Hydrodynamic modeling for determining pore properties of a screening device

Abstract

According to an example, an apparatus can include a processor that can access a digital design of a screening device having a pore, where the screening device can be used to filter a liquid from a slurry composed of the liquid and a material element. The processor can further apply a fluid dynamics modeling to the digital design of the screening device to model how the liquid is predicted to flow through the screening device during application of a pressure through the screening device, where the fluid dynamics modeling is applied to a plurality of digital designs of the screening device having various pore properties with respect to one another; and based on the applied fluid dynamics modeling, a pore property of the various pore properties can be determined that is predicted to result in a component being formed with an optimized attribute and / or the component being formed within a minimum length of time.

Description

BACKGROUND

[0001] Various types of products can be made from pulp material. In particular, a pulp molding mold including a body and a wire mesh can be immersed in a pulp of a material, and the material in the pulp can form a shape of the body and the wire mesh. The body and the wire mesh can have a desired shape of a product to be formed, and thus can have a complex shape. The body and the wire mesh can include a number of pores for liquid passage, where the pores in the wire mesh can be significantly smaller than the pores in the body. During formation of the product, a vacuum force can be applied through the pulp molding mold, which can cause the material in the pulp to be drawn onto the wire mesh and form a shape matching that of the pulp molding mold. The material can be removed from the wire mesh and can be solidified to have the desired shape. BRIEF DESCRIPTION OF DRAWINGS

[0002] Features of the present disclosure are illustrated by way of example and not limited to the following figure(s) in which like numerals refer to like elements in which:

[0003] Figure 1 A block diagram of an example device that can determine pore properties of an example screening device is shown;

[0004] Figure 2A and 2B Cross-sectional side views of example pulp molding molds in which the example screening devices discussed with respect to Figure 1 may be implemented are depicted;

[0005] Figure 3 An example 3D manufacturing system that can be used to manufacture Figure 2A and 2B the screening devices depicted is shown;

[0006] Figure 4 A flowchart of an example method for determining pores having a first property or a second property that is predicted to result in a component being formed with better attributes and / or the component being formed in a shorter length of time for manufacturing a screening device is shown; and

[0007] Figure 5 A block diagram of a computer-readable medium that can have stored thereon computer-readable instructions for selecting a digital design of a screening device that is predicted to result in a component being formed with better attributes and / or the component being formed in a shorter length of time for manufacturing a screening device is shown. DETAILED DESCRIPTION

[0008] For purposes of simplicity and illustration, the present disclosure is described by primarily referencing examples. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure. It will be readily apparent to one skilled in the art, however, that the present disclosure can be practiced without limitation to these specific details. In other instances, some methods and structures have not been described in detail in order not to unnecessarily obscure the present disclosure.

[0009] Throughout the present disclosure, the terms "a" and "one" are intended to denote at least one of a particular element. As used herein, the term "includes" means includes but not limited to, the term "including" means including but not limited to. The term "based on" means based at least in part on.

[0010] Disclosed herein are apparatuses that can determine properties of pores of a screening device that can be used to filter a liquid from a slurry composed of the liquid and material elements to form a part from the material elements that are compacted onto the screening device by exerting a vacuum force on the slurry via the screening device. Also disclosed herein are methods and computer readable media that can determine the properties of the pores.

[0011] As discussed herein, a processor of the apparatus can determine properties of pores of a screening device that can be a component of a pulp molding mold (or equivalently, a mold tool set), which can result in a part formed on the screening device having optimized attributes and / or the part being formed in a shortest length of time. The attributes can be, for example, a level of precision of the part, an amount of material used to form the part, and / or the like. An optimized level of precision can correspond to a part that most closely matches a design of the part. An optimized amount of material can be a minimum amount of material that can be used to form the part while satisfying a minimum expected structural attribute of the part.

[0012] The processor can determine the properties by applying a fluid dynamics modeling to various versions of a digital design of the screening device, where the various versions can include pores having various properties relative to each other. The various properties can include, for example, a size of the pores, a shape of the pores, a location of the pores, a density of the pores positioned across the screening device, and / or the like. The processor can also analyze results of the fluid dynamics modeling of the various versions to determine resulting properties and / or a length of time predicted to be consumed in forming the part of the various versions. The processor can further determine which of the resulting properties of the various versions is a better property and / or which of the various versions is predicted to result in the part being formed in a minimum length of time among the various versions.

[0013] The processor can design the screening device to be manufactured with pores having properties that are determined to result in the attributes being optimized and / or a length of time to form the part being reduced or minimized. Further, the processor can cause and / or control a manufacturing system to manufacture the screening device having the design.

[0014] By implementing features of the present disclosure, the porosity in a 3D manufactured screening device can be designed such that components formed on the screening device can be manufactured in an efficient manner. For example, a 3D manufactured screen can be designed with porosity having properties that enable components to be formed precisely in an efficient manner of material usage, reduced or minimized length of time, and / or the like.

[0015] Reference is first made to Figure 1 , 2A and 2B. Figure 1 A block diagram of an example device 100 is shown that can determine porosity properties of an example screening device 202 to be generated. Figure 2A and 2B respectively show cross-sectional side views of an example pulp molding mold 200 in which an example screening device 202 discussed with respect to Figure 1 may be implemented. It should be understood that, Figure 1 the example device 100 and / or Figure 2A and 2B the example pulp molding mold 200 depicted can include additional features and some features described herein can be removed and / or modified without departing from the scope of the device 100 and / or pulp molding mold 200.

[0016] The device 100 can be a computing system, such as a server, a laptop computer, a tablet computer, a desktop computer, and / or the like. As shown, the device 100 can include a processor 102, which can be a semiconductor-based microprocessor, a central processing unit (CPU), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), and / or other suitable hardware devices. The device 100 can also include a memory 110 on which the processor 102 can execute machine-readable instructions (which can also be referred to as computer-readable instructions). The memory 110 can be an electronic, magnetic, optical, or other physical storage device comprising or storing executable instructions. The memory 110 can be, for example, a random access memory (RAM), an electrically erasable programmable read-only memory (EEPROM), a storage device, an optical disc, and / or the like. The memory 110, which can also be referred to as a computer-readable storage medium, can be a non-transitory machine-readable storage medium, where the term “non-transitory” does not encompass transitory propagating signals.

[0017] Although device 100 is depicted as having a single processor 102, it should be understood that device 100 may include additional processors and / or cores without departing from the scope of device 100. In this regard, references to a single processor 102 and a single memory 110 can be understood to additionally or alternatively refer to multiple processors 102 and multiple memories 110. Furthermore, or alternatively, processor 102 and memory 110 may be integrated into a single component, such as an integrated circuit on which processor 102 and memory 110 may be provided.

[0018] like Figure 1 As shown, memory 110 may store machine-readable instructions 112-116 executable by processor 102. Although instructions 112-116 are described herein as being stored on memory 110 and thus may comprise a set of machine-readable instructions, device 100 may include hardware logic blocks capable of performing functions similar to instructions 112-116. For example, processor 102 may include hardware components capable of executing instructions 112-116. In other examples, device 100 may include combinations of instructions and hardware logic blocks to implement or perform functions corresponding to instructions 112-116. In any of these examples, processor 102 may implement hardware logic blocks and / or execute instructions 112-116. As discussed herein, device 100 may also include additional instructions and / or hardware logic blocks, enabling processor 102 to perform functions beyond those described above. Figure 1 Operations or executions other than those discussed above can replace the above-mentioned operations. Figure 1 The operations discussed.

[0019] Processor 102 can execute instructions 112 to access a digital design of a screening device 202 having pores 204, wherein the screening device 202 can be used to filter liquid from a slurry composed of a liquid and material elements to form parts from the material elements. In some instances, the liquid can be water or another suitable type of liquid, wherein pulp materials, such as paper, wood, fiber crops, bamboo, etc., can be mixed into a slurry. The material elements can be, for example, fibers of pulp materials.

[0020] In addition to the pores 204, the screening device 202 may include structures 206 such that, for example, the pores 204 can be formed between the structures 206. According to examples, the structures 206 can be formed by fusing build material particles together by a 3D manufacturing system during a 3D manufacturing process. In these examples, the build material particles can be any suitable type of material that can be used in 3D manufacturing processes, such as metals, plastics, nylon, ceramics, alloys, and / or the like. In some examples, the screening device 202 can be formed to have a relatively thin height and can be relatively flexible. In other examples, the structures 206 can be formed by implementing another manufacturing technique. For example, the structures 206 can be formed by selective laser ablation, selective laser melting, stereolithography, fused deposition modeling, and / or the like.

[0021] The pulp modeling mold 200 may also include a body 210 on which the screening device 202 may be covered. The body 210 may be formed to have a relatively greater thickness than the screening device 202 and may be much more rigid than the screening device 202. The body 210 can therefore provide structural support for the screening device 202. The body 210 may also be formed of solid portions 212 and open portions 214. The solid portions 212 may be formed of a substantially rigid material, such as metal, plastic, ceramic, and / or the like. Furthermore, the open portions 214 may be formed between the solid portions 212 using any suitable manufacturing technique. For example, the open portions 214 (which may also be referred to herein as openings, pores, through holes, etc.) may be formed by 3D manufacturing processes, drilling, using molds, and / or the like. In any of these examples, the open portions 214 may extend from one side of the body 210 to the opposite side of the body 210. In some examples, the body 210 and the screening device 202 may be formed together during a 3D manufacturing process.

[0022] Based on the example, and as follows Figure 2A and 2B As shown, the opening 214 can have a circular cross-section, and its diameter can be relatively larger than that of the pore 204. In other examples, the opening 214 can have other shapes, such as rectangular, elliptical, triangular, etc. In operation, when the pulp molding die 200 is immersed in the pulp or slurry 220 containing the material, a vacuum pressure can be applied from the side of the body 210 opposite to the screening device 202. As the liquid in the pulp or slurry flows through the pores 204 in the screening device 202 and the opening 214 in the body 210 as indicated by arrow 222, the material 224 in the pulp or slurry can be compressed into the screening device 202 and can take the shape of the screening device 202. In particular, when the liquid is extracted from the slurry 220 and the remaining material 224 is dried, the material 224 can be formed into a portion of the screening device 202.

[0023] In some examples, because the pores 204 in the screening device 202 may not be precisely aligned with the openings 214 in the body 210, the screening device 202 and / or the body 210 may include channels that allow liquid to flow between portions of the device 100 and the body 210 that may come into contact with each other. Thus, channels allow pressure to be applied through a greater number of pores 204, thereby causing liquid to flow through a greater number of pores 204.

[0024] The digital design of the screening device 202 can be a computer model of the screening device, such as a computer-aided design (CAD) file, or other digital representation of the screening device 202. Furthermore, the processor 102 can access the digital design from a data memory (not shown) or some other suitable source.

[0025] Processor 102 can execute instructions 114 to apply fluid dynamics modeling to the digital design of screening device 202, thereby modeling how slurry 220 is predicted to flow through screening device 202 during the application of pressure (e.g., vacuum pressure) through screening device 202. Specifically, for example, processor 102 can apply fluid dynamics modeling to multiple digital designs of screening device 202 that have various porosity properties to predict properties corresponding to the part to be formed and / or predict the length of time consumed in forming that part. The predicted flow rate through screening device 202 may include the predicted rate and direction of liquid and / or material elements flowing through pore 204 during the application of vacuum pressure through pore 204. Furthermore, fluid dynamics modeling can be applied to a particular type of slurry 220 and / or multiple types of slurries having, for example, different concentrations of material 224 and liquid.

[0026] By way of example, processor 102 can apply first fluid dynamics modeling to the digital design of a screening device 202 with pores 204 having a first property, to model how the slurry 220 will be predicted to flow through the screening device 202 when a vacuum pressure is applied, for example, as Figure 2B As shown. Furthermore, processor 102 can apply second fluid dynamics modeling to the digital design of the screening device 202 with pores 204 having a second property, to model how the slurry 220 will be predicted to flow through the screening device 202 when a vacuum pressure is applied. Processor 102 can apply additional fluid dynamics modeling to the digital design of the screening device with other properties, to model how the slurry 220 will be predicted to flow through the screening device 202 when a vacuum pressure is applied.

[0027] According to examples, the various pore properties can be size, shape, number, and / or location on the sieve device 202 at which the pores 204 are formed. These sizes can include sizes in which the pores are completely closed, such as locations on which no pores are provided. Thus, for example, the processor 102 can apply the fluid dynamics modeling to digital design versions of the sieve device 202 that can have different pore properties and pore granularity levels. In some examples, the processor 102 can also apply the fluid dynamics modeling to a reference version of the sieve device 202 having a uniform distribution of the pores 204 to determine a reference performance dataset.

[0028] In some examples, a first fluid dynamics modeling can be performed on a digital design of the sieve device 202 having pores 204 of a first size, a second fluid dynamics modeling can be performed on a digital design of the sieve device 202 having pores 204 of a second size, and so on. As another example, a first fluid dynamics modeling can be performed on a digital design of the sieve device 202 having pores 204 of various sizes and arranged in a first configuration (e.g., a first density), a second fluid dynamics modeling can be performed on a digital design of the sieve device 202 having pores 204 of other various sizes and arranged in a second configuration (e.g., a second density), and so on. The various sizes and / or configurations used in the fluid dynamics modeling can be determined automatically, such as by using a digital sieve device having a plurality of different pore sizes and / or configurations, and analyzing each iteration to determine the pore size and / or configuration that results in the properties being optimized and / or the length of time to form the component being reduced or minimized.

[0029] By way of example, the processor 102 can start the fluid dynamics modeling on a reference version of the sieve device 202, and can output data encoded in a manner to guide the design of an optimized version of the sieve device 202. In this example, areas of relatively low flow can be highlighted with one color, areas of relatively high flow can be highlighted with another color, and the pore sizes can be adjusted based on the designated colors of these areas.

[0030] Thus, for example, the processor 102 can apply the fluid dynamics modeling to various versions of the digital design of the sieve device 202, where the pores 204 in the various versions can have consistent properties relative to one another, or can have any of a variety of properties relative to one another. In some examples, the processor 102 can perform the fluid dynamics modeling iteratively on the various versions, where a certain number of iterations can be performed. This particular number of iterations can be a predefined number of iterations, a number of iterations that can be performed over a predefined period of time, a number of iterations that can be deemed to reach an optimized result, and / or the like.

[0031] Additionally or in other examples, the processor 102 can determine various properties to test in the fluid dynamics modeling based on results of previous fluid dynamics modeling. For example, the processor 102 can determine that certain pore sizes can result in poor results, and thus can increase the pore sizes until the results no longer become better. By way of example, the processor 102 can determine from the modeling that a certain pore size is predicted to result in a predicted flow rate through the pores 204 that is below an expected level. In further iterations, the processor 102 increases the size of some or all of the pores 204 until, for example, the processor 102 determines from the modeling that elements of the material 224 (e.g., fibers) are predicted to flow into the pores 204 at greater than an expected level.

[0032] In some examples, the fluid dynamics modeling employed can model how the slurry 220 is predicted to flow through the screening device 202 as the material elements begin to clog some of the pores 204 during formation of the component. That is, as the liquid in the slurry 220 is drawn through the pores 204, some of the material elements can block or can enter and can clog some of the pores 204. The fluid dynamics modeling can model this behavior in predicting the flow through the pores 204 of the screening device 202.

[0033] According to examples, the processor 102 can employ any suitable application that can perform fluid dynamics modeling. For example, the processor 102 can execute a computational fluid dynamics application on various versions of the digital design to model how the slurry 220 is predicted to flow through the screening device 202 under various pore property scenarios. The application can be an application specifically designed to model the behavior of the slurry 220 with respect to the digital design of the screening device 202, or a general fluid dynamics modeling application that is programmed to model the behavior of the slurry 220.

[0034] The processor 102 can execute the instructions 116 to determine, based on the fluid dynamics modeling applied, a pore property of the various pore properties that is predicted to result in the component being formed with optimized attributes and / or the component being formed in a shortest length of time. That is, the processor 102 can analyze results of the fluid dynamics modeling applied to various versions of the digital design of the screening device 202. The results can include, for example, a level of accuracy predicted for the component to be formed, an amount of material 224 predicted to be used to form the component having a predefined level of accuracy, a length of time predicted to be consumed to form the component on the screening device 202, and / or the like.

[0035] The optimized attributes can be, for example, a highest level of accuracy in the modeling results, a minimized use of the material 224 in the modeling results, and / or the like. Additionally, the minimized length of time can be a minimum length of time predicted to be consumed to form the component on the screening device 202 in the modeling results.

[0036] According to examples, the processor 102 can determine the pore properties that the screening device 202 is to form as the pore properties that are predicted to result in the component being formed with optimized properties and / or the component being formed in a minimum length of time. As discussed herein, the pore properties can include size, shape, number, location, etc., and thus, for example, the determined pore properties can indicate locations on the screening device 202 at which a certain number of pores 204 are to be formed, as well as the size and / or shape of the pores 204, where different locations can be indicated as having different numbers of pores 204 formed thereon relative to one another.

[0037] According to examples, the processor 102 can also access the digital design of the body 210, and can apply fluid dynamics modeling to both the digital design of the screening device 202 and the digital design of the body 210. In other words, in some examples, the processor 102 can apply fluid dynamics modeling to the digital design of the screening device 202 alone, while in other examples, the processor 102 can apply fluid dynamics modeling to both the digital design of the screening device 202 and the digital design of the body 210. As flow through the body 210 can affect flow through the screening device 202, applying fluid dynamics modeling on the combination of the screening device 202 and the body 210 can result in results that can be different from the results achieved by applying fluid dynamics modeling on the screening device 202 alone.

[0038] In examples in which fluid dynamics modeling is applied to the digital designs of both the screening device 202 and the body 210, the processor 102 can apply fluid dynamics modeling as discussed above to both the digital design of the screening device 202 and the digital design of the body 210 to model how the slurry 220 is predicted to flow through the screening device 202 as well as through the screening device 202 and the body 210. In addition, the processor 102 can determine the properties of the openings (opening portions 214) that are to be formed through the body 210 based on the applied fluid dynamics modeling, which will result in the component being formed with optimized properties and / or the component being formed in a minimum length of time. Thus, for example, in addition to various pore properties in the screening device 202, the processor 102 can determine the results of various properties of the opening portions 214 in the body 210, and can determine the properties that are predicted to result in the component being formed with optimized properties and / or the component being formed in a minimum length of time in the modeling results.

[0039] According to an example, the processor 102 can cause a three-dimensional (3D) manufacturing system to manufacture the screening device 202 with the porosity 204 having the determined porosity property(s). Further, the processor 102 can cause the 3D manufacturing system to manufacture the body 210 to have the open portion 214, thereby having the open determined property(s). Figure 3 An example of a suitable 3D manufacturing system 300 that can be used to manufacture the screening device 202 and, in some examples, the body 210 is depicted in FIG. 3. It should be appreciated that the 3D manufacturing system 300 depicted in FIG. 3 can include additional features, and some of the features described herein can be removed and / or modified without departing from the scope of the 3D manufacturing system 300. Figure 3 The example 3D manufacturing system 300 depicted in FIG. 3 can include additional features, and some of the features described herein can be removed and / or modified without departing from the scope of the 3D manufacturing system 300.

[0040] The build material particles 302 can be formed into the build material layer 304 on the build platform 306 during the manufacture of the screening device 202 and, in some examples, the body 210. The build material particles 302 can include any suitable material for forming 3D objects, such as a polymer, a plastic, a ceramic, a nylon, a metal, combinations thereof, and the like, and can be in the form of a powder or a powder-like material. According to one example, a suitable build material can be a PA12 build material commercially known as V1R10A “HP PA12” available from HP Inc. In another example, a suitable build material can be a PA11 build material commercially available from HP Inc.

[0041] As shown, the 3D manufacturing system 300 can include a recoater 308 that can spread, spray, or otherwise form the build material particles 302 into the build material layer 304 as the recoater 308 is moved (e.g., scanned) across the build platform 306 as indicated by arrow 310. According to an example, the build platform 306 can provide a build area for the build material particles 302 to be spread into a successive layer 304 of build material particles 302. The build platform 306 can be movable in a direction away from the recoater 308 during the formation of the successive build material layer 304.

[0042] According to an example, the 3D manufacturing system 300 can include a platform 312 or multiple platforms 312, 314 from which the build material particles 302 can be supplied to be formed into the build material layer 304. For example, the platform 312 can provide an amount of build material particles 302 on top of the platform 312 that the recoater 308 can push onto the build platform 306 to form the build material layer 304 on the build platform 306 or on a previously formed build material layer 304 as the recoater 308 is moved across the build platform 306 as indicated by arrow 310.

[0043] As shown, the processor 102 can control operation of the re-coater 308. However, in other examples, the 3D manufacturing system 300 can include a separate controller (not shown) that can control operation of the re-coater 308, where the processor 102 can communicate with the controller. The processor 102 and / or the controller 320 can control other components of the 3D manufacturing system 300. For example, the 3D manufacturing system 300 can include a manufacturing component 330, and the memory 110 can have instructions that the processor 102 or the controller can execute to control the manufacturing component 330. In particular, the processor 102 or the controller can control the manufacturing component 330 to cause the build material particles 302 at the selected locations of the build material layer 304 to bind and / or fuse together to form the structure 206 of the screening device 202 in the build material layer 304.

[0044] The manufacturing component 330 can include a reagent delivery device that the processor 102 can control to selectively deliver a reagent onto the build material layer 304. For example, the processor 102 can control the reagent delivery device to deliver a fusing agent onto selected locations of the build material layer 304 that are to be bound / fused together to form the structure 206. As a particular example, the reagent delivery device can be a print head having a plurality of nozzles, where droplet ejectors such as resistors, piezoelectric actuators, and / or the like can be provided to eject droplets of the reagent through the nozzles.

[0045] According to an example, the reagent can be a fusing agent and / or a binding agent to selectively bind and / or solidify the build material particles 302 on which the reagent has been deposited. In particular examples, the reagent can be a chemical binding agent, a heat-cured binding agent, and / or the like. In other particular examples, the reagent can be a fusing agent that can increase absorption of energy to selectively melt the build material particles 302 on which the reagent has been deposited.

[0046] According to an example, a suitable fusing agent can be an ink-type formulation including carbon black, such as for example, a fusing agent formulation commercially known as V1Q60A “HP Fusing Agent” available from HP Inc. In one example, such a fusing agent can additionally include an infrared light absorber. In one example, such a fusing agent can additionally include a near-infrared light absorber. In one example, such a fusing agent can additionally include a visible light absorber. In one example, such a fusing agent can additionally include an ultraviolet light absorber. Examples of fusing agents including visible light enhancers are dye-based color inks and pigment-based color inks, such as inks commercially known as CE039A and CE042A available from HP Inc.

[0047] The manufacturing component 330 can also include another reagent delivery device that the controller 320 can control to selectively deliver another type of reagent onto the build material layer 304. The other type of reagent can be a detailing agent that can inhibit or prevent fusion of the build material particles 302 on which the detailing agent is deposited, for example, by modifying the effect of the fusing agent. According to one example, a suitable detailing agent can be a formulation commercially known as V1Q61A "HP Detailing Agent" available from HP Inc.

[0048] By way of example, the processor 102 can control the other reagent delivery device to selectively deposit the detailing agent onto areas of the build material layer 304 that are not to be fused. For example, the processor 102 can control the other reagent delivery device to deposit the detailing agent onto areas of the layer 304 adjacent to areas that are to be fused together to form the structure 206 of the device 100. Further, the processor 102 can control the other reagent delivery device to deposit the detailing agent onto the build material particles 302 located in areas of the layer 304 that are to remain unfused and form the pores 204 of the screening device 202 to have determined porosity properties. By implementation of the manufacturing component 330, the processor 102 can cause the pores 204 to be formed to be relatively small in diameter, for example, on the order of 0.2 mm to about 1 mm. In other examples, the processor 102 can cause the pores 204 to be formed in other shapes, for example, rectangular, triangular, oval, etc.

[0049] The manufacturing component 330 can also include an energy source that can apply energy, for example, heating energy, to the build material layer 304, for example, to heat the build material particles 302 in the build material layer 304 to a desired temperature. The energy source can output energy, for example, in the form of light and / or heat, and can be supported on a carriage that can be moveable across the build platform 306. In this way, for example, the energy source can output energy onto the build material layer 304 as the carriage is moved across the build platform 306 to cause the build material particles 302 on which the fusing agent is deposited to melt and subsequently fuse together.

[0050] According to an example, the processor 102 can control movement of the manufacturing component 330. That is, for example, the controller 320 can control actuators, motors, etc. that can control movement of the manufacturing component 330 across the build platform 306. As shown, the 3D manufacturing system 300 can include a mechanism 332 along with the manufacturing component 330, for example, a carriage on which the manufacturing component 330 can be supported, can be moved across the build platform 306. The mechanism 332 can be any suitable mechanism by which and / or by which the carriage can be moved. For example, the mechanism 332 can include actuators, belts, and / or the like that can cause the carriage to move.

[0051] Turning now toFigure 4 FIG. 4 shows a flowchart of an example method 400 for determining pores having a first property or a second property that are predicted to result in a part being formed with better attributes and / or the part being formed in a shorter period of time for manufacturing. It should be understood that Figure 4 The method 400 depicted in FIG. 4 can include additional operations, and some of the operations described therein can be removed and / or modified without departing from the scope of the method 400. The method 400 is also described with reference to features described in Figures 1-3 The method 400 is described with particular reference to the processor 102 performing some or all of the operations included in the method 400. In particular, the processor 102 can perform some or all of the operations included in the method 400.

[0052] At block 402, the processor 102 can access a digital design of a sieve device 202 having attributes (e.g., shapes and pores 204) that are predicted to result in a part being formed with matching attributes, where the part is to be formed from a slurry 220 including liquid and material 224 elements. The processor 102 can access the digital design of the sieve device 202 in any manner discussed herein, such as a 3D model.

[0053] At block 404, the processor 102 can apply first fluid dynamics modeling to the digital design of the sieve device 202 having pores 204 of a first property to model how the slurry 220 composed of liquid and material elements is predicted to flow through the pores 204 of the first property during formation of the part on the sieve device 202, such as when vacuum pressure is applied through the sieve device 202. At block 406, the processor 102 can apply second fluid dynamics modeling to the digital design of the sieve device 202 having pores 204 of a second property to model how the slurry 220 is predicted to flow through the pores 204 of the second property during formation of the part. The processor 102 can apply the first and second fluid dynamics modeling by applying the first fluid dynamics modeling and the second fluid dynamics modeling to the digital design of the sieve device 202 to model how the slurry 220 is predicted to flow through the sieve device 202 during formation of the part as the material 224 elements begin to clog some of the pores 204. The first fluid dynamics modeling and the second fluid dynamics modeling can be a common modeling program and can be applied to different digital designs of the sieve device 202.

[0054] At block 408, the processor 102 can determine which of the digital designs of the screening device 202 having the first property and the second property is predicted to result in the part being formed with better attributes and / or the part being formed in a shorter length of time. In particular, for example, the processor 102 can determine a digital design of the screening device 202 in which the pores 204 having a particular property among the first property and the second property are predicted to result in the part being formed with a maximum level of precision, a minimum amount of material used to form the part, and / or the like. Additionally, or alternatively, the processor 102 can determine a digital design of the screening device 202 in which the pores 204 having a particular property among the first property and the second property are predicted to result in the part being formed in a shorter length of time.

[0055] As discussed herein, the processor 102 can also apply a fluid dynamics model to the digital design of the body 210. Additionally, or alternatively, the processor 102 can cause the manufacturing component 330 of the 3D manufacturing system 300 to manufacture the screening device 202 to have pores containing the determined properties.

[0056] Some or all of the operations illustrated in the method 400 can be included in any desired computer-accessible medium as utility, program, or subprogram. Moreover, the method 400 can be embodied by a computer program, which can exist in a variety of forms. For example, the method 400 can exist as machine readable instructions, including source code, object code, executable code, or other formats. Any of the above can be embodied on a non-transitory computer readable storage medium.

[0057] Examples of non-transitory computer-readable storage media include computer system RAM, ROM, EPROM, EEPROM, and magnetic or optical disks or tapes. It is therefore to be understood that any electronic device capable of executing the above-described functions can perform those functions, either directly or after

[0058] Turning now to Figure 5 , a block diagram of a computer-readable medium 500 is shown, which can have stored thereon computer-readable instructions for selecting a digital design of a screening device 202 that is predicted to result in a part being formed with better attributes and / or the part being formed in a shorter length of time for manufacturing the screening device 202. It is to be understood that Figure 5 The computer-readable medium 500 depicted in FIG. 5 can include additional instructions and some of the instructions described herein can be removed and / or modified without departing from the scope of the computer-readable medium 500 disclosed herein. The computer-readable medium 500 can be a non-transitory computer-readable medium, where the term “non-transitory” does not encompass transitory propagating signals.

[0059] The computer-readable medium 500 can store machine-readable instructions 502-506 thereon, such as Figure 1 The processor of the processor 102 depicted in the middle can execute these instructions. The computer-readable medium 500 can be an electronic, magnetic, optical, or other physical storage device that contains or stores the executable instructions. The computer-readable medium 500 can be, for example, Random Access Memory (RAM), an Electrically Erasable Programmable Read-Only Memory (EEPROM), a storage device, an optical disc, and the like.

[0060] The processor can fetch, decode, and execute the instructions 502 to apply fluid dynamics modeling to a first digital design of the screening device 202 having pores 204 of a first property to model how liquid in a slurry 220 composed of liquid and material elements is predicted to flow through the pores 204 having the first property during formation of a part on the screening device 202. The processor can fetch, decode, and execute the instructions 504 to apply the fluid dynamics modeling to a second digital design of the screening device 202 having pores 204 of a second property to model how liquid in the slurry 220 is predicted to flow through the pores 204 having the second property during formation of the part. As discussed herein, the processor can apply the fluid dynamics modeling to the first and second digital designs of the screening device 202 to model how liquid in the slurry 220 is predicted to flow through the screening device 202 when material elements can begin to clog some of the pores 204 during formation of the part.

[0061] The processor can fetch, decode, and execute the instructions 506 to select one of the first digital design and the second digital design of the screening device 202 that is predicted to result in the part being formed to have better properties and / or the part being formed in a shorter length of time for manufacturing the screening device 202. As discussed herein, the first property can include different pore sizes, different pore quantities, and / or different pore locations compared to the second property.

[0062] While representative examples of the present disclosure have been described in detail herein, representative examples of the present disclosure have utility in a wide variety of applications and the described discussion is not intended to be limiting, but rather illustrative of aspects of the disclosure. Modifications and alterations will occur to others upon reading and understanding the preceding detailed description in this application and the following appended claims in light of the benefits provided within the purposes of the present disclosure. Accordingly, it is the intent of the present disclosure that includes all such modifications and alterations and equivalents of the

[0063] What has been described and illustrated herein is an example of the disclosure and some of its variations. The terms, descriptions and figures used herein are set forth by way of illustration only and are not meant as limitations. Many variations are possible within the scope of the present disclosure, which is intended to be defined by the following claims and their equivalents, in which all terms are meant to be construed in their broadest reasonable sense, unless otherwise expressly indicated.

Claims

1. An apparatus for determining a pore property of a screening device, comprising: a processor; and a memory having instructions stored thereon that, when executed by the processor, cause the processor to: determine the pore property for the screening device that is to be manufactured with pores having the determined pore property by: accessing a digital design of the screening device, the screening device having an attribute that is to be formed on a part, wherein the part is to be formed from a slurry composed of a liquid and material elements; applying a first fluid dynamics modeling to the digital design of the screening device with pores having a first property to model how the liquid in the slurry composed of the liquid and material elements is predicted to flow through the pores having the first property during formation of the part on the screening device; applying a second fluid dynamics modeling to the digital design of the screening device with pores having a second property to model how the liquid in the slurry is predicted to flow through the pores having the second property during formation of the part, wherein the first property comprises a different number of pores and / or a different location of the pores compared to the second property; and determining which one of the digital designs of the screening device with the pores having the first property and the second property is predicted to result in the part being formed with a better attribute and / or the part being formed in a shorter length of time, wherein applying the first fluid dynamics modeling and the second fluid dynamics modeling further comprises applying the first fluid dynamics modeling and the second fluid dynamics modeling to the digital design of the screening device to model how the liquid is predicted to flow through the screening device during formation of the part when the material elements start to clog some of the pores; and causing a manufacturing part of a three-dimensional (3D) manufacturing system to manufacture the screening device with pores having the determined pore property.

2. The apparatus of claim 1, wherein the first property further comprises a different pore size compared to the second property.

3. The apparatus of claim 1, wherein the attribute comprises a level of precision on the part and / or a minimum amount of material used to form the part when forming the part at a predefined level of precision.

4. The apparatus of claim 1, wherein, the instructions are further to cause the processor to: access a digital design of a host, the screening device to be positioned on the host; apply fluid dynamics modeling to the digital design of the screening device and the digital design of the host to model how the slurry is predicted to flow through the screening device and how the liquid is predicted to flow through the screening device and the host during application of pressure by the screening device and the host; and determine, based on the applied fluid dynamics modeling, a property of an opening to be formed through the host that is to result in the part being formed with the better attribute and / or the part being formed in the shorter length of time.

5. The apparatus of claim 4, wherein, The instructions are further to cause the processor to: cause a manufacturing part of a three-dimensional (3D) manufacturing system to manufacture the sieve device with pores having the determined pore properties.

6. A method for determining pore properties of a sieve device, comprising: determining the pore properties for the sieve device that is to be manufactured with pores having the determined pore properties by: accessing, by a processor, a digital design of a sieve device, the sieve device having an attribute that is to be formed on a part, wherein the part is to be formed from a slurry comprising a liquid and material elements; applying, by the processor, a first fluid dynamics modeling to the digital design of the sieve device with pores having a first property to model how the liquid in the slurry consisting of the liquid and material elements is predicted to flow through the pores having the first property during formation of the part on the sieve device; applying, by the processor, a second fluid dynamics modeling to the digital design of the sieve device with the pores having a second property to model how the liquid in the slurry is predicted to flow through the pores having the second property during the formation of the part, wherein the first property comprises a different number of pores and / or a different location of pores compared to the second property; and determining, by the processor, which one of the digital designs of the sieve device with the pores having the first property and the second property is predicted to result in the part being formed with a better attribute and / or the part being formed in a shorter length of time, wherein applying the first fluid dynamics modeling and the second fluid dynamics modeling further comprises applying the first fluid dynamics modeling and the second fluid dynamics modeling to the digital design of the sieve device to model how the liquid is predicted to flow through the sieve device during the formation of the part when the material elements start to clog some of the pores; and causing a manufacturing part of a three-dimensional (3D) manufacturing system to manufacture the sieve device with pores having the determined pore properties.

7. The method of claim 6, wherein the first property further comprises a different pore size compared to the second property.

8. The method of claim 6, wherein the attribute comprises a level of precision on the part and / or a minimum amount of material used to form the part when the part is formed with a predefined level of precision.

9. The method of claim 6, further comprising: controlling the manufacturing part to manufacture the sieve device with pores having one of the first property and the second property based on which one of the sieve device with pores having the first property or the second property is predicted to result in the part being formed with the better attribute and / or the part being formed in the shorter length of time.

10. A non-transitory computer readable medium having computer readable instructions stored thereon that, when executed by a processor, cause the processor to: Determine a pore property for a screening device to be manufactured with pores having the determined pore property by: applying a fluid dynamics modeling to a first digital design of a screening device with pores having a first property to model how a liquid in a slurry consisting of the liquid and material elements is predicted to flow through the pores having the first property during formation of a part on the screening device; applying the fluid dynamics modeling to a second digital design of the screening device with the pores having a second property to model how the liquid is predicted to flow through the pores having the second property during formation of the part, wherein the first property comprises a different pore quantity and / or a different pore location compared to the second property; and selecting one of the first digital design and the second digital design of the screening device predicted to result in the part being formed with better properties and / or the part being formed within a shorter length of time for manufacturing the screening device; and causing a manufacturing part of a three-dimensional, 3D, manufacturing system to manufacture the screening device with pores having the determined pore property, wherein the instructions are to cause the processor to apply the fluid dynamics modeling to the first digital design and the second digital design of the screening device to model how the liquid is predicted to flow through the screening device during formation of the part when the material elements start to clog some of the pores.

11. The non-transitory computer-readable medium of claim 10, wherein, The first property further comprises a different pore size compared to the second property.

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