A parametric and automated tool for the design of steel substructures of composite molds.

Abstract

A method for manufacturing a metal frame support for a wind turbine blade mold includes receiving a wind turbine blade mold surface including a three-dimensional shape file. The method includes receiving at least one input parameter and receiving a design scheme. The method includes outputting a first plurality of files including at least one line model, the line model representing a generated framework. The method includes outputting a second plurality of files including at least one geometric data element that can be edited and refined. The method includes performing a finite element analysis of the line model and the at least one geometric data element, thereby enabling substructure optimization even when the design phase is not yet complete. The method includes outputting a full-frame model and at least one technique drawing of the full-frame model.

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority under 35 U.S.C. §119 to U.S. Provisional Application No. 63 / 482,833, filed February 2, 2023, the entire contents of which are incorporated herein by reference.

[0002] Subject matter of the present disclosure The subject matter of this disclosure relates to a metal frame generation system (e.g., geometry, strut position / shape / size / etc., load distribution, etc.). In particular, the subject matter of this disclosure relates to the automated generation of metal frames by one or more computer programs for support structures of fiber-reinforced plastic molds, such as wind turbine blades. [Background technology]

[0003] Fiber-reinforced plastic (FRP) parts used in composite structures such as wind turbines, automobiles, and ships are primarily manufactured in molds with complex surface geometries. To ensure the integrity of the mold shape, the mold surface is supported by a metal substructure. The mold substructure supports the weight of the mold surface, the FRP part, and the manufacturing tools, such as jigs and fixtures, required to manufacture the FRP part. The integrity of the mold surface geometry must be ensured throughout the entire manufacturing process. The mold substructure is a framework, primarily made from tubular metal profiles, that is connected to the mold surface.

[0004] More and more industrial sectors rely on parts made from FRP. In the aircraft and wind power sectors, FRP parts are becoming larger and more complex, and as a result, the moulds are also becoming larger and more complex. As the moulds get larger and more complex, the design of these substructures becomes more complex and time consuming.

[0005] Therefore, there remains a need for efficient and economical methods and systems for algorithms that automate the design of mold support substructures or "bases" using modern computer technology. This paper describes a parametric, automated software tool for designing the metal substructures of molds for FRP components. Summary of the Invention

[0006] The objects and advantages of the presently disclosed subject matter will be set forth in and apparent from the following description, and will be learned by practice of the presently disclosed subject matter. Additional advantages of the presently disclosed subject matter will be realized and attained by the methods and systems particularly pointed out in this written description and claims thereof, as well as from the appended drawings.

[0007] Designing the metal substructure of a mold for fiber-reinforced plastic (FRP) parts requires a lot of repetitive manual work. This is because most molds have complex geometries, requiring designers to manually design the substructure step by step, following a strict iterative workflow. All parts of the tubular structure must be manually added to the 3D model. Furthermore, creating manufacturing drawings also requires manual work, which takes a considerable amount of time and is not standardized. Afterwards, a structural analysis of the framework must be performed to verify its integrity, and this process requires the application of multiple load cases.

[0008] To assist design engineers, drafters, and other users, the following software tool has been developed: The design engineer provides the Mold Frame Generator (MFG) with a list of input parameters and a complex mold surface geometry (3D CAD data). The tool automatically creates two 3D models of the substructure and manufacturing drawings based on the provided input parameters and mold surface geometry.

[0009] One of the two 3D models is a line model of the mold frame and can be used for finite element analysis. This option allows for easy integration of structural analysis into the design process. Therefore, substructure optimization can be performed even before the design phase is complete. The second 3D model is a solid-body 3D model that can be edited and refined. In each embodiment, one or more findings from the second 3D model may be incorporated into the first 3D model in one or more subsequent runs. This model is used by the program to generate manufacturing drawings.

[0010] The solution to this trend is to use algorithms that automate the design using modern computer technology. This article describes a parametric, automated software tool for designing the metal substructure of molds for FRP components.

[0011] To achieve these and other advantages and in accordance with the purpose of the presently disclosed subject matter, as embodied and broadly described, the presently disclosed subject matter includes a method for manufacturing a metal frame support of a wind turbine blade mold. The method includes receiving a wind turbine blade mold surface including a three-dimensional shape file. The method includes receiving at least one input parameter and receiving a design scheme. The method includes outputting a first plurality of files including at least one line model, the line model representing a generated framework. The method includes outputting a second plurality of files including at least one geometry data element in text format. The method includes performing a finite element analysis of the line model and the at least one geometry data element. The method includes outputting a full-frame model and at least one technique drawing of the full-frame model.

[0012] The at least one input parameter includes one of a mold shell thickness, a distance from the mold surface to the ground, and a structural tube. The design scheme is automatically scaled to the at least one input parameter and the mold surface. The design scheme includes a cross-section of the metal frame. The design scheme includes an adjacent side connection and a bottom connection. The design scheme is selected from a plurality of design schemes. The design scheme includes an adjacent side connection and a bottom connection. The second plurality of files includes at least one data element representing a line, a start point, an end point, and an orientation of a portion of the metal frame. The method further includes performing quality control on the at least one input parameter and / or converting the mold surface to a point cloud. The point cloud includes 100 points per 100 millimeters.

[0013] To achieve these and other advantages and in accordance with the purpose of the presently disclosed subject matter, as embodied and broadly described, the presently disclosed subject matter includes a system for manufacturing a metal frame support for a wind turbine blade mold. The system includes a first module for receiving input data including a wind turbine blade mold surface including at least a three-dimensional shape file, at least one input parameter, and a design scheme. The system includes a second module for generating a first plurality of files including at least one line model, the line model representing a generated framework, and a second plurality of files including at least one geometry data element in text format. The system includes a third module for performing a finite element analysis of the line model and the at least one geometry data element, outputting a full-frame model, and outputting at least one technique drawing of the full-frame model.

[0014] The at least one input parameter includes one of a mold shell thickness, a distance from the mold surface to the ground, and a structural tube. The design scheme is automatically scaled to the at least one input parameter and the mold surface. The design scheme includes a cross section of the metal frame. The design scheme includes an adjacent side connection and a bottom connection. The design scheme is selected from a plurality of design schemes. The second plurality of files includes at least one element of data representing a line, a start point, an end point, and an orientation of a portion of the metal frame. Quality control is performed on the at least one input parameter. The mold surface is converted into a point cloud. The point cloud includes 100 points per 100 millimeters.

[0015] It is to be understood that both the foregoing summary and the following detailed description are exemplary and intended to provide further explanation of the subject matter of the present disclosure as claimed.

[0016] The accompanying drawings, which are incorporated in and constitute a part of this specification, are included to illustrate and provide a further understanding of the methods and systems of the disclosed subject matter and, together with the description, serve to explain the principles of the disclosed subject matter.

[0017] A detailed description of various aspects, features, and embodiments of the subject matter disclosed herein is provided with reference to the accompanying drawings, which are briefly described below. The drawings are illustrative and are not necessarily drawn to scale, and some components and features are exaggerated for clarity. The drawings illustrate various aspects and features of the inventive subject matter and may illustrate, in whole or in part, one or more embodiments or examples of the inventive subject matter. [Brief explanation of the drawings]

[0018] [Figure 1] 1 is a schematic diagram of a method for producing a metal frame according to the subject matter of the present disclosure. [Figure 2A] Schematic diagram of the framework associated with the 3D and shape files output according to the method shown in Figure 1. [Figure 2B]Schematic diagram of the framework associated with the 3D and shape files output according to the method shown in Figure 1. [Figure 2C] Schematic diagram of the framework associated with the 3D and shape files output according to the method shown in Figure 1. [Figure 2D] Schematic diagram of each scheme according to the method shown in Figure 1. [Figure 2E] Schematic diagram of each scheme according to the method shown in Figure 1. [Figure 2F] Schematic diagram of each scheme according to the method shown in Figure 1. [Figure 2G] Schematic diagram of each scheme according to the method shown in Figure 1. [Figure 2H] Schematic diagram of each scheme according to the method shown in Figure 1. [Figure 3] 1 is a diagram of a 3D shape associated with an FRP mold in accordance with the subject matter of the present disclosure. [Figure 4] 3D shape diagram representing a metal frame in a design process according to the subject matter of the present disclosure. [Figure 5] 1 is a diagram of a technique associated with the generated metal frame according to the subject matter of the present disclosure. [Figure 6] 1 is a diagram of a cloud computing node according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0019] DETAILED DESCRIPTION OF THE INVENTION Reference will now be made in detail to exemplary embodiments of the presently disclosed subject matter, as illustrated in the accompanying drawings. The methods and corresponding steps of the presently disclosed subject matter will be described in conjunction with a detailed description of the system.

[0020] The methods and systems presented herein may be used to generate metal frames. The presently disclosed subject matter is particularly suited for the automated generation of metal frames for support structures of FRP molds. For purposes of explanation and illustration, and not limitation, an exemplary embodiment of a system according to the presently disclosed subject matter is shown in FIG. 1 and generally designated by the numeral 100. Similar numerals (distinguished by leading numerals) may be provided between the figures and drawings presented herein to indicate functionally corresponding, but not necessarily identical, structures.

[0021] As shown in FIG. 1 , method 100 includes, in step 105, receiving a mold surface including a three-dimensional shape file. For example, the mold surface can include design specifications for a wind turbine blade, such as span, root and tip contours, curvature, chord length, and weight. The mold surface may be one or more mold surfaces configured to mold an FRP part, such as that shown in FIG. 3 . The mold surface may include multiple mold surfaces configured to mate with each other to form the entire FRP part. The shape file may be uploaded to one or more computers, computer programs, servers, etc. The shape file may be a 3D computer-aided design (CAD) file or computer-aided manufacturing (CAM) file specific to one or more CAD / CAM programs. The shape file may be downloaded from the internet or one or more other locations. The shape file may be generated by one or more computers, servers, or computer programs on which the method is executed. The shape file may be one or more two-dimensional representations that are electronically manipulated to form a three-dimensional representation of the mold surface.

[0022] Continuing with reference to the drawings, as shown in Figure 1, step 105 may include automatically creating one or more cross sections at each location along the blade (and mold, and underlying base or substructure) from an input 3D shape file. The 3D shape file may include information related to the cross sections and may be generated by one or more computing systems.

[0023] As shown in FIG. 1, method 100 includes converting the mold surface into a point cloud. The point cloud includes 100 points per 100 millimeters. In some embodiments, selected regions of the FRP can have a greater concentration of points (e.g., the root of the blade can have a greater point density than the tip). For purposes of this disclosure, a "point cloud" is one or more electronic representations of a shape (blade, mold, and / or base substructure) that includes multiple points sharing a common coordinate system that represent elements of the overall shape. For example, without limitation, a point cloud may include points that represent lines or edges of a part. For example, without limitation, a point cloud may include points that represent corners or vertices of a part. For example, without limitation, a point cloud may include points that represent voids, interior corners and / or cavities, shear resistance locations (and shapes) of webs, core panels within a blade, or mold lines on the exterior of a part, or interior shapes of a part. A point cloud may include one or more levels of granularity. For example, without limitation, a point cloud may have an increased or decreased number of points per length. For example, without limitation, a point cloud may include 10 points per 100 mm. For example, without limitation, according to one embodiment of the present method, a point cloud may include 1000 points per 10 mm. The point cloud may include a mesh or alternatively or additionally use a superimposed mesh. The mesh may be generated by one or more meshing tools utilizing one or more meshing algorithms, methodologies, and / or processes.

[0024] As shown in FIG. 1 , method 100 includes, in step 110, receiving at least one input parameter. The at least one input parameter may be one or more desired criteria (e.g., strut dimensions, positions, center of gravity, global coordinates, etc.) of the metal frame by a user, who may be one or more designers. The at least one input parameter may include mold-related parameters (e.g., mold shell type, mold position, and / or parameters calculated therefrom). The at least one input parameter may include frame (e.g., metal frame)-related parameters, such as floor level, segment distance, flange dimensions, and / or parameters calculated therefrom. The at least one input parameter may include hinge-related parameters, such as hinge type, height position, hinge dimensions, and / or parameters calculated therefrom. The at least one input parameter may include box-related parameters, such as box size and / or parameters calculated therefrom. The at least one input parameter may include a parameter related to a frame shell attachment, such as a spreader rule, spreader dimensions, spreader distance, web dimensions, and / or parameters calculated therefrom. The at least one input parameter may include a parameter related to a beam, such as a brace dimension, a runner dimension, a stringer dimension, and / or other suitable parameters. The at least one parameter may include a suitable parameter related to any component of the system described herein. For example, without limitation, the at least one input parameter may include a mold shell thickness, a mold type such as a hinged clamshell, a hinge location and dimension, a taper of one or more surfaces, a mold range of motion (if applicable based on the mold type), a distance from the mold surface to the ground, and / or a structural tube. The at least one input parameter may include a selection of material, structural steel such as box steel, or round tube. The at least one input parameter may be provided by a list or entered into a graphical user interface (GUI).The at least one input parameter may be selected from a list by clicking a box, radio button, or other selection method on a computer, tablet, or smartphone. The at least one input parameter may include an automatically generated input parameter previously uploaded by a user or associated with one or more 3D shapes received by the computing system. The at least one input parameter may be generated based on one or more received mold surfaces. The at least one input parameter may be received as part of the 3D shapes received in step 105, such as properties described in a CAD / CAM file.

[0025] In an exemplary method, all input parameters are first generated in a file (e.g., an Excel file) and provided to the user as a sample guideline. The user can use this guideline to select one or more input parameters. For example, based on the sample guideline and the user's experience, the user can generate a first approximation using an automated tool described herein. The tool then generates a line model (e.g., as shown in FIG. 3 ), from which the user can manually perform a visual reliability check (e.g., the “Is the frame OK?” step in FIG. 1 ). If the results are undesirable, the user can modify the parameters in the file (e.g., based on the user's input) until a satisfactory result is achieved. Next, a finite element analysis (FEA) is performed manually. Based on the results from the FEA, the user can check whether the generated model meets requirements such as weight limits, deflection, and / or safety factors. In various embodiments, these requirements can be defined by the customer, the supplier, or a standard (e.g., a government standard). If one or more requirements are not met, the user can modify the input parameters. For example, but not limited to, if there is a safety factor that does not meet the code, the user can strengthen the frame in this area by changing the scheme, adding a section in this area, or using a stronger steel pipe.

[0026] In various embodiments, method 100 includes performing quality control of input data (e.g., provided by a user). For example, without limitation, a system according to method 100 can determine the condition of the input data and provide a message to the user (e.g., the job cannot be completed due to poor input data quality). In another example, the user can determine the condition of the input data based on a sample file containing all input parameters, as described above. In various embodiments, the condition of the data is determined based on factors such as accuracy, completeness, consistency, reliability, and / or whether the data is up-to-date.

[0027] Continuing with reference to FIG. 1, as shown in FIG. 1, method 100 includes receiving a design scheme at step 115. After a short computational time, the mold frame generator (MFG) may prompt the user / designer to select one or more design schemes (e.g., cross-sectional schemes) to use for the framework. The distances between these sections may be predefined in a parameter list, an example of which is shown in FIGS. 2A-2C. Design schemes selectable by one or more users or received by the methods described herein may include pictorial representations of the design schemes, such as those shown in FIGS. 2A-2C. One or more users may select a design scheme based on at least one input parameter and other elements of the data described herein, such as the mold surface geometry. The design scheme may be associated with the product to be manufactured (e.g., the size / shape / profile / weight of a particular wind turbine blade), such as a stronger mold frame for heavier parts or a more flexible mold frame for parts requiring various degrees of flexibility. The user is prompted to select from schemes that are automatically scaled according to the provided parameters and the specific contour of the mold surface. Schemes can be selected for cross sections as well as adjacent side and bottom connections. One or more users can select a desired beam scheme from various schemes based on experience. One or more users can create a beam layout scheme based on one or more parameters or one or more saved schemes, as needed. If one or more users want to optimize the frame according to finite element analysis (FEA), one or more users can slightly modify the scheme and rerun the program. The beam type selection criteria are determined by the user. Users can select beam types based on local standards and availability, such as national, regional, or other limiting factors such as purchasing and operation. For example, ANSI or ISO standard profiles can be selected. One or more users can define the beams they want to use in the scheme, for example, by cross section. Figures 2A-2C show an exemplary embodiment.Figure 2A shows a mold surface that provides input data. Figure 2B shows an example design scheme. Figure 2C shows an example output. Figures 2D-2H show additional exemplary embodiments, including cross-sectional schemes (Figures 2D-2E), side schemes (Figures 2F and 2G), and a bottom scheme (Figure 2H).

[0028] In each embodiment, specific parameters are required for a particular scheme. These parameters can be provided by the user. If these parameters are not provided, the system's program may notify the user. If these parameters are provided but the scheme is not selected, the parameters may not be selected. For each cross-section, the user can define the scheme. Thus, multiple schemes (e.g., one as shown in FIG. 2D and another as shown in FIG. 2E) are possible for the output model. As shown in FIGS. 2D and 2E, these parameters can represent one or more distances, thicknesses, slopes, or other suitable parameters within the scheme (e.g., cross-sectional scheme). These parameters can be associated with the frame and / or mold in the scheme, such as the distance between the frame and the mold flange (e.g., "a" and / or "b" in FIG. 2D), the thickness of the mold shell (e.g., "c" in FIG. 2D), the distance between the mold surface and the frame (e.g., "d" in FIG. 2D), the distance between the metal tubes (e.g., "e" in FIG. 2D), the slope of the mold surface (e.g., "f" in FIG. 2D), and / or the distance from the mold surface to the ground (e.g., "g" in FIG. 2D). Still referring to FIG. 1 , method 100, in step 115, includes outputting a first plurality of files including a line model representing at least one generated framework. This framework can be used for wind turbine blade molds. This framework can also be used for other applications (e.g., molds used in aerospace, automotive, or shipbuilding). The first plurality of output files can be a collection of initial graphics exchange specification files (IGES files). These files can represent the generated framework as a line model. In an embodiment, one or more files may represent one or more portions of the generated framework. For example, one or more files may be associated with a profile type, such as, but not limited to, a structural steel shape or a beam type. Each profile type may be represented by its own IGES file and may include all of the associated beams represented by lines.In some embodiments, one or more laser-cut metal plates can also be created by MFG. These are also exported as IGES files and include the boundaries of the metal plate areas. An example embodiment is shown in Figure 3. The mold frame generator creates two different sets of output files based on the provided input files.

[0029] Continuing with reference to FIG. 1 , method 100, in step 115, includes a second plurality of files containing at least one geometry data element in text format. The second plurality of files includes at least one data element representing lines, start points, end points, and orientation of a portion of the metal frame. The second set of output files is a collection of JavaScript Object Notation files (JSON files). JSON files may be an interchange file format using human-readable text. At least one of these files contains geometry data such as points, lines with start points and end points, profile information and orientation, as well as all information about the laser-cut metal sheet, such as boundaries and thickness. Other files may contain meta-information. Meta-information may include materials, costs, bills of materials, material properties, or the like. Meta-information may include contact information for one or more suppliers associated with the generated framework and / or model. In various embodiments, the meta-information may be an estimated weight of the framework. In various embodiments, the meta-information may be an estimated price from one or more suppliers based on information such as the weight of the framework (i.e., how much material is required). The meta-information may be utilized to perform any number of calculations automatically or at the direction of one or more users. The meta-information may be used to estimate the manufacturing capabilities of any number of suppliers or in-house.

[0030] Continuing with Figure 1, the IGES file can be reviewed by one or more users and / or designers to begin an iterative optimization loop. If the designer is not satisfied with the line model created by MFG, it can be re-run with modified input parameters and scheme information. After the model is positively evaluated, it can be used for finite element analysis (FEA).

[0031] Continuing with reference to FIG. 1 , method 100 includes, at step 120, performing a finite element analysis of the line model and at least one geometric data element. The first and second plurality of files can be manipulated, processed, or combined to define one or more geometric objects, including associated mechanical and / or material properties. In this disclosure, "finite element analysis (FEA)" refers to a method for numerically predicting how an object will respond to forces, vibrations, heat, fluid flow, and other physical phenomena. For example, but not by way of limitation, FEA may be performed on a beam model, including connections and applied forces along them, to predict bending moments, torsion, shear, and other resultant forces. FEA may be performed on the generated framework or portions thereof, and structural analysis may be performed and visualized, including, for example, a color-coordinated resultant model of the framework, including a chart correlating color with the intensity of forces or moments. FEA may include generating one or more meshes conforming to one or more bodies. These meshes may be the same as or similar to any mesh generated in this manner, including but not limited to meshes generated from a point cloud of the mold surface.

[0032] Depending on the results of the FEA, at least one input parameter can be changed again and the method or parts of it can be re-run. This iterative method allows the framework to be optimized during the design phase.

[0033] Continuing with reference to FIG. 1 , method 100 includes outputting the full-frame model at step 125. After optimizing the framework, the second set of output files can be read by a second portion of the software tool, which is a macro integrated into a parametric computer-aided design (CAD) program. The macro reads the JSON file and creates a complete three-dimensional solid framework based on the previously created files, which is shown in FIG. 4.

[0034] Continuing with reference to FIG. 1 , method 100 includes outputting at least one technical drawing of the full frame model in step 130. After the complete solid model is completed, the macro generates manufacturing drawings, such as overviews, cross sections, cutting lists, or bills of materials, from the framework, which can be used to manufacture the actual frame and to request quotes from suppliers. An exemplary embodiment is shown in FIG. 5 . The at least one technical drawing may include identical or similar meta-information, shape information, supplier or contractor information, revision history, etc. The at least one technical drawing may include all information necessary to manufacture the metal framework produced by the methods described herein. The at least one technical drawing may include embedded CAD and / or CAM data for interfacing with one or more automated manufacturing processes, such as a six-axis milling machine, an industrial robot, a conveyor, a lifter, an electrical discharge machining (EDM) system, an additive manufacturing system, etc.

[0035] Although this disclosure includes detailed descriptions of cloud computing, it is understood in advance that implementation of the teachings described herein is not limited to a cloud computing environment. Rather, embodiments of the present disclosure may be implemented in conjunction with any other type of computing environment now known or later developed.

[0036] Generally, cloud computing is a service delivery model that provides convenient, on-demand network access to a shared pool of configurable computing resources (such as networks, network bandwidth, servers, processing, memory, storage, applications, virtual machines, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. This cloud model can include at least five characteristics, at least three service models, and at least four deployment models, as described below.

[0037] In general, characteristics of the cloud model can include on-demand self-service, widespread network access, resource pooling, rapid elasticity, and / or measured service.

[0038] In embodiments, on-demand self-service refers to the ability of cloud consumers to automatically and unilaterally provision computing capabilities, such as server time and network storage, as needed, without the need for human intervention with a service provider.

[0039] In each embodiment, broad network access means that the functionality is available over the network and accessed through standard mechanisms that facilitate use by heterogeneous thin-client or thick-client platforms (e.g., cell phones, laptops, PDAs).

[0040] In embodiments, resource pooling refers to the pooling of provider computing resources to serve multiple consumers in a multi-tenant model, with different physical and virtual resources dynamically allocated and reallocated according to demand. Consumers generally have no control over or knowledge of the exact location of the resources provided to them, but may have a sense of location independence in that they may be able to specify location at a higher level of abstraction (e.g., country, state, data center).

[0041] In embodiments, rapid elasticity means that features can be delivered quickly and elastically, sometimes automatically, to rapidly scale out and rapidly release to rapidly scale in. To the consumer, the available features are often perceived as unlimited, available for purchase in any quantity at any time.

[0042] In embodiments, a metered service means that the cloud system automatically controls and optimizes resource usage by leveraging metering capabilities at a level of abstraction appropriate to the type of service (e.g., storage, processing, bandwidth, active user accounts). Resource usage can be monitored, controlled, and reported, providing transparency to both providers and consumers of the services being utilized.

[0043] Generally, service models can include Software as a Service (SaaS), Platform as a Service (PaaS), and / or Infrastructure as a Service (IaaS).

[0044] In various embodiments, Software as a Service (SaaS) refers to the functionality provided to consumers through the use of a provider's applications running on a cloud infrastructure. The applications are accessible from a variety of client devices through thin-client interfaces such as web browsers (e.g., web-based email). The consumer does not manage or control the underlying cloud infrastructure, including the network, servers, operating systems, storage, or even individual application functions, except for limited user-specific application configuration settings.

[0045] In embodiments, Platform as a Service (PaaS) refers to the capability provided to consumers to deploy applications they create or acquire, written using programming languages ​​and tools supported by the provider, onto a cloud infrastructure. The consumer does not manage or control the underlying cloud infrastructure, including the network, servers, operating systems, or storage, but does control the deployed applications and, in some cases, the configuration of the application hosting environment.

[0046] In each embodiment, Infrastructure as a Service (IaaS) means that the functionality provided to the consumer is the provision of processing, storage, network, and other basic computing resources on which the consumer can deploy and run any software, including operating systems and applications. The consumer does not manage or control the underlying cloud infrastructure, but has full control over the operating systems, storage, deployed applications, and possibly limited control over certain network components (e.g., host firewalls).

[0047] In general, deployment models can include private clouds, community clouds, public clouds, and / or hybrid clouds.

[0048] In embodiments, a private cloud refers to a cloud infrastructure operated solely for an organization. A private cloud may be managed by the organization or a third party and may reside on-premises or off-premises.

[0049] In embodiments, a community cloud refers to a cloud infrastructure shared by multiple organizations to support a specific community with common interests (e.g., mission, security requirements, policies, compliance considerations). A community cloud may be managed by an organization or a third party and may exist on-premises or off-premises.

[0050] In embodiments, a public cloud refers to a cloud infrastructure that is available to the general public or a large industry group and is owned by an organization that sells cloud services.

[0051] In embodiments, a hybrid cloud refers to a cloud infrastructure that is a combination of two or more clouds (private, community, or public) that maintain unique entities but are tied together by standardized or proprietary technologies that enable data and application portability (e.g., cloud bursting for load balancing between clouds).

[0052] In general, cloud computing environments are service-oriented, focusing on statelessness, low coupling, modularity, and semantic interoperability. At the heart of cloud computing is an infrastructure that consists of a network of interconnected nodes.

[0053] Referring to Figure 6, a schematic diagram of an example cloud computing node is shown. Cloud computing node 10 is merely one example of a suitable cloud computing node and is not intended to suggest any limitation as to the scope of use or functionality of the embodiments described herein. In any event, cloud computing node 10 may implement and / or perform any of the functions described herein.

[0054] Cloud computing node 10 includes computer system / server 12, which may operate in conjunction with many other general-purpose or special-purpose computing system environments or configurations. Examples of known computing systems, environments, and / or configurations suitable for computer system / server 12 include, but are not limited to, personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments that include any of the above systems or devices.

[0055] The computer system / server 12 may be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, etc. that perform particular tasks or implement particular abstract data types. The computer system / server 12 may also be practiced in distributed cloud computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computer system storage media, including memory storage devices.

[0056] 6, computer system / server 12 within cloud computing node 10 is depicted as a general-purpose computing device. Components of computer system / server 12 include, but are not limited to, one or more processors or processing units 16, system memory 28, and a bus 18 that couples various system components, including system memory 28, to processor 16.

[0057] Bus 18 represents any one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, and a processor or local bus using any of a variety of bus architectures, including, by way of example only, but not limited to, an Industry Standard Architecture (ISA) bus, a Micro Channel Architecture (MCA) bus, an Enhanced ISA (EISA) bus, a Video Electronics Standards Association (VESA) local bus, a Peripheral Component Interconnect (PCI) bus, a Peripheral Component Interconnect Express (PCIe), and an Advanced Microcontroller Bus Architecture (AMBA).

[0058] Computer system / server 12 typically includes a variety of computer system-readable media, which can be any available media that can be accessed by computer system / server 12 and includes both volatile and nonvolatile media, removable and non-removable media.

[0059] System memory 28 may include computer system-readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. Computer system / server 12 may also include other removable / non-removable, volatile / non-volatile computer system storage media. As an example, storage system 34 may be provided for reading from and writing to a non-removable, non-volatile magnetic medium (not shown, typically referred to as a "hard drive"). Although not shown, a magnetic disk drive may be provided for reading from and writing to a removable, non-volatile magnetic disk (e.g., a "floppy disk"), and an optical disk drive may be provided for reading from or writing to a removable, non-volatile optical disk, such as a CD-ROM, DVD-ROM, or other optical medium. In such cases, each may be connected to bus 18 by one or more data media interfaces. As further shown and described below, memory 28 may include at least one program product including a set (e.g., at least one) of program modules configured to perform the functions of embodiments of the present disclosure.

[0060] The programs / utilities 40 comprise a set (at least one) of program modules 42, which may be stored in memory 28 along with, by way of example, but not limitation, an operating system, one or more application programs, other program modules, and program data. Each operating system, one or more application programs, other program modules, program data, or combinations thereof may include an implementation of a network environment. The program modules 42 generally perform the functions and / or methodologies of the embodiments described herein.

[0061] The computer system / server 12 may also communicate with one or more external devices 14, such as a keyboard, pointing device, and display 24, one or more devices that allow a user to interact with the computer system / server 12, and / or any device (e.g., network card, modem, etc.) that allows the computer system / server 12 to communicate with one or more other computing devices. Such communication may occur via an input / output (I / O) interface 22. Additionally, the computer system / server 12 may communicate with one or more networks, such as a local area network (LAN), a general wide area network (WAN), and / or a public network (e.g., the Internet), via a network adapter 20. As shown, the network adapter 20 communicates with other components of the computer system / server 12 via a bus 18. Although not shown, it should be understood that other hardware and / or software components may be used in combination with the computer system / server 12. Examples include, but are not limited to, microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data archive storage systems, etc.

[0062] The present disclosure may be a system, a method, and / or a computer program product. The computer program product may include a computer-readable storage medium (or media) having computer-readable program instructions thereon for causing a processor to perform aspects of the present disclosure.

[0063] A computer-readable storage medium can be a tangible device capable of retaining and storing instructions for use by an instruction execution device. A computer-readable storage medium can be, for example, but not limited to, an electronic storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device, or any suitable combination of the foregoing. A non-exhaustive list of more specific examples of computer-readable storage media includes the following: portable computer diskettes, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disk read-only memory (CD-ROM), digital versatile disks (DVD), memory sticks, floppy disks, punch cards or mechanically encoded devices such as ridge structures in grooves having instructions recorded thereon, and any suitable combination of the foregoing. As used herein, computer-readable storage media should not be construed as being, per se, transitory signals, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagating through a waveguide or other transmission medium (e.g., light pulses passing through a fiber optic cable), or electrical signals transmitted over a wire.

[0064] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device or to an external computer or external storage device over a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network may include copper transmission cables, optical fiber transmissions, wireless transmissions, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions for storage on a computer-readable storage medium within the respective computing / processing device.

[0065] The computer-readable program instructions for carrying out the operations of the present disclosure may be either assembler instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state-setting data, or source or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, and traditional procedural programming languages ​​such as the "C" programming language or similar programming languages. The computer-readable program instructions may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet Service Provider). In some embodiments, electronic circuitry including, for example, a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA) may execute computer-readable program instructions by utilizing state information of the computer-readable program instructions to personalize the electronic circuitry to perform aspects of the present disclosure.

[0066] Aspects of the present disclosure are described herein with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present disclosure. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-readable program instructions.

[0067] These computer-readable program instructions may be provided to a processor of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, executed by the processor of the computer or other programmable data processing apparatus, create means for implementing the functions / acts specified in the flowchart and / or block diagram blocks. These computer-readable program instructions may also be stored on a computer-readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to function in a particular manner, such that the computer-readable storage medium having instructions stored therein comprises an article of manufacture containing instructions that implement aspects of the functions / acts specified in the flowchart and / or block diagram blocks.

[0068] Computer-readable program instructions can also be loaded into a computer, other programmable data processing apparatus, or other device to generate a computer-implemented process such that a series of operational steps executed on the computer, other programmable apparatus, or other device implement the functions / acts specified in the flowchart and / or block diagram block(s).

[0069] The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to embodiments of the present disclosure. In this regard, each block in the flowcharts or block diagrams may represent a module, segment, or portion of instructions, including one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending on the functionality involved. It should also be noted that each block in the block diagrams and / or flowchart diagrams, and combinations of blocks in the block diagrams and / or flowchart diagrams, may be implemented by a special-purpose hardware-based system that performs the specified functions or actions or executes a combination of special-purpose hardware and computer instructions.

[0070] While the subject matter of the present disclosure is described herein with respect to certain preferred embodiments, those skilled in the art will recognize that various modifications and improvements can be made to the subject matter of the present disclosure without departing from its scope. Moreover, although individual features of one embodiment of the subject matter of the present disclosure may be discussed herein or shown in the drawings of one embodiment and not shown in other embodiments, it should be apparent that individual features of one embodiment may be combined with one or more features of another embodiment or with features of multiple embodiments.

[0071] In addition to the specific embodiments claimed below, the presently disclosed subject matter is also directed to other embodiments having any other possible combinations of the dependent features claimed below and those disclosed above. Accordingly, it should be recognized that the specific features presented in the dependent claims and disclosed above can be combined with each other in other manners within the scope of the presently disclosed subject matter, thereby specifically directing the presently disclosed subject matter to other embodiments having any other possible combinations. Accordingly, the foregoing descriptions of specific embodiments of the presently disclosed subject matter have been presented for purposes of illustration and description. The foregoing description is not intended to be exhaustive or to limit the presently disclosed subject matter to those disclosed embodiments.

[0072] It will be apparent to those skilled in the art that various modifications and variations can be made in the methods and systems of the presently disclosed subject matter without departing from the spirit or scope of the presently disclosed subject matter. Thus, it is intended that the presently disclosed subject matter cover modifications and variations that come within the scope of the appended claims and their equivalents.

Claims

1. 1. A method for manufacturing a metal frame support for a wind turbine blade mold, the method comprising: receiving a wind turbine blade mold surface including a three-dimensional shape file; receiving at least one input parameter; receiving a design scheme; outputting a first plurality of files including at least one line model, the line model representing the generated framework; outputting a second plurality of files including at least one shape data element in text format; performing a finite element analysis of the line model and at least one shape data element; Outputting a full-frame model; and outputting at least one technique view of the full-frame model.

2. The method of claim 1 , wherein the at least one input parameter includes one of a mold shell thickness, a distance from the mold surface to the ground, and a structural tube.

3. The method of claim 1 , wherein the design scheme is automatically scaled to the at least one input parameter and the mold surface.

4. The method of claim 1 , wherein the design scheme comprises a cross section of a metal frame.

5. The method of claim 1 , wherein the design scheme includes an adjacent side connection and a bottom connection.

6. The method of claim 1 , wherein the design scheme is selected from a plurality of design schemes.

7. The method of claim 1 , wherein the second plurality of files includes at least one element of data representing a line, a start point, an end point, and an orientation of a portion of the metal frame.

8. The method of claim 1 , further comprising performing a quality control on the at least one input parameter.

9. The method of claim 1 , further comprising converting the mold surface into a point cloud.

10. The method of claim 9 , wherein the point cloud comprises 100 points per 100 millimeters.

11. 1. A system for manufacturing a metal frame support for a wind turbine blade mold, the system comprising: a first module for receiving input data including a wind turbine blade mold surface including at least a three-dimensional shape file, at least one input parameter, and a design scheme; a second module for generating a first plurality of files including at least one line model, the line model representing the generated framework, and a second plurality of files including at least one shape data element in text format; a third module for performing a finite element analysis of the line model and the at least one shape data element, outputting a full frame model, and outputting at least one technique view of the full frame model.

12. The system of claim 11 , wherein the at least one input parameter comprises one of a mold shell thickness, a distance from the mold surface to the ground, and a structural tube.

13. The system of claim 11 , wherein the design scheme is automatically scaled to the at least one input parameter and the mold surface.

14. The system of claim 11 , wherein the design scheme includes a cross section of a metal frame.

15. The system of claim 11 , wherein the design scheme includes an adjacent side connection and a bottom connection.

16. The system of claim 11 , wherein the design scheme is selected from a plurality of design schemes.

17. The system of claim 11 , wherein the second plurality of files includes at least one element of data representing a line, a start point, an end point, and an orientation of a portion of the metal frame.

18. The system of claim 11 , wherein the system performs quality control on the at least one input parameter.

19. The system of claim 11 , wherein the mold surface is a point cloud.

20. 20. The method of claim 19, wherein the point cloud comprises 100 points per 100 millimeters.

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