ARTICLE pubs.acs.org/IECR
Simulation of Real Wastewater Supercritical Water Oxidation at High Concentration on a Pilot Plant Scale Violeta Vadillo,* M. Belen García-Jarana, Jezabel Sanchez-Oneto, Juan R. Portela, and Enrique J. Martínez de la Ossa Department of Chemical Engineering and Food Technology, Faculty of Sciences, University of Cadiz, 11510 Puerto Real, Spain ABSTRACT: Supercritical water oxidation (SCWO) has been studied for the past three decades and is now a well-known process. However, the commercial development of this technique is currently delayed due to several drawbacks such as corrosion, salt precipitation, and high costs. In an effort to overcome these constraints several authors have studied and designed new SCWO reactor concepts, but these technical solutions involve the use of special materials and complex designs that increase the process costs. However, conventional SCWO could be commercialized for certain wastewaters that satisfy certain requirements, e.g., very low salt and chloride contents, and it is necessary to continue studying the SCWO process at high concentrations and on the pilot plant scale. At present, simulations based on the SCWO of real wastewaters at high concentrations on the pilot plant scale are scarce in the literature. Process simulation is a powerful tool to study processes in depth and to make advances in the scale-up process. Nevertheless, the use of specific chemical engineering software, such as Prosim Plus or Aspen Plus, is not applicable to simulate a complex wastewater. In addition, the use of the kinetic data available in the literature is not straightforward because these kinetic parameters were obtained from experiments conducted under very different conditions (isothermal, low concentration, etc.). In the work described here, the simulation of Biocut 35 cutting fluid SCWO on a pilot plant scale has been conducted satisfactorily. The model was developed using a Microsoft Excel spreadsheet and a kinetic model obtained on the laboratory scale. Fifteen experiments were carried out in order to validate the simulator. These experiments were conducted on a pilot plant scale at a constant pressure of 250 bar and initial temperatures ranging from 388 to 428 °C. The cutting fluid concentration used in these experiments was varied from 19 to 95 g of O2/L. Finally, the simulator was used to check the effect of the operational variables such as wastewater concentration, initial temperature, wastewater flow rate, and thermal insulation.
1. INTRODUCTION Supercritical water oxidation (SCWO), i.e., oxidation of organic matter at temperatures and pressures above the critical point for pure water (374 °C and 220 bar), is an alternative to conventional methods for the treatment of wastewaters.14 Above its critical point, water is a nonpolar solvent that is completely miscible with organics and gases such as oxygen. These characteristics result in a homogeneous reaction medium in which there are no mass transfer limitations. Furthermore, as the reactions take place at high velocity due to the high temperature used, the residence times necessary to achieve high destruction levels (99%) are reduced due to the very small reactor volume required.5 Another advantage of this approach is that the reaction products are not toxic. The production of NOx, SOx, and dioxins is negligible because the temperature is too low for the formation of these compounds.6 Thus, carbon is oxidized into carbon dioxide, hydrogen is oxidized into water, and heteroatoms such as chlorine, sulfur, and phosphorus are converted into their corresponding acids.3 As a result, supercritical water is a very suitable medium for the oxidation of organic and inorganic compounds.7 Studies of real wastewaters by SCWO at high concentration and on a pilot plant scale are scarce. Besides, the application of SCWO on a commercial scale is very rare because SCWO has certain drawbacks such as corrosion, salt-plugging, and cost problems.8 Numerous authors have made significant efforts to solve corrosion and salt-plugging problems using different reactor configurations or corrosion-resistant r 2011 American Chemical Society
materials.9,10 However, the use of these specific materials and reactor configurations increases the overall cost because they increase the SCWO process costs, and moreover, if the salt or chloride content is high, these technical solutions also fail after long-term operation. On the other hand, some wastewaters, such as cutting fluid1114 and flammable industrial wastewaters,8 have low salt and chloride contents and they can therefore be treated by SCWO. As a consequence, simulation studies of real wastewaters are very desirable in order to progress the scale-up of the SCWO process. Some authors have successfully carried out SCWO process simulation for model compounds by means of specific software such as Prosim Plus,1517 Aspen Plus,18,19 and other solver software.20 However, all chemical engineering software requires at least a known molecule and the reaction stoichiometry to proceed, i.e., to calculate the physicochemical properties, heat of reaction, etc.16 As a result, such software packages cannot be used to simulate real wastewaters, such as the cutting fluid wastewater studied in this work. Cutting fluid is a type of coolant and lubricant designed for metalworking and machining processes. There are three types of cutting fluids, and these are classed as mineral, semisynthetic, and Received: July 27, 2011 Accepted: September 26, 2011 Revised: September 22, 2011 Published: September 26, 2011 12512
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Industrial & Engineering Chemistry Research synthetic. The main components present in cutting fluids are as follows: refrigerant (water), lubricants, tensioactives, corrosion inhibitors, humectants/stabilizers, biocides, additives for high pressure operation, and antifoaming compounds.11 After prolonged use, cutting fluids lose their properties and accumulate physical and chemical contaminants and they must be replaced.21 Under most current legislation, used cutting fluids are considered to be hazardous waste and the safe collection and disposal of these materials must be ensured. In previous studies our group has investigated the SCWO of several cutting fluids on the laboratory scale in order to ascertain the effect of the operational parameters and the reaction kinetics data.1114 In the work described here the simulation of the SCWO process at the pilot plant scale of a semisynthetic cutting fluid was carried out using a Microsoft Excel spreadsheet. Thermophysical properties for water, nitrogen, and oxygen were obtained from the NIST Chemistry WebBook.22 The aim of the work was to build a simulator in order to determine whether it is possible to use the kinetics data available in the literature to represent the data obtained in a quasi-adiabatic pilot plant working at high concentration. The fact that most kinetic studies reported in the literature were carried out under very different conditions, mainly in lower ranges of temperature in laboratory scale systems working at low concentrations, makes the simulation more difficult. In addition, the simulator was designed to determine the maximum efficiency that can be reached as a function of the operational conditions;wastewater flow rates, organic matter concentration, and temperature;in order to advance in the process scale-up. In order to achieve the above objective, in the first stage, experiments were carried out in the SCWO pilot plant located at the University of Cadiz and, in the second stage, these experiments were used to check and validate the SCWO simulator built at the pilot plant scale.
2. EXPERIMENTAL SECTION The pilot plant, located at the University of Cadiz, was designed to treat up to 23 kg/h aqueous waste. The aqueous feed solution was pressurized up to 250 bar with a high pressure pump. The oxidant (air) was pressurized by a high pressure compressor. Both feed streams were separately preheated in countercurrent heat exchangers using the effluent from the reactor to heat the feed stream up to 400 °C. This pilot plant included a new system and a procedure to treat oily wastewaters, an approach that was developed by our group23 and is now under patent.23,24 This procedure consists of a new feed stream that includes a high pressure pump able to pressurize oily wastewaters up to 250 bar. The new stream is mixed, without preheating, with the main stream that contains supercritical water.23 The main equipment of the pilot plant is the tubular reactor, which is made of 3/4 in. stainless steel AISI 316 L pipe with a total volume of 1.2 L. The reactor is surrounded by fiberglass insulation in order to minimize the thermal losses so that the behavior can be considered quasi-adiabatic. A first countercurrent heat exchanger was used to preheat the liquid feed with the effluent of the reactor, and the effluent then crossed a second countercurrent heat exchanger to preheat the air feed. A final cooler was used to decrease the effluent temperature to below 50 °C before it reached the back-pressure regulator, which was employed for depressurization. After that, the gas stream was separated from the liquid stream in the gas/liquid separator.
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Table 1. Elemental Analysis of the Biocut35 Concentrated Cutting Fluid elemental analysis (wt % dry basis)
Biocut 35
C
70.1 ( 0.42
H N
16.54 ( 2.61 0.26 ( 0.05
S
0.36 ( 0.04
others (remainder to 100%)
12.74
The composition of the gas stream was characterized using a continuous gas analyzer. During the startup of the process it was necessary to heat the liquid stream, which contained water, with electrical preheaters before mixing it with the wastewater (cutting fluid) stream at the reactor entrance. That preheating increased the temperature at the beginning of the reactor up to 380 °C in order to start the oxidation reactions. Once the oxidation reactions had started, their exothermic nature and the thermal insulation of the reactor ensured that the reactor effluent had a high temperature due to the reaction heat released. This effluent stream was used to preheat the gas and liquid streams by means of the gas and liquid heat exchangers. Besides, if the reaction heat was high enough to preheat both feed streams and to reach the initial temperature, the electrical preheating could be turned off and the pilot plant would be able to work under autothermal conditions, which is a major advantage of this process to minimize operational costs. More details about the SCWO pilot plant can be found in our previous publication.8 Biocut 35 (Houghton Iberica S.A.) is the commercial name of the semisynthetic cutting fluid studied in this work. This cutting fluid has a “mass chemical oxygen demand” (referred to the concentrated cutting fluid) of 2.264 ( 0.041 (g of O2/g of concentrated cutting fluid). The C, H, N, and S contents were determined by elemental analysis (wt % dry basis), and it is assumed that the remainder is oxygen. The values obtained are shown in Table 1. Based on these results, and neglecting the small contributions of N and S, the molecular formula of the cutting fluid can be represented as C6H17O. The efficiency of the oxidation process was followed in terms of the reduction in the chemical oxygen demand (COD). COD concentrations of liquid samples were monitored. The COD analysis was performed by the closed reflux colorimetric method (5220D) according to the standard methods for water and wastewater analysis.25
3. RESULTS AND DISCUSSION In order to simulate the SCWO process, it was necessary to know the thermal losses along the reactor as well as the kinetic data and the heat of reaction, because the reactor showed nonadiabatic behavior in the experiments. Consequently, the development of a thermal loss model is very desirable. 3.1. Model Description. 3.1.1. Thermal Loss Modeling. Although the pilot plant is thermally isolated, blank experiments conducted with water and air as the liquid stream and gas stream, respectively, showed that there were thermal losses along the reactor. The evaluation of these thermal losses is necessary to develop a model that can predict accurately the experimental temperature profile along the reactor and the COD removal efficiency when the reactor behavior is not adiabatic. Therefore, the net heat produced (Qnet) in the SCWO reaction will depend on the gross heat produced (Qgross) in the reaction and on the 12513
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where he is the external convection heat transfer coefficient and ra is the external radius including the insulation and the aluminum shell. Rs ¼
ln re =ri 2πks
ð8Þ
where ks is the thermal conductivity of the stainless steel (16.3 W m1 K1) and re is the pipe outer radius. Rinsulation ¼ Figure 1. Sketch of the insulated reactor.
ð1Þ
Different thermal loss models were studied and finally the model that best represented the experimental temperature profiles was developed bearing in mind the conduction, convection, and radiation heat transfer phenomena. Qloss ¼ Qconvcond þ Qrad
ð2Þ
The evaluation of the thermal losses related to convection and conduction were developed by calculating the global heat transfer coefficient (U) for the heat losses (as can be seen in eqs 3 and 4) based on the reactor pipe dimensions and the insulation properties. As can be seen in Figure 1, the reactor pipe had an inner diameter (Di) of 12.32 mm and a pipe thickness (tp) of 6.73 mm. The pipe was surrounded by fiberglass insulation with a thickness of 75 mm (ti) and thermal conductivity of 0.14 W m1 K1. In addition, the fiberglass insulation was surrounded by a white aluminum shell with a thickness (ta) of 1.2 mm. Qconvcond ¼ UAðTw T∞ Þ 1 1 ln re =ri ln re0 =re ¼ þ þ UA hi Ai 2πks tp 2πkinsulation ti ln ra =re0 1 þ þ he Ae 2πkaluminum ta
Ra ¼
Nu ¼
Re > 10 000 ð11Þ
ð4Þ Hausen equation: Nu ¼
ð7Þ
0:14 hi di μ ¼ 0:116ðRe2=3 125ÞPr 1=3 ½1 þ ðD=LÞ2=3 b ki μw
ð12Þ
2100 < Re < 10 000
where Nu is the Nusselt dimensionless number, di is the pipe inner diameter, k is the fluid thermal conductivity, Re and Pr are the Reynolds and Prandtl dimensionless numbers, respectively, L is the reactor length, and μb and μw are the viscosities of the bulk fluid and the wall fluid, respectively. The external convection heat transfer coefficient was calculated by considering a simplified equation for natural convection in horizontal pipes and laminar flow (ambient air at atmospheric pressure).
ð6Þ
where hi is the internal convection heat transfer coefficient and ri is the internal radius. 1 2he πra
hi di ¼ 0:023Red 0:8 Pr 0:4 ki Pr > 0:6
where Tw is the fluid temperature in the reactor, Ti is the inner wall temperature, Te is the pipe wall external temperature, Te0 is the insulation external temperature, Ts is the aluminum shell external temperature, T∞ is the ambient temperature, Ri is the inner heat transfer resistance, Re is the external heat transfer resistance, Rs is the stainless steel thermal resistance, Rinsulation is the insulation thermal resistance, and Ra is the aluminum shell thermal resistance. These variables were calculated using the following equations:
Re ¼
ð10Þ
Dittus Boelter equation:
ð3Þ
Tw Ti Ti Te Te Te0 Te0 Ts Ts T∞ ¼ ¼ ¼ ¼ Ri Rs Rinsulation Ra Re ð5Þ
1 2hi πri
ln ra =re0 2πkaluminum
where kaluminum is the aluminum thermal conductivity (237 W m1 K1). It is important to remark that the thermal resistance due to the aluminum shell is negligible in relation to the other thermal resistances due to the small aluminum shell thickness and the high thermal conductivity of aluminum. It can therefore be assumed that Te0 ≈ Ts. Two expressions were used to calculate the internal convection heat transfer coefficient as a function of the Reynolds number and, consequently, the flow regime. If the operational conditions produce a turbulent flow, the Dittus Boelter equation can be used. However, if the flow is in the transition regime, the Hausen equation can be used.
To solve these equations, it is necessary to carry out an energy balance (eq 5) on the system shown in Figure 1.
Ri ¼
ð9Þ
where kinsulation is the insulation thermal conductivity and re0 is the pipe outer radius plus the insulation thickness (ti).
thermal losses (Qloss). Qnet ¼ Qgross Qloss
ln re0 =re 2πkinsulation
he ¼ 1:32
ðTs T∞ Þ1=4 De þ ti þ ta
104 < Gr 3 Pr < 109
ð13Þ
To obtain the global heat transfer coefficient, it is necessary to solve eqs 513 by means of an iterative procedure. In relation to the radiation heat transfer (Qrad), this term was estimated by means of the StefanBoltzmann law bearing in 12514
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mind the emissivity of white paint (ε = 0.9). Qrad ¼ εσAðTs 4 T∞ 4 Þ
ð14Þ
where ε is the emissivity of white paint and σ is the Stefan Boltzmann constant (5.67 108 W/m2 K4). Therefore, the temperature profile along the reactor was calculated with the following expression: ΔT ¼
Qloss m_ i Cp, i
ð15Þ
∑
where m_ i is the mass flow rate and Cp,i is the heat capacity for each fluid, water, and air. The fluid properties were obtained from the NIST Database22 for water, oxygen, and nitrogen at 250 bar and experimental temperatures. A comparison between experimental and simulated temperature profiles along the reactor is shown in Figure 2. The selected blank experiments were conducted at a constant pressure of 250 bar, with different initial temperatures and a water flow rate of 10 kg/h, as can be seen in Table 2. It can be seen from Figure 2 that the heat loss model predicts accurately the temperature profile along the reactor during the blank tests and the model can therefore be used to predict the heat losses during the Biocut SCWO experiments. 3.1.2. Reactor Modeling. In order to develop the simulation of the SCWO experiments, the reactor behavior was considered as a plug flow system because the flow was turbulent within the reactor (Reynolds number is greater than 2200 and the reactor has an L/D relation ≈760).16 The mass balance was therefore carried out in a reactor volume differential element at steady state, resulting in eqs 16 and 17. τ¼
Z COD
dCOD
COD0 ð rCOD Þ
ð rCOD Þ ¼
dCOD ¼ k½COD dτ
ð16Þ ð17Þ
where τ is the residence time, COD0 is the initial chemical oxygen demand, (rCOD) is the COD disappearance rate, and k is the kinetic constant for the cutting fluid. The SCWO kinetics for the cutting fluid Biocut 35 considered in this work were developed by Sanchez-Oneto et al.11 This kinetic model consists of a two-parameter mathematical model involving two steps (a fast reaction followed by a slow reaction) because a one-step model predicts COD removal efficiencies close to 100%, values that are not found experimentally. The twostep kinetic model is shown in eqs 18 and 19. COD concentration was chosen as a parameter to describe the SCWO global kinetics for Biocut 35. This model was developed in a continuous flow reactor at the laboratory scale at a constant pressure of 250 bar, using pure oxygen as the oxidant in excess, different temperatures ranging from 400 to 500 °C, and an initial Biocut 35 COD concentration of 5 g of O2/L. The values of the kinetic parameters obtained at the laboratory scale for each step,11 on one hand, were 3207 ( 222 (s1) for the fast step pre-exponential factor and 62 200 ( 3400 (J/mol) for the activation energy. On the other hand, for the slow step the preexponential factor was 13 020 ( 2080 (s1) and the activation energy was 86 700 ( 9100 (J/mol). Between those confidence limits the best results were obtained with the data shown in eqs 18 and 19.
Figure 2. Comparison between experimental and simulated temperature profiles of blank tests.
first step: dCOD 58800 ¼ 3429 exp ½COD ð rCOD Þ ¼ dτ RT ð18Þ second step:
dCOD 82200 ð rCOD Þ ¼ ¼ 15100 exp ½COD dτ RT
ð19Þ In addition, this work was used to validate the kinetic model obtained on the laboratory scale and with low concentrations by 12515
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means of simulation experiments conducted at high concentration and on a pilot plant scale. In order to obtain the temperature profile along the reactor, an energy balance was carried out and this resulted in eq 20.
As a result of the complexity of the wastewater, the heat of reaction for SCWO was expressed in terms of COD and this had a value of 17.31 kJ/g COD converted. This unit change from kJ/mol to kJ/g COD converted was carried out using the molecular weight from the molecular formula and the “mass chemical oxygen demand” referred to the concentrated cutting fluid. The heat of reaction was also experimentally measured using an isoperibol bomb calorimeter, and similar results were obtained. 3.2. Modeling of Experimental Results. Bearing in mind all of the considerations outlined above, an SCWO tubular reactor simulator was built using Microsoft Excel. Fifteen experiments were chosen to simulate the SCWO of Biocut 35. In these experiments the initial temperature, organic matter concentration, Biocut 35 flow rate, and air flow rate were changed from 386 to 431 °C, 19 to 95 g of O2/L, 10 to 16 kg/h, and 3 to 10 kg/h, respectively, in order to validate the simulator over a wide range of operational conditions. The operational conditions and results for each experiment are given in Table 3, and a comparison between temperature profiles resulting from the experimental simulation and the actual experimental data are shown in Figure 3. As can be seen in Figure 4, the model predicts accurately the temperature profile along the reactor in low concentration experiments. Nevertheless, on increasing the concentration there was a slight deviation in the initial data points for the reactor. This change could arise because the kinetic model was obtained at lower concentrations than the experimental ones. This is because most of the SCWO reactions are radical reactions that take place by complex mechanisms. As the kinetic model was obtained at lower concentrations and at the pilot plant scale, we treated higher concentrations, where some pathways in the reaction mechanisms may be enhanced at higher concentrations and consequently the global activation energy of the process can decrease, as has been found in the simulation. Therefore, in order to improve the model, the kinetic parameters were modified between the confidence limits published.11
Toutlet ¼ Tinlet þ
ð ΔHr ÞCOD0 Q0 ð1 Xinlet ÞðXoutlet Xinlet Þ m_ i Cp, i
∑
ð20Þ
where Tinlet and Toutlet are the temperatures at the entrance and exit of the volume differential element, respectively, (ΔHr) is the heat of reaction, COD0 is the initial chemical oxygen demand, Q0 is the initial flow rate, Xoutlet and Xinlet are the reactive conversions at the entrance and exit of the volume differential element, respectively, m_ i is the mass flow of the compound i (water, nitrogen, or oxygen), and Cp,i is the heat capacity of the compound i. The heat of reaction for the SCWO process was obtained from the Biocut 35 molecular formula C6H17O obtained by elemental analysis and using the empirical expression found in the literature26 for the SCWO of model compounds at a temperature of 400 °C and a pressure of 250 bar: ð ΔHr Þ ¼ 415n þ 107m þ 193f
ð21Þ
where (ΔHr) is the heat of reaction in kJ/mol, n is the number of carbon atoms, m is the number of hydrogen atoms, and f is the number of oxygen atoms. Table 2. Operational Parameters in “Blank” Experiments initial
liquid flow
air flow
experiment
temperature (°C)
rate (kg/h)
rate (kg/h)
blank 1 blank 2
365.2 377.1
10.43 10.02
3.4 4.34
blank 3
350.2
10.38
5.17
Table 3. Operational Conditions and Results of Biocut 35 SCWO Experiments initial temperaturea
initial concentrationb
wastewater flow
air flow
oxidant excess
residence
COD removal
experiment
(°C)
(g of O2/L)
rate (kg/h)
rate (kg/h)
coefficient (nc)
time (s)
efficiency (%)
1 2
428 410
19.0 21.5
10.6 10.8
4.07 3.74
4.2 3.9
60.1 70.0
80.8 74.6
3
431
28.8
10.4
3.40
2.4
43.8
84.9
4
403
28.9
10.1
4.68
3.6
87.4
78.2
6
410
39.4
10.7
4.00
2.9
47.1
80.0
5
431
39.6
10.7
5.18
2.1
32.9
89.8
7
414
54.5
10.3
3.39
1.4
35.3
85.1
8
408
57.2
10.0
4.34
2.0
42.2
90.5
9 10
386 409
83.1 86.7
14.2 15.8
3.88 6.60
0.8 1.1
37.4 17.8
75.1 92.2
11
407
87.3
15.7
9.29
1.6
16.5
93.4
12
392
93.5
9.3
4.63
1.2
36.7
92.7
13
388
94.4
10.1
4.22
1.0
46.6
85.2
14
395
94.6
9.1
4.18
1.1
35.7
92.6
15
388
95.1
10.0
3.96
1.0
43.6
85.4
Measured at the beginning of the reactor. b Calculated by means of a mass balance with the water and oily stream flow rates and concentrations. c n = feed oxygen/stoichiometric oxygen. a
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Figure 3. Comparison between experimental and simulated temperature profiles.
Despite the small differences in the temperature profiles, the predicted COD removal is close to the experimental value because there is a low dispersion of the data from the diagonal, as can be seen in Figure 4. This model can therefore be used to predict the behavior of the Biocut 35 SCWO on the pilot plant scale. 3.3. Simulation Results. Once the simulator had been validated, several Biocut 35 SCWO simulations were conducted
to study the effect of the operational variables at a constant pressure of 250 bar. First, simulations were carried out to assess the effect of the initial temperature on the temperature profile along the reactor and the COD removal efficiency. The simulation conditions were as follows: the wastewater concentration was 90 g of O2/L, the wastewater flow rate was 10 kg/h, and the oxidant excess coefficient was 1.1. The initial temperature 12517
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Figure 4. Comparison between experimental and predicted COD removal values with a 95% of confidence level.
Figure 5. Simulation of initial temperature effect with a wastewater flow rate of 10 kg/h, a wastewater concentration of 90 g of O2/L, an oxidant excess coefficient n = 1.1, and initial temperatures from 380 to 420 °C.
was changed from 380 to 420 °C. As can be seen in Figure 5, an increase in the initial temperature led to an increase in the temperature profile along the reactor and, consequently, the COD removal efficiency increased up to 99% for an initial temperature of 420 °C. Small changes in the initial temperature can therefore lead to considerable improvements in the efficiency obtained. In relation to the effect that wastewater flow rate has on the temperature profile and the COD removal efficiency, four simulations were carried out by increasing the wastewater flow rate from 10 to 40 kg/h. These simulations were carried out with an initial COD concentration of 90 g of O2/L, an oxidant excess coefficient of 1.1, and an initial temperature of 400 °C. As shown in Figure 6, the higher the wastewater flow rate the lower the COD removal efficiency, and as a result, a longer reactor would be required to achieve the same results. Specifically, when the wastewater flow rate was 40 kg/h, it would be necessary to have a reactor that was 12 m long to achieve a COD removal efficiency of 92.41%. Furthermore, to achieve 96% COD removal efficiency, the reactor length would have to be 86 m. On the other hand, four simulations were conducted to assess the effect of wastewater concentration. The wastewater concentration was varied from 80 to 120 g of O2/L while maintaining constant operational variables such as the initial temperature of 400 °C, a wastewater flow rate of 20 kg/h, and an oxidant excess coefficient of n = 1.1. The results are shown
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Figure 6. Effect of wastewater flow rate from 10 to 40 kg/h with a wastewater concentration of 90 g of O2/L, an oxidant excess coefficient n = 1.1, and an initial temperature of 400 °C.
Figure 7. Simulation results on varying the wastewater concentration from 80 to 120 g of O2/L with a wastewater flow rate of 20 kg/L, an oxidant excess coefficient n = 1.1, and an initial temperature of 400 °C.
in Figure 7, and an increase in the temperature profile was predicted through the reactor along with an increase in the COD removal efficiency as a consequence of increasing the wastewater concentration. Therefore, to achieve a COD removal efficiency close to 99%, it is necessary to work with a wastewater concentration of around 120 g of O2/L for an initial temperature of 400 °C, a wastewater flow rate of 20 kg/h, and an oxidant excess coefficient of n = 1.1. On the other hand, the simulator was used to evaluate the effect of different insulation thicknesses and also the maximum possibility for reducing heat losses by using a new insulation material with a lower thermal conductivity. As can be seen in Figure 8, the COD removal efficiency can be improved by increasing the insulation thickness up to 20 cm or by replacing the insulation with a new material with a thermal conductivity of 0.07 W m1 K1. These simulations were carried out for a wastewater flow rate of 10 kg/h, with a wastewater concentration of 90 g of O2/L, an oxidant excess coefficient n = 1.1, and an initial temperature of 400 °C. It can be seen from Figure 8 that an increase in the insulation thickness improved the process efficiency due to a reduction in thermal losses and an improved temperature profile along the reactor. Similar results were obtained when the insulation material was replaced by another with a lower thermal conductivity. Nevertheless, although insulation can be improved, heat 12518
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Figure 8. Effect of the thickness (left) and material of insulation (right).
losses will always occur but the optimization of insulation is very desirable in order to achieve higher process efficiency.
4. CONCLUSIONS A model to simulate the SCWO process at high concentration and at the pilot plant scale for the cutting fluid Biocut 35 has been developed. In the first stage, thermal losses were modeled using “blank” experiments that were conducted without wastewater. The thermal loss model required to represent the experimental results in a satisfactory manner must consider thermal losses due to convection, conduction, and radiation heat transfer. Once the thermal losses had been evaluated, the second stage involved building an SCWO model using a Microsoft Excel spreadsheet. Good agreement was obtained between experimental and simulated removal efficiencies. Thus, the SCWO model can be used to predict the SCWO reactor behavior at the pilot plant scale and for high concentrations, a possibility that is very useful to advance the SCWO scale-up process. Finally, the simulator was used to check the effects of operational variables and to identify the best operational conditions by working at a high initial temperature and high wastewater concentration. Simulations carried out at higher wastewater flow rate showed that it may be necessary to increase the reactor volume (i.e., increased length or pipe diameter) to achieve the same COD removal as the efficiency obtained using the same operational conditions (i.e., wastewater concentration, flow rate, and initial temperature). Although the simulator showed that heat losses can not be totally removed, it is necessary optimize the thermal insulation by increasing the thickness of the insulation or by using an insulation material with a lower thermal conductivity. ’ AUTHOR INFORMATION Corresponding Author
*E-mail:
[email protected].
’ ACKNOWLEDGMENT We would like to thank the Spanish Ministry of Education for financial support through a Ph.D. student grant and the Andalusian regional government for funding Project P07-RNM-03276. ’ NOMENCLATURE SCWO = supercritical water oxidation COD = chemical oxygen demand (mg of O2/L) Qnet = net heat produced per unit of time (W)
Qgross = gross heat produced per unit of time (W) Qloss = loss heat per unit of time (W) Qconvcond = loss heat due to convection and conduction heat transfer (W) Qrad = loss heat due to radiation heat transfer (W) U = global heat transfer coefficient (W m2 K1) A = heat transfer area (m2) Tw = fluid temperature (K) T∞ = ambient temperature (K) Di = pipe inner diameter (mm) tp = pipe thickness (mm) ti = insulation thickness (mm) ta = aluminum shell thickness (mm) ks = stainless steel thermal conductivity (W m1 K1) kinsulation = insulation thermal conductivity (W m1 K1) kaluminum = aluminum thermal conductivity (W m1 K1) hi = internal convection heat transfer coefficient (W m2 K1) he = external convection heat transfer coefficient (W m2 K1) Ai = internal heat transfer area (m2) Ae = external heat transfer area (m2) re = pipe outer radius (mm) ri = internal pipe radius (mm) re0 = pipe outer radius plus insulation thickness (mm) ra = outer radius including insulation and aluminum shell thicknesses (mm) Ti = inner wall temperature (K) Te = pipe wall external temperature (K) Te0 = insulation external temperature (K) Ts = aluminum shell external temperature (K) Ri = inner heat transfer resistance (W1 m K) Rs = stainless steel thermal resistance (W1 m K) Rinsulation = insulation thermal resistance (W1 m K) Ra = aluminum shell thermal resistance (W1 m K) Re = external heat transfer resistance (W1 m K) Nu = Nusselt dimensionless number Re = Reynolds dimensionless number Pr = Prandtl dimensionless number Gr = Grashof dimensionless number ki = fluid thermal conductivity (W m1 K1) di = pipe inner diameter (mm) L = reactor length (m) μb = bulk fluid viscosity (kg m1 s1) μw = wall fluid viscosity (kg m1 s1) ε = white paint emissivity σ = StefanBoltzmann constant (W m2 K4) ΔT = temperature gradient (K) mi = mass flow rate (kg s1) 12519
dx.doi.org/10.1021/ie201625y |Ind. Eng. Chem. Res. 2011, 50, 12512–12520
Industrial & Engineering Chemistry Research Cp,i = fluid heat capacity (kJ kg 1 K1) (rCOD) = COD disappearance rate (mg of O2 L1 s1) k = kinetic constant (s1) τ = residence time (s) R = universal gas constant (J mol1 K1) Toutlet = temperature at the exit of a volume differential element (K) Tinlet = temperature at the inlet of a volume differential element (K) (ΔHr) = heat of reaction (kJ/g COD converted) COD0 = initial chemical oxygen demand (g of O2/L) Q0 = initial volumetric flow rate (L s1) Xoutlet = conversion at the exit of a volume differential element Xinlet = conversion at the inlet of a volume differential element n = oxidant excess coefficient
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