Experimental Study on the Flow Field of Particles Deposited on a Gasoline Particulate Filter

energies

Article Experimental Study on the Flow Field of Particles Deposited on a Gasoline Particulate Filter

Mingfei Mu 1,2 , Jonas Sjöblom 2,* , Nikhil Sharma 2, Henrik Ström 2 and Xinghu Li 1

1 School of Transportation Science and Engineering, Beihang University, Beijing 100083, China 2 Department of Mechanics and Maritime Sciences, Chalmers University of Technology, Göteborg SE-41296, Sweden * Correspondence: [email protected]; Tel.: +46(0)31-772-1389

Received: 13 June 2019; Accepted: 12 July 2019; Published: 15 July 2019

Abstract: The abatement of particulate matter in gasoline vehicle exhaust has prompted the development of gasoline particulate filters (GPFs). The spatial distribution of the deposited particles inside a GPF has profound implications for its regeneration behavior, ash-induced aging, and multiscale modeling efforts. The connection cones will affect the flow into the monolith and the package structure needed to meet the system space requirements. In this paper, nonuniform rational B-splines (NURBSs) were applied to the cone design to optimize the flow uniformity and particle distribution inside a gasoline particulate filter. NURBS and conventional cones were manufactured using 3D printing, and the velocity profiles and pressure drops were measured under the loading of synthetic particles. The results shows that the cone shape will influence the pressure drop and the velocity profile, which is evaluated as the uniformity index. The test results indicate that better performance is achieved when using the NURBS cone, especially at low particle loads. The results also show that the cone shape (which determines the velocity profile) influences the particle deposition distribution, although the apparent pressure drops are similar. These results are important for exhaust aftertreatment system (EATS) design and optimization, where the NURBS cone can improve flow uniformity, which causes better particle deposition distribution and lower pressure drop.

Keywords: ﬂow uniformity; connection cone; nonuniform rational B-splines (NURBS); pressure drop; PM deposition distribution

1. Introduction

1.1. Particulate Mater Emission of Gasoline Engines The gasoline engine has been widely used in cars and trucks, and the technology of gasoline direct injection (GDI) has been highly regarded during the application and development of the gasoline engine, as it has good dynamic characteristics and fuel economy. Since fuel is directly injected into the cylinder when preparing the mixed gas, the fuel can absorb the heat in the cylinder after atomization and evaporation, which decreases the temperature, increases the volumetric efficiency, and reduces the knocking tendency. Therefore, GDI engines generally have higher, compression ratios and higher thermal efficiencies, and the stratified charge lean burn can further improve their performance. GDI engines can reduce fuel consumption by 15%–20% comparing with traditional port fuel injection (PFI) engines [1]. The GDI technology also accurately measures and controls the amount of fuel injected, which avoids the extra fuel supply due to the low speed at idling, thus improving the engine response and reducing emissions [2].

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GDI engines are widely used because of their many advantages, but particulate emissions are greatly increased while reducing gaseous pollutants. The generation of particulate matter (PM) is mainly caused by the direct injection of gasoline into the cylinder, and the preparation process of the mixed gas is then completed in the cylinder so that the gas is ignited without being sufficiently mixed; hence, the combustion is also insufficient. In addition, wall wetting is also a cause of PM [3,4]. It has been reported that the PM emissions per kilometer of GDI engines is approximately 10 mg, and the particulate number (PN) can reach up to 1013 #/km, while the emissions per kilometer of PFI engines is less than 1 mg and the PN is only 1212 #/km [5].The particles of GDI engines are smaller than those of diesel engines. Graskow et al. [6] studied the distribution range of the particle size of GDI engines. The results show that the average geometric diameter distribution of the particles is 68–88 nm, and the average PN concentration is 108 #/cm3 [7]. Theoretically, smaller particles have a larger surface, and smaller particles per unit mass can carry more toxic and harmful substances. In addition, the small particle volume makes it easier to enter the respiratory tract and threaten human health; the particles can travel through the lungs and may eventually enter the cellular membranes and finally enter the bloodstream of the human body [8–10]. In previous studies, most researchers have focused on diesel engines when considering PM emission research. However, in urban areas where vehicles are intensively used, diesel vehicles are relatively scarce; most vehicles are gasoline vehicles, so the PM emitted by gasoline vehicles must be seriously considered. Fujita et al. [11] and Gildemeister et al. [12] studied the PM concentration emitted by gasoline vehicles in the Denver and Detroit regions of the United States. The results showed that three more PM emissions are generated by gasoline vehicles than by diesel vehicles. For this and similar reasons, the emission standards of gasoline vehicles have been raised repeatedly by relevant emissions regulations in different countries. In Europe, the Euro-6 emissions regulations stipulate a PM emissions limit of GDI engines (6 1011 #/km) [13,14]. The emission standards of PM for GDI × engines are rising in many countries. Therefore, how to reduce the PM emissions from GDI engines needs to be thoroughly studied. Currently, the methods for reducing the PM emissions of GDI engines are mainly internal purification and exhaust aftertreatment systems (EATS). The principle of internal purification to reduce PM emissions is to take various measures to optimize the combustion process and accurately control the fuel injection, ignition timing, and other parameters, so that the gas mixture is more evenly mixed, the combustion is more complete, and more PM is directly burned in the cylinder, which in turn reduces the particulate emissions. Internal purification has high requirements for engine design and manufacturing and may increase the emissions of other pollutants when adjusting the in-cylinder combustion parameters; internal purification is very effective, but it is still not sufficient to meet stringent emissions limits.

1.2. EATS and Gasoline Particulate Filter The principle of the exhaust aftertreatment method is to connect an aftertreatment device in the vehicle exhaust system to physically and chemically eliminate the PM in the exhaust gas. Three-way catalytic converters, four-way catalytic converters, particulate filters, etc. [15,16] are different EATS components used to reduce particulate emissions. Although the three-way catalytic converter has a certain effect on the soluble organic fractions (SOFs) in the particles, its processing ability is limited. The four-way catalytic converter actually combines an oxidation catalyst, particulate filter and NOx reduction catalyst to form a complete EATS. At present, research on the four-way catalytic converter is still in the exploration stage. The gasoline particulate filter (GPF) is a porous medium that is utilized to capture PM in the exhaust. Energies 2019, 12, 2701 3 of 18

The GPF has characteristics of a moderately high filtration efficiency, versatility, and flexibility and has been widely studied by researchers. At present, there are few models equipped with GPFs on the Chinese market, and only automobile companies such as Mercedes-Benz and Toyota are equipping their luxury models with filter devices. With the further popularization of GDI engines and the increasingly strict environmental regulations, the research and application of particulate filters for GDI engines will need to be deeply studied. The performance of GPFs is mainly influenced by the monolith. Currently, silicon carbide (SiC), cordierite, aluminum titanate (AT) and foam metals are the most widely studied monolith materials, and these materials have been applied worldwide. Due to the different structural characteristics of the different filter materials, their filtration performance levels are also different. Cordierite is well suited for GPFs during gasoline engine operation (rapid heating and cooling conditions), and it has good thermal shock performance and a low coefficient of thermal expansion. Other materials, like SiC and AT, due to their inherent high density and high heat capacity, are widely used in the high soot load applications that are typical of diesel. Compared with those in diesel engines, the smaller soot loads in GDI engines make cordierite the material of choice for GPF applications [17], and cordierite has higher regeneration efficiencies and chemical robustness than SiC and AT [18]. Moreover, cordierite can withstand the ash interaction of gasoline applications [19]. The structural design of the GPF is very important, and designing sophisticated aftertreatment systems is extremely challenging when considering the efficacy and pressure drop of every device within a limited space. To address the pressure drop, previous research on DPFs has focused on the filter monolith itself together with the deposited soot, which generates most of the overall pressure drop [20–22]. The results can also be applied to GPFs. Methods of reducing pressure drop have been investigated from multiple perspectives, such as channel structure optimization, new material development, and particle deposition [20,21,23,24]. Some methods address the flow uniformity improvement in the monolith; however, flow management before the monolith has received scant attention in previous studies.

1.3. Connection Cone Optimization The connection cone can affect the flow into the monolith, as the cross-section changes from the inlet to the monolith. A linear cone has been used as the simplest way to connect the exhaust pipes and the monolith. However, a linear cone with a large expansion angle will separate the flow and create a recirculation zone inside the cone, which deteriorates flow uniformity. The exhaust flow in a linear cone usually concentrates near the center, (approximately 88% of the flow passes through 53% of the filter cross-sectional area in certain case); accordingly, the researchers proposed a streamlined cone using a unipolar sigmoid function, which avoids the recirculation zone and increases the flow uniformity approximately 30% [25]. The flow uniformity of other EATSs, like the catalytic convertor, has also been studied. An increase in both the inlet flow velocity and the expansion angle can worsen the flow uniformity [26,27]. Flow nonuniformity will decrease the monolith performance during the cold-start operations [28]. To improve flow uniformity, flow-tailoring devices placed before the monolith have been studied to ensure a uniform flow distribution, but these devices cause the pressure drop to increase [29,30]. One special cone called the enhanced and diagonal (EDH) cone tube has shown promise for reducing the pressure drop, which makes the catalyst structure more compact and improves the flow distribution [31–33]; however, the tube also requires a relatively large installation space. Reducing the cone expansion angle represents another method of improving the flow distribution [34]. Moreover, the monolith has an installation limit, and if it is close to the engine, it can lead to highly nonuniform flow behavior [35,36], which will affect the monolith performance. Energies 2019, 12, 2701 4 of 18

1.4. NURBS Cone Application The streamlined (nonuniform rational B-splines, NURBS) cone’s improvement of the flow uniformity has been verified from previous experimental results, and the overall pressure drop of the test system can be reduced up to 12% in a special case [37,38]. Simulation results revealed significant changes to the flow structures before the monolith, which illustrates the value of the NURBS cone. The influence of the cone on the monolith flow distribution and the pressure drop has been researched both experimentally and via simulation [38]. However, its influence on the particle distribution has rarely been studied through experiments because it is difficult to obtain a precise and stable test bench, and the use of simulations makes the study more convenient and safer. However, during full-scale simulations, the detailed geometry and flow inside the monolith must be described in a coarse, averaged manner to make the simulations feasible. For example, the parameters to define the monolith in the commercial computational fluid dynamics (CFD) software contain the viscous resistance and void fraction, but the inertial resistance is often ignored [39], and the three-dimensional passage from the inlet to outlet channels is typically unresolved. Experimental results, on the other hand, innately account for all relevant factors and can thus be used to establish correction factors and subgrid models for the validation and verification of the simulation procedures. To obtain accurate data inside the monolith from a full-scale simulation, experimental results are required to make the simulation data more credible, especially for a newly designed cone. In addition to flow uniformity and pressure drop, the connection cone can also affect the regeneration temperature, which is highly relevant to the particle distribution. E et al. contrasted three different cones to the same DPF, and the distributions of the radial and axial temperatures were detected [40]. The researchers found that the cone had a lower temperature gradient with better flow uniformity. It could be concluded that such a cone would have a longer service life. Thus, the cone’s influence on the particle distribution needs to be determined. There is also a trend for aftertreatment devices to be more compact; therefore, how to save space and make more efficient use of the filterability should also be considered in cone optimization. In addition, NURBS cones can be applied not only to GPFs but also to other devices. With the improvement of manufacturing, the NURBS cone can be promoted in the future.

2. Experimental Setup and Test Procedure

2.1. Setup Figure1 shows the particle loading and velocity measurement system, which was similar to the system described in our previous paper [38], contained a gas source system, operation part (monolith and inlet cone), data acquisition system, ventilation system, and an extra particle source system. The gas source system provided the gas needed in the experiment, and included the compressed air, pressure regulator, laminar air flow element, and the ejector dilutor. The data acquisition system included the pressure transmitters, pressure sensors, Prandtl tube, fast particle analyzer DMS 500, and the links to the laptop. The ventilation system included the hose, the fan and the filter inserted in the hose; the particle source system provides the particle aerosol in the system, connected with the gas source system by the ejector dilutor, including the compressed air, pressure regulator to control the flow, and the Topas Solid Aerosol Generator (SAG) 410 to produce the particle aerosol. To determine the influences of the cones on the particle distribution in the equilibrium state, the gas and particle source needed to be easy to control, the cones to be easily replaceable, the system needed to have no leakage during particle loading for safety and health considerations, and the Prandtl tube sensor had to be easy to move to different locations. The experimental equipment with focus points are listed below. Energies 2019, 12, 2701 5 of 18 Energies 2019, 12, x FOR PEER REVIEW 5 of 18

FigureFigure 1.1. Schematic ofof thethe experimentalexperimental setup.setup. 2.1.1. Gas Source 2.1.1. Gas Source In the laboratory, a flow restrictor and a laminar air flow element (Tsukasa Sokken, LFE-50B) were In the laboratory, a flow restrictor and a laminar air flow element (Tsukasa Sokken, LFE-50B) used to control the compressed and dried air. A differential pressure transmitter (Fuji, FKC-5) and one were used to control the compressed and dried air. A differential pressure transmitter (Fuji, FKC-5) pressure sensor (VEGA, VEGABAR 14) were connected to the laminar air flow element. and one pressure sensor (VEGA, VEGABAR 14) were connected to the laminar air flow element. The compressed air provided stable gas flows at different velocities. The pressure regulator The compressed air provided stable gas flows at different velocities. The pressure regulator controlled the volumetric flow into the monolith. An orifice with a diameter of 4.2 mm was inserted controlled the volumetric flow into the monolith. An orifice with a diameter of 4.2 mm was inserted between the laminar air flow element and the pressure regulator to reduce the flow passing through. between the laminar air flow element and the pressure regulator to reduce the flow passing through. The laminar air flow element provided uniform flow. Then, the air was blown into an injector dilutor The laminar air flow element provided uniform flow. Then, the air was blown into an injector dilutor to mix the particle aerosols from the particle source system. to mix the particle aerosols from the particle source system. 2.1.2. Particle Source 2.1.2. Particle Source The components of the particles (soot) were influenced by the types of engines, fuels, and operating conditions,The components and carbon blackof the (Printex-U, particles (soot) PU), whichwere hasinfluenced been widely by the used types as a commercialof engines, dieselfuels, andand gasolineoperating soot conditions, surrogate and due carbon to its black repeatability (Printex-U, [18, 41PU–),44 which]. In this has study, been widely the focus used was as ona commercial the cone’s influencediesel and on gasoline flow field soot with surrogate particle due deposition, to its repeatab the particleility [18, size’s 41–44]. influence In this study, on the the flow focus filed was is not on involved.the cone’s However, influence the on preciousflow field papers with aboutparticle the deposition, particle oxidation the particle all using size’s the influence standard on size the carbon flow black,filed is and not involved. the authors However, also will the proceed precious to papers thermal about study the in particle the future, oxidation for the all convenience using the standard of the continuity,size carbon repeatability,black, and the and authors the comparison also will proceed with previousto thermal papers, study in a the carbon future, black forthe the sameconvenience size as thoseof the incontinuity, the reference repeatability, papers was and chosen the comparison in this study. with The previous physical papers, properties a carbon of the black carbon the blacksame (suppliedsize as those by Orionin the Engineeredreference papers Carbons) was arechosen summarized in this study. in Table The1 .physical properties of the carbon black (supplied by Orion Engineered Carbons) are summarized in Table 1. Table 1. Physical properties of the carbon black. Table 1. Physical properties of the carbon black. Primary Particle Diameter. nm BET. m2/g Volatility. % Oil Absorption. mL/(100 g) Ash Content. % Primary particle diameter. nm BET. m2/g Volatility. % Oil absorption. ml/(100 g) Ash content. % 25 92 5 115 0.02 25 92 5 115 0.02

TheThe particleparticle aerosolaerosol waswas generatedgenerated inin thethe TopasTopas SolidSolid AerosolAerosol GeneratorGenerator (SAG)(SAG) 410,410, whichwhich alsoalso neededneeded compressedcompressed air.air. TheThe concentrationconcentration ofof thethe aerosolaerosol couldcould bebe adjustedadjusted throughthrough thethe feedingfeeding unitunit speedspeed andand thethe injectioninjection pressurepressure inin thethe TopasTopas SAG SAG 410. 410. TheThe particleparticle aerosolaerosol was mixed with the air from thethe laminarlaminar ﬂowflow element in the ejector dilutor, afterafter whichwhich a didifferentialﬀerential pressure transmitter (Yokogawa, EJA110E) was connected to measuremeasure thethe pressure drop between the ejector dilutor and ventilation hose, and another pressure sensor (VEGA,

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EnergiesEnergies 2019 2019, 12, 12, x, xFOR FOR PEER PEER REVIEW REVIEW 6 of6 18of 18 pressure drop between the ejector dilutor and ventilation hose, and another pressure sensor (VEGA, VEGABARVEGABARVEGABAR 14)14) 14) was was was used usedused to measuretoto measuremeasure the absolutethe absoluteabsolute pressure pressurepressure change. change. change. Then, Then, theThen, mixed the the mixed gasmixed passed gas gas passed through passed through the steel pipe and reached the cone and the monolith. thethrough steel pipethe steel and pipe reached and thereached cone andthe cone the monolith. and the monolith.

2.1.3.2.1.3.2.1.3. Inlet Inlet Cone Cone Two inlet cone shapes were employed: conventional and NURBS. The conventional cone was a TwoTwo inletinlet conecone shapesshapes werewere employed:employed: conventionalconventional andand NURBS.NURBS. TheThe conventionalconventional conecone waswas aa straight linear cone, and the NURBS cone was the streamlined cone. The shape of the NURBS was straightstraight linearlinear cone,cone, andand thethe NURBSNURBS conecone waswas thethe streamlinedstreamlined cone.cone. The shapeshape ofof thethe NURBSNURBS waswas drawn by choosing points along the flow lines from the convention cone simulations in drawing and drawndrawn byby choosingchoosing pointspoints alongalong thethe ﬂowflow lineslines fromfrom thethe conventionconvention conecone simulationssimulations inin drawingdrawing andand meshing software (Gambit 2.4.6) [38]. meshingmeshing softwaresoftware (Gambit(Gambit 2.4.6)2.4.6) [[38].38]. Both cones had d = 27.3 mm and D = 104 mm and an expansion angle, α, of 45°. To fit the monolith Both cones had d = 27.3 mm and D = 104 mm and an expansion angle, α, of 45°. To fit the monolith andBoth steel cones pipe, hadthe twod = 27.3cones mm were and manufacturedD = 104 mm andvia 3D an printing, expansion as angle,shown in, of Table 45◦. 2, To and ﬁt thethe monolithshape and steel pipe, the two cones were manufactured via 3D printing, as shown in Table 2, and the shape andof steelGPF is pipe, shown the in two Figure cones 2. wereThe cone manufactured shapes are shown via 3D in printing, Figure 3, as and shown Figure in Table4 shows2, and the theprinted shape ofofcones. GPFGPF isis The shownshown NURBS inin FigureFigure cone occupied2 2.. TheThe conecone a smaller shapesshapes volume. areare shownshown in in Figure Figure3 ,3, and and Figure Figure4 shows4 shows the the printed printed cones.cones. The NURBS cone occupied a smallersmaller volume.volume. Table 2. Physical properties of the cones. TableTable 2.2. PhysicalPhysical propertiesproperties ofof thethe cones.cones. Criteria Cone 1 Cone 2 Pipe diameterCriteriaCriteria d (mm) Cone Cone 27.3 1 1 Cone 27.3Cone 2 2 MonolithPipe diameterdiameter diameter d d (mm) D(mm) (mm) 27.3 104 27.3 104 27.3 27.3 MonolithMonolithCone diameterlengthdiameter L D(mm) D (mm) (mm) 38.35104 104 38.35 104 104 ConeCone lengthlength type L L (mm) (mm) Conventional 38.35 38.35 NURBS 38.35 38.35 MonolithConeCone type type type Conventional Conventional GPF NURBS GPFNURBS Monolith type GPF GPF Monolith type GPF GPF

Figure 2. Schematic of the gasoline particulate filter (GPF). Figure 2. Schematic of the gasoline particulate ﬁlter (GPF). Figure 2. Schematic of the gasoline particulate filter (GPF). 55 50 Conventional 55 45 NURBS 50 40 Conventional 45 35 NURBS 4030 3525 y. mm y. 3020 25 y. mm y. 15 2010 155 100 0 5 10 15 20 25 30 35 40 45 5 x. mm 0 Figure 3. The shapes of the0 conventional 5 10 cone 15 and 20 the nonuniform 25 30 rational 35 40 B-splines 45 (NURBSs) cone. x. mm

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Figure 3. The shapes of the conventional cone and the nonuniform rational B-splines (NURBSs) Energies 2019Figure, 12, 3. 2701 The shapes of the conventional cone and the nonuniform rational B-splines (NURBSs) 7 of 18 cone.

Figure 4. Printed cones (the right cone is the NURBS cone).cone). The shapes are depicted in Figure3 3.. 2.1.4. Monolith 2.1.4. Monolith The GPF monolith used in this work was made of cordierite without any catalytic coating from The GPF monolith used in this work was made of cordierite without any catalytic coating from Corning Inc. The properties are shown in Table3. Corning Inc. The properties are shown in Table 3. Table 3. Physical properties of the full-sized GPF monolith. Table 3. Physical properties of the full-sized GPF monolith. Channel Channel Size Filter Wall Thickness Diameter. mm Length (mm) Volume (dm3) Diameter. Length Volume ChannelDensity (cpsi) Channel(mm) size Filter(mm) wall 3 mm104 (mm) 140 (dm ) 1.19 density 300(cpsi) (mm) 1.1 thickness 0.1 (mm) 104 140 1.19 300 1.1 0.1 After the monolith, the mixed gas-particle aerosol traveled through a straight pipe and then a After the monolith, the mixed gas-particle aerosol traveled through a straight pipe and then a contraction (outlet) cone, as shown in Figure5. Before being emitted into ambient conditions, the mixed contraction (outlet) cone, as shown in Figure 5. Before being emitted into ambient conditions, the gas was filtered by an additional particulate filter in the exhaust pipe (ventilation hose) to ensure that mixed gas was filtered by an additional particulate filter in the exhaust pipe (ventilation hose) to there was no particle leakage. A differential pressure transmitter (Yokogawa, EJA110E) was connected ensure that there was no particle leakage. A differential pressure transmitter (Yokogawa, EJA110E) between the ejector dilutor and the monolith to measure the pressure drop. was connected between the ejector dilutor and the monolith to measure the pressure drop.

Figure 5.5. The cone and monolith. When the particle loading stopped, the contraction cone was dismounted. A Prandtl tube was used When the particle loading stopped, the contraction cone was dismounted. A Prandtl tube was to measure the velocity at the outlet surface of the monolith, and it was connected to a micromanometer used to measure the velocity at the outlet surface of the monolith, and it was connected to a (Furness Controls, FC014) to collect data. The distance between the outlet surface and the position micromanometer (Furness Controls, FC014) to collect data. The distance between the outlet surface where the data was collected was 40 mm to avoid disturbances from the sampling channels. The data and the position where the data was collected was 40 mm to avoid disturbances from the sampling were recorded by LabView (National Instruments). channels. The data were recorded by LabView (National Instruments). 2.2. Experimental Method 2.2. Experimental Method The experiment included two parts: particle loading and velocity measurement. The experiment included two parts: particle loading and velocity measurement. During particle loading, the entire experimental system was sealed to ensure no particle leakage, During particle loading, the entire experimental system was sealed to ensure no particle leakage, and pressure drop change data were collected. After a certain length of time, the particle injection and pressure drop change data were collected. After a certain length of time, the particle injection was stopped but the compressed air was kept on, the outlet cone was dismounted and the velocity was stopped but the compressed air was kept on, the outlet cone was dismounted and the velocity measurement was started. The weight of the monolith was used to determine the amount of particles measurement was started. The weight of the monolith was used to determine the amount of particles deposited inside the monolith. deposited inside the monolith. The center on the cross section was chosen as origin of the coordinate system. When the particle The center on the cross section was chosen as origin of the coordinate system. When the particle injection was stopped, the Prandtl tube will follow the sampling positions in the ﬁrst quadrant shown injection was stopped, the Prandtl tube will follow the sampling positions in the first quadrant shown in Figure6. Certain measurement points in the third quadrant were repeated to ensure that the ﬂow

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in Figure 6. Certain measurement points in the third quadrant were repeated to ensure that the flow waswas symmetricalsymmetrical andand thatthat thethe datadata werewere reliable.reliable. TheThe samplingsampling positionposition waswas setset atat 4040 mmmm fromfrom thethe monolithmonolith outletoutlet toto avoidavoid variationsvariations andand noisenoise [[38].38].

Figure 6. Prandtl sampling setup and sampling position schematic (right). Figure 6. Prandtl sampling setup and sampling position schematic (right). Three different velocities were studied to evaluate the effects of different flows, and 6 experimental Three different velocities were studied to evaluate the effects of different flows, and 6 cases were performed. The total weight of each case is shown in Table4. Due to the operation variability experimental cases were performed. The total weight of each case is shown in Table 4. Due to the of the SAG 410, the total weights were different. operation variability of the SAG 410, the total weights were different. Table 4. Experimental cases. Table 4. Experimental cases. Pressure Regulator Total Weight of the Cone # Case # 2 Cone # Case # Pressure regulator (lb/in(lb/in2)) Total weightDeposited of the deposited Particles (g) particles (g) Case 1 60 7.2 Cone 1 Case 1 60 7.2 ConeCase 1 3 40 5.1 Case 3 40 5.1 (Conventional)(Conventional) Case 5 Case 530 30 7.97.9 Case 2 Case 2 60 60 5.5 5.5 Cone 2 Cone 2 Case 4 Case 4 40 40 5.1 5.1 (NURBS) (NURBS) Case 6 Case 6 30 30 5.1 5.1

ToTo measuremeasure thethe particleparticle sizesize distributiondistribution duringduring thethe particleparticle injection,injection, aa CambustionCambustion DMSDMS 500500 MkIIMkII fastfast particleparticle analyzeranalyzer waswas usedused inin thisthis experimentalexperimental investigationinvestigation andand connectedconnected toto thethe samesame positionposition asas the the Yokogawa Yokogawa di ffdifferentialerential pressure pressure transmitter. transmitter. The DMSThe DMS 500 has 500 a built-inhas a built-in dilution dilution system withsystem two with diluters: two diluters: a primary a primary diluter anddiluter a secondary and a secondary diluter. diluter. The temperature The temperature in the primary in the primary dilutor dilutor was maintained at the maximum (150 °C) during sampling, and the secondary dilutor was was maintained at the maximum (150 ◦C) during sampling, and the secondary dilutor was operated at aoperated factor of at 1 a to factor maximize of 1 to signal maximize strength. signal To strength. obtain a To time obtain averaged a time value averaged of the value capture of the effi captureciency, samplingefficiency, was sampling done repeatedly was done beforerepeatedly and afterbefore the and GPF. after the GPF. TheThe capturecapture eefficiencyfficiency (CE)(CE) isis defineddefined as as [ 45[45]]

PSD −PSD CE =PSDbe f ore PSDa f ter (1) CE = PSD− (1) PSDbe f ore where PSD and PSD are the time-averaged particle size distributions before and after the whereGPF. PSDbe f ore and PSDa f ter are the time-averaged particle size distributions before and after the GPF. The measure of uncertainty (of CE) was calculated as The measure of uncertainty (of CE) was calculated as q 2 2 e =𝑒=𝑡tN ,%1,95% X𝑋var𝑣𝑎𝑟(Y)𝑌++𝑌Y var𝑣𝑎𝑟(X𝑋)++𝑣𝑎𝑟var(X𝑋) var∗𝑣𝑎𝑟(Y)𝑌 (2)(2) − ∗ where X = (PSD –PSD ) and Y = 1/PSD . where X = (PSDbe f ore – PSDa f ter) and Y = 1/PSDbe f ore.

3. Results and Discussion

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Energies 2019, 12, x FOR PEER REVIEW 9 of 18 3.1.3. Results Pressure and Drop Discussion 3.1. PressureThe pressure Drop drop was measured by the differential pressure transmitter. Taking case 1 as an 3.1. Pressure Drop example, the particle injections were split into 9 segments, hundreds of data were recorded and the The pressure drop was measured by the differential pressure transmitter. Taking case 1 as an collectedThe pressuredata are shown drop was in Figure measured 7 using by the of dia movingﬀerential average; pressure PM transmitter. loading is Takingthe total case weight 1 as anof example, the particle injections were split into 9 segments, hundreds of data were recorded and the depositedexample, theparticles particle in the injections monolith, were divided split into by the 9 segments, monolith hundredsvolume. The of dataaverage were pressure recorded drop and after the collected data are shown in Figure 7 using of a moving average; PM loading is the total weight of injectioncollected was data measured are shown each in Figuretime to7 compareusing of awith moving all cases average; shown PM in loadingFigure 8. is The the slope total weightchange ofof deposited particles in the monolith, divided by the monolith volume. The average pressure drop after pressuredeposited drop particles was inobtained the monolith, clearly divided after 1 byg/dm the3 monolithaccumulated, volume. which The means average the pressure filtration drop phases after injection was measured each time to compare with all cases shown in Figure 8. The slope change of changinginjection wasfrom measured ‘deep bed’ each to ‘soot time cake’. to compare with all cases shown in Figure8. The slope change pressure drop was obtained clearly after 1 g/dm3 accumulated, which means the filtration phases of pressure drop was obtained clearly after 1 g/dm3 accumulated, which means the ﬁltration phases changing from ‘deep bed’ to ‘soot cake’. changing from ‘deep bed’900 to ‘soot cake’. Case 1. coventional 900 800 Case 1. coventional 800 700 particle loading #1 700 600 particle loading #2 particle loading #1 particle loading #3 600 particle loading #2 500 particle loading #4 particle loading #3 particle loading #5 particle loading #4

Pressure drop. Pa 500 400 particle loading #6 particle loading #5 particle loading #7

Pressure drop. Pa 400 particle loading #6 300 particle loading #8 particle loading #7 particle loading #9 300 particle loading #8 200 01234567 particle loading #9 200 PM loading. g/dm3 01234567 PM loading. g/dm3 Figure 7. Pressure drop of case 1 during particle loading. PM: particulate matter. Figure 7. Pressure drop of case 1 during particle loading. PM: particulate matter. Figure 7. Pressure drop of case 1 during particle loading. PM: particulate matter. 900 Case 1. conventional Case 2. NURBS 900 800 CaseCase 3.1. conventionalconventional CaseCase 4.2. NURBSNURBS 700800 CaseCase 5.3. conventionalconventional CaseCase 6.4. NURBSNURBS 600700 Case 5. conventional Case 6. NURBS 500600

400500 Pressure drop. Pa 300400 Pressure drop. Pa 200300

100200 01234567 100 PM loading. g/dm3 01234567 Figure 8. Pressure dropPM loading. comparison g/dm of3 the 6 cases. Figure 8. Pressure drop comparison of the 6 cases. Table5 shows the pressure drop per unit of volumetric flow when there was no particle injection. Figure 8. Pressure drop comparison of the 6 cases. DuringTable measurements 5 shows the pressure acquisition, drop the per volumetric unit of volume flow wastric flow obtained when by there the integratingwas no particle the measuredinjection. During measurements acquisition, the volumetric flow was obtained by the integrating the measured velocityTable over 5 shows the cross the pressure section. drop Upon per comparing unit of volume case 1,tric case flow 2, when case 3, there and was case no 4, particle the NURBS injection. cone velocity over the cross section. Upon comparing case 1, case 2, case 3, and case 4, the NURBS cone Duringcan generate measurements a smaller acquisition, pressure drop the pervolumetric unit of volumetricflow was obtained flow. However, by the integrating case 6 shows the measured different can generate a smaller pressure drop per unit of volumetric flow. However, case 6 shows different velocityresults: theover NRUBS the cross cone section. has a largeUpon pressure comparing drop. case One 1, reasoncase 2, iscase that 3, the and cone case is 4, designed the NURBS at higher cone results: the NRUBS cone has a large pressure drop. One reason is that the cone is designed at higher velocitycan generate [38], anda smaller the other pressure reason drop is the per error unit when of volumetric calculating flow. the volumetricHowever, case flow. 6 shows different velocity [38], and the other reason is the error when calculating the volumetric flow. results: the NRUBS cone has a large pressure drop. One reason is that the cone is designed at higher velocity [38], and the other reason is the error when calculating the volumetric flow.

Energies 2019, 12, 2701 10 of 18

Energies 2019, 12, x FOR PEER REVIEW 10 of 18 Table 5. Comparison of the pressure drop per unit volumetric flow. Table 5. Comparison of the pressure drop per unit volumetric flow. Volumetric Space Velocity Pressure Drop per Unit Volumetric Flow Case # Volumetric flow Space velocity Pressure drop per unit volumetric flow Case # Flow (dm3/s) ( 104 h 1) (Pa s/dm3) (dm3/s) ×(×104 h−−1) (Pa·s/dm3·) 1 conventional1 conventional 16.88 16.88 5.11 5.11 28.20 28.20 2 NURBS 16.95 5.13 23.19 2 NURBS 16.95 5.13 23.19 3 conventional 11.97 3.63 24.48 4 NURBS3 conventional 13.97 11.97 4.23 3.63 24.48 20.32 5 conventional4 NURBS 9.29 13.97 3.25 4.23 20.32 22.11 6 NURBS 7.60 2.30 25.68 5 conventional 9.29 3.25 22.11 6 NURBS 7.60 2.30 25.68 Figure9 shows a comparison of the pressure drop per unit of volumetric flow during particle 3 injection.Figure Before 9 shows 1.5 g/dm a comparison, the NURBS of the cone pressure shows drop a smallper unit value of volumetric except in flow case during 6, and particle fluctuating valuesinjection. were observed Before 1.5 during g/dm3, thethe wholeNURBSinjection, cone shows which a small is alsovalue attributed except in tocase the 6, errorand fluctuating introduced by the integration.values were observed during the whole injection, which is also attributed to the error introduced by the integration. 3

60 Case 1. conventional 55 Case 2. NURBS Case 3. conventional 50 Case 4. NURBS Case 5. conventional 45 Case 6. NURBS 40

10 01234567 Pressure drop perunit volumetricflow.Pa·s/dm 3 PM loading. g/dm

FigureFigure 9. 9.Comparison Comparison ofof thethe pressure drop drop per per unit unit volumetric volumetric flow. ﬂow.

We canWe seecan thatsee that the the NURBS NURBS cone cone has has a a lowerlower pressure drop drop at atlow low PM PM loadings, loadings, but the but reduction the reduction 3 is diffiserent different for eachfor each case. case. For For the the comparison comparison ofof case 1 1 and and case case 2,2, the the reduction reduction ratio ratio at 0.92 at 0.92g/dm g3/ isdm is 10%,10%, while while the the value value is 17%is 17% with with a a clean clean monolith. monolith. Case Case 3 3and and case case 4 show 4 show the thesmallest smallest reduction reduction ratioratio during during the the particle particle loading, loading, between between 3%3% and 8%. 8%. The The pressure pressure drop drop shows shows a trend a trend of rapidly of rapidly increasingincreasing and and then then slowly slowly increasing, increasing, which which depictsdepicts the the flow flow changing changing from from deep deep bed bedfiltration filtration to to sootsoot cake cake filtration. filtration. After After 1.5 1.5 gg/dm/dm33 ofof particle particle injection, injection, the differences the differences between between case 1 and case case 1 and2 start case 2 3 startto disappear; disappear; after after 3 g/dm 3 g/dm, case3, case 3, case 3, case4, case 4, 5, case and 5,case and 6 showed case 6 showed roughly the roughly same pressure the same drop. pressure After 4 g/dm3, the pressure drops of the two comparison cases were roughly the same, with a drop. After 4 g/dm3, the pressure drops of the two comparison cases were roughly the same, with a difference less than 10%. difference less than 10%. 3.2. Velocity Profile 3.2. Velocity Profile Experimental velocities were measured after the surface of the monolith outlet after stop particle Experimentalinjection. The velocities velocities were were collected measured at intervals after the along surface the radial of the position monolith on the outlet outlet after surfaces stop particleof injection.the monolith. The velocities During were the velocity collected measurement, at intervals th alonge outlet the cone radial was position dismounted on the and outlet the particle surfaces of the monolith.injection was During stopped, the but velocity the compressed measurement, gas flow the was outlet maintained cone. was dismounted and the particle injection wasFigure stopped, 10 shows but the the velocity compressed changing gas with flow different was maintained.particle injections. The flow becomes more Figureuniform 10 when shows more the particles velocity are changing deposited with in the di channels,fferent particle that is because injections. most Theof the flow particles becomes were more uniformdeposited when in more the central particles channels, are deposited which blocked in the th channels,e channeled that and is push because more most flow ofpassing the particles through were deposited in the central channels, which blocked the channeled and push more flow passing through the border part and less flow passing through the center part. The average velocity means the average velocity on the outlet surface of the monolith calculated from the volumetric flow. Energies 2019, 12, x FOR PEER REVIEW 11 of 18

the border part and less flow passing through the center part. The average velocity means the average Energies 2019, 12, 2701 11 of 18 velocity on the outlet surface of the monolith calculated from the volumetric flow.

12 Case 1 no soot 0.1 g 10 0.4 g 0.6 g 8 1.1 g 1.6 g 2.4 g 6 3.5 g 5.1 g

Velocity. m/s Velocity. 4 7.2 g average velocity

0 0 5 10 15 20 25 30 35 40 45 50 Radial position. mm Figure 10. The velocity profile of case 1, conventional cone, the average velocity is 1.98 m/s. Figure 10. The velocity profile of case 1, conventional cone, the average velocity is 1.98 m/s. Figures 11–13 show the velocity comparisons between the two cones. Due to the nature of the Figures 11–13 show the velocity comparisons between the two cones. Due to the nature of the operationoperation of the of SAGthe SAG 410, 410, it was it was not not possible possible to to acquire acquire readings readings at at identical identical particleparticle mass loadings loadings into the monolith.into the monolith. Samples atSamples representative at representative intervals wereintervals instead were chosen instead to illustratechosen to theillustrate performance the of the diperformancefferent cases. of the But different still one cases. obvious But still conclusion one obvious can conclusion be obtained, can be theobtained, NURBS the coneNURBS had cone smaller centralhad velocity smaller evencentral with velocity loaded even particles, with loaded for example,particles, for the example, case 2 with the case 5.5 g2 with comparing 5.5 g comparing to case 1 with 5.1 g.to Moreover,case 1 with 5.1 the g.error Moreover, bar were the error all lessbar were than al 5l less %, than thebiggest 5 %, the biggest ones happened ones happened at radial at radial position aroundposition 30 mm, around which 30 mm, means which the means NURBS the improvement NURBS improvement was reliable. was reliable. TablesTables6–8 show6–8 show the velocitiesthe velocities in thein the outlet outlet central centra partl part of of each each case case withwith loadedloaded particles, particles, and and the the maximum velocities of the NURBS cones are all lower than the comparison cases. For the maximum velocities of the NURBS cones are all lower than the comparison cases. For the comparison comparison of case 1 and case 2, shown in Table 6, the reduction ratio of the velocity at the center at of case1.1 1g andis 11%, case while 2, shown the percentage in Table is6 ,10% the with reduction a clean ratio monolith, of the but velocity the reduction at the centerratio fluctuated; at 1.1 g is a 11%, whilereduction the percentage of 6% was is 10%obtained with at a clean2.4 g and monolith, a reduction but theof more reduction than 10% ratio was fluctuated; obtained aafter reduction 5 g. of 6% wasAdditionally, obtained for at 2.4case g 3 andand case a reduction 4, shown of in moreTable 7, than the 10%reduction was ratio obtained of the after center 5 velocity g. Additionally, profile, for casealso 3 and shown case in 4, shownFigure 11, in Tablechanged7, thefrom reduction 16% to 40%, ratio but of a the vibration center velocityerror was profile, found during also shown the in Figuremeasurement 11, changed of fromcase 4 16% without to 40%, particles, but a which vibration caused error the was value found to be duringabnormally the measurementlow. In case 5 and of case 4 withoutcase particles,6, shown in which Table caused 8, the reduction the value ratio to be is 13% abnormally to 19%. low. In case 5 and case 6, shown in Table8, the reduction ratio is 13% to 19%. Table 6. Central velocity comparison of case 1 (conventional cone) and case 2 (NURBS cone).

Table 6. CentralCase velocity 1 comparison of case 1 (conventional Case 2 cone) and case 2 (NURBS cone). Reduction Weight of loaded Central Weight of loaded Central Case 1 Case 2 ratio. % particles. g velocity. m/s particles. g velocity. m/s Reduction Weight of Loaded Central Velocity. Weight of Loaded Central Velocity. Ratio. % Particles.0 g 10.80m/s Particles.0 g 9.73m /s 10 1.1 6.73 1.1 5.99 11 0 10.80 0 9.73 10 2.4 5.39 2.4 5.05 6 1.1 6.73 1.1 5.99 11 5.1 4.45 5.5 3.70 17 2.4 5.39 2.4 5.05 6 5.1 4.45 5.5 3.70 17 Table 7. Central velocity comparison of case 3 (conventional cone) and case 4 (NURBS cone).

Case 3 Case 4 Table 7. Central velocity comparison of case 3 (conventional cone) and case 4 (NURBSReduction cone). Weight of loaded Central Weight of loaded Central ratio (%) particles (g) Case 3velocity (m/s) particles (g) Casevelocity 4 (m/s) Reduction Weight of Loaded Central Velocity Weight of Loaded Central Velocity 0 7.98 0 4.81 Ratio40 (%) Particles (g) (m/s) Particles (g) (m/s) 0 7.98 0 4.81 40 0.9 5.16 0.9 4.35 16 2.2 4.97 2.3 3.84 23 5.1 3.59 5.2 2.96 18 Energies 2019, 12, x FOR PEER REVIEW 12 of 18 Energies 2019, 12, x FOR PEER REVIEW 12 of 18

0.90.9 5.165.16 0.90.9 4.354.35 1616 2.22.2 4.974.97 2.32.3 3.843.84 2323 Energies 20195.15.1, 12 , 2701 3.593.59 5.25.2 2.962.96 1818 12 of 18

Table 8. Central velocity comparison of case 5 (conventional cone) and case 6 (NURBS cone). TableTable 8. 8. CentralCentral velocity velocity comparison comparison of of case case 5 5(conventional (conventional cone) cone) and and case case 66 (NURBS (NURBS cone). cone). Case 5 Case 6 CaseCase 5 5 Case Case 6 6 Reduction Weight of loaded Central Weight of loaded Central ReductionReduction WeightWeight of loaded of Loaded CentralCentral Velocity WeightWeight of ofloaded Loaded CentralCentral Velocity Rationrationration (%)(%) (%) particlesparticlesParticles (g) (g) (g) velocityvelocity(m (m/s) (m/s)/s) particlesparticlesParticles (g) (g) (g) velocityvelocity(m /(m/s) s)(m/s) 00 06.446.44 6.44 00 05.285.28 5.28 181818 1.11.1 1.14.414.41 4.41 11 13.583.58 3.58 191919 2.82.8 2.83.663.66 3.66 3.13.1 3.1 2.952.95 2.95 191919 5.7 2.97 5.1 2.58 13 5.75.7 2.972.97 5.15.1 2.582.58 1313

TheTheThe reduction reduction reduction ratio ratio ratio varies varies varies with with with the the the amount amount amount of of of load load loadededed particles, particles, particles, and and and there there there is is is no no no constant constant constant trend trend trend as as as thethethe inlet inlet inlet velocity velocity velocity increases. increases. increases. One One One reason reason reason is is is that that that the the the NURBS NURBS NURBS cone cone cone is is is designed designed designed based based based on on on one one one certain certain certain inlet inlet inlet velocity;velocity;velocity; a a adifferent different different inlet inlet inlet velocity velocity velocity will will will generate generate generate a a adifferent different different flow flow flow reduction reduction reduction inside inside inside the the the same same same cone, cone, cone, which which which needsneedsneeds to to to be be be further further further studied. studied. studied. As As As with with with the the the pressure pressure pressure drop, drop, drop, the the the velocity velocity velocity difference difference difference between between between the the the two two two cones cones cones decreasesdecreasesdecreases as as as more more more particles particles particles are are injected. injected.

12 12 12 12 Case 1 Case 2 Case 1 Case 2 10 10 10 10 no soot no soot no soot no soot 1.1 g 8 1.1 g 8 1.1 g 8 1.1 g 8 2.4 g 2.4 g 2.4 g 2.4 g 5.5 g 5.1 g 5.5 g 6 5.1 g 6 average velocity 6 average velocity 6 average velocity average velocity

Velocity. m/s Velocity. 4 m/s Velocity. 4 Velocity. m/s Velocity. 4 m/s Velocity. 4

2 2 2 2

FigureFigureFigure 11.11. 11. VelocityVelocityVelocity profilesprofiles proﬁles ofof of casecase case 11 1 (conventional(conventional (conventional cone)cone) cone) andand and casecase case 22 2 (NURBS(NURBS cone);cone); cone); thethe the averageaverage average velocitiesvelocitiesvelocities are are are 1.98 1.98 1.98 m/s m/s m/s and and 1.99 1.99 m/s, m/s, m/s, respectively. respectively.

10 10 10 10 Case 3 Case 4 Case 3 Case 4 8 8 8 no soot 8 no soot no soot 0.9 g no soot 0.9 g 0.9 g 2.2 g 0.9 g 6 2.2 g 6 2.2 g 6 5.1 g 6 2.2 g 5.1 g 5.1 g average velocity 5.1 g average velocity average velocity average velocity 4 4 4 4 Velocity. m/s Velocity. m/s Velocity. m/s Velocity. m/s

2 2 2 2

0 0 0 0 0 5 10 15 20 25 30 35 40 45 50 0 5 10 15 20 25 30 35 40 45 50 0 5 10 15 20 25 30 35 40 45 50 0 5 10 15 20 25 30 35 40 45 50 Radial position. mm Radial position. mm Radial position. mm Radial position. mm Figure 12. Velocity proﬁles of case 3 (conventional cone) and case 4 (NURBS cone); the average FigureFigure 12.12. VelocityVelocity profilesprofiles ofof casecase 33 (conventional(conventional cone)cone) andand casecase 44 (NURBS(NURBS cone);cone); thethe averageaverage velocities are 1.41 m/s and 1.64 m/s, respectively. velocitiesvelocities are are 1.41 1.41 m/s m/s and and 1.64 1.64 m/s, m/s, respectively. respectively.

Energies 2019, 12, x FOR PEER REVIEW 13 of 18

Energies8 2019, 12, 2701 8 13 of 18 Case 5 Case 6 Energies7 2019, 12, x FOR PEER REVIEW 7 13 of 18

8 8 6 no soot 6 Case 5 Case 6 no soot 1.1 g 75 75 1.0 g 2.8 g 3.1 g 5.7 g 5.1 g 64 no soot 64 average velocity noaverage soot velocity 1.1 g 1.0 g 53 53 Velocity. m/s 2.8 g m/s Velocity. 3.1 g 5.7 g 42 42 5.1 g average velocity average velocity 31 31 Velocity. m/s m/s Velocity.

20 20 0 5 10 15 20 25 30 35 40 45 50 0 5 10 15 20 25 30 35 40 45 50 1 1 Radial position. mm Radial position. mm 0 0 Figure0 5 13. 10 Velocity 15 20 profiles 25 30of case 35 5 40 (conventional 45 50 cone)0 and 5 case 10 156 (NURBS 20 25 cone); 30 the 35 average 40 45 50 velocities are 1.09Radial m/s andposition. 0.89 mmm/s, respectively. Radial position. mm

3.3. FlowFigureFigure Uniformity 13. 13. VelocityVelocity profiles proﬁles of of case case 5 5(conventional (conventional cone) cone) and and case case 6 6 (NURBS (NURBS cone); cone); the the average average velocitiesvelocities are are 1.09 1.09 m/s m/s and and 0.89 0.89 m/s, m/s, respectively. respectively. The flow uniformity index is used to reveal the cone’s influence on the flow distributions after 3.3. Flow Uniformity 3.3.particle Flow injectionUniformity [34].

The flow uniformity index is used to reveal the cone’s influence2 on the flow distributions after The flow uniformity index is used to reveal then cone’s()− influence on the flow distributions after particle injection [34]. 1 vvimean particle injection [34]. γ =−1 q (3) n 2 2nvi (v meanvmean) 1 X i 2 γ = 1 n ()−− (3) 1 vvimean γ =−− 2n vmean (3) Here, 𝛾 is between 0 and 1, vmean is the1 mean velocity,i and n is the total number of measured points. 2nvi mean Here,Figureγ is between 14 shows 0 and that 1, thevmean NURBSis the meancone improves velocity, and the nflowis the distribution total number well of for measured most samples. points. However,Figure compared 14 shows with that case the NURBS5, the NURBS cone improves cone did the not flow show distribution better results well before for most 1 g/dm samples.3 of Here, 𝛾 is between 0 and 1, vmean is the mean velocity, and n is the total number of measured3 points. particleHowever, deposition compared in with case case 6. 5,The the reason NURBS has cone been did discussed not show betterin previous results beforeresearch: 1 g /dmNURBSof particle cones Figure 14 shows that the NURBS cone improves the flow distribution well for most samples. designeddeposition for in a case certain 6. The velocity reason do has not been always discussed exhibit in better previous performance research: if NURBS switched cones to another designed inlet for However, compared with case 5, the NURBS cone did not show better results before 1 g/dm3 of velocitya certain [38]. velocity In addition, do not always we can exhibit see the better trend performance that the uniformity if switched index to anotherbecomes inlet similar velocity as more [38]. particle deposition in case 6. The reason has been discussed in previous research: NURBS cones particlesIn addition, are wedeposited can see inside the trend the thatchannel, the uniformity but for case index 3 and becomes case 4, similar they asneed more more particles particles are designed for a certain velocity do not always exhibit better performance if switched to another inlet depositeddeposited inside inside the the monolith channel, butto have for casea similar 3 and value case 4,after they 4.2 need g/dm more3 of particle particles deposition. deposited These inside are the velocity [38]. In addition, we can see the trend that3 the uniformity index becomes similar as more furthermonolith proof to have that aNURBS similar cone value has after the 4.2 potential g/dm ofimprovement particle deposition. even with These particle are furtherdeposition proof in thatthe particles are deposited inside the channel, but for case 3 and case 4, they need more particles monolith.NURBS cone has the potential improvement even with particle deposition in the monolith. deposited inside the monolith to have a similar value after 4.2 g/dm3 of particle deposition. These are further1.0 proof that NURBS cone has the potential improvement1.0 even with particle deposition in the Case 1. conventional Case 3. conventional monolith.0.9 0.9 Case 2. NURBS Case 4. NURBS 0.8 0.8 1.0 1.0 0.7 0.7 Case 3. conventional 0.9 Case 1. conventional 0.9 0.6 Case 2. NURBS 0.6 Case 4. NURBS 0.8 0.8 0.5 0.5 0.7 0.7 0.4 0.4 0.6 0.6 0.3 0.3 0.5 0.5 Flow uniformity index 0.2 indexFlow uniformity 0.2 0.4 0.4 0.1 0.1 0.3 0.3 0.0 0.0 Flow uniformity index 0.2 indexFlow uniformity 0.2 01234567 01234567 0.1 3 0.1 PM loading. g/dm PM loading. g/dm3 0.0 0.0

01234567Figure 14. Cont01234567. 3 3 PM loading. g/dm PM loading. g/dm

Energies 2019, 12, x FOR PEER REVIEW 14 of 18 Energies 2019, 12, 2701 14 of 18 Energies 2019, 12, x FOR PEER REVIEW 14 of 18 1.0 Case 5. conventional 0.9 1.0 Case 6. NURBS 0.8 Case 5. conventional 0.9 Case 6. NURBS 0.7 0.8 0.6 0.7 0.5 0.6 0.4 0.5 0.3 0.4

Flow uniformity index 0.2 0.3 0.1

Flow uniformity index 0.2 0.0 0.1 01234567 0.0 PM loading. g/dm3 01234567 PM loading. g/dm3 Figure 14. Comparison of flow uniformity index. Figure 14. Comparison of flow uniformity index. Figure 14. Comparison of flow uniformity index. 3.4. Particle Number and Size Distribution 3.4. Particle Number and Size Distribution 3.4. ParticleThe particle Number number and Size size Distribution distribution and capture efficiency were measured by the DMS 500. The particle number size distribution and capture efficiency were measured by the DMS 500. Figure 15 shows the particle number size distribution experimentally obtained for case 1, particle TheFigure particle 15 shows number the particlesize distribution number size and distribution capture efficiency experimentally were measured obtained by for the case DMS 1, particle500. loading #4 before and after the GPF. This case was selected to study the particle number size loadingFigure #4 before 15 shows and the after particle the GPF. number This case size was distributi selectedon to experimentally study the particle obtained number for size case distribution 1, particle distribution because it showed the maximum pressure drop among all the cases studied in loadingbecause it#4 showed before theand maximum after the pressureGPF. This drop case among was allselected the cases to studiedstudy the in investigation particle number (Figure size8). investigation (Figure 8). The particle number size distribution measurement was repeated four times. distributionThe particle numberbecause sizeit showed distribution the maximum measurement pressure was repeated drop among four times. all the The cases large studied difference in The large difference between the particle number size distribution before and after the filter shows a investigationbetween the particle(Figure 8). number The particle size distribution number size before distribution and after measurement the filter shows was repeated a higher four capturing times. higher capturing efficiency (CE) for the filter. Theefficiency large difference (CE) for the between filter. the particle number size distribution before and after the filter shows a higher capturing efficiency (CE) for the filter.

Figure 15. Particle number size distribution for case 1, loading #4. b—before; a—after; R—round. Figure 15. Particle number size distribution for case 1, loading #4. b—before; a—after; R—round. Figure 16 shows the size resolved CE for case 1, loading 4. CE ﬁrst increased within the size range Figure 15. Particle number size distribution for case 1, loading #4. b—before; a—after; R—round. from 10Figure nm to 16 50 shows nm, was the size nearly resolved constant CE from for case 50 to 1, 110loading nm, and4. CE then first decreased increased from within 110 the to size 1000 range nm. Thefrom errorFigure 10 barnm 16 for toshows 50 CE nm, withthe was size a diameter nearlyresolved constant less CE than for casefrom 50 nm 1, 50 loading was to 110 found 4.nm, CE to and first be relativelythen increased decreased high, within and from the the size110 error torange 1000 bar fromfornm. CE 10The with nm error particlesto 50 bar nm, for greater was CE nearlywith than a 50constantdiameter nm was from less very than50 low. to 50110 nm nm, was and found then todecreased be relatively from high, 110 to and 1000 the nm.error The bar error for CEbar with for CE particles with a greater diameter than less 50 thannm was 50 nm very was low. found to be relatively high, and the error bar for CE with particles greater than 50 nm was very low.

EnergiesEnergies 20192019,, 1212,, x 2701 FOR PEER REVIEW 1515 of of 18 18

Figure 16. Capturing efficiency for case 1, loading #4. Figure 16. Capturing efficiency for case 1, loading #4. 3.5. Future Work 3.5. FutureThe experiments Work in this paper were performed at room temperature; because the cones were printedThe inexperiments plastic, the in eff thisect ofpaper the NURBSwere performed cone on at the room flow temperature; field under highbecause temperature the cones would were printedneed to in be plastic, confirmed the effect with of more the NURBS simulations cone inon thethe future.flow field During under regeneration,high temperature heat would dissipation, need toflow be nonuniformityconfirmed with and more pressure simulations drop changesin the futu alsore. need During to be regeneration, studied under heat the dissipation, influence offlow the nonuniformitycone. A detailed and understanding pressure drop of changes the cone’s also influence need to be during studied particle under injection the influence can ensure of the thecone. high A detailedperformance understanding of future powertrains. of the cone’s influence during particle injection can ensure the high performance of future powertrains. 4. Conclusions 4. ConclusionsIn this paper, the influence of the cone on the flow and particle distribution was established via experiments.In this paper, The NURBSthe influence cone exhibitedof the cone good on the performance flow and particle with loaded distribu particles.tion was established via experiments.The cone’s The influence NURBS wascone established exhibited good for di performancefferent inlet velocities with loaded and particles. particle injections. The cone can influenceThe cone’s the influence flow field, was andestablished further for influence different the inlet particle velocities distribution and particle inside injections. the monolith The cone and canpressure influence drop. the The flow cone field, optimization and further results influence in improvements the particle distribution in unfavorable inside situations the monolith throughout and pressureall of the drop. particle The loading cone optimization phases, and results the NURBS in improvements cone shows in good unfavorable improvements situations in certain throughout cases, allbut of how the muchparticle the loading cone can phases, be developed and the NURBS depends cone on theshows shape good design, improvements which should in certain consider cases, the butinlet how velocity much and the injection cone can quantity be developed of particles. depends on the shape design, which should consider the inlet velocityThe slope and changes injection in quantity the pressure of particles. drop during particle injection illustrate how the filtration phasesThe change slope fromchanges deep in bed the to pressure soot cake, drop the during pressure particle drop reduction injection ofillustrate NURBS how cone comparingthe filtration to phasesconventional change cone from can deep be upbed to to 10% soot with cake, particle the pressure deposition. drop Thereduction maximum of NURBS velocities cone in comparing the central topart conventional of the monolith cone outletcan be in up all to cases 10% with decreased partic notablyle deposition. when usingThe maximum NURBS cone, velocities most in cases the hadcentral the partreduction of the betweenmonolith 6% outlet to 23%; in all The cases highest decreased reduction notably happened when whenusing noNURBS particles cone, between most cases the case had 3 theand reduction case 4, which between has the 6% similar to 23%; inlet The velocity highest asre theduction cone happened design velocity. when no particles between the case 3The and influence case 4, which of the has cone the on similar the flow inlet field velocity after the as monolith the cone decreasesdesign velocity. with the increased number of depositedThe influence particles, of the but cone the compared on the flow NURBS field cone after cases the demonstratemonolith decreases better flow with uniformity the increased after numberthe deep of bed deposited filtration particles, phase. The but significantly the compar diedfference NURBS of flow cone uniformity cases demonstrate was obtained better between flow 3 uniformitythe case 3 and after case the 4, deep even bed after filtration 4.2 g/dm phase.deposition, The significantly the NURBS difference cone demonstrated of flow uniformity more than was 21% obtainedimprovement. between Therefore, the case the NURBS3 and conecase may4, even exhibit after superior 4.2 g/dm flow3 uniformity deposition, performance the NURBS long cone into demonstratedthe particle loading more than phase, 21% implying improvement. that the Theref effect remainsore, the NURBS even after cone several may loading–regenerationexhibit superior flow uniformitycycles. But performance same as the resultslong into of velocitythe particle reduction, loading the phase, best implying performance that isthe not effect always remains happened even afteras we several want under loading–regeneration different cases, the cycles. best optimizationBut same as under the results different of casesvelocity can reduction, only been obtainedthe best performancewhen complying is not with always specific happened NURBS as designed we want with under di ffdifferenterent inlet cases, velocities. the best optimization under

Energies 2019, 12, 2701 16 of 18

However, the particle distribution and deposition inside the monolith caused by the cone optimization should be further studied, which is important for the heat distribution during regeneration. The flow nonuniformity, coming with the feedback of particle loading, must be accounted for in subgrid scale models for CFD simulations of particle deposition in GPFs. In summary, the connection cone has an important role in affecting the flow field. The NURBS cone can reduce the installation space and improve the flow distribution; thus, it is a suitable choice for cone design. The NURBS can also be applied to other aftertreatment systems.

Author Contributions: Conceptualization, M.M. and X.L.; methodology, M.M. and J.S.; validation, M.M. and J.S.; formal analysis, M.M.; investigation, M.M. and X.L.; resources, J.S.; writing—original draft preparation, M.M.; writing—review and editing, J.S., N.S., and H.S.; supervision, J.S. and H.S.; project administration, J.S.; funding acquisition, J.S. Funding: This research was funded by Chalmers University of Technology, 2018. This work was supported in part by a scholarship from the China Scholarship Council (CSC) under Grant File No. 201706020106. This research was funded by The National Key Research and Development Program of China, grant number: 2017YFB0103402 and 2018YFB0104103. Acknowledgments: All technical staff at the division of Combustion and Propulsion Systems is deeply acknowledged, including Patrik Wåhlin for printing the cones and Timothy Benham, Anders Mattsson, Robert Buadu and Alf-Hugo Magnusson for building the test bench. Conflicts of Interest: The authors declare no conflict of interest.

References

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