Method for determining erosion of an object

Abstract

The invention discloses a method for determining corrosion of an object during a time period. The methods determine physical factors of the object and environmental factors occurring over the time period. A node on the object is determined. At different moments in time within the time period, the methods determine corrosion of the object at the node based on physical and environmental factors. A cumulative corrosion of the object is determined based on the corrosion determined at each node at each moment in time.

Description

Technical Field

[0001] The present disclosure relates generally to the field of corrosion determination, and more particularly to corrosion determination based on physical and environmental factors. Background Art

[0002] Vehicles (e.g., aircraft, ships, trucks, cars, trains and other rail-based transportation vehicles, spacecraft, undersea equipment and trailers), equipment and buildings, and other fixed or non-fixed objects or structures (collectively referred to as "objects") are made of materials that are susceptible to corrosion. This is true for both the entire object and smaller components or portions thereof. Corrosion can be a particular problem for objects that are used or located in harsh environmental conditions.

[0003] The materials that make up an object can experience different types of corrosion. One example includes electrochemical corrosion, which occurs when two dissimilar materials come into contact with a corrosive electrolyte and the electrochemical potential difference between them drives a small current. Another example of corrosion is pitting due to environmental effects.

[0004] Regardless of how corrosion occurs, it is an important factor in determining the overall lifespan and maintenance schedule of an object, and corrosion primarily takes the form of shortening that lifespan compared to preventing corrosion or reducing its effects in some way. As an example of the negative impacts of corrosion, it is estimated that corrosion problems on military equipment alone cost the U.S. Department of Defense nearly $20 billion per year.

[0005] It is difficult to accurately determine the effects of corrosion when designing an object. The reality is that doing so often requires extensive design experience, subjective decision-making, and knowledge on the part of a skilled designer.

[0006] Existing solutions for determining the effects of corrosion on an object attempt to identify physics-based computational models for material interactions. However, these models are difficult to predict and often have little data to accurately rely on. In addition, the complex physics involved often require computationally expensive first-principles modeling, which can take a long time to arrive at a single solution. Empirical corrosion models have also been developed, but require extensive and expensive testing to construct and can take a long time to compare and validate due to the typical timescales over which corrosion damage occurs. Furthermore, empirical models often do not include time and / or location-dependent corrosion damage factors, but only provide a general estimate under specific environmental conditions.

[0007] Additionally, many design processes do not consider corrosion until the complete object design is complete. Sometimes, corrosion does not occur until after the object has been designed, manufactured, and put into use in the field. In some examples, corrosion analysis is not performed until damage is observed on the object. One current procedure is to conduct a root cause analysis (RCA) to determine the cause of corrosion. RCA is not used to design the object, but rather to remedy the problem after corrosion has already occurred, and therefore does not represent an ideal solution. Summary of the invention

[0008] One aspect relates to a method for determining corrosion of an object over a time period. The method includes: determining a physical factor of the object; determining an environmental factor occurring during the time period; determining a plurality of nodes on the object; determining corrosion of the object at the nodes based on the physical factor and the environmental factor at a plurality of times during the time period; and determining cumulative corrosion of the object based on the corrosion determined at each node at each of the plurality of times.

[0009] In another aspect, the method further includes determining the environmental factor based on historical weather data for one or more geographic locations where the subject was located during the time period.

[0010] In another aspect, determining the physical factor includes determining a shape of the object and a material of the object.

[0011] In another aspect, the method further includes determining, for each of a plurality of moments in time, whether a moisture condition occurs, and determining that the corrosion is zero when the moisture condition does not occur.

[0012] In another aspect, the method further includes determining an external force applied to the object during the time period.

[0013] In another aspect, the method further includes determining a grid extending over the object and determining a plurality of nodes based on the grid.

[0014] In another aspect, the method further includes determining a physical factor of the object based on a date range and a geographic location received from the user.

[0015] One aspect relates to a method for determining corrosion of an object over a period of time. The method includes: determining physical factors and environmental factors for a geographic location of the object over the period of time; determining corrosion at nodes spaced apart on the object at each of a plurality of moments occurring over the period of time; and accumulating the corrosion at the nodes for the plurality of moments and determining the accumulated corrosion of the object.

[0016] In another aspect, the method further includes receiving inputs including a date range for the time period, a geographic location, and an identification of the object.

[0017] In another aspect, the method further includes receiving a geometric model of the object and determining a location of the node on the object based on the geometric model.

[0018] In another aspect, the environmental factors include two or more of relative humidity, precipitation, temperature, and dew point.

[0019] In another aspect, the method further includes determining whether a moisture condition occurs at the node at each of a plurality of time instances; and determining that there is no corrosion at the node for a plurality of time instances when the moisture condition does not occur.

[0020] In another aspect, the time period is a historical period that has already occurred, and the environmental factors are based on weather conditions that occurred at the geographic location during the time period.

[0021] On the other hand, physical and environmental factors include predictive factors based on conditions that the subject is expected to encounter during use.

[0022] In another aspect, the object is an aircraft and the geographic location includes a plurality of locations flown by the aircraft during the time period.

[0023] One aspect relates to a computing device configured to determine corrosion of an object. The computing device includes: a memory circuit storing programming instructions; and a processing circuit configured to execute the programming instructions to cause the computing device to: receive a date range, a geographic location of an object, and an identification of the object; determine a plurality of nodes on the object based on the identification of the object; for a plurality of moments in the time period: determine an external force applied to the node; determine a film thickness on the node; determine an environmental condition at the node; and determine corrosion at the node based on the external force, the film thickness, and the environmental condition.

[0024] In another aspect, the processing circuit is further configured to determine cumulative erosion of the object based on erosion at the node for multiple time instants.

[0025] In another aspect, the processing circuit is further configured to determine a moisture condition of the node at each of a plurality of times and determine a film thickness on the node based on the moisture condition.

[0026] In another aspect, the processing circuit is further configured to determine that there is no film thickness on the node when a moisture condition does not occur.

[0027] In another aspect, the processing circuit is further configured to determine, from a remote source, environmental factors acting on the subject during a plurality of moments in time.

[0028] The features, functions and advantages discussed can be achieved independently in different aspects or can be combined in other aspects, and further details thereof can be seen with reference to the following description and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 This is a perspective view of the aircraft.

[0030] Figure 2 is a flow chart of a method for determining corrosion of an object.

[0031] Figure 3 is a flow chart of another method of determining corrosion of an object.

[0032] Figure 4 A computer-designed schematic diagram of an object having a mesh comprising nodes.

[0033] Figure 5 is a schematic diagram of a computing device. DETAILED DESCRIPTION

[0034] The present application relates to a method for determining corrosion of an object. The method takes into account the development of continuous or discontinuous films that may change over time and vary in the surface geometry of the object. The method can be used to predict corrosion on existing objects that have been exposed to environmental conditions that cause corrosion within a certain date range. The method can also be used to predict corrosion on objects that will be exposed to specific environmental conditions.

[0035] Figure 1 Examples of objects 90 associated with an aircraft are shown. In some examples, object 90A is an entire aircraft. In other examples, object 90 is one or more limited sections of a vehicle, such as a fuselage 90B, a wing 90C, a flight control member 90D, and an engine cowling 90E. Other examples in the context of an aircraft include, but are not limited to, ribs, spars, stringers, and engine parts.

[0036] Methods for determining corrosion use one or more factors. Examples of these factors include physical factors of the object 90 and environmental factors in which the object 90 is located or travels, visits, or is brought. These methods avoid the need for computationally expensive high-fidelity simulation methods while still retaining sufficient fidelity to determine the corrosion damage area of ​​the object 90 in a variety of environmental conditions in relation to time and location.

[0037] Figure 2A method for determining corrosion of an object is shown. The method includes determining one or more physical factors of the object (box 100). The physical factors may include, but are not limited to, the material that constitutes the object, and may include, but are not limited to, one or more of the substrate and finish of the material. Another physical factor is the thickness of the material, including but not limited to the thickness of the substrate and the finish. Physical factors also include, but are not limited to, the shape of the object. An example of a shape is a surface geometry, such as a curvature, an angled surface, an edge, an opening, a punch-out, a coupon, and a seam. Physical factors may also include, but are not limited to, connectors between two or more different sections, such as rivets, bolts, seams, welds, joints, and bonds.

[0038] The method also includes determining environmental factors (block 102). Examples include, but are not limited to, one or more weather conditions, which may include, but are not limited to, one or more of relative humidity, climate, precipitation, temperature, dew point, dry bulb or wet bulb temperature, wind speed, wind direction, and / or solar radiation. Another weather condition is distance from the ocean, which takes into account the salt content in the air (i.e., the air along the coast contains more salt than the air far from the ocean). Air pollution, smog (e.g., from wildfires), and haze are also non-limiting examples that may be included as environmental factors.

[0039] The method uses these factors to determine the corrosion of the object at one or more times during a given time period (block 104). The time period and times during the time period for testing can be established by the user or can be a default setting. In one non-limiting example, the time period is six months and testing occurs once a week.

[0040] In some examples, the determination of erosion at one or more time instances is a final output. In other examples, the method further includes determining cumulative erosion of the object based on erosion determinations from different time instances (block 106).

[0041] In some examples, the determination of corrosion on an object occurs for an existing object. For example, corrosion is determined on a wing assembly that is part of an aircraft and has been in continuous or active use during a given period of time (e.g., corrosion on a wing that has been in service for a period of nine months). Physical factors are established from existing objects, and environmental conditions are based on known weather and / or climate conditions that occurred during the period of time.

[0042] In some examples, the corrosion determination uses a proposed design and / or artificial weather conditions. In some examples, the proposed design uses the engineering specifications for the object. The weather conditions can be based on various numbers, such as an average for a given geographic location, or a recorded high or low value for a given geographic location. This test essentially determines the corrosion that would occur on the object if the object were exposed to the weather conditions.

[0043] Figure 3 A method of determining corrosion of an object is shown. The example uses an existing object that has been exposed to weather conditions within a given date range. The method of determining corrosion is generally divided into an input section 20, a calculation section 30 and an output section 50.

[0044] Input section 20 provides one or more factors for establishing corrosion of an object. These factors may be input by a user, or may be part of an automated process for analyzing corrosion. These factors include a date range and a geographic location (box 21). The geographic location may include various levels of detail. Examples include, but are not limited to, counties, regions, cities, specific addresses (such as airport addresses, building addresses), and latitude / longitude. For objects that move within a date range (such as aircraft), the geographic location may include multiple locations. In an example where the object is an aircraft, the geographic location includes each destination where the aircraft landed during a given time period.

[0045] Another input is a time schedule (box 22). The time schedule provides the frequency of corrosion calculations. Examples include but are not limited to monthly, weekly, daily, and hourly.

[0046] The input section 20 also includes physical factors (box 23), examples of which include, but are not limited to, material, thickness, shape, surface geometry, and connections. In some examples, the physical factor is a specific brand / model of the object (e.g., a 1997 BMW 328i sedan). In another example, the user inputs an engineering drawing of the object including shape and thickness. In some examples, one or more remote sources 70 are accessed to retrieve applicable data (e.g., the surface geometry of a Boeing 737 aircraft).

[0047] The calculation section 30 uses the factors from the input section 20 and calculates the erosion of the object. The environmental factors are determined for the input date range and geographic location (box 31). In one example, the environmental factors are accessed from one or more remote sources 70 containing environmental data such as historical weather data, climate data, and sensor measurements. The remote sources 70 may include, but are not limited to, different databases, sites available over a network (e.g., the Internet), and different model sources. In some examples, the database may be external (e.g., a publicly available API) or internal (e.g., a file of measurements or an internal server set). Examples of sources 70 available over the network include, but are not limited to, the National Oceanic and Atmospheric Administration (NOAA), the Integrated Surface Database (ISD), the Meteorological Assimilation Data Ingestion System (MADIS), and the Independent Slope Parameter-Altitude Regression Model (PRISM).

[0048] In some examples, one or more of the environmental factors are based on sensor readings. The object includes one or more sensors that monitor one or more environmental conditions. The readings from the one or more sensors are stored and accessed as needed to provide environmental data. In a specific example, the object is an aircraft that includes multiple sensors that monitor environmental conditions.

[0049] In the case where environmental factors are not available for a date range and / or geographic location, data is obtained by interpolation using known data (box 32). The location conversion and data conversion determine the nearest available environmental and geographic data. In a specific example, the location conversion transforms the input latitude / longitude to the nearest weather collection station where environmental data is available. In some examples, this step (box 32) includes supplementary calculations to determine additional environmental data (e.g., to determine dew point based on other known parameters).

[0050] One or more of the physical factors are used to determine a mesh 80 of the object (block 33). The mesh 80 corresponds to the surface geometry of the object. Figure 4 In one example shown, the grid 80 includes an interlaced network of nodes 81 extending along the surface of the object. The number and positioning of the nodes 81 on the object can vary. In some examples, and as shown in FIG. Figure 4 As shown, nodes 81 are evenly spaced and positioned around the object. Other examples include nodes 81 positioned at one or more limited sections of the object (such as, but not limited to, specific surfaces or exposed edges). In some examples, the mesh 80 is a geometric transformation from a digital file (such as a CAD geometry file). Other examples include meshes 80 based on spline geometry, and meshes 80 based on user-provided data (such as the position coordinates of the nodes 81).

[0051] The calculation assigns initial coordinates to the node 81 (box 34). In some examples, the initial conditions are based on user input. In other examples, the initial conditions include physical factors and / or environmental factors determined for the geographic location at the beginning of the date range 20.

[0052] The process starts the corrosion calculation at the first moment during the time schedule. Environmental factors are retrieved for this moment (box 35). In some examples, physical factors are also retrieved. The method determines the external forces applied to the node 81 (box 36). Examples of external forces include, but are not limited to, gravity based on the direction of gravity relative to the grid 80 (resulting in a static non-moving force distribution), a force schedule that changes with the time schedule caused by objects when they move (e.g., forces applied to an aircraft during flight), wind forces, thermal forces (e.g., radiative heating from reflection of sunlight), convective forces (e.g., forces generated by wind moving across the surface of the grid at a defined speed and direction), cleaning of objects, washing of objects, and changes in species concentrations in the atmospheric environment. The force schedule 74 can be input by a user, stored in a memory, and / or retrieved from a remote source 70.

[0053] The process determines the presence of an electrolyte membrane at node 81 (box 37). The presence of the membrane is calculated by an associated moisture condition 75, which is based on one or more of environmental factors and physical factors. In some examples, the moisture condition occurs due to the following conditions: the relative humidity (RH) at node 81 is higher than a predetermined level; the temperature at node 81 is lower than the dew point temperature; and the near-side environmental conditions (such as wall temperature) at node 81 are lower than the dew point. If the moisture condition is determined, the process determines the membrane thickness. If there is no moisture condition, the process determines that there is no corrosion at a given time. In some examples, the process assumes that the moisture condition is met and automatically determines the membrane thickness.

[0054] The film thickness is calculated by a film thickness model 71. The film thickness model 71 may be accessed from a source 70 and / or maintained in a memory circuit. The film thickness calculation may include various methods. Examples include, but are not limited to, analytical equations (e.g., Nusselt film model equations), heuristic algorithms based on empirically measured laboratory values, model fitting, machine learning models, film models (e.g., for situations such as icing), and more advanced physical simulations, such as full computational fluid dynamics simulations of the film.

[0055] Next, environmental factors are determined for the node 81 (box 38). In some examples, one or more of the environmental factors are the same for each node 81 (e.g., relative humidity, dew point). In some examples, the process determines the proximal environmental factors of the node 81. The term "proximal" refers to the conditions that are most local to the node 81. In some examples, the proximal calculation uses a physical model 72 (such as a heat transfer model) to determine the proximal temperature relative to the film temperature. In some examples, the heat transfer model calculates multiple layers. In a specific example, the calculation uses the ambient temperature, determines the internal film temperature from the convective heat transfer model for the ambient temperature, and calculates the proximal temperature from the conductive heat transfer model based on the internal film temperature.

[0056] Once the physical and environmental factors are known, the method calculates the corrosion damage at the node 81 (box 39). In some examples, the process uses the corrosion model 73. The corrosion model 73 may include various formats, examples of which include but are not limited to analytical equations (e.g., mathematical functions of near-side environmental conditions), empirically determined model fits, machine learning models, and more advanced calculations, such as macromolecular simulations, chemical simulations, or Monte Carlo simulations. The resulting corrosion damage at the node 81 is saved for a specified time in the time schedule (box 40).

[0057] The process then determines if there are additional moments in the time schedule (block 41). For each additional moment, corrosion damage is determined for node 81. Once corrosion is determined for each moment, data is analyzed for object 90. In some examples, this ends the process.

[0058] In other examples, one or more post-processing steps calculate one or more additional desired properties (box 42). In some examples, post-processing includes calculating the total mass loss over the entire exposed surface of the geometry. This can include summing all corrosion rates on the node 81 for a moment in the time schedule. In some examples, post-processing includes calculating the maximum corrosion rate. This includes calculating the maximum value (supremum) of the corrosion rate on the node 81 for a moment in the time schedule. In some examples, post-processing includes calculating the total wetting time (TOW), the presence of moisture throughout the object 90, the overall / average / distributed film thickness, and / or the corrosion current density. In some examples, post-processing includes integrating the corrosion current density to determine the total accumulated charge due to the corrosion activity.

[0059] The output section 50 provides for outputting various corrosion data (box 51). Examples of outputs include corrosion data for nodes 81, cumulative corrosion data for objects 90, and various other data calculated during post-processing steps. The output may include corrosion data for one or more moments from a time schedule, or cumulative corrosion taking into account corrosion that varies with different input moments.

[0060] In some examples, the process occurs during the design phase of determining corrosion predictions using laboratory testing and / or virtual testing. The physical factors used for corrosion calculations can be proposed design details for the proposed object 90. This provides proposed design details for the object 90 to be tested, and any necessary changes due to corrosion risks can be made early in the design process and before actual manufacturing. Additionally and / or alternatively, the environmental factors can be other data than historical record data. In some examples, average environmental conditions for a given geographic location can be used for corrosion testing. In other examples, higher levels of conditions can be used to ensure safety margins (e.g., 95% relative humidity and dew point temperature during testing).

[0061] In some examples, one or more of the inputs 20 are predicted values ​​based on conditions that the object is expected to encounter during use. For example, during the design phase of the object, designers / engineers assign numerical values ​​to one or more of the environmental factors and / or physical factors that are expected to be experienced by the object.

[0062] Figure 5 A computing device 60 configured to perform corrosion calculations is shown. The computing device 60 may include a variety of different forms, including but not limited to server computers, workstation computers, desktop computers, smart phones, tablet computers, and laptop computers. The computing device 60 may include, for example, one or more of each of several components of a processing circuit 61 (e.g., a processor unit) connected to a memory circuit 62 (e.g., a storage device).

[0063] The processing circuit 61 may be composed of one or more processors alone or in combination with one or more memories. The processing circuit 61 is typically computer hardware capable of processing information, such as data, computer programs, and / or other suitable electronic information. The processing circuit 61 is composed of a series of electronic circuits, some of which may be packaged as an integrated circuit or multiple interconnected integrated circuits (integrated circuits are sometimes more generally referred to as "chips"). The processing circuit 61 may be configured to execute programmed instructions 79, such as a film thickness model 71, a physical model 72, and a corrosion model 73, which may be stored on the processing circuit 61 or otherwise stored in a memory circuit 62 (of the same device or another device).

[0064] The processing circuit 61 may be a number of processors, a multi-core processor, or some other type of processor, depending on the particular implementation. In addition, the processing circuit 61 may be implemented using a number of heterogeneous processor systems, in which a main processor is present on a single chip with one or more secondary processors. As another illustrative example, the processing circuit 61 may be a symmetric multiprocessor system containing multiple processors of the same type. In another example, the processing circuit 61 may be embodied as or include one or more ASICs, FPGAs, and the like. Therefore, while the processing circuit 61 may be capable of executing a computer program to perform one or more functions, the processing circuit 61 in various examples may also perform one or more functions without the aid of a computer program. In either case, the processing circuit 61 may be appropriately programmed to perform functions or operations according to the example implementations of the present disclosure.

[0065] The memory circuit 62 is typically computer hardware that can temporarily and / or permanently store information, such as data, computer programs (such as computer readable program code), and / or other suitable information. The memory circuit 62 may include volatile and / or non-volatile memory and may be fixed or removable. Examples of suitable memory circuits 62 include random access memory (RAM), read-only memory (ROM), hard drive, flash memory, thumb drive, removable computer floppy disk, optical disk, tape, or some combination of the above devices. The optical disk may include a compact disk read-only memory (CD-ROM), a compact disk read / write (CD-R / W), a DVD, etc. In various examples, the memory circuit 62 may be referred to as a computer-readable storage medium. A computer-readable storage medium is a non-temporary device capable of storing information, which is distinguished from a computer-readable transmission medium, such as an electronic temporary signal capable of carrying information from one location to another. The computer-readable medium described herein may generally refer to a computer-readable storage medium or a computer-readable transmission medium.

[0066] The computing device 60 also includes a communication interface circuit 63, which is configured to transmit and / or receive information, such as to and / or receive from an information source 70, a user device, other devices, a network, etc. The communication interface circuit 63 can be configured to transmit and / or receive information via a physical (wired) and / or wireless communication link. Examples of suitable communication interfaces include a network interface controller (NIC), a wireless NIC (WNIC), or a similar device. The communication interface circuit 63 can have one or more transmitters and / or receivers.

[0067] The user interface 64 provides the user with control over one or more aspects of the corrosion test. The user interface 64 includes one or more input devices 65, such as, but not limited to, a keypad, a touch pad, a roller ball, and a joystick. The user interface 64 also includes one or more displays 66 for displaying information about the test and / or for the operator to input commands to the processing circuit 61.

[0068] It will be understood by those of ordinary skill in the art without undue experimentation that programming instructions 79 can be loaded from a computer-readable storage medium onto a computing device or other programmable device to produce a specific machine so that the specific machine becomes a means for implementing the functions specified herein. These programming instructions 79 can also be stored in a computer-readable storage medium that can instruct a computer, processing circuit, or other programmable device to operate in a specific manner to generate a specific machine or a specific product. The programming instructions 79 can be retrieved from a computer-readable storage medium and loaded into a computer, processing circuit, or other programmable device to configure the computing device 60, processing circuit 61, or other programmable device to perform operations to be performed on or by a computer, processing circuit, or other programmable device.

[0069] The retrieval, loading, and execution of the programming instructions 79 may be performed sequentially, such that one instruction is retrieved, loaded, and executed at a time. In some example embodiments, the retrieval, loading, and / or execution may be performed in parallel, such that multiple programming instructions 79 are retrieved, loaded, and / or executed together. The execution of the programming instructions 79 may produce a computer-implemented process such that the programming instructions 79 executed by a computer, processing circuit, or other programmable device provide operations for implementing the functionality described herein.

[0070] The present invention allows prediction of the corrosion damage behavior over time in a changing environment in which an object may be stored or used. The application takes into account the development of continuous or discontinuous films that may change over time and vary across the surface geometry of the vehicle platform. This can be used to predict corrosion damage to objects 90 stored for long periods of time or damage problems that may be caused by moisture. The present invention can also be used to study and predict the impact of environmental changes on damage caused by corrosion during storage or use.

[0071] Without departing from the essential features of the present invention, the present application may be implemented in other ways than those specifically described herein. The present embodiment should be considered as illustrative and non-restrictive in all aspects, and all changes within the meaning and equivalent scope of the appended claims should be included in these embodiments.

Claims

1. A method for determining corrosion of an object (90) over a period of time, the method comprising: determining physical factors of the object (90); determining environmental factors occurring during said time period; determining a plurality of nodes (81) on the object (90); determining, at a plurality of times during the time period, corrosion of the object (90) at the node (81) based on the physical factor and the environmental factor; as well as A cumulative erosion of the object (90) is determined based on the erosion determined at each of the nodes (81) at each of the plurality of times.

2. The method of claim 1, further comprising determining the environmental factor based on historical weather data for one or more geographic locations where the object (90) was located during the time period.

3. The method of claim 1, wherein determining the physical factor comprises determining a shape of the object (90) and a material of the object (90).

4. The method according to claim 1, further comprising: For each of the plurality of time instants, it is determined whether a moisture condition occurs, and when the moisture condition does not occur, the corrosion is determined to be zero.

5. The method of claim 1, further comprising determining external forces applied to the object (90) during the time period.

6. The method of claim 1, further comprising determining a grid (80) extending over the object (90) and determining the plurality of nodes (81) based on the grid (80).

7. The method of claim 1, further comprising determining the physical factor of the object (90) based on a date range and a geographic location received from a user.

8. A method for determining corrosion of an object (90) over a period of time, the method comprising: determining physical and environmental factors for a geographic location of the subject (90) for a time period; determining corrosion at nodes (81) spaced apart on the object (90) at each of a plurality of moments occurring during the time period; as well as The erosion at the node (81) at the plurality of time instants is accumulated and the accumulated erosion of the object (90) is determined.

9. The method of claim 8, further comprising receiving input including a date range for the time period, the geographic location, and an identification of the object (90).

10. The method of claim 8, further comprising receiving a geometric model of the object (90) and determining the location of the node (81) on the object (90) based on the geometric model.

11. The method of claim 8, wherein the environmental factors include two or more of relative humidity, precipitation, temperature, and dew point.

12. The method according to claim 8, further comprising: determining whether a wet condition occurs at the node (81) at each of the plurality of times; as well as When the wet condition does not occur, it is determined that there is no corrosion at the node (81) for the plurality of time instants.

13. The method of claim 8, wherein the time period is a historical period that has occurred and the environmental factors are based on weather conditions that occurred at the geographic location during the time period.

14. The method of claim 8, wherein the physical factors and the environmental factors include predictive factors based on conditions that the subject (90) is expected to encounter during use.

15. The method of claim 8, wherein the object (90) is an aircraft (99), and the geographic location comprises a plurality of locations that the aircraft (99) flew over during the time period.

16. A computing device configured to determine corrosion of an object (90), the computing device comprising: a memory circuit (62) storing program instructions; as well as processing circuitry (61) configured to execute the programming instructions (79) to cause the computing device to: receiving a date range, a geographic location of the object (90), and an identification of the object (90); Determining a plurality of nodes (81) on the object (90) based on the identifier of the object (90); For multiple moments during the time period: determining an external force applied to the node (81); determining the film thickness at the node (81); determining environmental conditions at the node (81); and Corrosion at the node (81) is determined based on the external force, the film thickness and the environmental conditions.

17. The computing device of claim 16, wherein the processing circuit (61) is further configured to determine a cumulative erosion of the object (90) based on the erosion on the node (81) for the plurality of time instances.

18. The computing device of claim 16, wherein the processing circuit (61) is further configured to determine a moisture condition of the node (81) at each of the plurality of moments in time, and to determine the film thickness on the node (81) based on the moisture condition.

19. The computing device of claim 18, wherein the processing circuit (61) is further configured to determine that there is no film thickness on the node (81) when the moisture condition does not occur.

20. The computing device of claim 16, wherein the processing circuit (61) is further configured to determine, from a remote source, environmental factors acting on the object (90) during the plurality of time instances.

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