Scholarly article on topic 'Could cyclone performance improve with reduced inlet velocity?'

Could cyclone performance improve with reduced inlet velocity? Academic research paper on "Earth and related environmental sciences"

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{Cyclones / Emissions / "Energy consumption" / "Fine particulate" / "PM2.5 "}

Abstract of research paper on Earth and related environmental sciences, author of scientific article — P.A. Funk, K. Elsayed, K.M. Yeater, G.A. Holt, D.P. Whitelock

Abstract Emission abatement cyclone performance is improved by increasing collection effectiveness or decreasing energy consumption. The object of this study was to quantify the pressure drop and fine particulate (PM2.5) collection of 1D3D cyclones (H=4Dc, h=1Dc) at inlet velocities from 8 to 18ms−1 (Stk=0.7–1.5) using heterogeneous particulate as a test material at inlet concentrations from 3 to 75gm−3. Cyclone exhaust was passed through filters. Laser diffraction particle size distribution analysis was used to estimate PM2.5 emissions. Response surface models showed a strong correlation between cyclone pressure loss (Euler number) and inlet velocity and predicted a 46% reduction in pressure loss for a 25% reduction in inlet velocity (Stokes number). The model for PM2.5 emissions was less definitive and, surprisingly, predicted a 31% decrease in PM2.5 emissions when operating 25% below the design inlet velocity. Operating below the design inlet velocity (at a lower Stokes number) to reduce pressure losses (Euler number) would reduce both the financial and the environmental cost of procuring electricity. The unexpected co-benefit suggested by these trials was that emission abatement may improve at the same time, though other empirical trials have shown emissions to be independent of inlet velocity and Stokes number.

Academic research paper on topic "Could cyclone performance improve with reduced inlet velocity?"

Accepted Manuscript




P.A. Funk, K. Elsayed, K.M. Yeater, G.A. Holt, D.P. Whitelock

Could cyclone performance improve with reduced inlet velocity?


doi: 10.1016/j.powtec.2015.04.026

PTEC 10936

To appear in: Powder Technology

Received date: 4 November 2014 Revised date: 6 March 2015

Accepted date: 15 April 2015

Please cite this article as: P.A. Funk, K. Elsayed, K.M. Yeater, G.A. Holt, D.P. White-lock, Could cyclone performance improve with reduced inlet velocity?, Powder Technology (2015), doi: 10.1016/j.powtec.2015.04.026

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Could cyclone performance improve with reduced inlet velocity?

P. A. Funk, K. Elsayed, K. M. Yeater, G. A. Holt, and D. P. Whitelock

The authors are Paul A. Funk, Ph.D., Agricultural Engineer, USDA Agricultural Research Service, Southwestern Cotton Ginning Research Laboratory, Mesilla Park, NM, Khairy Elsayed, Ph.D., Assistant Professor, Mechanical Power Engineering Department, Helwan University, Egypt, Kathleen M. Yeater, Ph.D., Statistician, USDA Agricultural Research Service, Plains Area, Fort Collins, CO., Gregory A. Holt, Ph.D., Research Leader and Agricultural Engineer, USDA Agricultural Research Service, Cotton Production and Processing Research Unit, Lubbock, TX, and Derek P. Whitelock, Ph.D., Agricultural Engineer, USDA Agricultural Research Service, Southwestern Cotton Ginning Research Laboratory, Mesilla Park, NM Corresponding author: Paul Funk, PO Box 578, Mesilla Park, NM 88047 USA; phone: 575-526-6381;


Emissions abatement cyclone performance is improved by increasing collection effectiveness or decreasing energy consumption. The object of this study was to quantify the pressure drop and fine particulate (PM2.5) collection of 1D3D cyclones (H = 4Dc, h = 1Dc) at inlet velocities from 8 to 18 m s-1 (Stk = 0.7 - 1.5) using heterogeneous particulate as a test material at inlet concentrations from 3 to 75 g m-3. Cyclone exhaust was passed through filters. Laser diffraction particle size distribution analysis was used to estimate PM25 emissions. Response surface models showed a strong correlation between cyclone pressure loss (Euler number) and inlet velocity and predicted a 46% reduction in pressure loss for a 25% reduction in inlet velocity (Stokes number). The model for PM25 emissions was less definitive and, surprisingly, predicted a 31% decrease in PM25 emissions when operating 25% below the design inlet velocity. Operating below the design inlet velocity (at a lower Stokes number) to reduce pressure losses (Euler number) would reduce both the financial and the environmental cost of procuring electricity. The unexpected co-benefit suggested by these trials was that emissions abatement may improve at the same time, though other empirical trials have shown emissions to be independent of inlet velocity and Stokes number.

Keywords. Cyclones, Emissions, Energy consumption, Fine particulate, PM2 5.

1 Introduction

1.1 Fine particulate (PM25) is a criteria pollutant

In the interest of protecting the public health, the United States Clean Air Act required states to develop a general plan to attain and maintain National Ambient Air Quality Standards (NAAQS) in all areas of the country and a specific plan to attain the standards for each area designated non-attainment for a NAAQS. These plans, known as State Implementation Plans (SIPs), are developed by state and local air quality management agencies and submitted to the U.S. Environmental Protection Agency (EPA) for approval. Particles less than 2.5 microns in aerodynamic equivalent diameter (PM2.5) were first included in the NAAQS in 1997. In 2006 EPA NAAQS for PM25 were lowered, to 15 ^g m-3 [1], and in 2012 they were lowered again, to 12 ^g m-3 [2]. As SIP authors may try to comply with EPA regulations through controlling anthropogenic sources of PM25, more stringent operating permit qualifications for agricultural processing facilities may arise.


Many agricultural processing facility exhaust flows are controlled with cyclones. Cyclones have no moving parts and a relatively low initial cost. Their operating costs are primarily due to the electrical energy required for fans to overcome the friction losses (pressure drop, related to Euler number) in the cyclone and connected ducts. Since generating electricity results in emissions at the power plant, reducing the energy required to operate cyclones potentially helps the environment [3]. Cyclone performance is a function of both particle separation and energy consumption. Cyclone performance may be improved by reducing pressure drop, and thus energy use, as well as by increasing collection efficiency. One option may be to operate cyclones below their traditional design inlet velocity [4]. Research has shown that operating cyclones that are 41% larger than normal, so the inlet velocity was 50% of the design inlet velocity, resulted in pressure losses that were only 28% of normal [5]. While numerous modeling studies have examined monodisperse particles, and empirical studies have reported the impact of inlet velocity on total particulate collection efficiency, this study is the first to report the impact of cyclone inlet velocity on PM25 emissions for heterogeneous material.


The cyclone design called the ' 1D3D' was first introduced by Texas A&M University [6]. Collection

efficiency improvements brought about by design modifications were confirmed through USDA ginning lab tests [7]; [8]. Modified 1D3D cyclones are widely used in agricultural processing, such as by the U.S. cotton ginning industry [9]. Figure 1 shows dimensions in cm of the modified 1D3D cyclones that were tested, with the overall height, H, = 4 diameters (D), and the barrel height, h, = 1 D, with the inlet height, a, and width, b, equal to 0.5 and 0.25 D, respectively. The diameter of the gas outlet, De, = 0.5 D, the vortex finder insertion depth, S = 0.625 D, and the particle outlet diameter, B, = 0.33 D.

The design inlet velocity for the 1D3D cyclone is 16.26 ± 2.03 m s-1 [10], [11], corresponding to a Stokes number of 1.4 for PM25 in the conditions tested. But as publications presenting empirical cyclone collection efficiencies at various inlet velocities have shown [12]; [13]; [14]; [15], cyclones of this design, and other designs, work well over a range of inlet velocities.

Differences in cyclone design, cyclone diameter, particulate inlet concentration and particle size distribution prevent direct comparisons of published results. However, a plot of the collective results (Figure 2) illustrates that gravimetric total suspended particulate (TSP) collection efficiency does not have a clear relationship to inlet velocity (or Stokes number) over the range of inlet velocities reported. This experiment was designed to test the relationship between PM25 emissions and inlet velocity for the 1D3D cyclone.

1.4 Cyclone Performance Indicies

Gas cyclones performance characteristics are estimated using the static pressure drop from the inlet to the outlet (A P) and the grade efficiency curve. The static pressure drop (A P) between the inlet and gas outlet of a cyclone is proportional to the square of the flow rate (Q), with a proportionality resistance coefficient ) defined on the basis of the inlet velocity (Vi = Q/a b), thus:

A P = <fc (1)

Alternatively, Dewil et al. [16] recommended avoiding the inlet velocity as a characteristic velocity and replacing it with the average velocity in the cyclone body (Vc = —tt"). Thus the Euler number (Eu) is related

n Dc /4

to Vc and the pressure drop as:

Eu = lp v c (2)

c pg vi

In this study, (following the recommendation of Svarovsky [17]), Eu will be used as a dimensionless

performance parameter [18].

The separation (grade) efficiency of cyclones represents the variation of the separation efficiency with the particle size. The particle size recovered at an efficiency of 50% is called the cut-size or d50 [16]. For estimating the cut-size, two different approaches are found in the literature [17]. In the first approach, the cut size is reported in ym. The second approach uses the Stokes number. In this study, based on the above-mentioned recommendation, the Stokes number based on the cut-size is:

Stk = Pv VC (3)

50 18 v '

Where d50 is the particle diameter, pp is the particle density, and y is the gas viscosity. In this study, a similar Stokes number will be used for the Stokes number when the particle diameter equals 2.5 m, as:

= (2.5 X10~6)2 Pv Vc (4)

StkPM2S = 18 mDc (4)

1.5 Test Objective

An agricultural processing facility typically has several pneumatic conveying systems that use cyclones to control emissions. Each system has a fixed airflow requirement based on pipe size and minimum carrying velocity. Cyclone inlet concentration varies with processing rate. Cyclone inlet velocity could be modified by substitution of a different sized cyclone. The object of this study was to evaluate the performance (pressure drop and PM25 particulate collection) of 1D3D cyclones over a range of inlet velocities using typical agricultural processing facility particulate matter over a range of inlet concentrations.

2 Materials and Methods

2.1 Test Cyclones

Two modified 1D3D cyclones, 30.5 cm in diameter, were fabricated for this study (Figure 1). The 1D3D cyclones had a barrel that was one diameter in height (1D) and a cone that was three diameters in height (3D). All dimensions in Figure 1 were determined based on published ratios to barrel diameter [9]. The percentage of processing facilities using the modified 1D3D design has continued increasing as older abatement devices and older cyclone designs have been replaced through repairs or new construction. This design is called "modified" because it has a 0.5 D x 0.25 D inlet and a D/3 particle outlet, both of which were not part of the

original design [6]. There also was an expansion chamber (product receiver, or dust bin) at the bottom; this modification is not as widely used as the first two, but it is still common. These test cyclones were fabricated following current industry practices and using 24 gage galvanized lock forming-quality steel sheet metal. All seams were lapped away from the direction of airflow, spot welded and polished until smooth. All joints between connected sections (i.e., cones and barrels) were sealed to prevent leaks. A sealed container 28 cm in diameter by 30.5 cm high was affixed to the bottom of the expansion chamber to hold collected particulate and to prevent air flow (though industry applications are not always able to prevent air flow at the dust outlet.)

2.2 Test Apparatus

Testing was conducted using an apparatus specifically built for this research (Figure 3). A variable speed feed conveyor belt was used to meter test material into the blades of a variable speed trash fan (MF7, Murray Co., Dallas, TX) with a 1.49 kW DC motor (M-200-A, T.B. Wood's Sons Co., Chambersburg, PA). The trash fan conveyed the test material in air through a Venturi tube, through a 10.2 cm diameter pipe, and into the test cyclone. All cyclone exhaust air passed through a filter aided by a filter fan (2206 Alum, New York Blower, Willowbrook, IL) with a 5.59 kW AC motor (M3769T, Baldor, Ft. Smith, AK). Prior to each test a Pitot-static tube was used to measure the air velocity in the duct before the cyclone in order to set the cyclone inlet velocity (by adjusting the speed of the trash fan) according to the velocity called for by the experiment design. During each test the differential pressure through the Venturi tube was monitored, providing feedback control for a variable frequency drive (VFD) (VLT 8000 AQUA, Danfoss, Nordborg, Denmark) that controlled the filter fan's motor. The filter fan produced additional fan pressure to maintain constant air flow as flow through the filter became more restricted with particle accumulation.

Ambient and cyclone exhaust air temperatures (type K thermocouples), and differential pressures across the Venturi tube, the cyclone, the filter and the Pitot-static tube downstream of the filter fan were also measured and recorded. The recorded differential pressure from the Pitot-static tube downstream of the filter fan provided an independent value of instantaneous air velocity throughout each test. The 4-20 mA pressure transmitter signals (Model 614, Dwyer Instruments, Inc., Michigan City, IN) were converted to voltages by a custom-made signal-conditioning card. Voltage signals were recorded continuously at 1 s intervals using a data logger (Model 34970A, with 34908A switch units, Agilent Technologies, Santa Clara, CA) and averaged over

the duration of the test to determine their respective values.

2.3 Filters

Particulate matter escaping the dust cyclone was collected on 56 cm x 61 cm hydrophobic filter media (Type FP2063, Hi-Q Environmental Products Co., Inc., San Diego, CA) made of borosilicate glass microfibers with a minimal amount of an acrylic resin binder to maintain filter integrity. Filters had 97% collection efficiency for 0.3 micron dioctyl phthalate [19]. Filters were conditioned in a controlled atmosphere environmental chamber (21 C and 35% relative humidity) for 72 hours or more before weighing, following guidelines published by the EPA [20]. Each filter was carefully handled with gloves, folded in quarters, and stored and weighed in a dedicated 4 mil anti-static polybag (Part No. 49115, Protektive Pak, Chino, CA) to prevent the incidental loss of glass fiber or particulate. The bagged and conditioned filters were weighed before and after testing in an environmental chamber on an electronic balance (PG1003-S, Mettler-Toledo Inc., Columbus, OH) after passing them through an anti-static device. The balance was leveled on a brass slab and housed inside an acrylic box to minimize the effects of air currents and vibrations. Each filter was weighed three times. If the standard deviation of the weights exceeded 10 mg, the filter was re-weighed.

2.4 Experimental design

This response surface experiment used a central composite design. There were nine combinations of two continuous variables: inlet concentration and cyclone inlet velocity. Five replicates at the center point estimated variability (Figure 4). Four corner and four axial points were equidistant from the center to attain a rotatable design with uniform precision of estimation in all directions. Commensurately, the resulting five levels of inlet velocity and five levels of particulate inlet concentration provided an estimate of curvature for potential non-linear responses. The experiment design called for inlet velocities of from 8 to 18 m s-1 (corresponding to a PM25 Stokes number between 0.7 and 1.5). This range was selected based on earlier work [5] and included the design inlet velocity for 1D3D cyclones (16.26 m s-1). The experiment design called for inlet concentrations from 3 to 75 g m-3, the range of inlet concentrations from published research [21].

A comparison was made between two identical cyclones (A and B) across the full range of inlet velocity and inlet concentration. Thirteen runs (four corner points, four axial points, and five replicated center points) were

conducted with each cyclone for a total of 26 experimental runs. The runs were conducted in a completely randomized design. Uncontrolled variables such as air temperature were measured throughout the six weeks of testing to control for potential covariance.

2.5 Particle Size distribution Analysis

All filters, cyclone catch and feed material samples were sent to the USDA-ARS Air Quality Laboratory in Lubbock, TX for Particle Size Distribution (PSD) analysis. These were conditioned in an environmental chamber for at least 48 hours at 21 C and 35% relative humidity. Bagged cyclone catch and feed samples from each test were weighed on an electronic balance (A & D HP-20K, Data Weighing Systems, Elk Grove, IL). After removing sample material, the bags were reweighed. Cyclone catch from each test were sieved using standard procedures [22] and equipment (Ro-tap, W.S. Tyler, Mentor, OH) to obtain coarse gradation above 106 ^m. Particles larger than 100 ^m aerodynamic equivalent diameter (AED) have a high probability of being captured by the cyclone. The fine portion (below 106 ^m) was sub-sampled three times for PSD analysis.

Particle size analyses were conducted on a laser diffraction (LD) system (Beckman Coulter LS230, Beckman Coulter Inc., Miami, FL) with software version 3.29 to calculate the PSD. The instrument measured particles over the range of 0.375 to 2000 ^m that were suspended in a 5% lithium chloride/methanol electrolyte solution. The LD particle-size analyses consisted of the following procedures: The electrolyte was pre-filtered using a filtration system that removed all particles larger than 0.2 ^m. A background count of the filtered electrolyte was made with the LD system to ensure that there was minimal particulate contamination of the electrolyte. Background counts of less than 300 particles per cm3 of electrolyte were considered acceptable. For PSD analysis of particulate on filters, the particulate must be extracted from the filter media and suspended in the electrolyte solution. Particulate was extracted from the loaded filters by cutting three 2-cm diameter samples from a heavily loaded area of the filter, placing the samples in a 100-ml beaker with 50 ml of electrolyte, and processing the sample in an ultrasonic bath for 5 min. The particulate/electrolyte solution was then introduced into the fluid module of the LD system to run a PSD analysis.

Optical model parameters used with the LD system software to determine the sample PSDs were 1.56 for the real part of the sample refractive index, 0.01 for the imaginary part, and 1.326 for the suspension fluid refractive index. [These values are used in the Lorenz-Mie solution to Maxwell's equations. These equations

describer light scattering by spherical particles in a transparent medium.] LD system results in terms of equivalent spherical diameter were corrected to aerodynamic equivalent diameter (AED) by multiplying equivalent spherical diameter by the square root of the product of the density (2.65 g cm-3) divided by the shape factor (1.40). This PSD analysis was used to estimate PM25 emissions (particulate 2.5 ^m AED and smaller).

2.6 Test Material

Since this research was intended to assist agricultural processing facilities with energy conservation as well as regulatory compliance, agricultural particulate from the cotton ginning industry was used. The range of particulate inlet concentration values chosen for this study, from 3 to 75 g m-3, was influenced by that reported by earlier empirical studies: 2-16 g m-3 [5]; 7-15 g m-3 [23]; 8-10 g m-3 [24]; 8-100 g m-3 [25]; and 75 g m-3 [7].

The test material consisted of soil particles, fibers, leaf particles, and stems. The composition of this test material represents the type of material that might be handled by dust cyclones at an agricultural processing facility. Each test run used 0.8 kg of test material so that the filter would have close to its maximum load of dust (pre-trial runs with more than 0.8 kg resulted in filter damage). The largest possible quantity was selected to minimize experimental error by maximizing test run time and filter weight, and hence signal-to-noise ratio. Eight sub-samples each weighing 100 g were evenly distributed on eight contiguous sections 30.5 cm long on the variable speed feed conveyor. The conveyor speed was set before each test so that the test material metered into the airstream of the test apparatus at the dust inlet concentration required by the experimental design. Lower inlet concentration trials took more time; time was recorded to independently verify inlet concentration.

2.7 Test Material Characterization

Nine samples of test material were collected throughout the test period for particle size distribution analysis. The size distribution of the test material was somewhat bi-modal. The major constituents were leaf particles (in the size range between 250 and 850 ^m) and soil particles (greater than 10 ^m and less than 106 ^m), as presented in Table 1. Note that for this test material, considered representative of that handled by cotton gin cyclones, only a small part (6%) was particulate less than 10 ^m and considerably less than that (0.9% of the total) was fine particulate less than 2.5 ^m.

The sieved portion of each feed sample, the 40.8% that was below 106 ^m, was sub-sampled three times for

particle size distribution analysis. The sieved test material had an aerodynamic equivalent mass median diameter (AED) of 41.56 ^m and a geometric standard deviation of 3.07. The percentage of sieved material < 2.5 ^m was 2.266%, with a standard deviation of 0.389 percentage points (17%); the percentage of sieved material < 10 ^m was 14.742%, with a standard deviation of 2.893 percentage points (20%). Figure 5 presents the size distribution of the sieved portion of the test material. Test material variability had the potential to contribute to uncertainty in the results.

2.8 Reported Units - PM2.5 per kg fed

Publications analyzing cyclone performance historically have reported collection efficiency as the collected percent of mass entering, or they have reported the cut point - that particle size for which the collection efficiency is 50 percent [26]; [27]. The fraction escaping is quantified by isokinetically sampling a portion of the exhaust as per EPA Method 201A [28], or by passing all of the cyclone exhaust through a filter weighed before and after the test under standard conditions (as with this study). The mass lost is compared to the sum of the mass collected and lost, or to the weight metered into the air stream (as in these tests), or the exhaust concentration is compared to results from isokinetically sampling the inflow. In all cases, whether sampling a portion of the gas flow or filtering all of it, whether reporting overall collection efficiency or cut point, results have also varied with the inlet concentration and particle size distribution of material entering the cyclone [29].

Reporting emissions concentration would have been confusing in a test where inlet concentration varied over a wide range. Since the rate of material escaping a cyclone has nearly a direct relationship to the rate of material entering it, emissions concentration would have been confounded by inlet concentration. Therefore, emitted PM25 was normalized to 1000 g of feed material. Emissions values are presented as grams PM25 collected on the filter per kg of all material entering the cyclone. The PM25 mass on each filter was multiplied by 1 kg and divided by the mass of material entering the cyclones for each test run (nominally 800 g). The normalized mass of PM25 escaping the cyclone and collected on the filter was expected to give an independent indication of performance that would reveal the influence of inlet concentration and inlet velocity. Since the same mass of feed material was used in each test run, reporting fine particulate mass escaping the cyclone per run is similar to reporting an emissions factor, as is done with AP 42 process rate tables [30]. This relative performance metric is specific to these trials; it is not an indication of absolute collection efficiency, nor is it a

universal predictor of emissions concentration.

2.9 Data Analysis

The theoretical collection efficiency of a cyclone is largely determined by particle velocity [21] and particle velocity is closely related to air velocity. For this reason, actual values of local air density (based on temperature, barometric pressure and relative humidity) at the time of each test were calculated and used to determine the Pitot-static tube velocity pressure corresponding to the desired inlet velocity and inlet concentration. Uncontrolled variables (run number, date, barometric pressure, temperature, relative humidity, air density and cyclone) were tested for significance (proc mixed, SAS 9.2, SAS Inc., Research Triangle Park, NC) at the 5% level to verify that they did not significantly impact the response variables (PM2.5 emissions and pressure drop). Insignificant uncontrolled variables thus could be omitted from the analysis.

Response surface methodology was performed using experimental design and analysis software (Design-Expert (DX8), Stat-Ease, Inc., Minneapolis, MN). Actual values for inlet velocity and inlet concentration (based on local air density) were used in constructing the response surface models. Two responses, PM25 emissions (emitted grams per kg of material entering the cyclone), and pressure drop (Pa), were modeled. Numerous models were tested in the process of arriving at the "best" one; the criteria for choosing one model over another, in decreasing order of importance, were: 1) its terms made sense from the standpoint of the laws of physics; 2) it was simpler; 3) it had a better fit (ANOVA) than a lower-order model, or adding the higher order terms significantly increased the sum of squares; 4) its lack of fit was still insignificant; 5) it resulted in significantly higher coefficients of determination, or adjusted R2 values.

3 Results

3.1 uncontrolled Variables

Table 2 lists the F value and the probability of exceeding it for each input variable using the proc mixed output type 3 tests of fixed effects (SAS 9.2, SAS Inc., Research Triangle Park, NC) by response variable; there were 16 degrees of freedom. For both responses, each one of the uncontrolled variables were not significant -justification for omitting uncontrolled variables from the response surface models. Inlet velocity was significant for both PM25 and pressure drop. Inlet concentration appeared to have a significant influence on

PM2.5 emissions, but not on pressure drop, based on this data. There was not a significant interaction between inlet velocity and inlet concentration. 3.2 Response Surface Model

Table 3 lists the selected response surface models. A linear model was selected for PM2.5 emitted per kg entering the cyclone. Higher-order models improved the adjusted R2 slightly, but were difficult to justify since the higher-order terms were not significant. The significance of inlet velocity and inlet concentration in the DX8 model was confirmed by the SAS analysis (Table 2). The adjusted R2 of the selected model for PM25 was 0.6599. PM25 emitted per kg entering the cyclone was plotted as a response surface over inlet velocity and inlet concentration (Figure 6).

The selected pressure drop model included terms for inlet velocity to the first and second power. The adjusted R2 of the selected model for pressure drop was 0.9396. Considering the range of predicted and measured values for pressure drop in antecedent publications, which vary by a factor of 2.8 for this particular design [31], and the fact that this model had only inlet velocity as a predictor, it fit this data fairly well. The influence of inlet concentration on pressure drop has long been documented [32]. Pressure drop decreases as inlet concentration increases up to about 200 g m-3 [33]. Inlet concentration levels were below that range for this experiment, but this study lacked the necessary power to detect statistical significance for that variable. In these trials the Stokes number for PM25 was directly proportional to inlet velocity (Stk = 0.0863 Vi), and the Euler number was a linear function of pressure drop (Eu = 21.72 + 0.074AP).

When substituting an inlet velocity of 12.19 m s-1 for 16.26 m s-1 in the selected response surface models (a 25% reduction, equivalent to reducing the Stokes number from 1.403 to 1.052) they predicted a 31% decrease in PM25 emissions: from 0.473 to 0.324 g kg-1; a 46% reduction in pressure loss: from 514 to 280 Pa, and a 29% reduction in Euler number, from 59.8 to 42.4, at an inlet concentration of 45 g m-3 (Table 4). Table 4 also presents a 95% confidence interval range based on the response variables models (assumed: normal distribution, model standard deviation and number of observations). The lack of overlap for the 95% confidence interval ranges on PM25 emissions, pressure drop, and Euler number indicate a statistically significant difference between the two inlet velocities; they predict that an agricultural processing facility may both save energy and reduce emissions simply by operating its 1D3D cyclones at a lower inlet velocity.


The significance of these results comes from the nexus of emissions and energy. The energy cost of operating cyclone abatement devices is directly proportional to pressure drop, and producing electricity to power abatement devices results in air pollution, favoring lower inlet velocities. At the same time, fine particulate emissions did not increase as expected, but appeared to decrease slightly at lower inlet velocities.

For this particular configuration, set of operating conditions, and inlet material PSD there was a strong correlation between inlet velocity and pressure drop (model adjusted R2 = 0.94), and a weaker association between inlet velocity and emissions (model adjusted R2 = 0.66). The second order pressure drop relationship was expected as it agreed with published results from both modeling and empirical trials. The relationship between emissions and inlet velocity contradicted many classical numerical models [34]; [35]; [36] and some empirical research [37] that predict continuously increasing collection efficiency with increasing inlet velocity. This is best illustrated by Figure 7, a plot of PM25 emissions over Stokes number for each run in this trial. A lower Stokes number predicts that a particle will better follow a streamline, implying an increase in emissions as particles would be more likely to be carried out of the cyclone by the air. However, this data set showed emissions decreasing at lower Stokes numbers. Correlation coefficients were between 0.5 and 0.6, partly due to varying inlet concentration. Other empirical research indicates little correlation between emissions and inlet velocity, especially with heterogeneous particulate (Figure 2), or at least an upper limit to inlet velocity beyond which emissions increase. This conflict has been discussed elsewhere [11]. Some authors hypothesize that turbulence or interior surface roughness induces particle bounce, causing particle re-entrainment [38]; [39], a phenomenon that is thought to increase with gas and particle velocity. This trial suggested that inlet velocity, and Stokes number, in 30.5 cm diameter 1D3D cyclones handling heterogeneous particulate, may have little impact on emissions. Perhaps particle agglomeration, a mechanism for fine particulate capture, is favored by lower turbulence.

Considering the potential importance of these findings in terms of energy savings and reduced power plant emissions, the challenge of balancing energy savings to the increased capital cost of larger cyclones, and the potential difficulty in terms of changing existing environmental regulations, it is important that these experiments be replicated under field conditions. If confirmation of these experiments were to result in more

relaxed regulation, it may lead to reductions in the energy consumption of pneumatic conveying systems at agricultural processing facilities and perhaps elsewhere. This work has a high priority for two reasons. First, energy costs are rising relative to other costs of operation, and pneumatic conveyance fans account for more than half of the energy used by some agricultural processing facilities [40]. Second, energy production is a significant source of air pollution, so reducing energy requirements of abatement devices would benefit the environment [3].

4 Conclusion

Cyclones were tested to better understand the effects of inlet velocity and inlet concentration on pressure drop and emissions. Modified 1D3D cyclones were operated at inlet velocities from about half to slightly more than design, from 8 to 18 m s-1, over a range of inlet concentrations from 3 to 75 g m-3. Cyclone pressure drop, AP, was measured directly. Emitted total mass collected on filters and particle size distribution analysis was used to estimate PM25 emissions, presented in this paper as mass of PM25 for each kg of total material fed to the cyclone. Cyclone performance models were developed using response surface methodology. Based on the obtained results, the following conclusions were drawn:

• Response surface models showed a strong correlation between cyclone pressure loss and inlet velocity and predicted a 46% reduction in pressure loss for a 25% reduction in inlet velocity, as well as a 29% reduction in Euler number for a 25% reduction in Stokes number.

• The model for PM25 emissions was less definitive and, surprisingly, predicted a 31% decrease in PM25 emissions when operating 25% below the design inlet velocity (at a 25% lower Stokes number).

• Operating below the design inlet velocity to reduce pressure losses would require larger, costlier cyclones, but may reduce both the financial and the environmental cost of procuring electricity.

Dr. Paul Funk is an Agricultural Engineer working on diverse projects including non-chemical harvest

preparation, renewable energy production, specialty crop mechanization, trace analytical chemical detection of contaminants, and air quality. He earned an M.S. from the University of Minnesota and a Ph.D. from the University of Arizona, both in Agricultural Engineering. He was a professor of Mechanical Engineering before becoming a Research Scientist with the USDA Agricultural Research Service in Mesilla Park, New Mexico.

Dr. Khairy Elsayed is a Mechanical Engineer working on diverse research projects including Cyclone separators, CFD simulations, surrogate based optimization and shape optimization. He earned an M.S. from Helwan University in Egypt and a Ph.D. from Vrije Universiteit Brussel (VUB), both in Mechanical Engineering. He is a Professor/Senior Research Scientist at VUB and Assistant Professor at Helwan University.

Dr. Kathleen M. Yeater is an Area Statistician for the United States Department of Agriculture, Agricultural Research Service, where she provides consultative support to research scientists on the development and implementation of scientific studies, sampling methodology, and data analysis. She is actively involved in working with researchers in developing and presenting inferences from statistical results as well as consulting and training a diverse group of research personnel. Kathy received a Ph.D. in Biometry and Statistics from the Department of Crop Sciences at the University of Illinois.

Dr. Greg Holt is the Research Leader at the Cotton Production and Processing Research Unit in Lubbock, Texas. He has conducted research related to development of more efficient pollution abatement devices for cotton gins, optimization of cotton harvesting and ginning machinery, sensor development for microwave imaging of cotton moisture, and value-added processing of cotton byproducts and agricultural fibers. He earned B.S. and M.S. degrees from Texas A&M University in Agricultural Engineering and a Ph.D. from Texas Tech University in Industrial Engineering.

Dr. Derek Whitelock is an Agricultural Engineer conducting cotton ginning and agricultural air quality research at the USDA-ARS Southwestern Cotton Ginning Research Lab in Mesilla Park, New Mexico. He earned B.S. and M.S. degrees from Texas A&M University and a Ph.D. from Oklahoma State University in Agricultural Engineering. His research, mainly in the areas of air quality and seed-cotton and lint cleaning, covers a broad spectrum of issues in both saw and roller ginning.

Paul Funk Khairy Elsayed Kathleen Yeater Greg Holt Derek Whitelock


The authors wish to recognize the outstanding contributions of their technical staff, including Juan Gomez

and Branyan Sanxter at the Southwestern Cotton Ginning Research Laboratory and Bud Welch at the Air

Quality Laboratory.


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Captions for Figures and Tables

Figure 1. Modified 1D3D cyclones used in this study were 30.5 cm (12 in) in diameter. This design, both with and without the expansion chamber, is widely used in agricultural processing. Note the protrusion of the vortex finder below the tangential inlet and the cone below the top of the expansion chamber. Two cyclones were built to the same specifications for this experiment. Dimensions are in cm.

Figure 2. Plot showing total suspended particulate gravimetric collection efficiency (percent) for different inlet velocities (meters per second) tabulated by four research teams over five decades. Cyclones were 30 to 76 cm (12 to 30 inches) in diameter. These results illustrate that dust cyclone performance is relatively insensitive to cyclone inlet velocity. Sources: Baker and Stedronski (1967); Wesley, Mayfield and McCaskill (1972); Gilum and Hughs (1983); Faulkner and Shaw (2006) where "2006a" = alumina and "2006c" = cornstarch as the test particulate. The design inlet velocity of a 1D3D cyclone, 16.26 m s-1 (3200 ft min-1) is indicated by the vertical line.

Figure 3. Experiment apparatus. A: variable speed test material feed conveyor; B: variable speed trash fan; C: Venturi tube flow meter; D: removable Pitot-static tube; E: test cyclone with sealed collection bucket; F: filter to collect cyclone losses; G: variable speed filter fan; H: fixed Pitot-static tube; T: temperature sensing (thermocouple) locations. Pressure sensing locations: Venturi tube (1-2); cyclone pressure loss (3-4); and filter pressure loss (5-6). Not to scale.

Figure 4. Experiment design showing the combination of the two controlled variables, inlet velocity and inlet concentration. Each circle represents the target values for test conditions for one test of each cyclone. Five replicates were run at the center (39 g m-3 and 13 m s-1).

Figure 5. Sieved test material aerodynamic equivalent diameter size distribution (particles < 106 ^m).

Figure 6. PM25 emissions (in g kg-1 test material entering cyclone) over the tested range of inlet concentration and velocity. The response surface is bounded by actual data points; gradations are uniformly distributed between them. Emissions per kg of material entering the cyclones increased significantly with increasing inlet velocity and emissions increased with decreasing inlet concentration.

Figure 7. PM25 emissions (in g kg-1 test material entering cyclone) as a function of Stokes number for PM25 separated by the cyclone. Normally, emissions would be greater at lower Stokes numbers, where drag forces are greater than inertial forces. This result, for heterogeneous particulate, indicates that other factors may be present that the Stokes number does not account for. Perhaps particle agglomeration, a mechanism for fine particulate capture, is favored by lower turbulence.

Table 1. Size distribution of test material (gin trash) used in the experiment.

Table 2. Test statistics indicating the influence of uncontrolled and controlled variables for each response variable (bold indicates significance).

Table 3. Selected response surface models for cyclone performance (PM25 emissions per kg fed and pressure drop) as functions of inlet concentration (g m-3) and actual inlet velocity (m s-1). Model statistics are from Design Expert (2010, Stat Ease, Minneapolis, Minnesota).

Table 4. Response surface model results and 95% confidence intervals for two velocities at 45 g m-3 inlet concentration.

Collection Efficiency Reported in Prior Publications


¿3 99.7% 01 E

Design 16.26 ms"1

♦ 1967 □ 1972 A 1983 S2006a

• 2006c

Velocity (3200 fpm)

Entrance Velocity (m s1)

Figure 1

Figure 2

Figure 3

Inlet Velocity (ft. mlrr1) 1575 1870 2559 3248 3543

(V u c o

u c o u

Inlet Velocity (m s1)

Figure 4

Average (n=9) Particle Size Distribution of Sieved (<106^im) Test Material

Mass Median Diameter = 41.56 |im AED Geometric Standard Deviation = 3.07

< PM2 5 = 2.27 %

< PM10 = 14.74%

50 100 150 200

Particle Aerodynamic Equivalent Diameter (n)

Figure 5

PM,, Emissions (g Met kg'}

<=0.200 3= 0.300 H <=0.400 H <= 0.500

m <=o.6oo mm <=o.7oo H 1= 0.800 H > 0.800

10.0 12.5 15.0 Inlet Velocity (in S'1)

Figure 6

0.9 -,

PM2.5 Emissions v. Stokes Number

Rz =0.5916

.¡2 0.4 E


Rz =0.5127

♦ C1-PM2.5 □ C2-PM2.5

-Linear (C1-PM2.5)

—- Linear (C2-PM2.5)

1 1.2 PM2.5 Stokes Mumber

Figure 7

< 2.5 < 10 < 106 < 150 < 250 < 850 > 850

Particle Size_[m_[m_[m_[m_[m_[m_[am


Percent 0.90% 5.10% 34.80% 6.10% 7.80% 31.20% 14.00%


Total 0.90% 6.00% 40.80% 46.90% 54.80% 86.00% 100.00%

Table 2

Pressure Drop (Pa) PM2 5 (g/kg fed) and Euler Number

Statistic F Value Pr > F F Value Pr > F

Run Number 0.46 0.5051 0.02 0.8818

Date 0.72 0.4083 0.21 0.6545

Barometric Pressure 0.21 0.6552 0.84 0.374


Variables Temperature 0.25 0.6251 1.1 0.3099

Relative Humidity 0.03 0.8656 2.59 0.127

Air Density 0.25 0.6268 0.9 0.358

Cyclone A or B 0.11 0.7474 0.14 0.7095

Controlled Variables Inlet Velocity Inlet Concentration Velocity* Concentration 15.92 8.16 2.73 0.0011 0.0114 0.119 237.86 1.29 2.66 <.0001 0.2734 0.1238

Response [a] Model [b] Model adj. R2 Std. Dev.

PM2.5 (g/kg) = + 0.0051617 + 0.036549*V - 0.0028133*C 0.6599 0.095

AP (Pa) = + 80.679 - 14.504*V + 2.5314*V2 0.9396 40.87

PM2.5 (g/kg) = + 0.0051617 + 0.42351*Stk - 0.0028133*C 0.6599 0.095

Eu = + 21.72 + 0.074*(80.679 - 168.065*Stk + 339.89*Stk2) 0.9534 3.024

[a] Eu = Euler Number [b] V = Inlet Velocity (m s-1), C = Inlet Concentration (g m-3), Stk = Stokes Number Table 4


Inlet Velocity = 16.26 m s-1 (3200 fpm) (Stokes Number, Stk = 1.403)

Inlet Velocity = 12.19 m s-1 (2400 fpm) (Stokes Number, Stk = 1.052)

PM2.5 (g/kg) AP (Pa) Eu


95% Confidence Interval


95% Confidence Interval

514 59.8

498 58.6

530 60.9

280 42.4

264 41.3

296 43.6

600 i Response surface from empirical cyclone test produced an unexpected result:

Energy consumption and PM2.5 emissions both increased with inlet velocity.


PMZ5 Emissions (mgkg1)

10 11 12 13 14

Inlet Velocity (m s1)

Graphical Abstract


• The significance of these results comes from the nexus of emissions and energy.

• Producing electricity to power abatement devices results in air pollution.

• Reducing inlet velocity reduced pressure drop and hence energy required.

• Empirical PM2.5 emissions also appeared to decrease at lower inlet velocities.