitation phenomenon, which occurs in liquids, in addition to being produced during vibrations, is also generated under the influence of high-intensity ultrasound (HIU) waves. The cavitation phenomenon, in addition to corrosion, has chemical impacts in liquid environments (Lifka. j et al., 2003). The cavitation creates phenomena in the environment surrounding them, which can be used in wastewater treatment. The most important of these phenomena are the generation of tiny cavitation bubbles throughout the liquid environment, increased production of free radicals such as H and OH radicals in the liquid environment, generation of a pressure gradient and shear stress in the liquid environment, and generation of local heat around the water jet created by the cavitation (Majumdar S, 1998). Cavitation in water occurs at different frequencies, but is generally used at 5 kHz to 5 MHz frequencies. Bubble size increases with decreases in frequency, which reduces the explosive power. The required power for cavitation in water at the frequency of 400 kHz is 10 times more than that needed at the frequency of 10 kHz. That is why a frequency range of 20 to 500 kHz is selected for sonochemical processes (Majumdar S, 1998; Margulis M.A, 2003; Mason .T.J, 2003). On the other hand, the optimum frequency for degradation of pollutants depends mainly on properties of substance like its volatility (Lifka. j et al., 2003). In addition to the frequency of the irradiated waves, other important factors affecting the ultrasonic process include power of the waves and duration of their irradiation. This research studied the effects of irradiation of waves under different conditions using Response Surface Method (RSM) in order to find the best possible conditions for using ultrasonic waves to accelerate the sludge dewatering process. Moreover, specific resistance to filtration, SRF, was used as a criterion for the degree of sludge dewatering capability. 1.2. Response Surface Method (RSM) In RSM, two levels of a variable are specified by (+1) and (-1) codes. These codes are, in fact, the only information regarding the levels of each variable. In this way, the third level, as the zero or central level (0), has a value between these two levels. Two levels before (-1) coded level and after (+1) coded level 4

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were calculated. These levels are named (-α) and (+α) coded levels, respectively. After selecting the plan, equation of the model is determined and its coefficients are predicted. In RSM the equation of model is full second order generally. The second order model can be written in the form of equation (1): 4

𝑌 = 𝛽0 +

4

4 2 𝛽𝑖𝑗𝑥𝑖𝑥𝑗 𝛽𝑖𝑖𝑥 𝑖 + 𝑖=1 𝑖<𝑗=2

∑𝛽 𝑥 + ∑ 𝑖 𝑖

𝑖=1

∑

(1)

Where 𝛽0 ،𝛽𝑖 ،𝛽𝑖𝑖 and 𝛽𝑖𝑗 Are the constant, linear effect, second order effect and interaction effects of regression coefficients, respectively. 𝑥𝑖 and 𝑥𝑗 are encoded independent variables (Shi et al., 2015; Yang et al., 2011). Matrix notation is shown in the following equations:

𝑦 = 𝑋𝛽 + 𝜀

[][

(2)

][ ] [ ]

𝑦1 1 𝑥11 𝑥12 . . . 𝑥1𝑘 𝛽0 𝜀1 𝑦2 1 𝑥21 𝑥22 . . . 𝑥2𝑘 𝛽1 𝜀2 . = ……………………….. . + . . ……………………….. . . . ……………………….. . . 𝑦𝑛 1 𝑥𝑛1 𝑥𝑛2 . . . 𝑥𝑛𝑘 𝛽𝑘 𝜀𝑛

(3)

Equation systems (2) and (3) are solved using the least square method and the coefficients of the equations are determined. After obtaining the coefficients of the equations, the equations are solved and the response is predicted. Compatibility of the model with test data must then be checked. Different methods are available for this purpose including analysis of the remainder, root-mean-square of the predicted errors and the mismatch test. The overall prediction capability of the model was expressed by the coefficient of determination (R2) and its statistical importance was specified using the Fisher test. The importance of each regression coefficient (model) was derived based on the t-test. It should be noted, however, that R2 is not able to show the accuracy of model by itself as it shows the variations around the 2 mean response. Therefore, another coefficient, called the adjusted coefficient of determination, 𝑅𝑎𝑑𝑗 , is

also used. Unlike R2 , in the calculation of this coefficient, sum of squares is replaced by the mean sum of squares (Khuri and Mukhopadhyay, 2010; Shi et al., 2015; Vega et al., 2015).

2. Materials and Methods 2.1. Ultrasonic irradiation facility The set required for the generation and irradiation of ultrasonic vibration including power supply, converter, booster and radiator (horn) was designed and constructed in order to perform tests to investigate the effects of ultrasonic vibrations on sludge characteristics. Fig. 1 shows a view of the apparatus and layout of the components. The transducer module is the heart and the power supply is the 5

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brain of the ultrasonic treatment apparatus. Ultrasonic oscillations enter the liquid chamber by the booster made of Al7075-T6 aluminum alloy and the radiator made of Ti-6Al-4V titanium alloy. The ultrasonic transducer has 1 kW of power and operating frequency of 20 kHz. The ultrasonic transducer converts high-frequency electricity into mechanical vibrations with the amplitude of about 10 micrometers and frequency of 20 kHz. With the aid of a finite element software, the vibrating radiator inside the liquid was designed and optimized to transfer the maximum possible amount of ultrasonic intensity into the liquid compartment. The radiator is the main component of the vibrating system in relation to the liquid environment which, due to the generation of the cavitation phenomena around it, is exposed to corrosion. That is why the radiator is made of the Ti-6Al-4V alloy with high corrosion fatigue strength and suitable capability of transferring oscillations. The electric power supply converts the power it receives from the urban electricity system (220 V, 50Hz) into high frequency (20 kHz) electric power. It should supply the required power in a given voltage and resonant frequency for the vibrating system. It is equipped with a self-tuning system that keeps the vibrating system in the resonant state even if its resonance frequency changes due to variations in boundary conditions and liquid properties. The vibrating system is connected to base plate from the vibration node in order to avoid transfer of oscillations to the apparatus frame and its other components.

Fig. 1: layout and equipment for performing the ultrasound-processing test on the liquids and sludge.

Ultrasonic oscillations were applied to the sludge samples taken from the mixture entering digester input at the south Tehran wastewater treatment plant in order to study the effects of the parameters power, time, 6

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and sample volume. According to Table 1, ultrasonic oscillations were applied to the sludge samples at power range of 330-920 watts, ultrasound irradiation time of 6 to about 20 minutes, and the sample volume of 1.5 to 3.9 liters. Table 1 presented the levels of independent variables of this research based on RSM. Table 1: Levels of independent variables of this research based on RSM

Variable\Level A:Power (W)

-α

-1

0

1

+α

330.69 450 625 800 919.31

B: Volume (Lit)

1.52

2

2.7

3.4

3.88

C: Time (min)

6.27

9

13

17

19.73

In this paper, low and high levels of independent variables (ultrasonic irradiation power, exposure duration and sludge volume) were selected based on pretests. Beyond these levels, the variation of SRF results were less than 5% of SRF result related to latest selected level of independent variables in this paper.

2.2. Evaluation of the sludge characteristics After applying the ultrasonic oscillations to the samples, the SRF assessment test was conducted. SRF was measured using the vacuum filtration method. In this method, 100 ml of the sample was poured inside a standard Buchner funnel having filter paper with a diameter of 9 cm. The sample was then put under the constant pressure of 46 kPa for 20 minutes. Volume of the sample passing through the funnel as well as the duration of filtration was recorded at 5 minutes intervals. The slope of line was determined by drawing the volume-time diagram. The SRF was determined by placing the value of this slope in equation 4.

r=

2𝑃𝐴2𝑏 𝜇𝐶

(4)

Where P: pressure inside tank (Pa); that is 46000 Pa. A: filter surface area (m2); that is the area of circle with 0.09 meter diameter.

: Sludge viscosity (Pa.s); that is determined by sludge viscosity meter. r: SRF (m/kg) C: suspended particles concentration (kg/m3); that is called MLVSS. b: the slope of the line of best fit which is given from plotting t/V against V (V is the volume of filtrate (m3) and t is elapsed time for filtering). The MLSS test is used to calculate the concentration of the suspended solid particulates. To perform this test, a given volume is first prepared considering the concentrations of the samples. The filter paper is 7

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then dried at 103oC for 10 minutes and its dry weight is determined. The sample is then passed through the filter paper and the filter paper is dried again, this time at 103oC for an hour and weighted. The concentration of the MLSS is derived by dividing the difference between the weights of the filter paper before and after the sample passes through it to the initial volume of the sample.

2.3. Application of the Response Surface Method to Extract the Mathematical Model This study uses the RSM in order to extract the model and to find the maximum effect. By taking number of the variables and maximum and minimum limits determined for each variable into account, this method designs the experiment matrix.This way, number of tests and the levels of each variable in each test are determined. If there are a large number of variables, this method is preferred to complex largevolume methods like the full factorial. The experimental design is reliable. Therefore, this method facilitates the research process and reduces the time required, and the costs involved. To this end, the tests were designed using Design Expert software and statistical analyses were performed on them. The Design Expert is a powerful software for the statistical simulation of various processes. It makes it possible to model the desired processes statistically. In addition, it enables drawing 3D graphs for identifying and analyzing various processes.

3. Results and Discussions This study tried to estimate the relationship between design inputs and output characteristics using the experimental design based on the RSM. In this study estimation of the response surface was done for prediction and optimization of the results. On this basis, three main factors were determined as the independent variables for each sample: 1) the power of the ultrasound irradiation, 2) the volume of the sample exposed to ultrasound irradiation and 3) the duration of irradiation. Different combinations of the values of these variables were used to prepare samples that were sent to laboratory for measuring SRF. In addition to MLSS values, which itself is one of the variables that determine the SRF, the values of MLVSS and pH were also measured. Table 2 shows the full results of the tests conducted on each sample. In this table, the three main factors were the variables of each sample. The first one was the power of the ultrasonic waves, the second was the sludge volume, and the third was durations in which the samples were exposed to the ultrasonic waves. The last column shows the SRF value for each sample at various power levels of the ultrasound, volume of the samples, and durations that samples were exposed to ultrasonic waves. The results of various powers of ultrasound waves, samples volumes and exposure durations to ultrasound waves were assessed to determine maximum sludge disintegration. In addition to the samples shown in Table 2, another sample called the control sample was assessed prior to applying ultrasonic waves and the 8

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SRF, MLSS, MLVSS, and pH tests were conducted on it. Having these values prior to applying ultrasonic waves enables us to study the extent of change in SRF and other parameters. The test results shown in Table 2 indicates the positive effect of ultrasonic waves on SRF. Table 2: conditions related to irradiation of ultrasonic waves on the samples and test results Factors

Result

A

B

C

Power W

Volume lit

Time min

pH

MLSS mg/L

MLVSS mg/L

SRF 1013 × m / kg

Sample

-

-

-

7.40

20,640.00

13,060.00

209.80

1

450.00

3.40

17.00

7.50

14,480.00

9,500.00

306.00

2

450.00

2.00

9.00

7.30

20,780.00

14,540.00

228.30

3

800.00

3.40

17.00

7.40

20,250.00

12,760.00

232.00

4

625.00

3.88

13.00

7.20

14,820.00

21,880.00

227.90

5

800.00

2.00

17.00

7.30

14,410.00

21,530.00

420.90

6

800.00

3.40

9.00

7.20

14,780.00

21,210.00

220.90

7

625.00

2.70

6.27

7.40

14,090.00

21,000.00

246.60

8

450.00

3.40

9.00

7.60

13,750.00

20,690.00

253.40

10

800.00

2.00

9.00

7.50

14,460.00

23,140.00

221.50

12

625.00

2.70

19.73

7.30

17,580.00

24,370.00

521.30

13

625.00

1.52

13.00

7.30

15,730.00

22,340.00

364.20

14

919.31

2.70

13.00

7.30

14,980.00

23,820.00

330.90

15

330.69

2.70

13.00

7.30

16,470.00

23,460.00

243.90

16

450.00

2.00

17.00

7.30

15,880.00

23,040.00

303.70

17

625.00

2.70

13.00

7.45

14,585.00

22,650.00

277.05

Number

This study is concentrated on obtaining optimum values for three variables of the power of ultrasound waves, the ultrasonic exposure duration, and the sample volume. Considering the results of the tests and comparing the SRF values of samples enable us to introduce one sample as the optimum one and to select the power of the ultrasound waves, the duration of exposure, and the sludge volume related to it as the optimum values. On this basis, the irradiation of ultrasound with the power of 625 watts on a sludge sample with a volume of 2.7 liters and duration of exposure of 13 minutes resulted in the optimum extent of SRF. In this paper, the model is extracted by using Design Expert software and through employing the response surface method. Use of statistical methods for experimental designs is one of the methods for mathematical modeling. In these methods, a complete modeling of the system under study is performed through sampling carried out at determined times. Based on the developed model, optimization and analysis of the system are performed. 9

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Table 3 shows the design conditions, in which all of the variables are considered. The first and second columns show the variables (i.e., the power of the ultrasound waves, the volume of the sample, and the duration of ultrasonic exposure). The following columns indicate the values of each variable at the level of 1 and -1, the last column presents the standard deviations related to the three variables, and the final section list shows minimum and maximum values of SRF that have been determined by using the quadratic model. Table 3: a summary of conditions related to designing the model based on the parameters power of ultrasound waves, volume of the sample, exposure duration, and SRF results

Design summary Study type Initial Design Design Model Factor A B C Response Y1

Response Surface Central Composite Quadratic

20 No Blocks None High Coded 1.00 1.00 1.00 Mean

Mean

Std.Dev

625.00 2.70 13.00 Std.Dev

144.61 0.578 3.305 Ratio

283.718

77.178

3.110

Numeric Numeric Numeric Obs

Low Actual 450.00 2.00 9.00 Analysis

High Actual 800.00 3.40 17.00 Minimum

Trans Low Coded -1.00 -1.00 -1.00 Maximum

20

Polynomial

167.60

521.30

Name

Units

Type

Power Volume Time Name

W Lit min Units m/kg ( × 1013)

SRF

Runs Blocks

3.2. 3D Diagrams This section studies 3D diagrams that show the pairwise relationship of variables in relation to SRF. Fig. 2 illustrates the relationship between power of ultrasound waves, volume of the irradiated sludge, and SRF values. According to this diagram, the optimum efficiency is achieved at 800 watts and 2 liters at which the maximum SRF is a little less than 330 × 1013m/kg. This diagram shows the positive effect of increasing the power of ultrasound waves on the value of SRF, while changes in volume do not have this effect. However, simultaneous increases in both factors, up to a certain point, increase SRF values. The positive effect of increasing the power of ultrasound waves on the value of the SRF is due to effect of the waves on the sludge molecules membranes and destruction of them. Fig 3 illustrates the relationship between the power of ultrasound waves and duration of irradiation and SRF values. According to this diagram, the optimum values are 800 watts and 17 minutes, which result in the maximum SRF value of about 380 × 1013m/kg. This graph shows the gently positive effect of increasing the power of the ultrasound waves on SRF values. According to this diagram increase of time increases SRF value. However, simultaneous increases in both factors increase the SRF values. It shows that with increase of irradiation duration, the waves have more time to influence the molecules membranes and collapse them. 10

ACCEPTED MANUSCRIPT Design-Expert® Sof tware SRF 521.3 220.9 X1 = A: Power X2 = B: Volume

SRF (*10^13 m/kg)

Actual Factor C: Time = 13.00

340

310

280

250

220 3.40

800.0 3.05

712.5 2.70

Volume (Lit)

625.0 2.35

537.5 2.00 450.0

Power (W)

Fig 2: Relationship between the power of the ultrasound waves, volume of the sludge exposed to them, and the SRF Design-Expert® Sof tware values (Time= 13 min) SRF 521.3 220.9 X1 = A: Power X2 = C: Time

SRF (*10^13 m/kg)

Actual Factor B: Volume = 2.70

380

343

305

268

230 17.00

800.0 15.00

712.5 13.00

Time (min)

625.0 11.00

537.5 9.00 450.0

Power (W)

Fig 3: Relationship between the power of the ultrasound waves, the exposure duration, and the SRF values (Volume=2.7 Lit).

11

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Fig 4. illustrates the relationship between volume and duration of ultrasonic exposure on the SRF values. According to this diagram, the optimum values are 2 liters and 17 minutes, which result in the maximum SRF value of more than 400 × 1013m/kg. This shows that, at a constant volume, increase in duration of ultrasonic exposure will increase the SRF values but simultaneous increase in volume will reduce the SRF values. It can be concluded that by increasing the sludge volume, the effect of ultrasonic waves on material decreased. Therefore in a constant power, the only ways to increase SRF are increasing duration Design-Expert® Sof tware

of ultrasonic exposure or decrease of volume.

SRF 521.3 220.9 X1 = B: Volume X2 = C: Time

SRF (*10^13 m/kg)

Actual Factor A: Power = 625.0

420

373

325

278

230 17.00

3.40 15.00

3.05 13.00

Time (min)

2.70 11.00

2.35 9.00 2.00

Volume (Lit)

Fig 4: Relationship between volume of the sludge, the exposure duration, and the SRF values (Power=625 W).

3.3. One-Dimensional Diagram In this step, the relationship between each variable and the SRF values is illustrated separately. In Fig. 5, diagram (a) shows SRF values against the power of the ultrasonic waves. According to this diagram, SRF increases with a very gentle slope as the power of the ultrasound waves increases. No maximum is shown but based on the diagram it can be predicted that a maximum will be observed if ultrasound waves of greater power are used. Beyond this maximum, an opposite result will be obtained and the SRF value will decline.

12

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Diagram (b) also illustrates SRF variations caused by changes in sludge volume exposed to ultrasonic waves. The diagram shows that there is an inverse relationship between these two parameters so that increases in the volume of sludge alone will reduce SRF values. From this graph it can be concluded that this is a permanent decrease and increases in the sludge volume alone will always decrease SRF values.

One Factor Design-Expert® Software

sign-Expert® Software 320

295

X1 = B: Volume

270

Actual Factors A: Power = 625.00 C: Time = 13.00

SRF(*10^13 m/kg)

tual Factors Volume = 2.70 Time = 13.00

335

SRF

245

305

274

244

214

220 450.00

537.50

625.00

712.50

2.00

800.00

2.35

(a)

Actual Factors A: Power = 625.00 B: Volume = 2.70

3.40

396

SRF X1 = C: Time

3.05

(b)

One Factor

Design-Expert® Software

2.70

Volume (Lit)

Power (W)

SRF(*10^13 m/kg)

= A: Power

SRF(*10^13 m/kg)

F

One Factor

351

306

260

215 9.00

11.00

13.00

15.00

17.00

C: Time

(c) Fig 5: (a) Diagram of SRF against the power of the ultrasound waves (Volume=2.7 Lit, Time=13 min); (b) Diagram of SRF values against sludge volume exposed to ultrasound waves (Power=625 W, Time=13 min); (c) Diagram of SRF values against duration of exposure to ultrasound waves (Power=625 W, Volume=2.7 Lit).

13

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Diagram (c) illustrates SRF values against duration of exposure to ultrasonic waves. This diagram shows a non-linear relationship between these two parameters. It can be concluded from the diagram that as the exposure duration increases, SRF values will increase but not linearly. In addition, it can be predicted that the minimum of SRF in this diagram happens at the exposure duration of less than 9 minutes, beyond this time, increases in time duration will increase SRF values.

3.4. Cubic Diagram The cubic diagram illustrates changes in SRF values against simultaneous changes in all three variables. In Fig. 6, the cubic diagram shows the simultaneous effects of the parameters power of ultrasound waves, exposure duration, and sludge volume on SRF values. According to this diagram, the maximum SRF value (456.13 × 1013m/kg) was achieved at exposure duration of 17 minutes, power of 800 watts and volume of 2 liters, while the minimum SRF value (206.74 × 1013m/kg) is obtained at power of 800 watts, exposure duration of 9 minutes, and volume of 3.4 liters.

A-: 800.00

n-Expert® Software

SRF(*10^13 m/kg)

A: Power B: Volume C: Time

303.42

259.59

Volume (Lit)

B+: 3.40

291.82

206.74

359.28

456.13

C+: 17.00

Time (min) B-: 2.00 209.90 A-: 450.00

Power (W)

C-: 9.00 265.50 A+: 800.00

Fig. 6: the simultaneous effects of the three variables on SRF

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3.5. Interactive Diagrams Interactive diagrams show the pairwise effects of variables on changes in SRF values, which will be either synergistic or antagonistic. In Fig. 7, diagram (a) illustrates the interactive effects of the power of the ultrasound waves and the sludge volume at exposure duration of 13 minutes. According to this diagram, increasing the power of the ultrasound waves at the minimum volume (2 liters) will increase SRF values, while increasing the power of the ultrasound waves at the maximum volume (3.4 liters) will decrease SRF values.

Interaction

® Software

Time (min)

421

SRF(*10^13 m/kg)

328

X1 = A: Power X2 = C: Time Actual Factor B: Volume = 2.70

278

229

179

361

300

240

179 450.00

537.50

625.00

712.50

800.00

450.00

Power (W)

537.50

625.00

712.50

800.00

Power (W)

(a)

(b)

Interaction

Design-Expert® Software SRF

Time (min)

458

C- 9.000 C+ 17.000 X1 = B: Volume X2 = C: Time Actual Factor A: Power = 625.00

SRF(*10^13 m/kg)

.00

SRF C- 9.000 C+ 17.000

SRF(*10^13 m/kg)

er me

377

Interaction

Design-Expert® Software

Volume (Lit)

388

319

249

179 2.00

2.35

2.70

3.05

3.40

Volume (Lit)

(c) Fig. 7: interactive pairwise effects of the variables on SRF,(a) interactive effects of the power of the ultrasound waves and sludge volume on SRF (Time=13 min); (b) interactive effects of the power of the ultrasound waves and exposure duration on SRF (Volume=2.7 Lit); (c) interactive effects of the power of the ultrasound waves and sludge volume on SRF (Power=625 W). Diagram (b) illustrates the interactive effect of exposure duration and

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power of the ultrasound waves at the constant volume of 2.7 liters on SRF values. According to this diagram, at the minimum duration of irradiation (9 minutes), SRF remains almost constant and shows no tangible changes with increases in power of the ultrasound waves, but at the maximum exposure duration (17 minutes) SRF values increase with increases in the power of the ultrasound waves. Diagram (c) illustrates the interactive effects of exposure duration and sludge volume on SRF at the constant power of 625 watts. According to this diagram, at the minimum exposure duration (9 minutes) SRF remains almost constant and shows no tangible changes with increases in sludge volume, while at the maximum exposure duration (17 minutes) SRF decreases with increases in sludge volume.

3.6. Presenting Mathematical Model After performing the analyses, the model introduced in this study is presented in the form of equation 5. In this model, for every unit increase in ultrasound wave power, exposure duration, the multiplication of ultrasound wave power and exposure duration, square of exposure duration, square of ultrasound wave power, 0.77, 12.73, 0.01, 1.68 and 2.38 units will be added to SRF, respectively. Moreover, with every unit increase in sludge volume, multiplication of ultrasound wave power and sludge volume, multiplication of sludge volume and exposure duration, square of sludge volume, SRF will decrease by 266.54, 0.22, 9.42, and 8.64 units, respectively. 𝑆𝑅𝐹 = 0.77 × 𝑃𝑜𝑤𝑒𝑟 ‒ 266.54 × 𝑉𝑜𝑙𝑢𝑚𝑒 + 12.73 × 𝑇𝑖𝑚𝑒 ‒ 0.22 × 𝑃𝑜𝑤𝑒𝑟 × 𝑉𝑜𝑙𝑢𝑚𝑒 + 0.01 (5 × 𝑃𝑜𝑤𝑒𝑟 × 𝑇𝑖𝑚𝑒 ‒ 9.42 × 𝑉𝑜𝑙𝑢𝑚𝑒 × 𝑇𝑖𝑚𝑒 + 2.38 × 𝑃𝑜𝑤𝑒𝑟2 ‒ 8.64 × 𝑉𝑜𝑙𝑢𝑚𝑒2 + 1.68 ) × 𝑇𝑖𝑚𝑒2 ‒ 279.48 3.7. Analysis of Variance (ANOVA) ANOVA is a method based on partitioning total variation or dispersion in a set of data into various components. ANOVA is a variance-based test, and a parameter that compares several groups. In the output table of this test, if a significance level is lower than the amount of error, it will be argued that there is a difference in at least one pair of groups. Statistical analyses based on the ANOVA model showed that the introduced mathematical model for samples can be used at the probability level of 95%. Table 4 shows the ANOVA results. The output shown in Table 4 is the analysis of variance with Fisher statistic, and contains sums of squares, degrees of freedom between and within groups, and the totals. Mean squares and Fisher statistic

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are also included in the table. Attention must be paid to the P value column. The P value of the model is 0.0134, which caused the rejection of the null hypothesis. Therefore, the model is significant statistically. Table 4: ANOVA related to the RSM

ANOVA for Response Surface Quadratic Model Sum op squares

df

Mean squares

F value

p-value prob. > F

84,444.30

9

9,382.70

4.54

0.0134

1,652.27

1

1,652.27

0.80

0.3921

B-Volume

11,231.26

1

11,213.26

5.43

0.0420

C-Time

46,920.16

1

46,920.16

22.72

0.0008

AB

5,880.70

1

5,880.70

2.85

0.1224

AC

850.78

1

850.78

0.41

0.5354

BC

5,570.40

1

5,570.40

2.70

0.1315

A2

765.78

1

765.78

0.37

0.5561

B2

258.02

1

256.02

0.12

0.7311

C2

10,386.37

1

10,386.37

5.03

0.0488

Residual

20,648.12

10

2,064.81

Lack of fit

20,648.12

5

4,129.62

Pure Error

0.00

5

Source Model A-Power

Cor. Total

5

1.051×10

significant

0.00

19

3.8. Optimum point According to RSM results, the best SRF result occurs at an ultrasound wave power of 625 watts, sludge volume of 2.7 liters and exposure duration of 13 minutes. Also according to experiments result, it was found that amount of difference between this result and actual values is less than 2 percent.

4. Conclusion Today, in very wastewater treatment plant, biological digestion is used for solving and dewatering sludge. Biological digestion has many operation problems and needs long time. According to this paper results, ultrasonic waves can be used for accelerating sludge dewatering and degradation in short time exposure. Use of ultrasound in liquids causes the generation of cavitation phenomenon that has strong mechanical and sonochemical impacts affecting suspended particles and large molecules in liquids which turns them 17

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into finer particles. This can be concluded from improvement of SRF results after using ultrasonic waves, based on this research results. Finer molecules resulted from using ultrasound will improve bio-digestion and increase rates of reactions in biological processes. Results presented in this article show that ultrasonic waves can accelerate some processes involved in sewage treatment operations. Based on this results, using ultrasonic is proposed in every wastewater treatment. Optimum conditions for best efficiency in each process is very important. In this study, RSM was used to derive a mathematical model with the purpose of achieving the most optimal conditions for the influential variables. Based on RSM, the best SRF result occurs at an ultrasound power of 625 watts, sludge volume of 2.7 liters and exposure duration of 13 minutes. Also RSM was used to predict the results based on a mathematical model. The quadratic model presented in this study includes exposure duration, sludge volume, and power of ultrasound waves. The effects of each parameter on SRF were specified by determining the parameters coefficients in the model. In this model, sludge volume has the maximum negative effect and exposure duration has the maximum positive effect among the variables on the SRF value. Based on ANOVA for response surface quadratic model, P value was equal to 0.0134 that showed this model is significant in 0.95 of confidence level.

Acknowledgments The authors are thankful to Dr. Farhad Qaderi, because of his collaborations in this research.

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