Systems and methods for industrial waste containers

Abstract

A method for manufacturing an on-site optimized containment vessel includes obtaining location data and waste characteristic data for at least one waste at an industrial site, generating or obtaining parameter / characteristic data for at least one waste stream for the at least one waste, determining at least one material for containing the waste based on the waste stream parameters and the location data, and generating an optimized vessel design based on the at least one material and containment facility data. A containment vessel is manufactured based on this design. A complete digital record of custom design parameters, testing, and / or life measurements for each vessel is maintained.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the full benefit (including priority) of U.S. Provisional Patent Application No. 63 / 433,352, filed December 16, 2022, entitled "SYSTEMS AND METHODS FOR INDUSTRIAL WASTE CONTAINERS," the entire contents of which are incorporated herein by reference. [Technical Field]

[0002] Aspects of the present disclosure relate to the field of industrial waste containers, and more particularly to systems and methods for shape-optimized waste containers for radioactive waste. [Background technology]

[0003] Nuclear power plant operation produces radioactive waste that must be disposed of safely and securely for thousands of years. Regulations are strict, placing strict limits on the strength and performance required to qualify any component for safety functions. Due to the risks posed by radioactive waste releases, it is in the best interest of all stakeholders to minimize the amount of containment required. Furthermore, the high costs associated with producing safe-to-use containers mean reduced containment. Summary of the Invention [Problem to be solved by the invention]

[0004] Containment facilities are complex and highly dependent on the local geography as well as available resources and regulatory frameworks.

[0005] Existing manufacturing processes have a large carbon footprint, as the material is produced off-site and then transported to a filling facility. [Means for solving the problem]

[0006] In one aspect, a method for manufacturing an on-site optimized containment vessel using one or more aspects described herein is provided. In some embodiments, the method includes obtaining location data and waste characteristic data for at least one waste product at an industrial site, generating or obtaining parameter / characteristic data for at least one waste stream, determining at least one material for containing the waste product based on the waste stream parameter and location data, and generating an optimized vessel design based on the at least one material and containment facility data.

[0007] In another aspect, there is provided an in-situ optimized containment vessel manufactured based on a design generated using one or more aspects of the methods described herein, hi some embodiments, the containment vessel has an irregular hexagonal footprint.

[0008] In yet another aspect, a containment kit is provided that includes a digital record of the design considerations, testing and / or life measurements for a particular containment vessel. [Brief explanation of the drawings]

[0009] The preferred and other exemplary embodiments are disclosed in connection with the accompanying drawings. [Figure 1] 1 is a cross-sectional view of an exemplary cylindrical waste container within a waste package. [Figure 2A] 1 illustrates an embodiment of an exemplary system for manufacturing industrial waste containers. [Figure 2B] FIG. 1 illustrates aspects of an exemplary metrology, manufacturing, or computing device. [Figure 3] 1 illustrates an exemplary method aspect for an industrial waste container. [Figure 4] 1 illustrates an exemplary footprint or cross section of a custom waste container. DETAILED DESCRIPTION OF THE INVENTION

[0010] Existing processes are based around what is currently available and qualified, resulting in the repurposing of containers designed for one waste stream for another, containers designed for one facility being used for containment at a different facility, containers made from available materials rather than those considered optimal, and containers certified in one region (e.g., North America) being used in another region (e.g., Europe) without fully evaluating the impact of different regulatory frameworks.

[0011] In some embodiments, aspects of the present disclosure provide systems and methods for fabricating shape-optimized waste containers on-site. In some embodiments, the waste containers are configured for containment of radioactive waste. In some embodiments, the containers are produced using wire arc additive manufacturing.

[0012] In safety-critical industries, two approaches typically exist: a prescriptive approach, where requirements are strictly defined and inflexible (e.g., the United States); and a permissive approach, where design justification is strong within fundamental constraints (e.g., the United Kingdom). The former limits options, while the latter allows for greater freedom in areas where many competing design parameters exist, but both complicate design decisions. In some situations, aspects of the present disclosure can provide an algorithmic approach to the design of nuclear waste containers, with tools that generate one or more designs within a basic set of rules (e.g., minimum load limits, radiation exposure).

[0013] Additionally, the existing design process involves multiple review periods to select a design candidate from multiple options. The design review focuses primarily on structural behavior and does not consider containment layout or logistical considerations. Furthermore, as noted above, the design review considers a vessel that has already been certified, regardless of whether it is suitable for the application, adding additional time and cost to the design review process. Streamlining this process through automation would allow for a combination of logistical and structural considerations to quickly eliminate options at an early stage.

[0014] Traditional manufacturing techniques require large factory footprints that scale linearly with the number of designs to be produced. Each design requires a dedicated production facility to create the molds and other related equipment, similarly increasing costs. Additive manufacturing allows multiple designs to be manufactured in a single factory cell, optimizing overall factory footprint and allowing for greater customization to provide better containment solutions.

[0015] Figure 1 shows an example of the problem described above. A cylindrical container 10 is originally housed within a larger package 20 that has a packaging stillage (a wine bottle carrier crate-like structure adapted for waste receptacles). The presence of corner posts 30 and a central inspection port 40 results in a lot of wasted space. This can add millions of pounds to the cost of the waste containment solution, depending on the type and amount of waste being contained.

[0016] Finally, the Regulatory Safety Case (UK term, local terminology varies) is required to document the many analytical tasks and assessments that are required to demonstrate that the container complies with regulations and is safe for use. This is in addition to the control documents, applications, certificates and tracking information that apply to each container. These are often physical paper documents, which creates storage and traceability problems because: a. Securing storage space, b. Direct association with the relevant vessel and / or design; c. Maintaining the quality and safe storage of waste containers over their lifespan (100 years or more); This is because:

[0017] Therefore, the ability to manufacture custom-designed waste containers optimized for storage space and maintain secure and robust digital records offers many benefits to the industry.

[0018] 2A illustrates an exemplary system 100 for manufacturing industrial waste containers. In some instances, aspects of the system can be utilized to generate custom waste containers based on observed / measured waste and location characteristics. In some instances, aspects of this exemplary system can be part of a larger process for waste containment and storage.

[0019] In the illustrated example, the system 100 includes one or more metrology devices 110 that can be used to acquire location data and / or waste characteristic data. In some embodiments, the metrology devices can include laser, ultrasonic, or other distance measurement sensors. In some embodiments, the metrology devices can include temperature, humidity, toxicity, pH, radiation, and / or other types of environmental sensors. In some embodiments, the metrology devices can include lidar or other sensors that detect the (three-dimensional) size and / or shape of the waste, the environment (e.g., geographic location, surrounding obstacles / objects, location and surrounding area, surrounding objects on the waste exit path, obstacles, the transport mechanism exit path, or storage facility). In some embodiments, the metrology devices can include material composition sensors. In some embodiments, the metrology devices can include one or more data storage devices that store circuit diagrams, blueprints, chemical / material composition properties, and / or other previously measured / generated location and / or waste characteristic data. In some embodiments, the metrology equipment can include a data storage device having a database stored therein that stores characteristics of different materials / waste products and / or containment vessels (e.g., reactivity, radiation type, heat generation capacity, chemical phase, containment material properties (strength, reactivity, thermal diffusivity, corrosion resistance, etc.), safety / regulatory / containment requirements, etc.) In some embodiments, the metrology equipment can include any combination of the above equipment and / or other equipment for obtaining characteristics that can be utilized in generating a vessel design.

[0020] In some examples, metrology device 110 can be connected to computing device 120, which in some examples can be a server or a standalone computing device that performs calculations for generating designs and sending / controlling instructions to the manufacturing process. Metrology device 110 can also include software applications or modules for implementing aspects of the container production system.

[0021] In some embodiments, an exemplary industrial waste container system can include multiple metering devices 110 that measure or acquire different data. In some examples, the metering devices 110 and the computing device 120 can be in different locations, such as removable or handheld devices in different locations, or a server or database hosted at a remote location. Data can be transmitted and received between the devices over a network 130. The network 130 can include one or more private and / or public networks. The network 130 can include a wired network, such as a wired local area network or the Internet, a direct link, or a wireless network, such as a cellular network, Bluetooth, or Wi-Fi network. In some embodiments, the network 130 can include any communication channel capable of communicating data. A communication channel can include wires, vias, or other communication means within a single device.

[0022] In the illustrated example, system 100 includes one or more manufacturing systems 140. In some embodiments, the manufacturing systems can include any additive manufacturing system, such as an arc-based additive manufacturing system, a 3D printing system, and / or any other manufacturing system capable of receiving a custom container design and manufacturing the container. In some embodiments, manufacturing system 140 is located on-site at the waste site. In other situations, the manufacturing system can be located nearby or at an operationally efficient location based on manufacturing inputs, energy inputs, transportation availability, and / or the location and characteristics of the waste.

[0023] Although the exemplary system shows three metrology devices, one manufacturing system, and one computing device, any number of metrology devices, manufacturing devices, or computing devices may be used, and these devices may be used in any suitable configuration.

[0024] In some examples, computing device 120 may host or have access to a database that stores material, storage, and / or waste information. In some examples, computing device 120 may host applications or software modules accessible to client devices and provide processing for performing aspects of the methods described herein.

[0025] In some examples, the computing device 120 may itself be or be part of the metrology device 110 and / or manufacturing system 140. For example, the manufacturing device or metrology device may include a processor capable of performing the computational aspects of the processes described herein.

[0026] In some examples, the system can include a database located on the client device 110, a database located on the central device 120, or a database located elsewhere on the network. The database can, in some examples, store waste, material, location, facility, and / or regulatory information. In some examples, a local or backup copy of the orthodontic information can be stored on the metrology device 110, the computing device 120, the manufacturing system 140, or elsewhere in the system.

[0027] Examples of measurement device 110 and computing device 120 include, but are not limited to, computers, servers, tablet or mobile computers, mobile phones, etc., which may have one or more attached or peripheral devices (e.g., input devices, sensing systems, measurement devices, etc.).

[0028] 2B illustrates an exemplary metrology device 110, manufacturing device 140, or computing device 120 configuration. The devices 110, 120, 140 include one or more processors 210 connected to one or more memories 220, communication modules 230, input devices 240, or displays 250. In some embodiments, the devices 110, 120 may include one or more manufacturing systems 140, 260.

[0029] In some examples, memory 220 can store modules that enable processor 210 to perform any aspect of the methods described herein. In some examples, memory 220 can store waste, location, transportation, material, and / or regulatory information.

[0030] In some examples, the devices 110 , 120 may include a communications module 230 that includes hardware or software for communicating data or instructions over the network 130 .

[0031] In some examples, the apparatus 110, 120 can include or be connected to one or more input devices 240 that receive input for adjusting parameters, making design choices, controlling a process, or otherwise operating the apparatus 110. Examples of input devices can include a keyboard, a mouse, a touchscreen, a touchpad, a navigation device, a remote control, a tablet computer, a mobile phone, or other suitable input device. These devices can be integrated, connected, peripheral, or other suitable types of devices.

[0032] In some examples, the devices 110, 120, 140 may include or be connected to a display 250 that displays aspects of the manufacturing process.

[0033] In some examples, computer readable instructions, such as a computer program or application, may be installed on or operable on a client or central device, or may be stored on a non-transitory computer readable medium.

[0034] In some instances, measurements or other information may be stored on one device and be accessible by different users in different locations or on different devices.

[0035] System 100, in some examples, provides a digital design environment in which aspects of the system can be used to create, store, and / or manufacture container designs.

[0036] In some examples, one or more of the devices 110, 120 and / or one or more of their processors 210 may be configured to perform any aspect of the methods described herein.

[0037] 3 illustrates a flowchart of an exemplary method 300 for in-situ optimized containment. While these flowcharts illustrate one example of an operational sequence for the exemplary system 100, it should be understood that aspects of different flowcharts may be combined and performed in any suitable order. In some embodiments, aspects of the method may be performed by a single processor / device / system, while in other cases, they may be performed by different processors / devices / systems.

[0038] At 310, the one or more processors are configured to acquire location data and waste characteristic data. As described below, in some embodiments, the acquired data may include data regarding the layout of the containment facility (e.g., blueprints, maps, dimensions of exits or potential exits, other waste pathways, and structural / spatial constraints on those pathways).

[0039] In some embodiments, the data obtained may include measured, detected, observed, accessed, or otherwise data regarding the type of waste being contained, including, but not limited to, size, weight / mass, radioactive characteristics, heat generating characteristics, state (solid, liquid, gas), corrosivity, toxicity, venting, reactivity, chemical composition, etc.

[0040] In some embodiments, the data obtained may include geographic location data and / or relevant regulations of the jurisdiction in which the waste is located and / or stored.

[0041] In some embodiments, the data obtained may include submission requirements, such as size of waste material, ability to safely reduce / crush, conversion to waste streams (e.g., containment in mixtures such as molten glass, concrete, etc.), etc. [Table 1]

[0042] In some embodiments, the processor obtains a design along with the overall space constraints governing the containment facility, allowing the containment facility's constraints to be defined in a manner compatible with computer-based processes. The design is provided as a CAD file derived from a manual modeling process or using laser scanning hardware to create a digital shadow of the facility.

[0043] The electronic design is converted into a set of data points that capture the layout of the facility, including all obstacles (stairs, hallways) and other geometric features.

[0044] At 320, the processor is configured to generate / obtain characteristic data for at least one waste stream.

[0045] In some situations, there may be multiple radioactive waste streams (including solid and liquid wastes, and waste streams encapsulated in glass or concrete). The waste streams of interest are processed and analyzed to generate multiple inputs to the algorithm. These inputs and associated outputs include: a. Chemical phase (e.g., solid, liquid, sludge, resin), b. reactive substances (e.g., acids, chelating agents); c. the type of radiation present; d. Heat generating capacity, Includes:

[0046] In some embodiments, the processor is configured to generate characteristic data for a sludge or resin that may be a mixture of different types of waste, but the solid waste may have different unit sizes.

[0047] At 330, the processor is configured to select an appropriate material for waste containment based on the waste stream parameters and the location data.

[0048] Example 1: If vitrified waste is selected as input, the tool may recommend 316L as the material because of its good overall structural and chemical performance. However, if corrosive chemicals in liquid form are present, duplex stainless steel may be recommended because of its high pitting and corrosion resistance. By analyzing the specific region, this recommendation can be cross-referenced with the appropriate regulatory documents to ensure the recommended alloy is likely to be certified.

[0049] Example 2: If the containment area has high humidity and above average salt content, the tool may recommend a duplex stainless steel due to the increased risk of stress corrosion cracking.

[0050] At 340, the processor is configured to generate a vessel design based on the at least one of material and containment facility data.

[0051] In some embodiments, the processor utilizes the output of the previous stage to generate a container cross-section or "footprint" that will optimize the packing density of the container within the facility in two dimensions. In some embodiments, the container cross-section is defined based at least in part on the size of the waste, limiting size factors on the route the waste takes to the containment facility (e.g., doors, exit routes from the facility where the waste resides, transportation restrictions, and containment facility requirements).

[0052] In some embodiments, the processor is configured to generate a path for the treated waste from its original location, exiting the facility / environment where the waste resides, via any transportation route, to the proposed containment facility. In some embodiments, the processor is configured to determine the most restrictive size-limiting factor along that path and determine the size / design of the container. In some embodiments, the processor is configured to generate the container based on any combination of the factors described herein or other factors. The following are non-limiting examples of factors:

[0053] Example 3: When the minimum and maximum container widths (e.g., 1m to 2m) are specified, the optimal container cross section is suggested from the viewpoint of packing efficiency.

[0054] Example 4: If the waste stream is a high heat waste, the tool can calculate the ideal surface area to volume ratio for the container and recommend the following design options:

[0055] A square cross section is used rather than a circle or hexagon to improve heat dissipation because it has a higher surface area to volume ratio for the same height and volume.

[0056] It may be advisable to increase the spacing between the containers to prevent the heat generated from diffusing to the surrounding area and affecting the surrounding containers.

[0057] Features such as ribs and fins are provided to aid in heat dissipation by increasing the surface area to volume ratio.

[0058] Example 5: If the waste stream is solid waste with a maximum size of 300 mm, a container design will be generated with an opening that will fit that size.

[0059] Example 6: If the waste stream is laser scannable solid waste, an arrangement is proposed in which the components are stacked to optimize space utilization within the container.

[0060] Example 7: If the radioactivity level of waste contained in a waste stream exceeds a given threshold, the tool can suggest an appropriate container thickness depending on the shielding provided by the facility.

[0061] Example 8: If a waste stream generates gas, the tool will suggest a vent to prevent pressure buildup within the vessel.

[0062] Example 9: If a facility is designed to store individual containers within a waste package with a central inspection port and corner posts (see Figure 1), the tool can suggest a more space-efficient design, such as that shown in Figure 4.

[0063] Example 10: A square is the most suitable design shape, but its corners can be a source of stress concentrations. The tool recognizes this as a problem and applies a smooth profile to the corners, which would be difficult to achieve with traditional manufacturing methods.

[0064] Example 11: If the user wants to avoid sharp corners completely, they specify minimum and maximum angles and generate an optimal design shape that meets this constraint.

[0065] Figure 4 shows an exemplary irregular hexagonal waste container located within a single quadrant of a waste package, which is more space efficient than Figure 1 and can incorporate corner posts and a central inspection port.

[0066] In some embodiments, the vessel design is generated as a 3D CAD model that is generated based on the optimal containment vessel footprint. In some embodiments, the processor is configured to simulate and generate a vessel that is sized and stress tested for stacking within the 3D space of the facility and / or containment location. After this stage, details such as vents, lids / fasteners, mechanical handling features, serial numbers, and tracking information may be added by the processor.

[0067] Using the generated CAD files, automated basic structural analysis can be performed to determine whether the resulting structure can withstand basic load cases. Using data extracted from the CAD model (e.g., surface area, volume), basic load cases can be applied to the design to rule out problems and calculate bulk stress and strain information. This allows for an immediate assessment of whether the vessel is suitable for the selected application, allowing concepts to be automatically eliminated from consideration.

[0068] EXAMPLE 12: In an exemplary situation based on available vertical space, the optimal logistical solution may be to stack the containers 10 high. However, depending on the density of the waste stream, the load-bearing capacity of the selected material may be limited, making a thicker wall solution counterproductive. In some embodiments, the processor utilizes an iterative procedure to find an ideal weight-to-size ratio that balances waste containment, geometric efficiency, and structural capacity with a material suitable for the defined waste stream.

[0069] Output 1: Build strategies, including: a. The process parameter window that provides the optimum build for the application (e.g., feed rate, arc voltage, arc current, wire bead size); b. Manufacturing sequence of different features

[0070] Output 2: Non-destructive testing (NDT) strategy, including: a.What are the governing regulations regarding testing; b. What NDT methods are required; c. Directive on features / areas that require inspection; d.What parameters will be used for testing; e. Projected costs and values.

[0071] Using supply chain and operational data, a cost per vessel is calculated, which is extrapolated to a facility-wide containment solution cost based on the number of vessels required.

[0072] Example 13: If the waste stream is low-level radioactive waste and the total waste volume is small, the tool may recommend the use of a conventionally manufactured container (e.g., a rolled steel drum). The processor can also suggest the break-even point where additive manufacturing becomes economically advantageous based on the total waste volume and type of container required.

[0073] Additive manufacturing reduces supply chain emissions and brings many non-financial benefits to the production process because it is relatively energy efficient, consumes relatively little raw materials, and can be deployed locally where needed, which is a significant factor in some geographic locations, and design tools can calculate these quantities in real time using available data.

[0074] Example 14: If a container is to be used in the UK, government procurement is subject to the Social Value (Procurement Policy Notice 06 / 20) and Carbon Reduction (Procurement Policy Notice 06 / 21) procurement policies. The carbon emissions associated with a conventionally manufactured equivalent design can be calculated by estimating the energy consumption and material waste in manufacturing and transportation, and the social value element can be calculated by estimating the benefits to the local community from local production, using statistical data available online. These calculations can be added to the digital shadow and can form the basis of government grant applications and / or justification for the advantages of the AM container design.

[0075] Design details

[0076] At this stage, the details recommended in the previous stage are implemented into the design, any other customizations required are also inserted here, and a final set of CAD files is created that is attached to the digital shadow of the design.

[0077] Features and stress concentrations can be used in combination with 3D CAD data to identify areas that require inspection.

[0078] Detailed Proof

[0079] The CAD file is imported into a finite element (FE) model and the governing regulatory load cases are applied to the design. The relevant results of the analysis are extracted from the model and subjected to additional calculations using software tools and algorithms before being compiled into a data file. The data file is attached to a digital shadow of the design, highlighting specific problem areas for analysis.

[0080] The following proposals will also be made: a. Areas where properties can be tuned to improve performance (this is one of the benefits of additive manufacturing (AM)); b. Areas where the use of multiple materials is required (this is another benefit of AM), c. Problem areas such as stress concentrations based on design best practices.

[0081] Example 15: When storing certain types of solid, unencapsulated waste, e.g. metal, the inside surface of the container may need to be hard to resist abrasion, while the outside surface needs to have more fracture toughness. This process parameter can be defined.

[0082] Example 16: A small non-structural section of a vessel may be more susceptible to stress corrosion cracking than the rest of the vessel. The process parameters are adjusted to accommodate duplex stainless steel processing parameters in the stress corrosion cracking prone section, while the rest of the vessel remains an austenitic steel such as 316L. Duplex stainless steels are more difficult to process, but are more resistant to SCC than austenitic steels.

[0083] Example 17: FE analysis highlights areas where distortion exceeds acceptable limits. These are extracted onto the CAD file along with their 3D location information to guide NDT inspection.

[0084] In some embodiments, the analysis files that make up the safety case are stored together in a database (i.e., a digital shadow). In some embodiments, a digital shadow of each manufactured container is stored with one or more identifiers mapped to a tag or other identifier printed, embedded, or otherwise associated with the container.

[0085] At 350, one or more containment vessels are manufactured or provided using the generated vessel design (e.g., a CAD file). In some embodiments, the processor is configured to transmit the design to a manufacturing device. In some embodiments, the processor is configured to direct or control aspects of a manufacturing system to manufacture the vessel.

[0086] Example 18: Even if design tools and machines are in different locations, if they are both connected to a cloud-based storage system, CAD files can be uploaded from anywhere, supporting remote / hybrid work.

[0087] Non-destructive testing

[0088] Quality control can be performed using a robotic head to perform specified NDT tests, such as ultrasonic testing, to verify the quality of the manufactured container. This is done simultaneously with production and in combination with other monitoring systems to monitor key parameters to ensure they are within defined parameter windows. Temperature measurements are taken using pyrometers or thermocouples, and the weld pool is photographed with a camera. Image processing software evaluates the shape of the weld pool.

[0089] Using expected windows for WAAM parameters and temperature measurements together, data points are flagged with red, yellow, or green: green indicates within the window, yellow indicates the process should be paused and investigated with NDT before resuming, and red indicates production should be stopped and repairs required. This contrasts with traditional manufacturing, where problem areas are not apparent until after the part is completed, making repairs difficult.

[0090] A record of all results is generated and added to the digital shadow. In some embodiments, the digital shadow (e.g., database record) of each container can be maintained and updated throughout all stages of the container's life, including design, testing, qualification, manufacturing, filling, transportation, storage, and routine inspection.

[0091] In some embodiments, basic information about the container is entered by the user during the process described above, and a generic certification document is automatically generated within a designated template.

[0092] The geometric and material data for the containment are calculated and automatically entered into the data sheet.

[0093] The design justification and analysis data is electronic and can be added to the file to show that the load cases have been met.

[0094] The generated CAD portfolio is automatically attached, clearly electronically defining the design to be certified.

[0095] Manufacturing instructions and NDT definitions are electronic and defined for the qualification process and can be used by any cloud-connected machine, separate from the design process.

[0096] Manufacturing measurements of process parameters are compiled with associated location and build history to clearly demonstrate that the process was performed within qualification requirements.

[0097] Non-financial data (social value, carbon reduction) will be generated and added to the design justification document.

[0098] All of the above is compiled into a digital shadow of the container, which is then ready for certification.

[0099] Although the foregoing invention has been described in detail for purposes of clarity and understanding, those skilled in the art will recognize that various changes in form and detail can be made after becoming familiar with this disclosure. Accordingly, the invention is not limited to the exact components or methodology or structural details described above. Except to the extent necessary or essential to the process itself, no specific order of steps or stages of the methods or processes described herein is intended or implied. In many cases, the order of process steps can be changed without altering the purpose, effect, or spirit of the methods described.

Claims

1. 1. A method for manufacturing an in-situ optimized containment vessel, comprising: obtaining location data and waste characteristic data for at least one waste at an industrial site; generating or obtaining parameter / characteristic data for at least one waste stream for said at least one waste; determining at least one material for storing the waste based on the waste stream parameters and the location data; and generating an optimized vessel design based on the at least one material and containment facility data; A method comprising:

2. The method of claim 1 , comprising manufacturing the in-situ optimized containment vessel based on the optimized vessel design.

3. The method of claim 1 , comprising generating the optimized container design based on routing data from an original location of the at least one waste material at the industrial site to a containment facility.

4. The method of claim 1 , comprising generating a digital shadow for the in-situ optimized containment vessel, the digital shadow comprising the optimized vessel design and vessel design analysis data.

5. The method of claim 4 , further comprising updating the digital shadow to include manufacturing data for the particular container.

6. The method of claim 4 , comprising performing non-destructive testing on the containment vessel and adding non-destructive testing data to the digital shadow.

7. 7. An in-situ optimized containment vessel manufactured based on a design generated using the method of any one of claims 1 to 6.

8. The containment vessel of claim 6 , wherein the footprint is an irregular hexagon.

9. 7. The containment vessel of claim 5 or claim 6, wherein the vessel is sized to reduce storage space footprint when placed adjacent to a plurality of other containment vessels.

10. A qualified containment kit including an in-situ optimized vessel and at least one non-transitory computer readable medium having stored thereon a digital shadow for the in-situ optimized vessel.

11. 1. A system for manufacturing an in-situ optimized containment vessel, comprising: at least one measurement device for acquiring location data and waste characteristic data for at least one waste material at the industrial site; and at least one processor, generating or obtaining parameter / characteristic data for at least one waste stream for said at least one waste; determining at least one material for storing the waste based on the waste stream parameters and the location data; a processor configured to generate an optimized vessel design based on the at least one material and containment facility data; A system comprising:

12. The system of claim 11 , comprising at least one manufacturing device for manufacturing a container based on the optimized container design.

13. 12. The system of claim 11, wherein the at least one processor is configured to generate the optimized container design based on routing data from an original location of the at least one waste material at the industrial site to a containment facility.

14. 12. The system of claim 11, wherein the at least one processor is configured to generate a digital shadow of the in-situ optimized containment vessel, the digital shadow including the optimized vessel design and vessel design analysis data.

15. The system of claim 14 , wherein the at least one processor is configured to update the digital shadow to include manufacturing data for the particular container.

16. The system of claim 14 , wherein the at least one processor is configured to perform non-destructive testing on the containment vessel and add non-destructive testing data to the digital shadow.

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