Method of creating heat sink design

Abstract

A method or system of creating a design of a heat sink includes receiving a property input from a user, including a target physical dimension of the heat sink, including its build material, a maximum temperature of an electrical element adjacent to the heat sink, and a power level of the electrical element; calculating a predicted temperature of the electrical component; generating a comparison showing the effect of independently changing each property input and build material and the resulting change to the predicted temperature of the electrical element; allowing a user to change a property input after generating the comparison; selecting the design of a radiator; and creating a design specification to manufacture the heat sink.

Description

[0001] background

[0002] field

[0003] The present disclosure relates to designs for creating heat sinks to dissipate heat from electrical components, and in non-limiting embodiments, methods and systems for manufacturing heat sinks.

[0004] Related technical description

[0005] Heat sinks are used in conjunction with electrical components, such as light fixtures. During the operation of an electrical component, heat is generated due to the technology of the electrical components, materials, and power used. Although heat is generally an unwanted side effect of electrical components, its generation does not always require a heat sink. However, as more electrical components and materials are placed in a smaller area, heat sinks are often used and relied upon to prevent heat buildup that could damage the electrical components. Therefore, heat sinks are generally required when used in conjunction with such electrical components.

[0006] Existing methods for designing heat sinks can be time-consuming and resource-intensive. First, an application analysis is performed, in which the cooling requirements are determined by the expected power output of the device. Computer-aided design (CAD) is known for designing heat sinks. Then, a simulation is run using computational fluid dynamics (CFD) and subsequent analysis, which may take several hours to complete. Based on the results of the analysis, it can be determined whether the heat sink design is over-performing and causing waste or abuse of resources, or under-performing so that the heat sink is unacceptable for the application. Then, the designer must predict what modifications must be made to the design and repeat the process, performing another CFD simulation and subsequent analysis. If the result is determined to be over-performing or under-performing, the design is modified, and repeated CFD simulations, analysis, and modifications to the CAD design are continued. Once the performance of the heat sink is determined to be acceptable, there may be another step to optimize the design. For example, aluminum plates can be added or removed from the design, and the CFD simulation and analysis steps are performed again. When the design is finally completed, the user must then determine how it can be manufactured.

[0007] In addition, newer technologies and materials are now available that can improve heat sink design. This combination of new technologies and materials results in new methods and systems to design and manufacture heat sinks more efficiently in a shorter period of time, and to design and manufacture heat sinks in an integrated manner.

[0008] Overview

[0009] One embodiment is a method for creating a design for a heat sink, comprising receiving at least four property inputs from a user via a user interface, the property inputs comprising (i) at least two target physical dimensions of the heat sink, (ii) at least one power level of an electrical component adjacent to the heat sink, and (iii) at least one thermal conductivity of a thermally conductive polymer composition comprising the heat sink; calculating a predicted temperature of the electrical component based on the at least four property inputs with at least one processor; generating from 0 to 5 first comparisons with at least one processor, each first comparison showing the effect of independently changing each of the at least four property inputs and the resulting change in the predicted temperature of the electrical component; generating with at least one processor a second comparison showing the effect of independently changing each of the at least two physical dimensions on the predicted temperature of the electrical component; generating with at least one processor a third comparison showing the effect of changing a construction material on the predicted temperature of the electrical component; allowing the user to change at least one of the at least four property inputs after generating each of the above comparisons; after displaying the predicted temperature of the electrical component via the user interface, the user selecting a heat sink design having at least two target physical dimensions and a construction material; and creating design specifications to manufacture the heat sink.

[0010] In another embodiment, a method for creating a design for a heat sink includes: receiving, via a user interface, (i) at least one power level of an electrical component adjacent to the heat sink, and (ii) a maximum acceptable application temperature of the electrical component; calculating, with at least one processor, a modified heat sink design based on the power level and maximum acceptable temperature input by the user and based on a standard heat sink design having standard physical dimensions, including heat sink size, number of fins, fin height, and fin spacing, wherein the modified heat sink design has physical dimensions that are changed from the standard design to allow the input maximum temperature and power level given a fixed heat sink size and thermal conductivity of a thermally conductive polymer composition comprising the heat sink; generating, with at least one processor, 0 to 5 first comparisons, each of which is a first comparison of the input power level and maximum acceptable temperature input by the user and ... a first comparison showing the effect of independently changing at least two physical dimensions, a power level input by a user, and at least one thermal conductivity of a thermally conductive polymer composition constituting the heat sink; generating, with at least one processor, a second comparison showing the effect of independently changing at least two physical dimensions on the predicted temperature of the electrical component; generating, with at least one processor, a third comparison showing the effect of changing a material of construction on the predicted temperature of the electrical component; after generating each of the above comparisons, allowing the user to change at least one of the physical dimensions, the power level, or the thermal conductivity; after displaying the predicted temperature of the electrical component via a user interface, the user selecting a heat sink design having at least two physical dimensions and a material of construction; and creating design specifications to manufacture the heat sink.

[0011] In other embodiments, the property input is selected from the group consisting of number of fins, fin height, fin spacing, and heat spreader thickness. In yet another embodiment, the property input includes at least three target physical dimensions of the heat sink product, and the user selects a heat sink design having at least three target physical dimensions and a material of construction. In another embodiment, the fixed heat sink size includes a fixed heat sink diameter and a fixed heat sink thickness.

[0012] In a different embodiment, the predicted temperature of the electrical component is calculated using a neural network model prepared from a training set and a validation set of previous CFD simulations to optimize a proposed heat sink design based on the property input, or to compare feasible heat sink designs and material selections with the input design parameters to optimize the proposed heat sink design based on the predicted weight of the heat sink.

[0013] In other embodiments, each of the 0 to 5 first comparisons is selected from a table and a line graph. The method may further include generating three, four, or five first comparisons with at least one processor, each first comparison showing the effect of independently changing each of the at least four property inputs and the resulting change in the predicted temperature of the electrical component. The second comparison may be a heat map, and the predicted temperature of the electrical component may be shown in a color in the heat map, the color changing as the predicted temperature changes.

[0014] In another embodiment not yet disclosed, the method further comprises: a user changes at least one property input; and recalculates with at least one processor based on the changed input. In another embodiment, the user changes the at least one property input by moving a point in a line graph or heat map of the first comparison or the second comparison to represent a change in the at least one property input. In yet another embodiment, the method further comprises: regenerating at least one of the first comparison, the second comparison, and the third comparison based on the changed input.

[0015] In more embodiments, the method further includes sending design specifications for manufacturing the heat sink to an injection molding machine, a 3D printer, or an external molder.

[0016] These and other elements and features of the present invention and the methods of operation and function of the associated elements of the structure and the combination and manufacturing economy of the parts will become more apparent when considering the following description and the appended claims with reference to the accompanying drawings, all of which form a part of this specification and in which like reference numerals refer to corresponding parts in the various figures. However, it is to be expressly understood that the drawings are for illustration and description only and are not intended to define the limits of the present invention. As used in the specification and claims, the singular forms "a", "an" and "the" include plural referents unless the context clearly dictates otherwise. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Further advantages and details are explained in more detail below with reference to the exemplary embodiments shown in the attached schematic drawings, in which:

[0019] Figure 1 is a schematic diagram of a system for creating a heat sink design;

[0020] Figure 2 is a schematic diagram of another system for creating heat sink designs;

[0021] Figure 3 is a schematic diagram of a neural network; and

[0022] Figure 4-Figure 6 Various schematic diagrams of the comparison and user interface used to create heat sink designs.

[0023] Details

[0024] The term "computing device" as used herein may refer to one or more electronic devices configured to communicate directly or indirectly with one or more networks or communicate through one or more networks. A computing device may be a mobile device. As an example, a mobile device may include a cellular phone (e.g., a smart phone or a standard cellular phone), a portable computer (e.g., a notebook computer or a tablet computer), a wearable device (e.g., a watch, glasses, lenses), a personal digital assistant (PDA), and / or other similar devices. In other non-limiting embodiments, a computing device may be a desktop computer or other non-mobile computer. In addition, the term "computer" may refer to any computing device including the necessary components for receiving, processing, and outputting data, and generally includes a display, a processor, a memory, an input device, and a network interface. "Interface" refers to a generated display, such as one or more graphical user interfaces (GUIs) that a user may interact with directly or indirectly (e.g., via a keyboard, a mouse, etc.). In addition, one or more computers (e.g., servers or other computerized devices) that communicate directly or indirectly in a network environment may constitute a "system".

[0025] Methods and systems for creating heat sink designs are described herein. In one embodiment, a user specifies inputs of properties of the heat sink, including physical dimensions, power levels, and thermal conductivity of the material, and the method or system calculates the predicted temperature and gives the user an opportunity to view the results of these inputs, including how changing one or more inputs will affect the predicted temperature. In another embodiment, the user specifies the power level and maximum temperature, and the method or system uses a standard design to calculate the physical dimensions of the heat sink, while giving the user an opportunity to view the results of these inputs, including how changing one or more inputs will affect the predicted temperature. In each case, the method or system provides back-and-forth interaction between the user and the system, so that the user can review, accept or change the heat sink design. This interactive communication between the user and the system can include an iterative process, in which the user and the system communicate with each other until the system or method will generate a heat sink design with desired properties, materials, and performance. Therefore, the user can maintain control of the design while still receiving recommendations from the system. Non-limiting embodiments enable the user to receive a heat sink design and select its manufacturing method.

[0026] The heat sink design described herein is a design having the following: diameter, wall thickness, number of fins, fin height per fin, fin pitch (distance between fins), optional heat sink with plate thickness, and material with thermal conductivity. One or more of these variables may be fixed, while others may be variable. Assume that the heat sink is adjacent to an electrical component with an input power level, and at an ambient air temperature that may also be fixed. There may be several different materials with different thermal conductivities. These materials are most commonly aluminum, which is traditionally used as a heat sink material, and there may also be one or more grades of thermally conductive thermoplastics that can be molded using one of the methods described herein. Finally, the electrical component has a temperature when it is operating. This property can be calculated using the methods or systems described herein, or it can be input as the maximum temperature at which the electrical component can operate, and the heat sink design is calculated from this input, etc.

[0027] The method and system described in detail in conjunction with the accompanying drawings are for a heat sink used in a dome reflector with a fixed diameter. However, it is easy to adapt to other geometries, but appropriate geometric input parameters for the geometry will be required. Additional simulations using CFD will be required, including verification using temperature measurements, and subsequent neural network model generation. Other geometries can be rectangular or square reflectors, or a series of circular, rectangular or square reflectors, which can be the same or different sizes to match any desired light design. Associated with these additional geometries may be additional physical dimensions, such as the height, width and number of elements in the series, as well as differences in height, width and diameter in the series.

[0028] refer to Figure 1, a system 100 for creating a heat sink design is shown. The system 100 includes a step of inputting properties 10 from a computing device via a user interface. The properties may include property inputs, including target physical dimensions of the heat sink, power levels of electrical components adjacent to the heat sink, and thermal conductivity of the material. The target physical dimensions of the heat sink may include the number of fins, fin height, fin spacing, and heat spreader thickness. The heat spreader is optional, and its construction material may be aluminum. Physical dimensions of diameter and wall thickness may also be included, or they may be fixed. The system then calculates a predicted temperature of the electrical component 11 based on the property inputs. Next, the system generates a comparison 12 of several property inputs, where the system may generate a graph to show how much the temperature will rise or fall if the input changes. Depending on the power level and thermal conductivity of the material, the system may generate 0 to 5 comparisons. Under some combinations of these inputs, there may be no selection left in the physical properties, so the number of comparison graphs may be less than other combinations of the inputs. Then, the system generates a comparison 13 of the physical dimensions of the electrical component temperature. In this comparison, it is shown how adjusting two physical dimensions at once can affect the temperature of the electrical component. Next, the system generates a comparison 14 of different materials used for the heat sink (where each material has a different thermal conductivity), and how the choice of material may affect the predicted temperature of the electrical component. In each of these comparisons, the user can make changes to the property inputs 15, and the system then recalculates the predicted temperature 11. If the user is satisfied with the heat sink design and makes no further changes, the system creates a design specification 16, which can be further sent to a molding machine 17 to create the heat sink. Other options include sending the design specification 16 to a 3D printer 18 or an external molder 19.

[0029] In such Figure 2In another embodiment shown in , a system 200 for creating a heat sink design is shown. The system 200 includes the steps of inputting the power level 20 of the electrical component adjacent to the heat sink, inputting the maximum operating temperature 21 of the electrical component, each of which is input from a computing device via a user interface. The system also has physical dimensions from a standard heat sink design 22 as input. The physical dimensions of a standard heat sink can include the number of fins, fin height, fin spacing, and heat spreader thickness. The heat spreader is optional, and its construction material can be aluminum. Physical dimensions of diameter and wall thickness can also be included, or they can be fixed. The system then calculates a predicted heat sink design 23, wherein the predicted heat sink design has physical dimensions that are changed from the standard heat sink design 22 to allow for the maximum operating temperature 21 of the electrical component and the power level 20 of the electrical component based on the property input. In this embodiment, the predicted heat sink design 23 also includes the selection of the material used to construct the heat sink. Next, the system generates a comparison 24 of several property inputs, wherein the system can generate a graph to show how much the temperature will rise or fall if the input changes. Depending on the power level and maximum operating temperature of the electrical component, the system can generate 0 to 5 comparisons. Under some combinations of these inputs, there may be no selection left in the physical properties, so the number of comparison graphs may be less than other combinations of inputs. The system then generates a comparison 25 of the physical dimension of the temperature of the electrical component. In this comparison, it is shown how adjusting two physical dimensions at once can affect the temperature of the electrical component. Next, the system generates a comparison 26 of using different materials for the heat sink (each material has a different thermal conductivity), and how the choice of material can affect the predicted temperature of the electrical component. In each of these comparisons, the user can make changes 27 to the property input, and then the system recalculates the predicted temperature 23. If the user is satisfied with the heat sink design so that no further changes are made, the system creates a design specification 28, which can be further sent to a molding machine 29 to create the heat sink. Other options include sending the design specification 28 to a 3D printer 30 or an external molder 31.

[0030] Calculations to achieve predicted temperatures of electrical components or predictive heat sink designs may rely on neural networks. An example of a neural network that may be used in one embodiment of the present invention is shown in Figure 3A neural network is a machine learning technique that is roughly based on networks in the human brain. A neural network model is used to predict heat sink temperatures generated by computational fluid dynamics (CFD) simulations. The model is constructed using the input variables power level 35, number of fins 36, fin length 37, fin spacing 38, heat spreader thickness 39, and thermal conductivity 40. Assume that the construction material of the heat spreader is aluminum. The neural network consists of a one-layer, four-node model with a first node 41, a second node 42, a third node 43, and a fourth node 44. Each of the first node, the second node, the third node, and the fourth node is used to calculate the electrical component temperature 45. The data set is used to train and validate the model consisting of more than 600 CFD simulations (with different settings for the input variables). For a small number of configurations, the electrical component temperature is determined using thermocouples and forward-looking infrared (FLIR) imaging. The data is compared with the CFD simulation to evaluate how well the CFD matches the experimental results. The electrical component temperature is then measured using thermocouples and forward-looking infrared imaging to confirm the accuracy of the model and CFD simulation. The measurements confirmed that the CFD simulations predicted the correct temperatures.

[0031] The equation below shows the format of a neural network equation for predicting the temperature of an electrical component used in conjunction with a heat sink. Each node has an equation, and the solution from each node equation serves as the input to equation 5 for predicting the temperature of the electrical component.

[0032] H1=Tanh(0.5*(B0+(B1*power level)+(B2*thermal conductivity)+(B3*number of fins)+(B4*fin length)+(B5*heat spreader thickness)+(B6*fin spacing)))

[0033] (II) H2 = Tanh (0.5*(B0+(B1*power level)+(B2*thermal conductivity)+(B3*number of fins)+(B4*fin length)+(B5*heat spreader thickness)+(B6*fin spacing)))

[0034] (III) H3 = Tanh (0.5*(B0+(B1*power level)+(B2*thermal conductivity)+(B3*number of fins)+(B4*fin length)+(B5*heat spreader thickness)+(B6*fin spacing)))

[0035] (IV) H4 = Tanh (0.5*(B0+(B1*power level)+(B2*thermal conductivity)+(B3*number of fins)+(B4*fin length)+(B5*heat spreader thickness)+(B6*fin spacing)))

[0036] (V) Predicted electrical component temperature = B0 + (B1*H1) + (B2*H2) + (B3*H3) + (B4*H4)

[0037] Reference again Figure 3 , nodes 41-44 are functions of input variables 35-40. Tanh is a hyperbolic tangent function. It has been found that including this hyperbolic tangent function in these formulas enhances the prediction of the temperature of the electrical component by providing a better fit to the temperature function for the prediction curve. Each of B0, B1, B2, B3, B4, B5 and B6 is a coefficient in each equation, which can be different from each other and different in each equation (I)-(V). These coefficients are determined using a neural network platform on a training set. The data generated by the above CFD simulation is randomly divided between a training set and a validation set. It has been found that this method can avoid overfitting and select a better prediction model. H1, H2, H3 and H4 are the outputs of each equation (I)-(IV). Equation V then uses outputs H1-H4 to solve and predict the temperature of the electrical component. If the model is rerun, the coefficients B0-B5 in each equation and the resulting electrical component temperature will be slightly different because the training set and the validation set are randomly selected.

[0038] The use of neural networks in these calculations provides significant benefits over existing techniques. It is possible to predict electrical component temperatures or heat sink designs much faster than traditionally using CFD simulations.

[0039] refer to Figure 4-Figure 6 , shows various non-limiting comparisons and user interfaces displayed on a computing device for system and method steps for creating a heat sink design. It will be appreciated that other arrangements of user interfaces may be used to create a heat sink design.

[0040] refer to Figure 4 , showing a first comparison and user interface 50. Such a first comparison and user interface 50 may be generated after a user inputs one or more physical dimensions, a power level of an electrical component, and a thermal conductivity of a heat sink material, and the temperature of the electrical component is calculated using the system described herein. In another embodiment, the first comparison and user interface 50 may be generated after a user inputs a power level of an electrical component and a maximum acceptable application temperature of the electrical component, and a predictive heat sink design is calculated using the system or method steps as described herein. In another embodiment, the first comparison and user interface 50 may be generated after one or more inputs are changed as described herein. A user may select the first comparison and user interface 50 by selecting a tab 51. The first comparison and user interface 50 displays a sensitivity analysis of selecting one or more inputs with respect to the temperature of an electrical component (displayed as LED temperature) or for another property. The comparison and user interface may be shown in a table or graphical form. The various fields may include drop-down boxes, free-form fields, radio buttons, or any type of field commonly used in user interfaces. As Figure 4As shown in FIG. 5 , the comparison and user interface can be displayed as a series of line graphs, such as a comparison graph 52 showing how the electrical component temperature 53 may change when the power level 54 is changed. In this embodiment, the user can slide the graph points 55 along the curve 56 to achieve different power levels 54 and electrical component temperatures 53. After changing this input, the system can regenerate each comparison graph, including a graph showing the effect of changing thermal conductivity 57, heat spreader thickness 58, number of fins 59, fin height 60, and fin spacing 61, and also including Figure 5 and Figure 6 Each comparison shown in .

[0041] refer to Figure 5 , a second comparison and user interface 65 is shown. The user can select the second comparison and user interface 65 by selecting a tab 66. The second comparison and user interface 65 can include one or more heat maps 67 that show the effect of the first property 68 and the second property 69 on the temperature 70 of the electrical component, which can be displayed in the heat map as different colors, depending on what the temperature is predicted to be given the combination of property values ​​shown at that point in the heat map 71. In this embodiment, the user can click on a point in the heat map and drag it to a different position to change two input properties at a time, and each comparison map, including the heat map 67 and the heat map 67, can then be updated. Figure 4 and Figure 6 The comparison shown in .

[0042] refer to Figure 6 , a third comparison and user interface 75 is displayed. The user may select the third comparison and user interface 75 by selecting tab 76. The third user comparison and interface 43 may include a comparison table 77 and one or more bar graphs 78, each showing a comparison of the effect of using different materials on the temperature of the electrical component, or a comparison of the effect that a material selection may have on performance, such as weight savings compared to using aluminum. Table 77 may further include a drop-down box with a list of possible materials to select from. The user may select a different material, and each of table 77 and bar graph 78 may then be updated, and Figure 4 and Figure 5 The comparison shown in .

[0043] Although the present invention has been described in detail for purposes of illustration based on what are presently considered to be the most practical and preferred embodiments, it is to be understood that these details are intended only for that purpose and that the present invention is not limited to the disclosed embodiments, but rather is intended to cover modifications and equivalent arrangements within the spirit and scope of the appended claims. For example, it is to be understood that the present invention contemplates that, to the extent possible, one or more features of any embodiment may be combined with one or more features of any other embodiment.

[0044] Further embodiments or aspects are set out in the following numbered clauses:

[0045] Clause 1: A system or method for creating a design for a heat sink, comprising:

[0046] receiving at least four property inputs from a user via a user interface, the property inputs comprising (i) at least two target physical dimensions of the heat sink, (ii) at least one power level of an electrical component adjacent to the heat sink, and (iii) at least one thermal conductivity of a thermally conductive polymer composition comprising the heat sink;

[0047] calculating, with at least one processor, a predicted temperature of the electrical component based on the at least four property inputs;

[0048] generating, with at least one processor, from zero to five first comparisons, each first comparison indicating the effect of independently varying each of the at least four property inputs and the resulting change in the predicted temperature of the electrical component;

[0049] generating, with at least one processor, a second comparison showing the effect of independently varying each of the at least two physical dimensions on the predicted temperature of the electrical component;

[0050] generating, with at least one processor, a third comparison indicating the effect of changing the material of construction on the predicted temperature of the electrical component;

[0051] After generating each of the above comparisons, allowing the user to change at least one of the at least four property inputs;

[0052] After displaying the predicted temperature of the electrical component via the user interface, a user selects a heat sink design having at least two target physical dimensions and a material of construction; and

[0053] Create design specifications to manufacture the heat sink.

[0054] Clause 2: A system or method for creating a design for a heat sink, comprising:

[0055] receiving, via a user interface, (i) at least one power level of an electrical component adjacent to a heat sink, and (ii) a maximum acceptable application temperature of the electrical component;

[0056] calculating, with at least one processor, a modified heat sink design based on a power level and a maximum acceptable temperature input by a user and based on a standard heat sink design having standard physical dimensions, including heat sink size, number of fins, fin height, and fin pitch, wherein the modified heat sink design has physical dimensions altered from the standard design to allow the input maximum temperature and power level given a fixed heat sink size and thermal conductivity of a thermally conductive polymer composition comprising the heat sink;

[0057] generating, with at least one processor, from 0 to 5 first comparisons, each first comparison showing the effect of independently varying each of at least two physical dimensions, a power level input by a user, and at least one thermal conductivity of a thermally conductive polymer composition comprising the heat sink;

[0058] generating, with at least one processor, a second comparison showing the effect of independently varying at least two physical dimensions on the predicted temperature of the electrical component;

[0059] generating, with at least one processor, a third comparison indicating the effect of changing the material of construction on the predicted temperature of the electrical component;

[0060] After generating each of the above comparisons, allowing a user to change at least one of the physical dimension, the power level, or the thermal conductivity;

[0061] After displaying the predicted temperature of the electrical component via the user interface, a user selects a heat sink design having at least two physical dimensions and a material of construction; and

[0062] Create design specifications to manufacture the heat sink.

[0063] Clause 3: The system or method of clause 2, wherein the fixed heat sink size comprises a fixed heat sink diameter and a fixed heat sink thickness.

[0064] Clause 4: The system or method of any of the above clauses, wherein the property input is selected from the group consisting of number of fins, fin height, fin spacing, and heat spreader thickness.

[0065] Clause 5: The system or method of any of the above clauses, wherein the property input comprises at least three target physical dimensions of the heat sink product, and the user selects a heat sink design having the at least three target physical dimensions and a material of construction.

[0066] Clause 6: A system or method of any of the above clauses, wherein the predicted temperature of the electrical component is calculated using a neural network model prepared from a training set and a validation set of previous CFD simulations to optimize a proposed heat sink design based on the property input, or to compare feasible heat sink designs and material selections with the input design parameters to optimize the proposed heat sink design based on the predicted weight of the heat sink.

[0067] Clause 7: The system or method of any of the above clauses, wherein each of the 0 to 5 first comparisons is selected from a table and a line graph.

[0068] Item 8: A system or method of any of the above items, comprising generating three, four or five first comparisons using at least one processor, each first comparison showing the effect of independently changing each of the at least four property inputs and the resulting change in the predicted temperature of the electrical component.

[0069] Clause 9: The system or method of any of the above clauses, wherein the second comparison is a thermal map, and the predicted temperature of the electrical component is shown in the thermal map as a color that changes as the predicted temperature changes.

[0070] Clause 10: The system or method of any of the above, further comprising:

[0071] A user changes at least one property input; and

[0072] Recalculating with at least one processor based on the changed input.

[0073] Clause 11: A system or method of any of the above, wherein a user changes at least one property input by moving a point in a line graph or heat map of the first comparison or the second comparison to represent a change in the at least one property input.

[0074] Clause 12: The system or method of any of the above, further comprising:

[0075] At least one of the first comparison, the second comparison, and the third comparison is regenerated based on the changed input.

[0076] Clause 13: The system or method of any of the above, further comprising sending design specifications for manufacturing the heat sink to an injection molding machine, a 3D printer, or an external molder.

Claims

1. A method of creating a design for a heat sink, comprising: receiving at least four property inputs from a user via a user interface, the property inputs comprising (i) at least two target physical dimensions of the heat sink, (ii) at least one power level of an electrical component adjacent to the heat sink, and (iii) at least one thermal conductivity of a thermally conductive polymer composition comprising the heat sink; calculating, with at least one processor, a predicted temperature of the electrical component based on the at least four property inputs; generating, with at least one processor, from zero to five first comparisons, each first comparison indicating the effect of independently varying each of the at least four property inputs and the resulting change in the predicted temperature of the electrical component; generating, with at least one processor, a second comparison showing the effect of independently varying each of the at least two physical dimensions on the predicted temperature of the electrical component; generating, with at least one processor, a third comparison indicating the effect of changing the material of construction on the predicted temperature of the electrical component; After generating each of the above comparisons, allowing the user to change at least one of the at least four property inputs; After displaying the predicted temperature of the electrical component via the user interface, a user selects a heat sink design having at least two target physical dimensions and a material of construction; and Create design specifications to manufacture the heat sink.

2. The method of claim 1, wherein the property input is selected from the group consisting of number of fins, fin height, fin spacing, and heat spreader thickness.

3. The method of claim 1, wherein the property input includes at least three target physical dimensions of a heat sink product, and a user selects a heat sink design having the at least three target physical dimensions and a material of construction.

4. The method of claim 1, wherein calculating the predicted temperature of the electrical component uses a neural network model prepared from a training set and a validation set of previous CFD simulations to optimize the proposed heat sink design based on the property input. The method of claim 1 , wherein each of the 0 to 5 first comparisons is selected from a table and a line graph.

6. The method of claim 1, comprising generating, with at least one processor, three, four or five first comparisons, each first comparison showing the effect of independently changing each of the at least four property inputs and the resulting change in the predicted temperature of the electrical component. 7 . The method of claim 1 , wherein the second comparison is a heat map, and the predicted temperature of the electrical component is shown in the heat map in a color that changes as the predicted temperature changes.

8. The method according to claim 1, further comprising: A user changes at least one property input; and Recalculating with at least one processor based on the changed input.

9. The method of claim 8, wherein the user changes the at least one property input by moving a point in a line graph or heat map of the first comparison or the second comparison to represent a change in the at least one property input.

10. The method according to claim 8, further comprising: At least one of the first comparison, the second comparison, and the third comparison is regenerated based on the changed input.

11. The method of claim 1 , further comprising sending design specifications for manufacturing the heat sink to an injection molding machine, a 3D printer, or an external molder.

12. A method of creating a design for a heat sink, comprising: receiving, via a user interface, (i) at least one power level of an electrical component adjacent to a heat sink, and (ii) a maximum acceptable application temperature of the electrical component; calculating, with at least one processor, a modified heat sink design based on a power level and a maximum acceptable temperature input by a user and based on a standard heat sink design having standard physical dimensions, including heat sink size, number of fins, fin height, and fin pitch, wherein the modified heat sink design has physical dimensions altered from the standard design to allow the input maximum temperature and power level given a fixed heat sink size and thermal conductivity of a thermally conductive polymer composition comprising the heat sink; generating, with at least one processor, from 0 to 5 first comparisons, each first comparison showing the effect of independently varying each of at least two physical dimensions, a power level input by a user, and at least one thermal conductivity of a thermally conductive polymer composition comprising the heat sink; generating, with at least one processor, a second comparison showing the effect of independently varying at least two physical dimensions on the predicted temperature of the electrical component; generating, with at least one processor, a third comparison indicating the effect of changing the material of construction on the predicted temperature of the electrical component; After generating each of the above comparisons, allowing a user to change at least one of the physical dimension, the power level, or the thermal conductivity; After displaying the predicted temperature of the electrical component via the user interface, a user selects a heat sink design having at least two physical dimensions and a material of construction; and Create design specifications to manufacture the heat sink.

13. The method of claim 12, wherein the fixed heat sink size comprises a fixed heat sink diameter and a fixed heat sink thickness.

14. The method of claim 12, wherein the calculating uses a neural network prepared from a training set and a validation set of previous CFD simulations to compare feasible heat sink designs and material selections with the input design parameters to optimize the proposed heat sink design based on the predicted weight of the heat sink.

15. The method of claim 12, wherein each of the four first comparisons is selected from a table and a line graph.

16. The method of claim 12, wherein the second comparison is a heat map, and the predicted temperature of the electrical component is shown in the heat map as a color that changes as the predicted temperature changes.

17. The method of claim 12, further comprising: A user changes at least one property input; and Recalculating with at least one processor based on the changed input.

18. The method of claim 17, wherein the user changes the at least one property input by moving a point in a line graph or heat map of the first comparison or the second comparison to represent a change in the at least one property input.

19. The method of claim 17, further comprising: At least one of the first comparison, the second comparison, and the third comparison is regenerated based on the changed input.

20. The method of claim 12, further comprising sending design specifications for manufacturing the heat sink to an injection molding machine, a 3D printer, or an external molder.

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