Modelling of fluid flow

Abstract

A digital 3D model of a component to be analyzed is obtained. The component includes regularly patterned holes. A first portion of the model is identified. The first portion includes the regularly patterned holes. A second portion of the model is identified. The second portion includes portions of the model that lack regularly patterned holes. A flow factor for the first portion is determined. The flow factor is indicative of flow characteristics of fluid flowing through the first portion with the regularly patterned holes. A numerical fluid simulation is performed using a mesh representing the geometry of the component. Performing the numerical fluid simulation includes modifying flow properties of the fluid simulation in the first portion based at least in part on the flow factor.

Description

Technical Field

[0001] This application relates to modeling fluid flow, for example, for use in injection molding. Background Technology

[0002] In various industries, injection molds are used to manufacture parts in which materials (such as plastic resins, thermoplastic, thermosetting, or elastomer materials, metals, etc.) are prepared in liquid form (e.g., by heating and melting) and then conveyed or injected under pressure through a pipe into the void of a hollow mold (also called a die head), and then cooled or subjected to a chemical reaction to permanently harden into the shape of the hollow mold cavity. The mold cavity has a shape corresponding to the part to be manufactured, and other components typically include a mold core fitted into the cavity and fixtures attached to the mold to maintain appropriate pressure on the liquid in the mold cavity as the liquid solidifies.

[0003] Injection molding involves removing solidified and hardened material from a mold to form a near-finished product, part, or component in the mold's shape. Injection molding can be an efficient production method because it typically allows manufacturers to reuse one or more molds and precisely replicate the product formed within them. However, the initial design and manufacturing costs of molds are usually quite high. In some cases, significant investments are made in designing and refining molds that will be reused millions of times over their lifespan. Therefore, injection molding is often characterized by high scale efficiency, and the return on investment for a particular mold depends on its durability and sustained precision. Consequently, typical injection mold cavity design is also a crucial, challenging, and costly process.

[0004] Thousands of polymer materials exist that can be used in injection molding applications. In some cases, the material used in an injection molding application can even influence the design of a given mold cavity, and vice versa. For example, some high-viscosity materials in their molten form may perform poorly in mold cavities machined with narrow gates, runners, and cavity clearances. Additionally, the geometry of the mold cavity can also affect the physical properties of the plastic parts manufactured using the mold. In fact, for example, two parts of the same size and made of the same thermoplastic material but molded under different conditions at different injection positions can have different levels of stress and shrinkage. Summary of the Invention

[0005] This disclosure describes techniques involving modeling fluid flow.

[0006] The subject matter described in this disclosure is exemplified by a method performed by a data processing device. The method includes the following features: obtaining a digital 3D model of a component to be analyzed. The component includes regularly patterned holes. Identifying a first portion of the model. The first portion includes regularly patterned holes. Identifying a second portion of the model. The second portion includes portions of the model lacking regularly patterned holes. Determining a flow factor for the first portion. The flow factor indicates the flow characteristics of fluid flowing through the first portion with regularly patterned holes. Performing a numerical fluid dynamics simulation using a mesh representing the geometry of the component. Performing the numerical fluid dynamics simulation includes modifying the flow properties of the simulated fluid in the first portion, at least in part, based on the flow factor.

[0007] Aspects of the exemplary method (which may be combined with the exemplary method individually or in combination with other aspects) include the following: Determining a thermal factor. The thermal factor indicates the thermal properties of a fluid flowing through a first portion with regularly patterned orifices. The thermal factor includes the growth rate of the frozen layer.

[0008] Aspects of the exemplary method (which may be combined with the exemplary method individually or in combination with other aspects) include the following: Dynamically modifying the flow factor to account for the growth rate of the frozen layer.

[0009] Aspects of the exemplary method (which may be combined with the exemplary method individually or in combination with other aspects) include the following. Regularly patterned holes are included in the digital 3D model. The method also includes the following features: Removing holes from the 3D model; Creating a mesh for performing numerical fluid simulations after removing holes from the 3D model.

[0010] Aspects of the exemplary method (which may be combined with the exemplary method individually or in combination with other aspects) include the following: Omitting regularly patterned holes from the digital 3D model. The method also includes the following features: Obtaining the flow characteristics of a first part of the model using analytical flow results or empirical flow data; Determining a flow factor based on the analytical flow results or empirical flow data; Obtaining the thermal characteristics of the first part of the model using analytical thermal results or empirical thermal data; Determining a thermal factor based on the analytical thermal results or empirical thermal data; Obtaining the fiber orientation characteristics of the first part of the model using analytical results or empirical fiber orientation data of fibers suspended in the fluid flow; Determining a fiber orientation factor based on the analytical results or empirical fiber orientation data.

[0011] Aspects of the exemplary method (which may be combined with the exemplary method individually or in combination with other aspects) include the following: Regularly patterned orifices include blind orifices. Determining the flow factor includes using analytical results or empirical data to obtain the flow characteristics of the blind orifices.

[0012] Aspects of the exemplary method (which may be combined with the exemplary method individually or in combination with other aspects) include the following: Regularly patterned orifices include varying orifice shapes. The varying orifice shapes define varying cross-sectional shapes at the depth of the orifice. Determining the flow factor includes using analytical results or empirical data to obtain the flow characteristics of the varying orifice shapes.

[0013] An exemplary embodiment of the subject matter described in this disclosure is a system having the following features: A computer-readable medium stores instructions executable by one or more processors to cause one or more processors to perform the following operations: Obtain a digital 3D model of a part to be analyzed. The part includes regularly patterned holes. Identify a first portion of the model. The first portion includes regularly patterned holes. Identify a second portion of the model. The second portion includes portions of the model lacking regularly patterned holes. Determine a thermal factor for the first portion. The thermal factor indicates the thermal properties of fluid flowing through the first portion with regularly patterned holes. The thermal factor includes the growth rate of a frozen layer. Perform a numerical fluid dynamics simulation using a mesh representing the geometry of the part. The execution of the numerical fluid dynamics simulation includes modifying the thermal properties of the numerical fluid dynamics simulation in the first portion, at least in part, based on the thermal factor. The numerical fluid dynamics simulation is used to determine the injection flow rate or injection location of an injection mold.

[0014] Aspects of the exemplary system (which may be combined with the exemplary system individually or in combination with other aspects) include the following. Regularly patterned holes are included in the digital 3D model. The instructions further cause one or more processors to perform the following operations: Remove the holes from the 3D model. Create a mesh after removing the holes from the 3D model.

[0015] Aspects of the exemplary system (which may be combined with the exemplary system individually or in combination with other aspects) include the following: Regularly patterned holes are omitted from the digital 3D model. The instructions further cause one or more processors to perform the following operations: Obtain the flow characteristics of a first portion of the model using analytical flow results or empirical flow data. Determine the flow factor of the first portion. The flow factor indicates the flow characteristics of the fluid flowing through the first portion with the regularly patterned holes. Determine the flow factor based on analytical flow results or empirical flow data. Obtain the thermal characteristics of the first portion of the model using analytical thermal results or empirical thermal data. Determine the thermal factor based on analytical thermal results or empirical thermal data. Obtain the fiber orientation characteristics of the first portion of the model using analytical results or empirical fiber orientation data of fibers suspended in the fluid flow. Determine the fiber orientation factor based on the analytical results or empirical fiber orientation data.

[0016] Aspects of the exemplary system (which may be combined with the exemplary system individually or in combination with other aspects) include the following. The instructions further cause one or more processors to perform the following operation: Dynamically modify the flow factor to account for the growth rate of the frozen layer.

[0017] Aspects of the exemplary system (which may be combined with the exemplary system individually or in combination with other aspects) include the following. Regularly patterned vias include blind vias. The instructions further cause one or more processors to perform the following operations: Determine the flow factor by using analysis results or empirical data to obtain the flow characteristics of the blind vias.

[0018] Aspects of the exemplary system (which may be combined with the exemplary system individually or in combination with other aspects) include the following. The regularly patterned aperture includes a varying irregularly shaped aperture that defines a varying cross-sectional shape at the depth of the aperture. The instructions further cause one or more processors to perform the following operation: Determine a flow factor by using analysis results or empirical data to obtain the flow characteristics of the varying irregularly shaped aperture.

[0019] An example of the subject matter within this disclosure is a computer-readable medium storing instructions executable by one or more processors to perform the following operations: Obtain a digital 3D model of a component to be analyzed. The component includes regularly patterned holes. Identify a first portion of the model. The first portion includes regularly patterned holes. Identify a second portion of the model. The second portion includes portions of the model lacking regularly patterned holes. Determine a fiber orientation factor. The fiber orientation factor indicates a fiber orientation property indicating the fiber orientation attribute of fibers suspended in fluid flowing through the first portion with regularly patterned holes. Perform a numerical fluid dynamics simulation using a mesh representing the geometry of the component. Performing the numerical simulation includes modifying the fiber orientation property of the numerical fluid dynamics simulation in the first portion, at least in part, based on the fiber orientation factor.

[0020] Aspects of the exemplary system (which may be combined individually with the exemplary system or in combination with other aspects of the exemplary system) include the following. Operation also includes the following: Determining a flow factor for the first portion. The flow factor indicates the flow characteristics of fluid flowing through the first portion with regularly patterned orifices. Determining a thermal factor for the first portion. The thermal factor indicates the thermal characteristics of fluid flowing through the first portion with regularly patterned orifices. The thermal factor includes the growth rate of the frozen layer.

[0021] Aspects of the exemplary system (which may be combined with the exemplary system individually or in combination with other aspects) include the following. Operation also includes the following: Dynamically modifying the flow factor to account for the growth rate of the frozen layer.

[0022] Aspects of the exemplary system (which may be combined with the exemplary system individually or in combination with other aspects) include the following. Regularly patterned orifices include blind orifices. Determining the flow factor includes using analytical results or empirical data to obtain the flow characteristics of the blind orifices.

[0023] Aspects of the exemplary system (which may be combined with the exemplary system individually or in combination with other aspects) include the following: Regularly patterned orifices include varying orifice shapes. The varying orifice shapes define varying cross-sectional shapes at the depth of the orifice. Determining the flow factor includes using analytical results or empirical data to obtain the flow characteristics of the varying orifice shapes.

[0024] Aspects of the exemplary system (which may be combined individually with the exemplary system or in combination with other aspects of the exemplary system) include the following. Operation also includes the following: Determining the injection rate, in part based on a determined flow factor and a determined thermal factor, through iterative calculations using a grid. Determining the injection temperature, in part based on a determined flow factor and a determined thermal factor, through iterative calculations using a grid. Determining the injection location, in part based on the determined injection rate and injection temperature.

[0025] Aspects of the exemplary system (which may be combined with the exemplary system individually or in combination with other aspects) include the following: Regularly patterned holes are included in the digital 3D model. Operations also include the following: Removing holes from the 3D model. Creating a mesh after removing holes from the 3D model.

[0026] Specific implementations of the subject matter described herein can be carried out to achieve one or more of the following advantages. The subject matter described herein allows the use of coarser meshes during numerical simulations, thereby reducing the time required to perform numerical simulations. Such meshes include fewer discrete points for iterative calculations, thus requiring less memory from the data processing equipment used to perform the calculations compared to simulations using other methods. The subject matter described herein improves the speed of tool design and manufacturing, in part, due to the reduction in computation time. The subject matter described herein allows for reduced CAD model preparation time because the effects of holes can be studied without explicitly including thousands of holes in the CAD design. The subject matter described herein allows for easier tuning of simulations with different hole configurations by changing factors related to the hole configuration, rather than actually modifying the geometry / mesh each time.

[0027] Details of one or more embodiments of the subject matter described in this disclosure are set forth in the accompanying drawings and the following description. Other features, aspects, and advantages of this subject matter will become apparent from the detailed description, the drawings, and the claims. Attached Figure Description

[0028] Figure 1This is a flowchart of an example of a method that can be used with various aspects of this disclosure.

[0029] Figure 2 This is an example of the part to be modeled.

[0030] Figure 2A This is an example of a 3D model of a component with sections featuring regularly patterned holes.

[0031] Figure 2B This is an example of a 3D model of a component with regularly patterned holes, after the holes have been removed.

[0032] Figure 3A The results are the result of simulation using an exemplary 3D model of a component having portions with regularly patterned holes.

[0033] Figure 3B The results are the result of simulation using an exemplary 3D model of a component with regular patterned holes, after the holes have been removed.

[0034] Figure 4A The result is a simulation using an exemplary 3D model of a component having portions with regularly patterned holes.

[0035] Figure 4B The results are from simulations using an exemplary 3D model of a component with regularly patterned holes, after the holes have been removed.

[0036] Figure 5 This is a block diagram illustrating an example of a processing device that can be used with aspects of this disclosure.

[0037] The same reference numerals and symbols in the various figures denote the same elements. Detailed Implementation

[0038] The number of pin connectors (holes) used in central processing unit (CPU) sockets has increased year by year. This increase in pin count increases the computational power required for injection molding modeling of such sockets. Simplified methods that can produce fairly accurate predictions with first- or second-order reductions in model preparation and computation time will save time and power usage. Other applications where repeating patterns of through-holes or blind holes appear in injection molding flow cavities include speaker grilles, filters, and repeating prism patterns in light guides, lenses (such as automotive headlight lenses), and reflectors. The repeating pattern of small prism indentations in headlight lenses is an example of a high-value part with many blind holes. Prism patterns increase thermal contact area and flow resistance, but are generally not modeled in injection molding simulations due to the need for very high discretization resolution. This disclosure describes a method for reducing computation time by replacing discrete holes in a model with global factors (such as flow factors, thermal factors, and / or fiber orientation factors for reinforced molded parts, such as injection molded parts, overmolded parts, and / or embedded molded parts)), which produces results substantially similar to numerical analysis on a full model (e.g., within 5%, within 10%, within 15%, or within 20%).

[0039] Figure 1 This is a flowchart of an exemplary method 100 that can be used with various aspects of this disclosure. The operation of method 100 will be described within the context of the remaining figures of this disclosure. The described operations are performed by a data processing device. In some embodiments, such a device includes one or more processors and a computer-readable medium storing instructions executable by the one or more processors to perform the instructions. Alternatively or additionally, the operations described herein may be stored in a readable format for use by a separate data processing device.

[0040] At point 102, a digital 3D model of the component to be analyzed is obtained. The component includes regularly patterned holes. In some cases, regularly patterned holes include through holes extending across the entire thickness of the component. Alternatively or additionally, in some embodiments, regularly patterned holes include blind holes extending only partially through the thickness of the component. Alternatively or additionally, regularly patterned holes include one or more varied irregularly shaped holes defining a varying profile with a varying cross-sectional shape at the depth of the hole. Such varied irregularly shaped holes may be blind holes or through holes without departing from this disclosure. Other types of holes may be used without departing from this disclosure.

[0041] Figure 2 This is an example of part 200 to be modeled. Exemplary models 200a and 200b of part 200 are shown in... Figure 2A and Figure 2B As shown in the image. Figure 2AIt is an exemplary 3D model 200a of a component 200 having a first portion 202a with regularly patterned holes. Figure 2B It is an exemplary 3D model 200b of a component 200 having a first portion 202b with regularly patterned holes, with the holes removed. Although it is primarily described and shown in this disclosure as having a uniform size, shape, and configuration, the subject matter described herein can be used with other configurations, such as hole patterns having varying distances or shapes relative to each other.

[0042] At 104, a first portion (202a, 202b) of component 200 is identified, which includes regularly patterned holes 204. This first portion (202a, 202b) is sometimes referred to as a grid portion, and these terms are used interchangeably in this disclosure. At 106, a second portion 206 of component 200 is identified, which lacks the regularly patterned holes 204. In cases where the model (such as model 200a) includes regularly patterned holes, at 107a, the holes are removed to produce model 200b. After removing the holes, at 107b, a mesh 208 is created. The created mesh 208 is coarser than a similar mesh created on a model where the regularly patterned holes 204 remain in place. In the context of this disclosure, mesh 208 is a discretized mesh applied to a digital model on which numerical computations are performed. For example, mesh 208 is used to perform numerical fluid simulations. In some embodiments, the regularly patterned holes 204 are omitted from the model before the model is obtained. In this implementation, operation 107a can be skipped.

[0043] Figure 3A The result 300a is a simulation using an exemplary 3D model 200a of a component having portions with regularly patterned holes 204 that was modeled separately during numerical simulation. Figure 3B The result 300b is a simulation using an exemplary 3D model 200b of a component having portions with regularly patterned holes, after the regularly patterned holes 204 have been removed. More specifically, Figure 3B The results of a simulation using a global model / representation of the first part to approximate a regularly patterned orifice are shown. At 108a, the flow characteristics of the first part 202b of the model are obtained, for example, by using analytical flow results or empirical flow data. At 109a, the flow factor of the first part 202b is determined based on the analytical flow results or empirical flow data. The flow factor indicates the flow characteristics of fluid flowing through the first part with the regularly patterned orifice, and in some embodiments, is used for models where the orifices have been removed and / or not included, such as model 200a. For example, in some embodiments, the flow factor is calculated using the following equation:

[0044]

[0045] Wherein the flow resistance factor is the flow factor, the shear area ratio is the ratio of the shear area without holes to the shear area with holes in the model, the shear area is the surface area of ​​the region where effective shear is applied, the thickness is the local part thickness, the distance is the local distance between holes (edge ​​to edge), and n is the power-law exponent, which describes the material property of viscosity decreasing with increasing shear rate. For non-power-law flows, the slope of the viscosity-shear rate curve under local temperature, shear rate, and pressure conditions can be used without departing from this disclosure.

[0046] The shear area ratio of a square hole can be calculated using the following equation:

[0047]

[0048] Where W is the width of the square hole, and the depth is the depth of the hole. The shear area ratio of a circular hole can be calculated using the following equation:

[0049]

[0050] Where D is the diameter of the circular hole.

[0051] In some implementations, the concepts described herein are used to obtain flow characteristics for blind orifices and / or irregularly shaped orifices of varying shapes. These flow characteristics can be determined from analytical results and / or empirical data, thus aiding in the determination of the flow factor. Regardless of the orifice pattern or geometry, the flow characteristics through such regular geometries are simplified to a flow factor that is globally analogous to discrete calculations provided by a fine mesh used to compute the flow around each orifice. That is, performing iterative calculations with the flow factor yields results substantially similar to iterative calculations involving individual orifices (e.g., ±5%, ±10%, ±15%, or ±20%). This example can be seen in the simulation results (300a, 300b) shown, illustrating simulations performed using two different methods, with result 300a using discrete orifices and result 300b using the flow factor.

[0052] Alternatively or additionally, at 108b, analytical thermal results and / or empirical thermal data are used to obtain the thermal properties of the first portion 202b of model 200b. At 109b, a thermal factor of the first portion 202b is determined based on analytical thermal results and / or empirical thermal data. The thermal factor indicates the thermal properties of the fluid flowing through the first portion 202b with regularly patterned orifices 204, as well as the thermal properties of the part or the mold forming the part itself. In some embodiments, the thermal factor includes the growth rate of the frozen layer. For example, in embodiments simulating plastic mold injection, it includes the hardening rate of the liquid plastic being injected.

[0053] For example, the thermal properties (density and heat capacity) of the molding material are modified based on the part volume fraction and shape factor value to account for the influence of the grille portion 202b on the temperature solution. In some embodiments, the heat capacity at the grille portion 202b is calculated using the following equation:

[0054]

[0055] Where SF is the shape factor, and where heat capacity (material) is the heat capacity of the material injected into the mold.

[0056] The density at grid section 202b is calculated using the following equation:

[0057] Density (grating) = VF * density (material) (5)

[0058] Where VF is the volume fraction of the grating portion, and density (material) is the density of the material injected into the mold.

[0059] In some implementations, the volume fraction and form factor of the square hole are calculated using the following set of equations:

[0060] PA = (W + distance) * (W + distance) (6)

[0061] Where PA is the projected area.

[0062]

[0063] Where VF is the volume fraction of the part.

[0064] SA (through hole) = 2*PA - 2*W 2 +4*W*Depth(8)

[0065] SA (blind hole) = 2 * PA + 4 * W * depth (9)

[0066] Where SA (through hole) is the surface area of ​​a square through hole, and SA (blind hole) is the surface area of ​​a blind hole, and the depth is the depth of the hole.

[0067]

[0068] Where SF is the shape factor.

[0069] The volume fraction and form factor of a circular hole can be calculated using the following set of equations:

[0070] PA = (D + distance) * (D + distance) (11)

[0071]

[0072] A = SA (through hole) = 2 * PA - 0.5π * D 2 +π*D*Depth(13)

[0073] SA (blind hole) = 2 * PA + π * D * depth (14)

[0074]

[0075] Figure 4A The result is the result of simulation using an exemplary 3D model 200a of a component 200 having portions with regularly patterned holes 204. Figure 4B The results are from a simulation using an exemplary 3D model 200b of a component having portions with regularly patterned holes 204, with the holes 204 removed. More specifically, Figure 4B The results of a simulation using a global model / representation of the first section to approximate a regularly patterned aperture are shown. Alternatively or additionally, at 108c, the fiber orientation characteristics of the suspended fibers 402 flowing through the first section 202b are obtained by analyzing the results and / or empirical fiber orientation data. At 109c, a fiber orientation factor is determined based on the analytical results or empirical fiber orientation data. The fiber orientation factor indicates how the fibers 402 suspended in the fluid are oriented in the fluid flow. For example, in some embodiments, a rotational diffusion model of fiber orientation is used. In this embodiment, fiber orientation is assumed to be in the planar direction of the grid section. Therefore, the following equation can be used:

[0076] GRAF=1+HF*(1–VF) (16)

[0077] Where GRAF is the fiber adjustment factor for the lattice region, and HF is the heuristic factor. In some implementations, the value of the heuristic factor is determined empirically. In some implementations, the heuristic factor is on the order of several hundred, for example, one hundred and ninety-nine.

[0078] In some implementations, the fiber orientation factor is modified to account for variations in flow and / or thermal factors. For example, changes in flow conditions may affect the rotational speed of the suspended fibers. Alternatively or additionally, the fibers may be trapped in the frozen layer, further influencing the flow conditions depending on the fiber orientation.

[0079] In some implementations, the flow factor is dynamically modified to account for the growth rate of the frozen layer. That is, the flow factor depends on and varies with the thickness of the frozen layer. The frozen layer effect can be included by changing the flow resistance factor. For this purpose, the modification distance between orifice values ​​is used in the flow resistance factor calculation:

[0080]

[0081] Dist_ modified =Dist-HF*FLF*thickness(18) where Dist_modified is the modification distance between holes, HF is the heuristic factor, FLF is the freeze layer fraction, and thickness is the local part thickness.

[0082] Similarly, the thermal factor can depend on the flow factor, as the flow state affects thermal convection. Therefore, in some embodiments, the operations of determining the flow factor (108a), determining the thermal factor (108b), and / or determining the fiber orientation factor (108c) are coupled to each other. In such embodiments, operations 108a, 108b, and 108c are performed simultaneously, concurrently, iteratively, or sequentially in any suitable combination. For example, operations 108a and 108b may be performed together while omitting operation 108c, operations 108a and 108c may be performed together while omitting operation 108b, and operations 108b and 108c may be performed together while omitting operation 108a. Nevertheless, in some embodiments, any one of operations 108a, 108b, or 108c is performed alone without performing any other operations. While several example equations have been provided, these equations are merely examples of specific implementations. Other equations for analysis or numerical solution can be used to determine the flow factor, thermal factor, and / or fiber orientation factor without departing from this disclosure.

[0083] At position 110, use grid 208 ( Figure 2B Numerical simulations of fluid flow through components are performed. In some cases, performing numerical fluid simulations includes modifying the thermal properties of the fluid simulation in the first part, at least in part, based on a thermal factor. In some embodiments, performing numerical fluid simulations includes modifying the fiber orientation properties of the fluid simulation in the first part, at least in part, based on a fiber orientation factor. In some embodiments, performing numerical fluid simulations includes modifying the fluid flow properties, at least in part, based on a flow factor. In some embodiments, any combination of the foregoing properties is modified by a flow factor, a thermal factor, and / or a fiber orientation factor.

[0084] At 112, the simulation results are provided. The results of the numerical simulation can be used for various applications; for example, when used to simulate mold injection, the numerical simulation can be used to predict the infill pattern, the likelihood of air traps forming at the final infill point, and the polymer cooling (and freezing) rate. Then, based on these predictions, the injection location, injection rate, and injection temperature can be changed (or newly determined), where a new injection location is selected to try to avoid undesirable infill patterns, weld lines, and air traps. That is, at 114, one or more parts, such as one or more molds, are manufactured based on the simulation results. Furthermore, these mold filling simulations can also serve as the basis for subsequent predictions of the final part shape (“warpage”), which rely on the fiber orientation, pressure, and temperature results from the filling simulation to determine material properties and residual stresses (these are inputs to the warpage calculation). In some embodiments, a model 200b without holes is also used for warpage calculations and / or simulations.

[0085] A digital 3D model (for simplicity, it will be referred to simply as a model) may, but does not need to, correspond to a file. A model may be stored as a part of a file that stores other models (e.g., an assembly file), in a single file dedicated to the model in question, or in multiple coordination files.

[0086] Figure 5 This is a schematic diagram of a data processing system including a data processing device 500, which can be programmed as a client or server. The data processing device 500 is connected to one or more computers 590 via a network 580. Although Figure 5 Only one computer is shown as data processing device 500, but multiple computers can be used. Data processing device 500 includes various software modules that can be distributed between the application layer and the operating system. These can include executable and / or interpretable software programs or libraries, including tools and services for the 3D modeling and simulation program 504 as described above. The number of software modules used can vary depending on the implementation. Furthermore, the software modules can be distributed across one or more data processing devices connected by one or more computer networks or other suitable communication networks.

[0087] The data processing device 500 also includes hardware or firmware devices, including one or more processors 512, one or more auxiliary devices 514, a computer-readable medium 516, a communication interface 518, and one or more user interface devices 520. Each processor 512 is capable of processing instructions for execution within the data processing device 500. In some embodiments, the processor 512 is a single-threaded or multi-threaded processor. Each processor 512 is capable of processing instructions stored on the computer-readable medium 516 or a storage device such as one of the auxiliary devices 514. The data processing device 500 uses its communication interface 518 to communicate with one or more computers 590, for example, via a network 580. Examples of user interface devices 520 include a display, camera, speaker, microphone, haptic feedback device, keyboard, and mouse. The data processing device 500 may store instructions for performing operations associated with the above-described programs on, for example, the computer-readable medium 516 or one or more auxiliary devices 514 (e.g., one or more of hard disk drives, optical disk drives, magnetic tape drives, and solid-state storage devices).

[0088] The embodiments of the subject matter and functional operation described in this specification can be implemented in digital electronic circuits, or in computer software, firmware, or hardware (including the structures disclosed in this specification and their structural equivalents), or in a combination of one or more of these. Embodiments of the subject matter described in this specification can be implemented using one or more modules of computer program instructions encoded on a non-transitory computer-readable medium to be executed by or control the operation of a data processing device. The computer-readable medium can be an manufactured product, such as a hard disk drive in a computer system, or an optical disc sold through retail channels, or an embedded system. The computer-readable medium can be acquired separately and subsequently encoded with one or more modules of computer program instructions, such as by transmitting one or more modules of computer program instructions via a wired or wireless network. The computer-readable medium can be a machine-readable storage device, a machine-readable storage substrate, a memory device, or a combination of one or more of these.

[0089] The term "data processing device" encompasses all devices, apparatuses, and machines used for processing data, including, for example, programmable processors, computers, or multiple processors or computers. In addition to hardware, the device may also include code that generates the execution environment for the computer program in question, such as code constituting processor firmware, protocol stacks, database management systems, operating systems, runtime environments, or combinations thereof. Furthermore, the device can employ a variety of different computing model infrastructures, such as network services, distributed computing, and grid computing infrastructures.

[0090] Computer programs (also called programs, software, software applications, scripts, or code) can be written in any programming language (including compiled or interpreted languages, declarative or procedural languages) and can be deployed in any form, including as standalone programs or as modules, components, subroutines, or other units suitable for a computing environment. A computer program does not necessarily correspond to a file in a file system. A program may be stored as part of a file containing other programs or data (e.g., one or more scripts stored in a markup language document), in a single file dedicated to the program in question, or in multiple co-located files (e.g., a file storing one or more modules, subroutines, or code sections). A computer program can be deployed to execute on one computer or on multiple computers (located at one site or distributed across multiple sites interconnected by a communication network).

[0091] The processes and logic flows described in this specification can be executed by one or more programmable processors that execute one or more computer programs to perform functions by manipulating input data and generating output. The processes and logic flows can also be executed by special-purpose logic circuitry (e.g., field-programmable gate arrays (FPGAs) or application-specific integrated circuits (ASICs)), and the device can also be implemented as said special-purpose logic circuitry.

[0092] Processors suitable for executing computer programs include, for example, both general-purpose and special-purpose microprocessors, as well as any one or more processors in any type of digital computer. Typically, a processor receives instructions and data from read-only memory or random access memory, or both. The fundamental elements of a computer are a processor for executing instructions and one or more memory devices for storing instructions and data. Typically, a computer will also include one or more mass storage devices (e.g., magnetic disks, magneto-optical disks, or optical disks) for storing data, or operatively coupled to receive data from or transfer data to said mass storage device, or both. However, a computer does not necessarily need to have such devices. Furthermore, a computer can be embedded in another device, such as a mobile phone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a global positioning system (GPS) receiver, or a portable storage device (e.g., a universal serial bus (USB) flash drive), to name just a few. Suitable devices for storing computer program instructions and data include all forms of non-volatile memory, media, and memory devices, such as semiconductor memory devices like EPROM (Erasable Programmable Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), and flash memory devices; magnetic disks, such as internal hard disks or removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. Processors and memory may be supplemented by or integrated into dedicated logic circuitry.

[0093] To provide interaction with the user, embodiments of the subject matter described in this specification can be implemented on a computer having a display device (e.g., an LCD (liquid crystal display), an OLED (organic light-emitting diode) display device, or another monitor) for displaying information to the user, and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices may also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback, such as visual feedback, auditory feedback, or tactile feedback; and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0094] Computing systems may include clients and servers. Clients and servers are generally geographically isolated from each other and typically interact via a communication network. The client-server relationship is established by computer programs running on respective computers that establish a client-server relationship between them. Embodiments of the subject matter described in this specification may be implemented in computing systems that include back-end components (e.g., as data servers), middleware components (e.g., application servers), or front-end components (e.g., client computers with a graphical user interface or web browser through which users can interact with embodiments of the subject matter described in this specification), or any combination of one or more such back-end, middleware, or front-end components. Components of the system may be interconnected via digital data communication (e.g., communication networks) of any form or medium. Examples of communication networks include local area networks (“LANs”) and wide area networks (“WANs”), interconnected networks (e.g., the Internet), and peer-to-peer networks (e.g., self-organizing peer-to-peer networks).

[0095] While this disclosure contains numerous specific details of embodiments, these should not be construed as limiting the scope of possible claims, but rather as descriptions of features specific to particular embodiments. For example, although described primarily in the context of modeling injection molding, the themes described throughout this disclosure are applicable to other simulations, such as computational fluid dynamics modeling of flow in complex lattice additively manufactured parts (i.e., CFD for modeling geometry using volumetric kernels). Some features described in this disclosure in the context of individual embodiments may also be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented individually or in any suitable sub-combination in multiple embodiments. Furthermore, while features are described above as operating in certain combinations and even initially required to be so, one or more features from the claimed combinations may, in some cases, deviate from said combinations, and the claimed combinations may involve sub-combinations or variations of sub-combinations.

[0096] Similarly, although the operations are depicted in a specific order in the accompanying drawings, this should not be construed as requiring such operations to be performed in the specific order shown or in a sequential order, or requiring all of the operations shown to achieve the desired result. In some cases, multitasking and parallel processing may be advantageous. Furthermore, the separation of the various system components in the embodiments described above should not be construed as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged in multiple software products.

[0097] Therefore, specific embodiments of this subject matter have been described. Other embodiments are also within the scope of the appended claims. In some cases, the actions set forth in the claims can be performed in a different order and still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing may be advantageous. Aspects of this disclosure can be implemented using 3D discretized models, shell (i.e., 2D) modeling and 1D modeling representations, as well as hybrid modeling (where some regions are 3D and others are 2D, etc.).

Claims

1. A method (100) performed by a data processing device, the method comprising: Obtain (102) a digital 3D model of the component to be analyzed, the component including regularly patterned holes; Identify (104) the first part of the model, the first part of the model corresponding to the first component part including the regular patterned hole; Identify (106) the second part of the model, the second part of the model including the part of the model corresponding to the second component part that lacks the regular patterned hole; Determine (109a) the flow factor of the first portion, the flow factor indicating the flow characteristics of fluid flowing through the first portion with the regularly patterned orifices; and (110) Numerical fluid simulation is performed using a mesh representing the geometry of a component without the regular patterned holes, the performance including modifying the flow properties of the fluid simulation in the first part that take into account the regular patterned holes based on the flow factor.

2. The method of claim 1, further comprising determining a thermal factor indicating the thermal properties of a fluid flowing through the first portion having the regularly patterned orifices, the thermal factor including the growth rate of the frozen layer.

3. The method of claim 1, further comprising: The flow factor is dynamically modified to account for the growth rate of the frozen layer.

4. The method of claim 1, wherein the regularly patterned holes are included in the digital 3D model, and the method further includes: Remove the hole from the 3D model; as well as After removing the holes from the 3D model, the mesh is created for performing the numerical fluid simulation.

5. The method of claim 1, wherein the regular patterned holes are omitted from the digital 3D model, the method further comprising: (108a) Flow characteristics of the first part of the model corresponding to the first component portion including the regular patterned holes are obtained using analytical flow results or empirical flow data, wherein the flow factor is determined based on the analytical flow results or the empirical flow data. The thermal properties of the first part of the model described in (108b) are obtained using analytical thermal results or empirical thermal data; The (109b) heat factor is determined based on the analytical thermal results or the empirical thermal data. The fiber orientation characteristics of the first part of the model (108c) are obtained by using the analysis results or empirical fiber orientation data of the fibers suspended in the fluid flow. as well as The (109c) fiber orientation factor is determined based on the analysis results or the empirical fiber orientation data.

6. The method of claim 1, wherein i) the regularly patterned orifice includes blind orifices, wherein determining the flow factor includes using analytical results or empirical data to obtain the flow characteristics of the blind orifices, and / or Wherein ii) the regular patterned orifice includes a variable orifice, wherein the variable orifice defines a variable cross-sectional shape at the depth of the orifice, wherein determining the flow factor includes obtaining the flow characteristics of the variable orifice using analytical results or empirical data.

7. A system comprising: One or more processors; as well as A computer-readable medium storing instructions executable by the one or more processors to cause the one or more processors to perform operations including: Obtain (102) a digital 3D model of the component to be analyzed, the component including regularly patterned holes; Identify (104) the first part of the model, the first part of the model corresponding to the first component part including the regular patterned hole; Identify (106) the second part of the model, the second part of the model including the part of the model corresponding to the second component part that lacks the regular patterned hole; Determine (109b) the thermal factor of the first portion, the thermal factor indicating the thermal properties of the fluid flowing through the first portion with the regularly patterned orifices, the thermal factor including the growth rate of the frozen layer; as well as (110) Numerical fluid simulation is performed using a mesh representing the geometry of a component without the regular patterned holes, wherein the performance includes modifying the thermal properties of the numerical fluid simulation in the first part that take into account the regular patterned holes based on the thermal factor.

8. The system of claim 7, wherein the numerical fluid simulation is used to determine the injection flow rate or injection location of the injection mold.

9. The system of claim 7, wherein the regular patterned holes are omitted from the digital 3D model, wherein the instructions further cause the one or more processors to: The flow characteristics of the first part of the model corresponding to the first component portion including the regular patterned holes are obtained by using analytical flow results or empirical flow data. A flow factor is determined for the first portion, the flow factor indicating the flow characteristics of fluid flowing through the first portion with the regularly patterned orifice, wherein the flow factor is determined based on the analytical flow results or the empirical flow data. The thermal properties of the first part of the model are obtained using analytical thermal results or empirical thermal data, wherein the thermal factor is determined based on the analytical thermal results or the empirical thermal data. The fiber orientation characteristics of the first part of the model are obtained using the analysis results or empirical fiber orientation data of the fibers suspended in the fluid flow. as well as The fiber orientation factor is determined based on the analysis results or the empirical fiber orientation data. The instructions therein further cause the one or more processors to: The flow factor is dynamically modified to take into account the growth rate of the frozen layer.

10. The system of claim 9, wherein i) the regularly patterned aperture includes blind apertures, wherein the instructions further cause the one or more processors to: The flow factor is determined by using analytical results or empirical data to obtain the flow characteristics of the blind orifice, and / or, Wherein ii) the regular patterned hole includes a variable irregular hole, the variable irregular hole defining a variable cross-sectional shape at the depth of the hole, wherein the instructions further cause the one or more processors to: The flow factor is determined by obtaining the flow characteristics of the varied orifice using analytical results or empirical data.

11. A computer-readable medium storing instructions executable by one or more processors to perform operations, the operations including: Obtain (102) a digital 3D model of the component to be analyzed, the component including regularly patterned holes; Identify (104) a first portion of the model, the first portion of the model including a first component portion corresponding to the regular patterned hole; Identify (106) the second part of the model, the second part of the model including the part of the model corresponding to the second component part that lacks the regular patterned hole; Determine (109c) fiber orientation factor, the fiber orientation factor indicating fiber orientation characteristics, the fiber orientation characteristics indicating the fiber orientation properties of fibers suspended in fluid flowing through the first portion with the regularly patterned holes; as well as (110) Numerical fluid simulation is performed using a mesh representing the geometry of a component without the regular patterned holes, the performance including modifying the fiber orientation properties in the first portion of the numerical fluid simulation that take into account the regular patterned holes based on the fiber orientation factor.

12. The computer-readable medium of claim 11, wherein the operation further comprises: Determine the flow factor of the first portion, the flow factor indicating the flow characteristics of the fluid flowing through the first portion with the regular patterned orifice; as well as A thermal factor is determined for the first portion, the thermal factor indicating the thermal properties of the fluid flowing through the first portion with the regularly patterned orifices, the thermal factor including the growth rate of the frozen layer. The operation also includes: The flow factor is dynamically modified to take into account the growth rate of the frozen layer.

13. The computer-readable medium of claim 12, wherein i) the regularly patterned apertures include blind apertures, wherein determining the flow factor includes using analytical results or empirical data to obtain the flow characteristics of the blind apertures, and / or Wherein ii) the regular patterned orifice includes a variable orifice, wherein the variable orifice defines a variable cross-sectional shape at the depth of the orifice, wherein determining the flow factor includes obtaining the flow characteristics of the variable orifice using analytical results or empirical data.

14. The computer-readable medium of claim 12, wherein the operation further comprises: The injection rate is determined by iterative calculations using the grid, based on the determined flow factor and the determined thermal factor. The injection temperature is determined by iterative calculations using the grid, based on the determined flow factor and the determined thermal factor. as well as The injection location is determined by iterative calculations using the grid, based on the determined injection rate and injection temperature.

15. The computer-readable medium of any of claims 11-14 or the system of any of claims 7-8, wherein the regularly patterned holes are included in the digital 3D model, and wherein the operation further comprises: removing the hole in the 3D model; and creating the mesh after removing the hole in the 3D model.

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