Zenamarkos B Sendekie

Patrice Bacchin

Colloidal Jamming Dynamics in Microchannel Bottlenecks

The purpose of this work is to examine the interplay between hydrodynamic conditions and physicochemical interactions from filtration experiments of microparticles. Experiments are performed in microfluidic filters with real-time visualization at pore scale. Both flow rate and pressure are measured with time to analyze the dynamics of pore clogging and permeability. Flux stepping experiments are performed at different physicochemical conditions to determine the different clogging conditions. The results allow distinguishing different clogging behaviors according to filtration conditions which are discussed by considering particle-particle and particle-wall colloidal interactions whose main characteristics are an important repulsive barrier at 0.01 mM, a significant secondary minimum at 10 mM, and low repulsive barrier at 100 mM. Clogging delay at moderate ionic strength and deposit fragility and associated sweeping out of aggregates of particles at high ionic strength are discussed from the deposit structure, specific resistance, and deposit relaxation analyses. It has also been observed that an opening angle at microchannel entrance causes rapid clogging, this effect being more pronounced when the repulsion is partially screened. Three different scenarios are discussed by analogy to crowd swarming: panic scenario (0.01 mM) where repulsion between particles induce pushing effects leading to the creation of robust arches at pore entrances; herding instinct scenario (10 mM) where the attraction (in secondary minima) between particles enhances the transport in pores and delays clogging; and sacrifice scenario (100 mM) where the capture efficiency is high but the aggregate formed at the wall is fragile.

INTRODUCTION

Transport and deposition of microparticles in porous media is of primary importance in many fields of science and process engineering. In such systems, pore clogging phenomena can have dramatic consequences. A lot of studies have then been performed for better understanding of the cause and the consequence of clogging for different discrete objects in different application fields. These studies cover systems of very different nature and spectrum such as colloidal dispersions for transport in soil, in blood vessels, in filtration processes, or in continuous flow reactors; granular materials for flow interruptions in silos; person or animal for panic disorder; vehicles for traffic jam, etc. Clogging can be understood as a transition between different flow regimes [START_REF] Zuriguel | Clogging transition of many-particle systems flowing through bottlenecks[END_REF] and then linked to jamming phenomena, [START_REF] Cates | Force Chains, and Fragile Matter[END_REF] the jamming being defined as the conversion of a liquid system into a solid by imposed stress. [START_REF] Haw | Two-Fluid Behaviour, and "Self-Filtration" in Concentrated Particulate Suspensions[END_REF] Different parameters can induce the unclogged/clogged states: the driving force (flow velocity), the constriction geometry (particle/constriction size ratio), and the background noise (Brownian motion, external excitation, etc.). [START_REF] Zuriguel | Clogging transition of many-particle systems flowing through bottlenecks[END_REF] The liquid/solid transition appears when a unidirectional load is applied on a concentrated dispersion of particles, 2 leading to the formation of force chains between particles forming a solid clog at the constriction level. When formed, the clog is considered as a "fragile matter". [START_REF] Cates | Force Chains, and Fragile Matter[END_REF][START_REF] Haw | Two-Fluid Behaviour, and "Self-Filtration" in Concentrated Particulate Suspensions[END_REF] The fragility of the clog depends on how the system came to be jammed ("construction history"). [START_REF] Cates | Force Chains, and Fragile Matter[END_REF] These authors also defined the concept of "bulk fragility" or "boundary fragility" to explain the way clogs can be liquefied under stresses. For example, if a force different to the unidirectional load leading to the clog formation is imposed at the base of the clog (i.e., the bond between the clog and the wall), it is certain that boundary fragility will occur: the boundary bonds will be broken, leading to clog fragility. In general, clogging occurs when an important number of discrete units pass through a constriction, i.e., competition of too many units for little space. The development of clogs obstructing the bottleneck can lead to intermittent flow [START_REF] Helbing | Analytical approach to continuous and intermittent bottleneck flows[END_REF] and to a partial or a complete blocking of the flow. This dynamic arrest or jamming, which is linked to intriguing rheological properties, occurs in a wide range of applications such as ceramic production, food processing, waste management, pharmaceuticals, cosmetics, medicine, etc.

Clogging has also been linked to a shear-induced gelation. [START_REF] Xie | Criticality for shear-induced gelation of charge-stabilized colloids[END_REF] The shear stress, when large enough, leads the particles to overcome the interaction barrier forming viscous non-Newtonian clusters that can occupy the available space. The interconnection of these clusters leads to the formation of solidlike gel with specific structure. This gelation process initiates from fractal clusters formed through diffusion-limited aggregation and reaction-limited aggregation mechanisms. The clogging is then described as a percolation transition which is also observed for granular materials: [START_REF] Zuriguel | Jamming during the discharge of grains from a silo described as a percolating transition[END_REF] the interconnection of clusters when they become crowded leads to clogging or jamming. The solidlike transition of stabilized colloidal dispersion has been observed and discussed with a gelation approach when imposing an intense shear by forcing it to pass through microchannels. [START_REF] Wu | High Shear-Induced Gelation of Charge-Stabilized Colloids in a Microchannel without Adding Electrolytes[END_REF] The key events involved in such gelation processes are the aggregation and the breakage of clusters. A breakage number (a dimensionless number that represents the ratio between the shearing energy acting on particles to the energy required to breakup an interparticle bond) has been introduced to define hydrodynamic conditions within microchannels where the shear rate is large enough to lead to clusters breakage. This regime has been previously reported as being linked to a critical Pećlet number that account for the maximum potential barrier and the type of flow. [START_REF] Zaccone | Theory of activated-rate processes under shear with application to shear-induced aggregation of colloids[END_REF] Such critical Pećlet numbers are very close to the one defined for the aggregation occurring on a membrane: [START_REF] Bacchin | Model for colloidal fouling of membranes[END_REF] below the critical value, the aggregation can only take place by Brownian diffusion and then is very slow because of the repulsive potential barrier whereas above the critical value the hydrodynamic force can overcome the potential barrier and then conduct to the aggregation (but also possibly to the aggregate breakage). Finally, the gelation approach of clogging using the Smoluchoski equation framework [START_REF] Xie | Criticality for shear-induced gelation of charge-stabilized colloids[END_REF] shows a lot of similarities with the mechanical approach of jamming based on force chains, 2 and both approaches underline the "soft aspect" of the clogs and the control of the clogging dynamics by their fragility.

With recent new advancements in the microfabrication technology enabling direct visualization of filtration processes, clogging has been experimentally investigated at the pore scale. [START_REF] Wyss | Mechanism for clogging of microchannels[END_REF] Clogging of a microsystem can occur through successive particle deposition, particle size exclusion, or a combination of these effects depending on the particle size distribution. [START_REF] Mustin | Deposition of particles from polydisperse suspensions in microfluidic systems[END_REF] Numerical studies revealed that particle deposition during filtration of colloidal suspensions is controlled by hydrodynamic conditions, fluid properties (ionic strength), and particle and substrate properties. [START_REF] Gassara | Modelling the Effect of Particle Size in Microfiltration[END_REF][START_REF] Kim | Particle-particle interactions during normal flow filtration: Model simulations[END_REF][START_REF] Agbangla | Collective dynamics of flowing colloids during pore clogging[END_REF][START_REF] Henry | Towards a description of particulate fouling: from single particle deposition to clogging[END_REF] However, very few of these simulations accounted for the possibility of particle reentrainment that seems to be an important event from the experimental studies.

The purpose of this work is to examine the interplay between hydrodynamics and colloidal interactions from clogging analysis during microfluidics filtration experiments. The coupling of colloidal interactions and hydrodynamics makes the analysis of the clogging phenomena complex. There have been studies on separate effects of colloidal interaction and hydrodynamics on clogging. However, for colloidal systems under flow, the interplay between the two factors has a very significant role in the dynamics of the aggregation of particles and the breakage of aggregates controlling the clogging establishment. In this work, we analyze the clogging mechanisms of microchannels using dispersion of charge-stabilized polystyrene latex particles. We vary the ionic strength of the suspension and the flow rate in order to explore the effect of the coupling between the colloidal interactions and the hydrodynamics on the filtration dynamics, the critical flux, the deposit morphology, and clog fragility. Dispersions with three well different interaction profiles are filtered through microchannels bottlenecks, and the flow rate is varied by about 2 orders of magnitude. Additionally, and in order to further analyze the fragility of the clogs, the complexity of the geometry will be investigated by using two bottleneck shapes (squared and tilted angle microchannel entrances).

EXPERIMENTAL METHODS

The experiments in this work have been performed with microfluidic devices fabricated with OSTEmerX 322 crystal clear polymer by soft lithography and replica molding techniques [START_REF] Whitesides | The origins and the future of microfluidics[END_REF] (see the Supporting Information section 1 for the description of the fabrication process). The microfluidic device consists of a main feeding channel (1.7 mm wide) followed by a filtering part constituted of an array of 29 parallel, narrow channels with widths of 10 μm (see Figure S1). The height of the microchannels and the main channel is 50 μm. The width of the pillars between the channels is 50 μm. Such devices allow realizing separation of microparticles with real-time visualization at pore scale through an optical microscope. The filtration experiments are performed in dead-end mode at both constant pressure and constant flow rate by using Microfluidic Flow Control System (MFCS) and Flowell (from Fluigent) (see Supporting Information section 2 for the description of the experimental setup and the filtration process). During experiments, the flow rate and the pressure are measured with time to analyze the dynamics of the pore clogging and the permeability.

The suspensions used in this experimental work consisted of monodisperse (5 μm in diameter) latex polystyrene microspheres (Invitrogen) dispersed in water. The latex particles are negatively charged with functional sulfate groups on the surface: the zeta potential, measured with a Malvern Zetasizer, is -57 ± 5 mV at pH 7. [START_REF] Bacchin | Colloidal surface interactions and membrane fouling: investigations at pore scale[END_REF] The latex suspensions used in the filtration experiments are obtained by diluting the stock suspension in KCl solution until a volume fraction of 10 -5 (1.5 × 10 5 particles/mL) is reached. The KCl concentration is varied in the range from 0.01 to 100 mM which allowed modifying the suspension stability by changing the magnitude of the repulsive electrostatic interaction between particles and between particles and the walls of the channels. These concentrations in salt are inferior to the critical concentration for coagulation (CCC) which is observed by sedimentation tests to be above 200 mM. Prior to experiments, the latex suspensions are exposed to ultrasonic waves for 3 min in order to break down aggregates of particles, if any.

During the experiments, filtration conditions are kept in laminar flow regime, and the maximum Reynolds number is 2.39 calculated at the maximum flow velocity (0.0835 m/s) using the channel hydraulic diameter as the characteristic length (the maximum shear rate at the wall being 66 800 s -1 ). The range of filtration velocities used in our experiments are in the range of those used in membrane microfiltration (up to 0.015 m/s, based on data for a MF-Millipore membrane with 8 μm pore size, operated at 100 mbar). The inertial effect and the Brownian motion are negligible due to the low Stokes number (10 -4 ) and the high Peclet number (10 5 ), respectively.

Three main classes of experiments have been performed in this work: flow stepping, constant pressure, and constant flow rate experiments. The flow stepping experiments are performed by running constant flow rate filtration starting from 5 μL/min and increasing the flow rate by 5 every 10 min until we reach 70 μL/min. The slope for each constant flow rate experiment (i.e., for 5, 10, 15, ..., 70 μL/min) is determined from the flow stepping experiments to evaluate the fouling rate (see Supporting Information section 3, Figure S3). Based on the results from the flow stepping experiments, three different constant flow rate experiments are performed at 15, 30, and 70 μL/min in order to study the effect of the hydrodynamics on the initial stages of the microchannel clogging and the deposit morphology. Constant pressure experiments are performed at 200 mbar. This pressure drop is selected in order to compare the results with constant flow rate experiments since the flow rate with the clean system at this pressure drop is 70 μL/min. All these experiments are performed with low (0.01 mM), moderate (10 mM), and high (100 mM) ionic strength suspensions with at least three times repetition for each run.

RESULTS

Filtration experiments with direct observation have been performed with different ionic strength suspensions using a microseparator. The following sections present the results for particle capture and deposit formation dynamics at low (0.01 mM), moderate (10 mM), and high (100 mM) ionic strengths. In section 3.1, flux stepping experiments will be analyzed in order to determine critical flux values for the clog formation. Section 3.2 will analyze the results obtained in constant flux experiments performed with filtration flux above or below the critical conditions in order to discuss the interplay between hydrodynamic and physicochemical conditions. Section 3.3 will present the importance of the microchannel entrance geometry on the clogging formation. Finally, section 3.4 analyzes the influence of the operating conditions on the deposit structure through the determination of the hydraulic resistances and specific deposit resistances.

3.1. Critical Flux Analysis. Flux stepping experiments are performed at different physicochemical conditions under the CCC of the particles to determine the different clogging conditions (Figure 1a). Identifying the clogging conditions is made possible through the monitoring of the pressure drop from the inlet to the outlet with respect to time [START_REF] Hartman | Managing Solids in Microreactors for the Upstream Continuous Processing of Fine Chemicals[END_REF] and from the microscopic observations. The results in Figure 1a show that particle capture occurs at low flow rates for high ionic strength (100 mM) suspensions. The high repulsion barrier between the particles and the microchannel walls causes a delay in particle capture at low ionic strength (0.01 mM). A huge delay in particle deposition was observed at moderate ionic strength (10 mM). With the microscopic observations, this delay can be linked to temporary deposition and sliding of particles over the walls and finally get swept out. This specific behavior will be discussed in section 4.1.3 by considering the significance of the secondary energy minimum and its consequences on the way particles are captured on collectors. [START_REF] Kuznar | Direct microscopic observation of particle deposition in porous media: Role of the secondary energy minimum[END_REF] These results are further substantiated by calculating the fouling rate (see Supporting Information Figure S3) for each constant flow rate filtration run. Figure 1b presents the fouling rate as a function of the permeate flow rate. Such a plot allows distinguishing critical flux behavior with negligible fouling below the critical flux value and a significant fouling rate above. [START_REF] Bacchin | Colloidal surface interactions and membrane fouling: investigations at pore scale[END_REF] The increase in the fouling rate is associated with the formation of dense deposit (inset images in Figure 1b). Figure 1b shows that the fouling rate increases rapidly at low flow rate for the high ionic strength suspensions, and it can be noted that there is a critical flux between 5 and 10 μL/min. There is a gentle increase in slope for the low ionic strength suspensions at a relatively higher flow rate, and the critical flux seems to be between 15 and 20 μL/min. These results are in agreement with theoretical studies, [START_REF] Bacchin | Colloidal surface interactions and membrane fouling: investigations at pore scale[END_REF] demonstrating that the critical flux increases when the colloidal repulsions are more important. For moderate ionic strength, the fouling rate hardly increases until we reach 60 μL/min, after which an abrupt increase is observed.

These observations help to realize that surface interactions play an important role in particle capture and hence the jamming of porous media. When the particle-particle and particle-wall interactions are strongly screened out (e.g., in the case of 100 mM suspension), the drag force overcomes the repulsive DLVO forces at low flow rate and particles are captured easily leading to clogging. At high repulsive forces, particle capture is delayed, and the clogging is controlled by many-body interactions. The dynamics of particle capture is very much progressive for moderate ionic strength due to the significant role of secondary energy minimum: this specific behavior will be discussed in section 4.1.3. Figure 1a also shows that at high flow rates important permeability fluctuations are observed. Thanks to microscopic observations, these variations are related to the collapse of jammed particles network that are expelled through the microchannels when the force chains formed by the particles are overcome by the flow.

3.2. Constant Flow Rate Filtrations. Based on the results from the flow stepping experiments, constant flow rate experiments are performed at three flow rates (15, 30, and 70 μL/min) with low (Figure 2a), moderate (Figure 2b), and high (Figure 2c) ionic strengths to study the effect of hydrodynamics on the clogging phenomena. The dynamics of particle deposit buildup is strongly dependent on the solution chemistry. Figure 2a shows that there is no increase in pressure drop at 15 μL/ min but only small fluctuations, while there is significant increase in pressure drop at 30 μL/min after collecting 0.5 mL permeate volume. Thus, a critical flux leading to deposit has been overcome between 15 and 30 μL/min. Above the critical flux, the drag force acting on particles overcomes the particlewall repulsive interactions leading to adhesion of particles onto the microchannel walls. These results are in agreement with the critical flux measurements done with flux stepping method (Figure 1b). At high flow rate (70 μL/min), one can note a more progressive increase in pressure until a certain permeate volume is collected (1 mL), after which the pressure drop increases by about 50 mbar. It seems that the hydrodynamic force is not only able to overcome the repulsive forces for particle capture but is also able to break the interparticle and particle-wall bonding forces. However, when clogging is initiated after 1 mL, the pressure increases rapidly: filtration of 0.5 mL leads to a pressure increase of 700 mbar. The pressure increment is less important for lower flow rate: at 30 μL/min, the pressure increases by 500 mbar for the same permeate volume. This difference is related to the difference in the deposit morphology formed.

At high ionic strength (100 mM in Figure 2c), increase of pressure is observed even at low permeate flux (15 μL/min). As for the low ionic strength, high velocity seems to delay the formation of clogs and deposit on the surface. With the microscopic observation, this effect is associated with frequent formation of clogs but that are often broken by the flow. After clogs are formed, the pressure increases by a value of 700 mbar while the permeate volume collected is about 0.75 mL at 70 μL/min; the corresponding volume for the same pressure increment is about 1.375 mL at 30 μL/min (Figure 2c). A relatively different behavior is observed for the moderate ionic strength (10 mM in Figure 2b). In these conditions, the flow rate is always enhancing the clogs formation, but the time (or the filtered volume) at which they are appearing is significantly delayed: for 30 μL/min, the clogging appears after 3.5 mL permeate volume is collected whereas this volume is 0.5 mL at 0.01 mM ionic strength. The pressure reaches 1 bar after about 5.5 mL permeate flow: the corresponding value for 100 mM ionic strength is about 2.25 mL (reduced by half). These results will be further analyzed and discussed by considering the effect of the coupling of colloidal interaction and hydrodynamic forces on the clogs formation and breakage in the Discussion section.

3.3. Microchannel Entrance Geometry Effect. The discrete geometry of the filter surface can have a significant impact on particle deposition, deposit morphology, and the subsequent permeability reduction particularly at the very first steps of deposit formation. The set of experiments presented in this section will investigate the effect of the discrete geometry of the filter surface on the deposition kinetics.

Two different microchannel entrance geometries (entrances with square pillars and entrances with tilted angle pillars at 45°) are designed to study the effect of microchannel opening on the jamming probabilities (Figure 3a,b). These geometry designs represent the two extremes that we can have on surfaces of separation systems, i.e., flat surfaces and sharply grooved surfaces. These entrance geometries can have significant effect on the jamming probability. Figure 3c presents the decrease in flow rate with time for constant pressure experiments realized with two ionic strength suspensions (0.01 and 100 mM) and for microchannels having square (DS10) and tilted angle (DT10) shapes. In these set of experiments, one can note the opposite effect of the increase in ionic strength (from 0.01 to 100 mM) on the permeability decrease. For square shape, increasing ionic strength leads to a lower permeability decline. As shown previously in Figure 2c for constant flow experiments, this effect seems to be due to the high fragility of the clogs: it is possible to see frequent expulsion of such clogs through the channels (second image in Figure 3a). Contrary to this, the increase in ionic strength leads to a more rapid clogging of the microchannels for tilted shape (the worst conditions for this set of experiments). The decrease of the permeability is severe, and the microchannels are almost totally clogged after 0.2 mL of permeate volume. These results underline the important role played by the bottleneck shape on the first steps of clogs formation as it was underlined previously [START_REF] To | Jamming of granular flow in a twodimensional hopper[END_REF] with consequences on the clogging kinetics (discussed in section 4.2). Greater particles deposition on the surfaces of square pillars was observed, and this is due to the larger forward flow stagnation surfaces available with this geometry. Greater capture of particles on the surfaces of the square pillars decreases the funnelling of particles into the constriction resulting in less permeability loss compared to the tilted shape geometry where the funnelling is inevitable. This principle is in agreement with the classical filtration theory. [START_REF] Johnson | Colloid Retention in Porous Media: Mechanistic Confirmation of Wedging and Retention in Zones of Flow Stagnation[END_REF] Tong et al. [START_REF] Tong | Funnelling of Flow into Grain-to-grain Contacts Drives Colloid-Colloid Aggregation in the Presence of an Energy Barrier[END_REF] observed temporal increases in colloid deposition rate (also called filter ripening) by carboxylatemodified polystyrene latex microspheres of sizes ranging from 0.1 to 2.0 μm in packed porous media with spheroidal grains. They reported that the transition from "clean bed" deposition to ripening was triggered by relatively subtle changes in solution chemistry and fluid velocity: slight increase in solution ionic strength and slight decrease in fluid velocity led to ripening for all microsphere sizes. The ripening was formed at grain-to-grain contacts due to the funnelling of fluid flow into these areas, which shows very close similarities with our case of tilted shape channels.

3.4. Deposit Characteristics. The previous section was analyzing the clogging kinetics. Here, we will focus on the deposit characteristics. Figure 4a shows the evaluations of the additional hydrodynamic resistances with the cumulative permeate volume collected for both constant pressure and constant flow filtration experiments performed with low, moderate, and high ionic strength suspensions. The additional resistances are induced by particle deposition and are calculated for constant pressure and constant flow rate experiments using the equations R a /R 0 = (J 0 /J) -1 and R a /R 0 = (ΔP/ΔP 0 ) -1, respectively, which are derived from the filtration equation. R a is the total resistance after deposit formation, R 0 the clean system resistance, J the evolving flux with time, J 0 the flux for the clean system, ΔP the evolving pressure drop with time, and ΔP 0 the pressure drop for the clean system.

The additional hydraulic resistance generally increases more rapidly for constant flow rate mode compared to constant pressure. This effect could be linked to the kinetics (constant pressure mode can be considered as self-regulatedthe clogging reduces the flow and then the particle flux coming to the membrane) or to the difference in the specific deposit resistance (because of a difference in the morphological properties). To go further in the analysis, Figure 4b shows the variation of the specific deposit resistance for both constant pressure and constant flow rate experiments at low and high ionic strengths. This specific deposit resistance is calculated from the measurement of the mean deposit thickness from microscopic observations. The specific deposit resistance is then the ratio of the hydraulic resistance (Figure 4a) to the mean deposit thickness. Higher specific deposit resistances are observed for low ionic strength suspensions (Figure 4b). This could be due to the formation of denser deposit because of the repulsive interaction: repulsion interaction leads to a reorganization before contact. This reorganization of particles gives rise to a more compact deposit structure. For similar conditions, the deposit created with a higher ionic strength have lower specific deposit resistance: this can be explained by the more open structure of the deposit formed in attractive conditions, i.e., for adhesion of particles at the first contact. The specific deposit resistance with high ionic strength at constant flow rate exceptionally increases with time. This could be due to the fragility of the deposit (due to its loose structure) and the resulting restructuring as the filtration proceeds (discussed in section 4.1.2).

The specific deposit resistance is higher for experiments performed at constant flow rate allowing internal reorganization. This effect is more pronounced for low ionic strength suspensions due to the formation of relatively ordered deposit. The lowest specific deposit resistance is obtained with high ionic strength suspensions (loose deposit) formed during constant pressure filtration (low reorganization).

DISCUSSION

The experiments have shown the sensitivity of the clogs formation at the pore entrance and of the clogs structure to the hydrodynamics and the surface interactions: a strong coupling exists between hydrodynamics and multibody surface interactions. The mechanisms involved in the clogging are different according the hydrodynamic/interaction balance. The following section highlights original features and clogging scenarios brought by these experiments.

4.1. Interplay between Surface Interaction and Hydrodynamics. The permeability variations induced by the formation of clogs with filtration time can be summarized in Figure 5 by plotting the couple of conditions (filtered volume and flow rate) leading to a significant fouling (through a criteria on the additional hydraulic resistance). The criteria taken for this plot is an additional resistance equal to the initial resistance to the clean system (i.e., R a /R 0 = 1). Such criteria correspond to a filtration volume (called hereafter clogging volume) where the filtration flux is half the clean system flux for pressure driven flow and is then an indicator of a significant clogging. The results obtained for 0.01 and 100 mM show that deposition is lower (or the clogging volume is higher) at very low or at very high velocities. The clogging is then maximized at intermediate flow rate. For example, for 100 mM suspension, about 2100 and 1300 μL permeate volumes are collected before a significant fouling at flow rates of 15 and 70 μL/min, respectively, while the corresponding volume at 30 μL/min is about 150 μL. These results are in agreement with previous studies of filtration in microchannels [START_REF] Dersoir | Clogging of a single pore by colloidal particles[END_REF] that often show no clogging zone for extreme flow rates. The results obtained for 10 mM are significantly different and show an important delay in clogging. About 2300 μL permeate volume is collected at 30 μL/min before clogging.

These clogging scenarios can be discussed by considering colloidal interactions whose main characteristics are an important repulsive barrier at 0.01 mM, a significant secondary minimum at 10 mM, and low repulsive barrier at 100 mM (as summarized in Table 1 from the DLVO calculations presented in Supporting Information Figure S4). These results allow distinguishing different behaviors (Figure 5) according to filtration conditions that will be discussed in the next sections: a zone at low flow rate where the repulsive potential barrier prevents the clogging due to the relative importance of particle-particle interactions compared to particle-wall interactions (discussed in section 4.1.1); a zone at high flow rate where the fragility and the re-entrainment of particles are significant when aggregates are formed with high ionic strength (high sweeping out by the shear rate) mainly because of the significant role played by particle-wall interactions (discussed in section 4.1.2); an important delay in clogging at moderate [START_REF] Zaccone | Charged Molecular Films on Brownian Particles: Structure, Interactions, and Relation to Stability[END_REF] The details of these calculations and the interaction energy potential curves for the different ionic strengths can be found in the Supporting Information, section 4).

ionic strength because of the secondary minima (discussed in section 4.1.3). These behaviors, summarized in the first lines of Table 2, are discussed in the next subsections. 4.1.1. Potential Barrier Limited Clogs. For relatively low flow rates (below 30 μL/min), the clogging volume decreased when the ionic strength increased (except for the 10 mM case that will be discussed in section 4.1.3). This result is expected (according to the DLVO theory and its application to slow regime of coagulation) and has been observed for various deposition configurations: a gradual increase in the attachment efficiency on collectors has been observed with increasing KCl concentration in packed column. [START_REF] Elimelech | Kinetics of deposition of colloidal particles in porous media[END_REF] As the electrolyte concentration increases, the repulsive potential barrier (or the stability ratio) is reduced, and as a result, the attachment efficiency is increased. In the same way, the increase in particle-wall collision efficiency should make more probable the formation of arches and clogs: arches being initiated by deposition of particles at microchannel corners. In these conditions, where the drag force is the acting force leading to overcome the potential barrier, increasing the flow rate reduces the clogging volume. Such results are coherent with the theory describing the shear-induced aggregation of colloids as an activated rate process where the potential barrier between colloids is crossed by the shear energy. [START_REF] Zaccone | Theory of activated-rate processes under shear with application to shear-induced aggregation of colloids[END_REF] 4.1.2. Clogs Limited by Their Shear Fragility. In contrast to intermediate flow rate, high flow rate leads to an increase of the clogging volume (retardation of the clogging). Analysis of the microscopic images shows frequent clogs collapse and sweeping out of the associated fragments through the microchannels. The fragility of the clogs seems then to be the main limiting effect controlling the clogging process dynamics. In these conditions, it is possible to note that the permeability decrease is less severe for 100 mM than for 0.01 mM salt concentration. The clogs formed at 0.01 mM are more robust and more resistant to the shear: the clogs collapse and sweeping out phenomena are rarely observed. In comparison, the fragility of the clogs formed at 100 mM (low repulsive potential barrier) is more important (see inset images in Figure 5).

To further investigate this vulnerability to fragility, the flow rate was suddenly stopped after forming thick deposit and different patterns of deposit relaxation have been observed depending on the solution chemistry. The images taken 10 s after stopping the flow rate are presented in Figure 6. The deposit relaxation is very different for 100 and 0.01 mM. For 0.01 mM, the relaxation shows either the dispersion of a loose layer close to the upstream part of the deposit (Figure 6b) or the detachment of large bands of the deposit which show rather cohesive aspect (Figure 6a). Contrary to this, relaxation of the deposit formed with 100 mM suspension is characterized by disintegration of the deposit into small aggregates or clusters (Figure 6d). This difference can also be linked to the hydraulic resistance of the deposit that has been estimated in Figure 4a (section 3.4). Such results reinforce the notion of dense and cohesive solid structure (clogs and deposit) with 0.01 mM and loose and fragile structure with 100 mM salt concentrations. Relaxation of the deposit formed with 10 mM salt concentration results in detachment of large bands of deposit with large amount of small fragments (primary particles, duplex, triplex, etc.) of particles (Figure 6c).

These results are qualitatively in agreement with the results usually obtained in aggregation conditions under diffusion and interaction coupling (quiescent conditions). It is known that aggregates formed under diffusion-limited cluster aggregation (DLCA) conditions (higher salinity) have loose structure with low fractal dimension while aggregates formed by reactionlimited cluster aggregation (RLCA) conditions (lower salinity) exhibit more compact structure with higher fractal dimension. [START_REF] Tang | Fractal Morphology and Breakage of DLCA and RLCA Aggregates[END_REF] Experiment and simulation show that the breakage rate of the dense aggregates is smaller than that of the open aggregates for the same hydrodynamic stress. [START_REF] Harshe | Breakage Rate of Colloidal Aggregates in Shear Flow through Stokesian Dynamics[END_REF] The role played by the fragility to explain the dynamics (and the flow intermittence) of clogging and jamming in sheared conditions has been discussed in the Introduction. The fragility of the clog depends on how the system came to be jammed ("construction history"). [START_REF] Cates | Force Chains, and Fragile Matter[END_REF] Thus, it can be noted here that when the clogs construction is rapid (the case with high ionic strength suspension), the structure of the clog is open and then is more fragile. Theoretical development [START_REF] Conchuir | Mechanism of flow-induced biomolecular and colloidal aggregate breakup[END_REF] have shown that open aggregates can collapse as soon as the flow induced drift acting on the aggregate structure is in the same order of magnitude with the intermolecular bonding forces: a breakup of few bonds in the aggregate interior by the flow leads to the collapse of the whole aggregate. Clogs formed with conditions of high repulsion (low ionic strength), and hence slower construction history, are more robust. Numerical simulations evidenced the effect of repulsive interaction magnitude on the clog structure and density. [START_REF] Wyss | Mechanism for clogging of microchannels[END_REF][START_REF] Agbangla | Collective dynamics of flowing colloids during pore clogging[END_REF] The force chains that sustain the clogs are stronger and probably more important (the coordination number in dense aggregate is higher) when aggregates are formed with more repulsive conditions. A change in flow conditions (and in the compression axis) does not allow then to break the clogs: the compatible load of the clog (according to Cates's 2 approach) is higher. Theories 28 demonstrate that in conditions of dense aggregates (in the limit of nonfractal aggregates) the collapse mechanism is replaced by a surface erosion mechanism. The robustness of the clogs is further discussed in section 4.2.

4.1.3. Secondary Minimum Leading to Gliding Phenomena. A surprising observation has been obtained for microparticles dispersed in 10 mM KCl solution: the results being uncorrelated to the ones obtained at high ionic strength. An important delay in clogging is observed at moderate ionic strength. At 0.01 mM, a significant clogging is observed after filtering 0.7 mL of permeate volume whereas the corresponding permeate volume for 10 mM to observe such a clogging is 2.2 mL. The propensity to clog is then reduced when the repulsive barrier is partially screened; this trend is opposite to the one expected from DLVO theory for aggregation discussed in the previous section. But microscopic observation of the dynamic behavior of particles at the beginning of the filtration in such conditions can explain this particular behavior. In these conditions, the particles are collected preferentially in the downstream corner of the pillars (Figure 7), and the particle capture in the upstream zone of the pillars is almost nonvisible or, if any, very short-lived.

Such an observation can be linked to the existence of a significant secondary energy minimum at 10 mM in KCl (Table 1). The effect of the secondary minimum on the capture of microparticles on collectors has been investigated. [START_REF] Kuznar | Direct microscopic observation of particle deposition in porous media: Role of the secondary energy minimum[END_REF][START_REF] Elimelech | Kinetics of deposition of colloidal particles in porous media[END_REF][START_REF] Tufenkji | Breakdown of Colloid Filtration Theory: Role of the Secondary Energy Minimum and Surface Charge Heterogeneities[END_REF] The explanation advanced in this paper is that the secondary minimum helps particles to translate or roll along the microchannel wall due to fluid drag and shear until they reach the stagnation point in the downstream zone of the pillars. The secondary energy minimum attraction force should result in a faster deposition rate (compared to "slow" deposition in the presence of an energy barrier), but the particle-particle attraction interaction in this region (not in direct contact with the wall) seems to promote the sweeping out (or gliding) of particles under the drag force. These results are in agreement with results obtained from porous media with spherical collectors where at moderate ionic strength particles translate along the collectors surface via secondary energy minimum association (without attachment) in the presence of an energy barrier and accumulate at the flow stagnation zones where there is low flow drag. [START_REF] Kuznar | Direct microscopic observation of particle deposition in porous media: Role of the secondary energy minimum[END_REF][START_REF] Johnson | Upscaling Colloid Transport and Retention under Unfavorable Conditions[END_REF][START_REF] Ma | Surface Heterogeneity on Hemispheres-in-Cell Model Yields All Experimentally-Observed Non-Straining Colloid Retention Mechanisms in Porous Media in the Presence of Energy Barriers[END_REF] 4.2. Bottleneck Shape: Tilted Wall Shape Increasing Arches Robustness. The results in Figure 3c show that the clogging depends on the microchannel bottleneck shape. In all cases, the results show that an opening angle at microchannel entrance leads to rapid clogging, this effect being more pronounced for the microparticles dispersed in 100 mM KCl (where the repulsion is significantly screened). The arches formed at low ionic strength (0.01 mM) are robust and dense. The opening angle seems to reinforce the robustness of the arches, leading to a more rapid decrease in the permeability. For arches formed at high ionic strength, the clogging transition is controlled by the fragility of the arches that are frequently broken and swept out. In this case, the square corners favor the frequent sweeping out of the arches leading to a delay in clogging. The convergent entrance (Figure 3b) seems to reduce the breakage events. Two explanations could be brought to support this observation. First, the convergent entrance could protect the clog formed at the bottleneck from flow changes. In the convergent zone, the flow is more regular (with less axis fluctuation) and then should reduce the collapse of clogs. Indeed, the fragility of clogs is linked 2 to changes (even small) in the direction of the flow: the force applied by the flow becomes different than the compression axis at the origin of the arches formation. The convergent entrance could then reduce this destructive change in flow direction. Second, the arches could be more frequent and more robust because of the tilted angle at the bottlenecks. It is easier to support force chains in a "conic" system. The lateral walls could partially help to support the thrust from the drag force on the arches. The inclined wall could then help to form force chains of the clog and to have clogs less sensitive to small lateral changes in the flow. Furthermore, it has been observed from the experiments that the arches with the titled bottlenecks are formed just above the microchannel entrance (Figure 3b) with parallel walls while the arches with the square corners are formed just below the microchannel entrance (Figure 3a) where there is less support from the lateral walls against the drag force. The worst conditions for clogging are reached when combining a high frequency for arches formation (at high ionic strength where the collision efficiency is higher) and durable arches (with an opening angle increasing the arches robustness). This occurs during experiments with tilted angle microchannels using high When repulsive particles are flowing near a constriction, because of multibody interaction, the particles can jam and form a network of arrested interacting particles slowing down the flow (a force chain of particles in repulsion blocking the flow). This "interaction pushing effect" has been already simulated. [START_REF] Agbangla | Collective dynamics of flowing colloids during pore clogging[END_REF] In this case, the force chain presents lateral component that make particles pushing on the bottleneck walls (mainly because of the high osmotic pressure exhibited by concentrated repulsive particles). When the force chain is destroyed by the flow, the flow accelerates and the permeability increases. This flow acceleration can lead to the capture of the particles at the bottleneck or to the collapse of successive force chains and then lead to the creation of arches. If this event does not occur, a new force chain can be created leading to a stop and go flow. These phenomena (left part of Figure 8) have been simulated and lead to permeability fluctuations or arches formation according to the particle/particle or wall/particle repulsion magnitude. [START_REF] Agbangla | Collective dynamics of flowing colloids during pore clogging[END_REF] The unexpected effect shown by these experiments is the delay in clogging observed for 10 mM experiments characterized by a significant secondary minimum. The formation of arches is prevented in these conditions. Because of the secondary minimum, we can deduce that particles will attract each other to form a cluster of attractive interacting particles. Such a cluster can be seen as a network of lubricated particles linked by "slippery" bondsunlike shear rigid bonds at contact. These slippery bonds have been discussed in the aggregation mechanisms of particles having secondary mini-mum interaction [START_REF] Seager | Slippery diffusion-limited aggregation[END_REF] and could be also responsible for the gliding phenomena of particles at wall (discussed in section 4.1.3). This cluster of attractive interacting particles can then be formed in the center of the flow through the shear-induced diffusion effect. This mechanism could lead to a coordinated transport of particles induced by the attraction between particles (the attraction leading to a pulling effect of particles through the bottleneck). Such an enhanced transport through the pore could delay the clogging. Simulation should be done to check the existence of this pulling effect.

4.3.2. Panic, the Herding Instinct, and the Sacrifice Scenarios. At the end, three well different scenarios for clogging can be drawn according to the particles interaction outline experimented with particles in different ionic strength environment (Table 2). These behaviors can be put in parallel of the general sketch of discrete bodies passing through a bottleneck that can be found in granular materials or in crowd swarming. [START_REF] Zuriguel | Clogging transition of many-particle systems flowing through bottlenecks[END_REF] Panic is a particular form of a collective behavior depending on "human" interactions. [START_REF] Helbing | Analytical approach to continuous and intermittent bottleneck flows[END_REF] This behavior is similar to the one we observe with repulsive particles where a pushing interaction effect is responsible to stop and go flow or to arches formation. At the opposite of panic, the herding instinct is a cooperative collective behavior which seems to be observed when we proceed with attractive (in secondary minima) particles. In this case, a pulling effect induced by attraction could help the transfer of the cluster of attractive particles through the bottleneck and delay the clog formation. In these last two cases, the collective effects (generated by the long-range interactions and the presence of concentrated dispersions in constrained environment) seem to control the transport of particles through the channels.

In the last case of attractive (in primary minima) particles, the collective effect seems less important. This case is characterized by a high collision efficiency leading to important capture of particles on the walls. The deposit on the walls is then a hydrodynamic (ballistic) limited aggregation. However, even if the deposit quantity is high, this deposit is loose (there is no "ordering" or ''spatial optimization" of the capture position induced by interactions) and lead to a dendritic or loose structure. This structure is then more fragile, and the clog formation is controlled by this fragility.

Figure 1 .

 1 Figure 1. (a) Flow stepping experiments at different solution ionic strengths: 0.01, 10, and 100 mM of KCl. (b) Fouling rates calculated from the flow stepping curves. The inset images are observations for 10 mM suspensions before and after deposit formation.

Figure 2 .

 2 Figure 2. Pressure drop vs cumulative permeate volume at different flow rates (15, 30, and 70 μL/min) for different solution ionic strengths: (a) 0.01, (b) 10, and (c) 100 mM.

Figure 3 .

 3 Figure 3. Microchannel bottleneck geometry effect on the clogging process during filtration of latex suspensions with demonstration of the typical particle deposition patterns: (a) for microchannels with square pillars entrance geometry, DS10; (b) for microchannels with tilted pillars, DT10; (c) filtration results at constant pressure (200 mbar) for the two geometries with low (0.01 mM) and high (100 mM) ionic strengths. D denotes dead-end flow, S and T denote square and tilted pillars, respectively, and 10 is the channel width.

Figure 4 .

 4 Figure 4. (a) Comparison of additional hydrodynamic resistances at low (0.01 mM), moderate (10 mM), and high (100 mM) ionic strengths. (b) Specific deposit resistances for low (0.01 mM) and high (100 mM) solution ionic strengths. The experiments are performed at constant pressure (200 mbar) and constant flow rate (70 μL/min).

Figure 5 .

 5 Figure 5. Filtered volume leading to clogging determined for different filtration flow rates and for different ionic strengths.

Figure 6 .

 6 Figure 6. Deposit relaxation observations. The images correspond to deposits formed with (a) 0.01 mM KCl after a constant flux filtration, (b) 0.01 mM KCl after a constant pressure filtration, (c) 10 mM KCl after a constant flux filtration, and (d) 100 mM KCl after a constant flux filtration.

Figure 7 .

 7 Figure 7. Observation of particle capture in the downstream corner of the pillars for 10 mM salt.

Figure 8 .

 8 Figure 8. Collective effect of the interaction on transport of particles through bottlenecks for repulsive particles (left part) and for attractive/ repulsive particles (right part).

Table 1 .

 1 Values of the Double Layer Thickness (λ D ), Secondary Energy Minima (U 2,min °/K B T), and the Repulsion Barrier (U max /K B T) Calculated from the DLVO Theory at

	Low (0.01 mM), Moderate (10 mM), and High Ionic (100 mM) Strengths a
	[KCl] (mM)	λ D (nm)	U 2,min °/K B T	U max /K B T
	0.01	92.6	-0.084	9620
	10	3.04	-22.1	5700
	100	0.962	-92.6	3100

a The modified Hamaker formula and the Sader-Carnie-Chan equation are used to calculate the van der Waals attractions and the electrostatic interactions, respectively.

Table 2 .

 2 Mechanisms Involved by the Coupling between Hydrodynamic and Surface Interaction Leading to Three Different Clogging Scenarios

	ionic strength (mM)	0.01	10	100
	interaction outline	repulsion	attraction/repulsion	attraction/contact
	coupling of	potential barrier	secondary minimum	primary minimum
	hydrodynamic with
	collective effect	interaction pushing effect	interaction pulling effect
	clogging mechanisms	clogs formation prevented by	clogs formation prevented by gliding phenomena	clogs limited by the fragility to shear/high
		potential barrier	(slippery bond)	collision efficiency
	clogging formation	few clogs but robust/dense and	gliding behavior/delay for clog formation	a lot of clogs but fragile/loose and
		cohesive deposit		noncohesive deposit
	main transitions	order under constraint competition	spontaneous order cooperation for space low	high collision efficiency
		for space	collision efficiency
	scenario	the panic	the herding instinct	the sacrifice

■ ACKNOWLEDGMENTS

The authors acknowledge the financial support of the Education, Audio-visual and Culture Executive Agency (EACEA) division of the European Union under the program of EUDIME (European Doctorate in Membrane Engineering) grant in the Erasmus Mundus framework. The authors would like to thank Van Nhat PHAM (PhD student at University of Toulouse) for his help in the fabrication of the microfluidic devices.

CONCLUSIONS

The dynamics of the clog formation at microchannel bottlenecks and their impact on the permeability are controlled by colloidal interaction outline (potential barrier, secondary and primary minima) when varying the dispersion ionic strength (0.01, 10, and 100 mM). At low flow rate in the presence of potential barrier, no clogging of the microseparator is observed which is linked to low collision efficiency. Higher flow rate induces pushing effect between particles leading to the creation of robust arches at pore entrances. The coupling of high flow rate and high ionic strength conditions show that the filtration process is dominated by the shear fragility of clogs: frequent sweeping out of the arches can delay the clogging. When a significant secondary energy minimum exists, an important clogging delay is observed. Such delay could be attributed to particle-particle or particle-wall slippery bond that leads to particle gliding on the wall and to a pulling effect between particles flowing through the bottleneck. Moreover, we find that these observations are sensitive to the geometry of the microchannel bottleneck. The results are discussed at the light of the force chains that could be created inside the concentrated dispersion prior to clog formation. This study illustrates then the importance of collective behavior exhibited by interacting particles during jamming or clogging.

■ AUTHOR INFORMATION

Corresponding Author *E-mail sendekie@chimie.ups-tlse.fr (Z.B.S.).

Notes

The authors declare no competing financial interest.


Richard Koech
email: richardkoech@hotmail.com

Antonio Pires De Camargo

Bruno Molle

Ezequiel Saretta

Jose Antonio Frizzone

Gao Benhu

David Pezzaniti

Intercomparison testing and evaluation of sprinklers within the INITL

Keywords: Intercomparison, sprinkler, radial distribution

The International Network of Irrigation Testing Laboratories (INITL) undertook a sprinkler intercomparison testing exercise to generate data for an objective comparison of the performances of the different facilities and identify opportunities for further improvements. Three impact sprinklers were tested in four laboratories in accordance with the standard ISO 15886-3. The plots of flow ratepressure profiles were found to be consistent, and correlated to those obtained from previous studies.

Although there were slight variations in the measured flow rate data, the mean flow rates at each pressure level were the same for the three sprinklers and the shapes of the radial distribution profiles

Introduction

The INITL, initiated in 2000, is a network of 18 laboratories spread out in 17 countries which are involved in testing of irrigation-related equipment. Some of these facilities are affiliated to educational institutions, and hence integrate academic research with testing for commercial purposes. Some of the facilities are recognised internationally through their accreditation to the ISO/IEC 17025 (2005), an international standard which certifies that the facility meets the general requirements for competence of testing and calibration. Apart from the international accreditation, the facilities are also accredited by their national accreditation authorities. For instance, in Australia and Brazil, the corresponding accreditation bodies are the National Association of Testing Australia (NATA) and the General Coordination for Accreditation of the National Institute of Metrology, Quality and Technology (Cgcre).

The motivation behind the creation of the INITL was to develop a framework by which facilities involved in irrigation and related testing could objectively engage with each other in a reciprocal manner. So far, the most popular form of engagement has been to participate in joint intercomparison testing, whereby the same products are tested in various laboratories and the results are compared.

This creates an opportunity for testing facilities, including those that are geographically isolated, to gauge their performance against their peers, and identify strategies for their improvement. The INITL's philosophy is very similar to the intercomparison exercises that exist in many domains, or proficiency testing as they are often called. In Australia and Brazil for example, the NATA and Cgcre

Author-produced version of the article published in Journal of Irrigation and Drainage Engineering-ASCE, 2016, N°142(2). The original publication is available at http://ascelibrary.org Doi: 10.1061/(ASCE) IR.1943-4774.0000937 respectively require that facilities participate in proficiency testing to maintain their accreditation or when seeking extensions of accreditations.

Additionally, since the procedures and guidelines used by these facilities are based on the same international standards, some form of engagement contributes towards more coordinated periodical reviews of these standards. The network, through the intercomparison activity, contributed to the latest modifications of the ISO 15886-3 and ISO 9261 standards. The INITL is the only organisation involved in international intercomparison exercises in metrology applied to irrigation equipment performance evaluation. Examples of published intercomparison exercises in other fields of metrology include the intercomparison of high pressure test facilities undertaken by ten of the major European companies [START_REF] Tedeschi | Intercomparison exercise of high pressure gas flow test facilities within GERG[END_REF].

The first intercomparison exercise initiated by the INITL, involving successively drippers and sprinklers, was undertaken between 2003 and 2007. The sprinkler and dripper results were respectively presented at the ISO/TC 23/SC 18 meetings held in Anaheim, United States, in 2008 (No. 884) and in Mexico in 2009 (No. 924). The second exercise occurred in 2013-2014, and the results of the dripper tests are documented in Koech et al. (unpublished) while the results of the sprinkler tests are presented in this paper.

Soon after the commencement of intercomparison testing more than a decade ago, the INITL members recognised the need for a central internet-based platform to harmonise the processing of results and test reports. Hence a web-based, open-source software, that allows harmonised processing of sprinkler results and reports was developed, and is presented in this paper. The software is internetbased, and can be used by irrigation practitioners free of charge for research and other purposes. A similar irrigation software that was freely available a decade ago is Catch3D [START_REF] Merkley | Catch3D User's Guide[END_REF]); however, it is no longer available and appears not to have been updated to enable it run using the current versions of computational operating systems.

The specific objective of this paper is therefore to present the results of the intercomparison testing of sprinklers within the INITL undertaken in 2013-2014, and describe the software developed for

Author-produced version of the article published in Journal of Irrigation and Drainage Engineering-ASCE, 2016, N°142(2). The original publication is available at http://ascelibrary.org Doi: 10.1061/(ASCE) IR.1943-4774.0000937 processing and harmonising results. The test results and the software are evaluated and aspects of sprinkler testing requiring further research identified.

Overview of sprinkler testing and evaluation

Typically, field evaluations of sprinkler performance are undertaken by laying catch-cans around a selected number of sprinklers, or full grid (rectangular or square) arrangement. The sprinkler is located at the centre of the grid and the distortion caused by wind or sprinkler's asymmetric coverage pattern can easily be detected. On the other hand, for research or developmental work in which more precise measurements are required, the characterisation of water distribution is often undertaken indoors because it is relatively easier to attain no-wind conditions. Depending on the wetted radius, full grid catch arrangement may also be used in laboratory testing, but more often catch-cans are arranged along one or more radial distance of a single sprinkler, technically referred to as single leg test [START_REF] Svubure | An investigation on the energy saving potential of mini-sprinkler irrigation systems[END_REF]). The single radial grid catch-can arrangement is widely used because of constraints of space in many laboratories. This arrangement is mostly applied when a symmetrical watering pattern is expected and in no-wind conditions (ISO 15886-3, 2012).

The design and size of the sprinkler, number and configurations of nozzles, and the operating pressure are the key factors determining its water distribution profile [START_REF] Tarjuelo | Irrigation uniformity with medium size sprinklers part II: Influence of wind and other factors on water distribution[END_REF]. Ideally, the water distribution patterns of a sprinkler of the same model and size operating under the same conditions would be expected to be the same. However, it has been demonstrated that they vary in some cases, mainly because of manufacturing inaccuracies [START_REF] Bean | Water distribution by irrigation sprinklers[END_REF]. Measurement uncertainties, which are related to procedures and equipment used for testing, may also cause disparities in the data. Normally, a sprinkler with a full rotation should have a circular wetting pattern. However, if factors such as manufacturing imperfections cause the impact-type sprinkler to have a variable rotational speed, an asymmetric coverage pattern may be expected [START_REF] Christiansen | Irrigation by sprinkling[END_REF]. An asymmetric coverage pattern may also be caused by the sprinkler riser not being perfectly vertical.

Author-produced version of the article published in Journal of Irrigation and Drainage Engineering-ASCE, 2016, N°142(2). The original publication is available at http://ascelibrary.org Doi: 10.1061/(ASCE) IR.1943-4774.0000937 In both the full and the radial grid arrangement, the sprinkler performance is determined by measuring the quantities of water collected in the catch-cans. Traditionally, these measurements have been carried out manually; however automatic evaluation procedures have been proposed (for instance [START_REF] Seginer | Indoor measurement of single-radius sprinkler patterns[END_REF]), but there is no evidence of their widespread adoption. Semi-empirical models used for the spatial distribution of water application under centre pivot sprinklers have been developed [START_REF] Molle | Model of Water Application under Pivot Sprinkler. II: Calibration and Results[END_REF].

The international standard used by the majority of INITL members for evaluation of sprinkler systems is ISO 15886-3 (2012). This standard specifies the conditions and procedures for testing and characterising the water distribution pattern of sprinklers specifically used for irrigation purposes.

The ISO standard specifies that test duration must comply with uncertainty requirements and the sprinkler jet must pass over the catch-cans at least 30 times. The measurement of the amount of water collected may be done by mass, volume or level, ensuring that uncertainty in measuring water depths does not exceed 3%. The number of catch-cans installed along a radius depends on the sprinkler jet length. If the jet length is longer than 4 m, at least 10 catch-cans must be installed.

Sprinkler test results may be presented in a variety of ways. One common example is a chart of the radial water distribution, which is a plot of the application rate (mm/h) observed along the jet length.

By adding to this chart a horizontal line representing the average application rate, areas receiving more or less water than the average can be easily identified. The use of charts representing the volume of water collected along the jet radius is another option of presenting the results. As per ISO 15886-3 (2012), the effective radius of throw is generally defined as the distance between the sprinkler and the point where the application rate is 0.25 mm/hr (sprinklers of flow rate > 75 L/h) or 0.13 mm/hr (sprinklers of flow rate < 75 L/h). Sprinkler performance may also be characterised by plots of operating pressure versus flow rate.

The ISO 15886 -3 (2012)

= ∑ (1)
where is the depth measured at radius , is the catch-can spacing and t is the test duration. The standard requires that for the results to be validated, the reconstituted flow rate shall not deviate by more than 5% from the measured flow rate for sprinkler rated at 507.6 L/h or higher and 7% for flow rates less than 507.6 L/h).

The distribution uniformity of water in a sprinkler system can be simulated using computer packages such as SPACE PRO TM [START_REF] Oliphant | SPACE PROTM Installation and Operation Manual[END_REF] based on the water application profile of a single sprinkler and the corresponding arrangement of sprinklers in the irrigated area. This is undertaken by overlapping the data and calculating uniformity using the following methods: Christiansen uniformity coefficient (CUC); Statistical coefficient of uniformity (SCU); Distribution uniformity (DU); and scheduling coefficient (SC). CUC is commonly used as a uniformity measure in agricultural and turf irrigation [START_REF] Zhang | Assessing whole-field sprinkler irrigation application uniformity[END_REF] and may be expressed as:

= 100 1 - ∑ | | ∑ ! (2)
where V i is the volume measured in an individual catch-can and " is the mean applied volume.

An example of a mathematical model proposed for the assessment of whole-field uniformity of a sprinkler system is described in [START_REF] Zhang | Assessing whole-field sprinkler irrigation application uniformity[END_REF]. The software can simulate the hydraulics and overlapping of sprinklers, using variables such as field size, shape and topography.

Materials and Methods

Intercomparison testing

Table 1 provides a list and brief description of the laboratories that participated in the 2013-2014 sprinkler intercomparison tests. The cross tests were undertaken using three overhead, metallic, The ISO 15886 -3 (2012) provides that sprinkler evaluations can be conducted indoors or outdoors.

However, as the objective of the tests was to obtain precise water distribution data (flow rate-pressure curves and water distribution patterns) for comparison, all the tests were performed in indoor facilities. Previous research [START_REF] Stambouli | Performance of new agricultural impact sprinkler fitted with plastic nozzles[END_REF]) has shown that no-wind conditions, as is expected in indoor facilities, are necessary in order to obtain reliable data.

All the participating laboratories undertook single-leg tests which involved mounting one sprinkler head at time on a sprinkler riser typically 1 m long and supported by a tripod. Water was delivered to the sprinkler head through the other end of the sprinkler riser. To measure the operating pressure, a pressure tapping point was made in the riser pipe just below the sprinkler head, and a pressure gauge connected. In some laboratories, to restrict sideways spread of water, the sprinkler system was enclosed in a shelter (Fig. 1).

Author and the surface of the catch-cans was maintained at 0.5 m. Control valves were installed in the pipeline to regulate the operating pressure. All tests were preceded by starting the pump and operating the sprinkler system for approximately one hour. This was necessary in order to condition the sprinklers, test all the system components, and expel any air that may have been in the system.

The flow rate-pressure curves were determined using the following pressures: 100,150,200,250,300,350,400,450, and 500 kPa. The key parameters measured in these tests were the operating pressure and the total flow rate, using respectively a pressure gauge and a flow meter installed in the delivery pipeline. Other measurements recorded were ambient and water temperature and relative humidity. The duration of the test was one hour for each pressure level. It is worth noting that these tests did not involve the use of the catch-cans. The flow rate-pressure data were used in Excel spreadsheet to plot the curves and regression equations were fitted.

The radial water distribution patterns were determined at only 300 and 400 kPa pressures. In this case, the total flow rate was measured and the catch-cans were used to determine the amounts of water collected along the radial length. The amount of water collected in each catch-can was determined by weighing and then converted into volumes using the water density determined by the laboratory. The

Software development and use

The INITL software was developed using ExtJs 4® framework and JavaScript, and is available online free of charge (http://143.107.212.131/initl/) in two languages, English and Portuguese. The general information of the sprinkler test, which must include the number of catch-cans and their spacings, are recorded as shown in Fig. 2.

Fig. 2 INITL software sprinkler information window

The current version of the software uses radial water distribution data, which can be entered manually or imported from Excel spreadsheet. The software processes the data and presents the following results: charts of water application rate and water volume applied along radius of throw, effective radius of throw, reconstituted flow rate and its deviation from measured flow rate. The application has a tool that simulates the uniformity of sprinklers arranged in rectangular or triangular spacing and determines the corresponding CUC (Eqn. 2). In addition, a three-dimensional rotatable chart illustrating the overlapped water applications corresponding to a given arrangement of lateral lines and sprinklers is generated (Fig. 3). Finally, all the results are automatically generated by the software in pdf format. The computational algorithm used to simulate uniformity of water application by overlapping radial distribution data is hereby briefly explained. The general idea consists of the calculation of the amount of water collected by each catch-can, considering the influence of up to 16 sprinklers around the catch-can (Fig. 4). According to the catch-can spacing and arrangement of sprinklers, an array of null values is set. Each position in the array represents a catch-can so that it records the volume of water a catch-can may receive from sprinklers. For each catch-can, the Pythagorean Theorem determines the distance between a catch-can and a sprinkler. Based on that distance, the application rate can be interpolated by a Lagrange polynomial of degree 2 (Eqn. 3):

# = # $ % (3)
where: # is the application rate at the distance , which is the distance between the sprinkler and the location where the application intensity may be calculated (target point); $ is the distance between the sprinkler and the catch-can just before the target point; ( is the distance between the sprinkler and the catch-can just after the target point; is the distance between the sprinkler and the second catch- can after the target point; # $ , # ( and # are the application intensities corresponding to the catch-cans positioned at the distances $ , ( and .

An iteration statement sums the amount of water collected by each catch-can considering that, up to 16 sprinklers may throw water inside that catch-can. If the jet length is shorter than the distance between sprinkler and catch-can, water would not reach the catch-can so that a null value is added to the cumulated value recorded in the considered position of the array. Successive iterations determine the amount of water collected by each catch-can. Finally, the array is filled with values corresponding to the amount of water in each catch-can and the CUC can be calculated.

The software has the ability to simulate sprinkler application uniformities for rectangular and triangular configurations of sprinklers. The sprinkler data collected and used in this study was used to test and validate the software, as is explained later in this paper.

Results and discussion

Intercomparison tests

The flow rate-pressure data were plotted in Excel spreadsheets (Figs. 567) and the regression analysis undertaken showed that the data fitted the power function (Table 2), with R 2 of 0.999 or better in all the results from all the participating laboratories. The value of the exponent was approximately 0.5 in all cases, which is expected for flow characteristics influenced by pressure [START_REF] Karmeli | Classification of Flow Regime Analysis of Drippers[END_REF]. The coefficients obtained varied slightly among laboratories, and ranged from 0.1000 to 0.1318.

Figs. 5-7 suggest a high degree of consistency, firstly with the three sets of data (representing each of the three sprinklers) submitted by each laboratory, and when results from all the laboratories are compared. The manufacturer's curves however were marginally above those measured by the laboratories. However, it is worth noting the manufacturer's data specified in the product brochure, is based on three pressures (300, 400 and 500 kPa) as opposed to nine pressures used by the testing laboratories. The tests to determine the flow rate-pressure curves did not require the measurement of the radial distribution of water and hence did not involve the use of catch-cans. Generally, there is less

Author-produced version of the article published in Journal of Irrigation and Drainage Engineering-ASCE, 2016, N°142(2). The original publication is available at http://ascelibrary.org Doi: 10.1061/(ASCE) IR.1943-4774.0000937 uncertainty in the measurement of flow rates and pressure in full-flow closed conduits and as a result the test data were consistent across all the four laboratories. A q = 0.1204P 0.5042 q = 0.1232P 0.4988 q = 0.1295P 0.4952 q = 0.1078P 0.5247 B q = 0.1212P 0.5038 q = 0.1215P 0.5014 q = 0.1318P 0.4929 q = 0.1025P 0.5335 C q = 0.1202P 0.5055 q = 0.1219P 0.5010 q = 0.1316P 0.4930 q = 0.1000P 0.5381 Fig. 8 shows that the shapes of all the radial water distribution profiles measured at the pressures 300 and 400 kPa are statistically similar, and according to [START_REF] Stambouli | Performance of new agricultural impact sprinkler fitted with plastic nozzles[END_REF], roughly correspond to typical profiles of sprinklers operating with two nozzles. However, the intensities obtained by IRSTEA appear to be slightly higher than the rest between 0.5 -2 m radius. This was most probably due to the effect of the shelter (Fig. 1) as explained later in this paper. The effective radius of throw was approximately 16 and 17 m at the operating pressure of 300 and 400 kPa respectively. As is typical of sprinkler tests, the intensity of water application is highest within the area closest to the sprinkler (about 0-2 m).

Radial application rate (mm/h)

Radius (m)

Average application rate

The measured total flow rates and the reconstituted flow rates (calculated using Eqn. 1) for all the tests are shown in Table 3. The mean of measured flow rates for each sprinkler, for all the tests were 2.15 m 3 /h for the 300 kPa and 2.48 m 3 /h for the 400 kPa pressures. The flow rates indicated in the manufacturer's specifications are 2.21 and 2.53 m 3 /h for the 300 and 400 kPa pressures respectively, translating to a corresponding variation of 2.7 and 2.0 %.

The ISO 15886-3 (2012) requires that the deviation of the reconstituted flow rate from the measured for a sprinkler discharging more than 0.141 L/s (0.51 m 3 /h) shall not be greater than ±5% for the results to be validated. The sprinklers tested discharged more than 2 m 3 /h, and hence in Table 3, any test with a deviation of greater than ±5% must be assumed to be invalid. The table shows that at least two results performed in each laboratory could not be validated. The two possible explanations for the results that could not be validated as per the recommendations of the ISO 15886-3 (2012) are the asymmetric coverage pattern of the impact sprinklers and uncertainty in the measurement process. As already explained, asymmetric coverage pattern may be caused by variation in the rotational speed of the sprinkler. However, as per [START_REF] Christiansen | Irrigation by sprinkling[END_REF], this was expected to have a minimal impact since the sprinklers used for the test were new and the radial water distribution was measured at the manufacturer's recommended operating pressure. Nonetheless, this poses the question of the adequacy of standard requirements compared to the capacity of laboratories to satisfy it. Further research may be required to ascertain if the threshold deviation of ±5% is too stringent.

A statistical analysis was undertaken using IBM SPSS Version 22 to assess the normality of the measured flow rates obtained from all the four participating laboratories (Table 3) for the three sprinklers at the two pressures, 300 and 400 kPa. The data are shown to be normally distributed, with a significance of ≥ 0.451 ( for small sample sizes (between 3 and 50). The results were expected to follow a normal distribution pattern since the tests were performed using the same sprinklers and under similar conditions.

Measurement uncertainty

Uncertainty is a parameter that characterises the dispersion of values caused by random and systematic errors associated with the measurement. Practically, this means that the true value of a measurement is the measured value plus or minus the uncertainty for that measurement. The procedure commonly used by metrological facilities to determine uncertainties in their measurements is described by [START_REF] Bentley | Uncertainty in measurement: the ISO guide[END_REF].

As mentioned earlier, the uncertainty in the measurement process is a probable reason why some of the results in Table 3 could not be validated in accordance with ISO 15886-3 (2012). This could be as a result of inaccuracies of the equipment used to measure flow rate and pressure (for instance pressure gauge, water meter, stop watch and measuring scale). This intercomparison exercise thus provided the participating laboratories with data necessary to further audit their measurement uncertainties and potentially improve the quality of testing. Although the general principles for the determination of measurement uncertainty for the sprinkler tests would be similar across all the laboratories that participated in the intercomparison tests, uncertainty budgets relate to the actual test procedures followed and the set of equipment used.

Consequently, the uncertainty budgets for the intercomparison tests would be different in each laboratory. These budgets have not been included in this paper, but a brief discussion on uncertainty in measurement is necessary in order to understand the results presented, and especially any disparities noted.

The procedure for determining the reconstituted volume, both the ISO 15886-3 method and the method proposed in this study, comes with some uncertainty. This is because the water collected in each catch-can is assumed to apply equally to the corresponding portion of area in the determination of the reconstituted volume and ultimately flow rate. Another potential source of error is the enclosure (Fig. 1) used around the sprinkler to direct the stream of water from the sprinkler into a smaller area of the laboratory. It is possible that the enclosure may affect air circulation and possibly the droplet size and may intercept some of the jet trajectory. Perhaps more importantly, if the window of the shelter is smaller and restricts part of the stream from exiting, the radial water distribution and hence the reconstituted flow rate will be affected. The shapes of the radial water distribution patterns measured by IRSTEA (Fig. 8) may suggest that the window of the shelter was not large enough to allow the passage of the entire jet or that water was splashing from inside the shelter and reaching the first collectors, hence increase in the catch-can volumes around the sprinkler (0.5 -2 m). This study has identified the effect of the enclosure on the hydraulic characteristics of the sprinkler jet as area that requires further research. IRSTEA laboratory has been correcting this factor using a shelter that is not covered and present a wider opening window.

INITL software test and validation

The radial water distribution profiles, the reconstituted flow rates and their deviations from the measured flow rates generated by the INITL software were compared with those processed using Excel spreadsheet (Fig. 8 and Table 3) and were found to be identical. software, the sprinkler uniformity performance indicators (CUC) obtained were compared with the results simulated using the commercial software SPACE PRO TM [START_REF] Oliphant | SPACE PROTM Installation and Operation Manual[END_REF]. This was undertaken using radial distribution profile data collected by IRSTEA and INCT-EI for Sprinkler A at a pressure of 300 kPa, with both rectangular and triangular sprinkler patterns being simulated (Table 5). The distances between sprinkler heads and laterals were kept identical, and ranged from 14 to 24 m. The results are shown in Table 5 to be highly correlated, with the maximum deviation being determined to be 1.3 %. The most likely causes of the slight differences in the results are interpolation algorithm and rounding off errors.

  and Hydraulics Technology Centre (AIHTC) is based at the University of South Australia, Adelaide and the primary focus includes testing of irrigation and hydraulic equipment. The facility is accredited to the NATA in the field of meteorology and complies with the requirements of ISO/IEC 17025 (2005). The facility has been appointed by the Australian Commonwealth's National Measurement Institute (NMI) as an approving and verification authority for water meters. IWHR Beijing, China The China Institute of Water Resources and Hydropower Research (IWHR) is based in Beijing, China and conducts hydraulic tests among other tests. The main functions of the facility are: (i) certification of irrigation equipment and other devices to local, national and international standards; (ii) laboratory and in situ tests of irrigation equipment; (iii) formulation of test procedures and revision of local and national standards; and (iv) training and research. The irrigation testing laboratory is located in the National Institute of Science and INCT-EI/ESALQ/USP Piracicaba, Brazil Technology in Irrigation Engineering (INCT-EI), Luiz de Queiroz College of Agriculture (ESALQ/USP), Piracicaba, Brazil. The laboratory has been undertaking accredited irrigation tests since 2010, as well as applied research in irrigation. The laboratory is accredited to the Cgcre /Inmetro and complies with the requirements of ISO/IEC 17025 (2005). IRSTEA Aix en Province, France The National Institute of Science and Technology for Environment and Agriculture (IRSTEA) is located in Aix en Province, France, and undertakes tests and research on irrigation equipment and practices, including sprinkler systems, drip systems, fluid mechanics and hydraulic modelling. A recent research outcome which is subject to a patent approval is the design of an emitter that is resistant to most of the forms of clogging. Regarding drip irrigation, the laboratory tests the hydraulic characteristics of drippers and their manufacturing variability. The facility's quality system complies with the requirements of ISO/IEC 17025 (2005), certified by external body.

Fig. 1

 1 Fig. 1 Sprinkler test setup

  version of the article published in Journal of Irrigation and Drainage Engineering-ASCE, 2016, N°142(2). The original publication is available at http://ascelibrary.org Doi: 10.1061/(ASCE)IR.1943-4774.0000937

  evaporative loss was estimated by placing a volume of water in one catch-can in the vicinity of the test, and measuring the mass of water at the start and at the end of the test. The evaporative loss was taken as the difference between mass measured before and at the end of the test, and was added to the amount collected in each catch-can. The ambient and water temperature and relative humidity data were also taken for these tests. The test duration was one hour for all the tests. The irrigation intensity was determined as the volume of water in each catch-can divided by the test duration (one hour). The radial distribution of water was determined by plotting the application rate or irrigation intensity against the radial distance from the sprinkler. Eqn. 1 was used to determine the reconstituted flow rate, and hence the validity of the test results. The statistical analysis of the data was undertaken using the software IBM SPSS Version 22.Author-produced version of the article published in Journal of Irrigation and Drainage Engineering-ASCE, 2016, N°142(2). The original publication is available at http://ascelibrary.org Doi: 10.1061/(ASCE)IR.1943-4774.0000937

Fig. 3

 3 Fig. 3 Chart displaying the overlapped application profiles of four sprinklers arranged in a square

Fig. 4

 4 Fig. 4 Schematic of the logic used for estimating the amount of water collected by each catch-

  Author-produced version of the article published in Journal of Irrigation and Drainage Engineering-ASCE, 2016, N°142(2). The original publication is available at http://ascelibrary.org Doi: 10.1061/(ASCE)IR.1943-4774.0000937

Fig

  Fig. 5 Pressure-flow rate curves for sprinkler A

Fig

  Fig. 8. Radial distribution of water

  outlines a method and criteria for validating test results based on a comparison between the measured and the reconstituted flow rate of the sprinkler. The reconstituted flow rate (Q re ) is determined as follows:

	Author-produced version of the article published in Journal of Irrigation and Drainage Engineering-ASCE, 2016, N°142(2).
	The original publication is available at http://ascelibrary.org
	Doi: 10.1061/(ASCE)IR.1943-4774.0000937

Table 1

 1 Author-produced version of the article published in Journal ofIrrigation and Drainage Engineering-ASCE, 2016, N°142(2). The original publication is available at http://ascelibrary.org Doi: 10.1061/(ASCE)IR.1943-4774.0000937 impact sprinklers, NaanDanJain Model 234 1 with two nozzles: 5 and 3.2 mm diameter, hereafter referred to as Sprinklers A, B and C. The same three sprinklers were successively tested in all the participating laboratories (in France, Brazil, China and Australia) in accordance with ISO 15886 -3 (2012) -Agricultural irrigation equipment -sprinklers -Part 3: Characterisation of distribution and test methods. The manufacturer's technical specifications for this sprinkler model are detailed inNAANDANJAIN Irrigation (2013). This document specifies that the expected flow rates of this sprinkler model at operating pressure of 300, 400 and 500 kPa are 2.210, 2.530 and 2.840 m 3 /h respectively. List of INITL members that participated in the sprinkler testing

  -produced version of the article published in Journal of Irrigation and Drainage Engineering-ASCE, 2016, N°142(2). The original publication is available at http://ascelibrary.org Doi: 10.1061/(ASCE)IR.1943-4774.0000937

  Author-produced version of the article published in Journal of Irrigation and Drainage Engineering-ASCE, 2016, N°142(2).

	The original publication is available at http://ascelibrary.org
	Doi: 10.1061/(ASCE)IR.1943-4774.0000937

  Author-produced version of the article published in Journal of Irrigation and Drainage Engineering-ASCE, 2016, N°142(2).

	The original publication is available at http://ascelibrary.org
	Doi: 10.1061/(ASCE)IR.1943-4774.0000937

Table 2

 2 Pressure-flow rate sprinkler regression equations

	Sprinkler	Laboratory
	IRSTEA	INCT-EI	IWHR	AIHTC

Table 3 -Measured and reconstituted flow rate, and the deviation

 3

	Laboratory Sprinkler	Pressure	Measured flow	Reconstituted	Deviation
			(kPa)	rate (m 3 /h)	flow rate (m 3 /h)	(%)
		A	300	2.14	2.34	9.35
		B	300	2.14	2.27	6.07
		C	300	2.14	2.38	11.2
	IRSTEA
		A	400	2.48	2.48	0.00
		B	400	2.48	2.71	9.27
		C	400	2.48	2.54	2.42
		A	300	2.11	2.19	3.94
		B	300	2.10	2.19	4.43
		C	300	2.12	2.28	7.89
	INCT-EI
		A	400	2.43	2.61	7.24
		B	400	2.43	2.50	2.59
		C	400	2.43	2.58	6.38
	IWHR	A	300	2.18	2.33	6.88

  Table 4). The Shapiro-Wilk's statistic was used because it is recommended Author-produced version of the article published in Journal of Irrigation and Drainage Engineering-ASCE, 2016, N°142(2). The original publication is available at http://ascelibrary.org Doi: 10.1061/(ASCE)IR.1943-4774.0000937

Table 4 -Shapiro-Wilk test for normality of measured flow rates

 4

	Sprinkler	Pressure (kPa)	Statistic	Sig. 1
		300	0.923	0.555
	A
		400	0.904	0.451
		300	0.993	0.971
	B
		400	0.943	0.675
		300	0.976	0.88
	C
		400	0.942	0.668
	¹ Sig. > 0.05 represents a group of data normally distributed

  Author-produced version of the article published in Journal of Irrigation and Drainage Engineering-ASCE, 2016, N°142(2). The original publication is available at http://ascelibrary.org Doi: 10.1061/(ASCE)IR.1943-4774.0000937

  To further validate theAuthor-produced version of the article published in Journal of Irrigation and Drainage Engineering-ASCE, 2016, N°142(2). The original publication is available at http://ascelibrary.org Doi: 10.1061/(ASCE)IR.1943-4774.0000937

Table 5 -Comparison of the CUC values obtained using the SPACE PRO TM and the INITL software

 5 ConclusionsAuthor-produced version of the article published in Journal ofIrrigation and Drainage Engineering-ASCE, 2016, N°142(2). The original publication is available at http://ascelibrary.org Doi: 10.1061/(ASCE)IR.1943-4774.0000937 The sprinkler intercomparison tests undertaken by INITL in 2013 to 2014 involved four laboratories in Australia, Brazil, China and France. The flow rate-pressure profiles fitted a power function with R 2 of 0.999 or better. The value of the exponent was approximately 0.5, which is consistent with values quoted in literature. It can be concluded that, after some minor adaptations and modifications in the protocol, the four laboratories have consistent and accurate measurement facilities. The radial distribution patterns were similar, while the average flow rates measured at 300 and 400 kPa pressures were 2.15 and 2.48 m 3 /h respectively, which translated to a variation of 2.7 and 2% from the values quoted in the manufacturer's specifications. The reconstituted flow rates for at least two tests (at 300 and 400 kPa) in each laboratory could not be validated, most probably due to asymmetric sprinkler coverage pattern, measurement uncertainties and the influence of the sprinkler shelter. The sprinkler simulation software developed by INITL was tested and validated in this study, and the uniformity results were found to be consistent with those obtained using the commercial software SPACE PRO TM . The INITL software is available free of charge at http://143.107.212.131/initl/.

	Spacing (m)			Christiansen Uniformity Coefficient -CUC (%)
			IRSTEA Sprinkler A, 300 kPa		INCT-EI Sprinkler A, 300 kPa
		Rectangular pattern	Triangular pattern	Rectangular pattern	Triangular pattern
		SPACE		SPACE		SPACE		SPACE
		PRO TM	INITL	PRO TM	INITL	PRO TM	INITL	PRO TM	INITL
	14 x 14	86	85.4	90	89.7	90	89.7	92	92.1
	15 x 15	85	84.6	89	88.8	85	85.2	90	89.7
	16 x 16	85	84.6	87	86	84	83.4	87	86.5
	17 x 17	86	85.4	84	83.2	83	82.8	83	82.6
	18 x 18	87	86	83	82.2	83	83.1	80	79.9
	19 x 19	86	84.9	82	81.7	84	83.3	79	78.6
	20 x 20	85	84.5	84	83.2	83	82.7	79	78.3
	21 x 21	84	83.3	85	84.9	83	83.3	80	79.7
	22 x 22	83	82.1	86	85.1	83	82.8	82	82.2
	23 x 23	80	79.6	84	83.3	82	81.6	84	84.2
	24 x 24	77	75.7	80	79.1	82	81.3	86	85.9

The mention of the sprinkler model is for the purpose of clarity only, and does not imply recommendation, endorsement or otherwise on the part of the authors.Author-produced version of the article published in Journal of Irrigation and Drainage Engineering-ASCE,

2016, N°142(2). The original publication is available at http://ascelibrary.org Doi: 10.1061/(ASCE)IR.1943-4774.0000937

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Author-produced version of the article published in Journal of Irrigation and Drainage Engineering-ASCE, 2016, N°142(2). The original publication is available at http://ascelibrary.org Doi: 10.1061/(ASCE)IR.1943-4774.0000937

Author-produced version of the article published in Journal of Irrigation and Drainage Engineering-ASCE, 2016, N°142(2). The original publication is available at http://ascelibrary.org Doi: 10.1061/(ASCE) IR.1943-4774.0000937