Airport airspace structure simulation verification method based on digital twinning

Abstract

The invention discloses an airport airspace structure simulation verification method based on digital twinning, and relates to the technical field of computers, and the method comprises the steps: employing preprocessed historical operation records and state event output to establish a target library, constructing an online monitor, maintaining the target library, and obtaining an online evidence state; performing early stop judgment by using an online evidence state to obtain a confirmation result and a prefix track, performing stepping and perturbation on the confirmation result and the prefix track to generate anti-fact disturbance, and performing pruning to obtain a boundary scene set; establishing a minimum change standard reaching model based on the boundary scene set, solving to obtain a minimum modification set, recharging the minimum modification set to the structure twinborn 2, and generating a standard reaching evidence packet; according to the method, the state event output is generated through the structural twin two-drive behavior simulation model, and the problem of lack of traceable simulation verification is solved.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a method for simulating and verifying airport airspace structure based on digital twins. Background Technology

[0002] In recent years, airspace assessments of airports and terminal areas have largely relied on rapid spatiotemporal simulations and procedural compliance checks. On the one hand, runways, taxiways, sectors, and arrival / departure procedures are geometrically represented, and discrete event simulations are performed in conjunction with flight schedules. On the other hand, rule-based approaches are used to implement operational regulations such as separation, wake turbulence, and runway occupancy, and to statistically analyze capacity, delays, and safety indicators. With the development of the "digital twin" concept, some solutions have attempted to map geometric and procedural data into structured models, use historical operational records to calibrate parameters, and employ target indicators to conduct batch evaluations of the solutions, forming a preliminary closed loop from data to simulation.

[0003] The existing methods still have room for improvement. First, simulation verification is mostly offline batch processing, lacking "online evidence status" and early stop confirmation mechanisms, and the coverage of boundary conditions is insufficient. Second, the verification conclusions mostly stop at "whether the requirements are met", lacking executable guidance on "how to achieve the standard with minimal modifications". Summary of the Invention

[0004] In view of the aforementioned existing problems, the present invention is proposed.

[0005] Therefore, this invention provides a digital twin-based airport airspace structure simulation verification method to solve the problem of lacking traceable simulation verification and a closed loop for achieving minimum modification compliance.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0007] This invention provides a method for simulating and verifying airport airspace structure based on digital twins, comprising:

[0008] Collect and preprocess operational data from airports and terminal areas; the operational data includes geometric elements, program elements, regulatory parameters, interface parameters, and historical operational records.

[0009] The preprocessed geometric and program elements are compiled into a structural twin to obtain structural twin one. An executable rule operator library is built using the preprocessed rule parameters and interface parameters and connected to structural twin one to form structural twin two.

[0010] A behavioral simulation model is established using preprocessed program elements and historical running records, and a structural twin two-drive behavioral simulation model is used to generate state event outputs.

[0011] A target database is established using preprocessed historical operation records and status event outputs. An online monitor is built and maintained to obtain the online evidence status.

[0012] Early stopping is determined using online evidence status to obtain confirmation results and prefix trajectories. Stepping and perturbation are applied to the confirmation results and prefix trajectories to generate counterfactual perturbations, and pruning is performed to obtain a set of boundary scenarios.

[0013] A minimum change compliance model is established based on the set of boundary scenarios, and the minimum modification set is obtained by solving the model. The minimum modification set is then fed back into the structural twin to generate a compliance evidence package.

[0014] As a preferred embodiment of the airport airspace structure simulation and verification method based on digital twins described in this invention, the preprocessing step includes the following specific steps.

[0015] Coordinate unification and topological verification are performed on geometric elements to obtain a geometric specification package. The program elements are then associated with the geometric specification package to form a standardized set of elements.

[0016] The historical operation records are standardized in terms of timestamps and units to form a standardized set of operations;

[0017] Standardize the regulatory parameters and interface parameters to generate a set of standardized regulatory interfaces.

[0018] As a preferred embodiment of the airport airspace structure simulation and verification method based on digital twins described in this invention, the step of compiling geometric elements and program elements into a structural twin to obtain structural twin one refers to mapping the geometric norm package in the element normalization set to nodes, edges and voxel domains, and mapping the program elements to a path set to form structural twin one.

[0019] As a preferred embodiment of the airport airspace structure simulation and verification method based on digital twins described in this invention, the step of establishing an executable rule operator library using regulatory parameters and interface parameters, and connecting it to structural twin one to form structural twin two, refers to instantiating the regulatory parameters in the standardized set of regulatory interfaces into rule entries, and attaching the rule entries and interface parameters to structural twin one to obtain structural twin two.

[0020] As a preferred embodiment of the airport airspace structure simulation and verification method based on digital twins described in this invention, the steps of establishing a behavioral simulation model using program elements and historical operation records, and generating state event outputs using a structural twin-driven behavioral simulation model, are as follows:

[0021] Event templates are defined based on program elements in the normalized set of elements and aligned with the path set to form an event template set.

[0022] The historical operation records and event template set are used to define the timing configuration, state field list, stage transition table and conflict judgment order, and associated with the executable rule operator library to form a behavior simulation model;

[0023] The structural twin is used to perform compliance checks on the behavioral simulation model and generate state event outputs.

[0024] As a preferred embodiment of the airport airspace structure simulation and verification method based on digital twins described in this invention, the step of establishing a target library using historical operation records and status event outputs refers to mapping historical operation records in the standardized operation set to target entries, and associating status event outputs with target entries to form a target library.

[0025] As a preferred embodiment of the airport airspace structure simulation and verification method based on digital twins described in this invention, the specific steps for constructing an online monitor and maintaining the target database to obtain online evidence status are as follows:

[0026] Each target entry in the target database is parsed to obtain a set of monitoring instances;

[0027] Configure time windows, sliding caches, and evaluation steps for the monitoring instance set, and establish a field binding table between the monitoring instance set and the status event output to form an online monitor;

[0028] Use the field binding table in the online monitor to perform streaming evaluation of status event outputs and generate stepwise evaluation results;

[0029] The satisfaction value, margin value, and time position of each target item are calculated using the results of step-by-step evaluation, forming a single target monitoring status;

[0030] The monitoring status of a single target is verified to obtain the verified targets. The verified targets are then set to a frozen state, and a frozen list is generated.

[0031] The frozen list and the single-target monitoring status that is currently undergoing confirmation and judgment will be merged into an online evidence status.

[0032] As a preferred embodiment of the airport airspace structure simulation and verification method based on digital twins described in this invention, the specific steps for pruning to obtain the boundary scene set are as follows:

[0033] Short-range verification simulation is performed on counterfactual disturbances to generate a target satisfaction rating table;

[0034] Based on the goal satisfaction rating scale, the counterfactual perturbations are deduplicated and pruned to generate a set of boundary scenarios.

[0035] As a preferred embodiment of the airport airspace structure simulation and verification method based on digital twins described in this invention, the specific steps for establishing a minimum change compliance model based on a set of boundary scenarios and solving for the minimum modification set are as follows:

[0036] By using the set of boundary scenarios as the constraint conditions and the structural twin and the target library as the decision set, a minimum change compliance model is formed.

[0037] The minimum change compliance model is solved using a mixed-integer linear programming solver to obtain the minimum modification set.

[0038] As a preferred embodiment of the airport airspace structure simulation and verification method based on digital twins described in this invention, the specific steps for feeding the minimum modification set back into the structural twin to generate the compliance evidence package are as follows:

[0039] Write the minimum set of modifications into the structural twin and re-drive the behavioral simulation model to generate new state event outputs;

[0040] The new status event output is sent to the target library and online monitor to complete the full target verification and obtain the compliance evidence package.

[0041] The beneficial effects of this invention are as follows: By generating state event outputs through a structural twin-driven behavioral simulation model, it enables real-time verification and early shutdown based on capacity, delay, and safety criteria, ensuring strong coverage and non-redundancy of the boundary scenario set, thus solving the problem of lacking traceable simulation verification; by constructing a minimum change compliance model through the boundary scenario set and solving for the minimum modification set, it transforms "whether it is satisfied" into an executable answer of "how to achieve the standard at the lowest cost," and the online evidence status and compliance evidence package form an auditable and reproducible evidence chain, reducing invalid simulations, improving boundary coverage and decision-making feasibility, and solving the problem of lacking a minimum modification compliance closed loop. Attached Figure Description

[0042] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a flowchart of a simulation verification method for airport airspace structure based on digital twins.

[0044] Figure 2 This is a schematic diagram of preprocessing and structural twin construction.

[0045] Figure 3 This is a diagram illustrating online monitoring.

[0046] Figure 4 A schematic diagram for generating a compliance evidence package. Detailed Implementation

[0047] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0048] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0049] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that is mutually exclusive with other embodiments.

[0050] Reference Figures 1-4 As one embodiment of the present invention, this embodiment provides a simulation and verification method for airport airspace structure based on digital twins, comprising the following steps:

[0051] S1: Collect and preprocess operational data from the airport and terminal areas; operational data includes geometric features, program features, regulatory parameters, interface parameters, and historical operational records.

[0052] S1.1: Collect geometric elements, procedural elements, regulatory parameters, interface parameters, and historical operation records of the airport and terminal areas;

[0053] Unify the geometric features to the Gauss-Kruger projection and check the region closure, adjacent edge sharing consistency, self-intersection and gap tolerance of the geometric features to obtain dangling nodes, cross-over and gaps;

[0054] For suspended nodes, overlapping intersections, and gaps, nearest neighbor snapping, endpoint clipping, line segmentation, and surface reconstruction are performed respectively to generate a geometric specification package;

[0055] The program elements are associated with the geometric specification package according to the program point identifier, program segment sequence and track constraints to form a standardized set of elements.

[0056] It should also be noted that nearest neighbor adsorption is to search for the endpoint or nearest point on the edge of the nearest geometric feature adjacent to the dangling node by spatial distance, and replace the dangling node with the endpoint or nearest point on the edge of the nearest geometric feature adjacent to the dangling node.

[0057] Endpoint trimming cuts off redundant segments at intersections or boundaries of geometric elements that intersect or exceed the boundaries.

[0058] Line segmentation is a process that divides intersecting or collinear overlapping line elements into non-intersecting and non-overlapping line segments by inserting new nodes at the intersection or overlapping start and end points.

[0059] Region reconstruction involves rebuilding closed surfaces after nearest neighbor adsorption, endpoint clipping, and line segmentation, forming a set of regions that are non-self-intersecting, seamless, and voxelizable.

[0060] S1.2: Unify the timestamps of historical operation records to Coordinated Universal Time, unify the physical units of historical operation records, and form a standardized set of operations;

[0061] The regulations and parameters are itemized, versioned, and their effective time ranges are fixed to generate a table of regulations and parameters items.

[0062] The interface parameters are arranged into a field mapping table according to the structure of device address-signal field-unit-refresh cycle-error handling. The rule parameter entry table is associated with the signal fields in the field mapping table to form a set of rule interface standardization.

[0063] It should also be noted that by standardizing the coordinates, time, and units of geometric elements, program elements, regulatory parameters, interface parameters, and historical operation records, digital twins can obtain unified standards and audit clues at the data entry point, reducing the risk of discrepancies and misjudgments between subsequent structural twin I, structural twin II, behavioral simulation models, and online monitors, and improving traceability and reproducibility.

[0064] S2: Compile the preprocessed geometric elements and program elements into a structural twin to obtain structural twin one. Use the preprocessed rule parameters and interface parameters to build an executable rule operator library and connect it to structural twin one to form structural twin two.

[0065] S2.1: Extract the boundaries, runway and taxiway centerlines, and sector areas from the geometric specification package of the element normalization set. Generate sequentially numbered nodes for the runway and taxiway centerlines at 10-meter intervals. The 10-meter interval is chosen because it can maintain the geometric realism and turning detail resolution of the digital twin under the common curvature and marking spacing scale of airport runways and taxiways, while controlling the number of nodes and edges within the simulation's acceptable range, and matching the accuracy of common field surveying and facility layout.

[0066] Connect adjacent nodes as edges, and perform three-dimensional voxelization on the boundary and sector regions to form voxel regions.

[0067] S2.2: Perform nearest neighbor matching on each program point identifier of the program element in the node, connect the program point identifiers in the order of program segments, and generate a path set;

[0068] Rule entries are extracted from the rule parameter entry table in the rule interface normalization set, including separation, wake turbulence, turning, height restriction, runway occupancy and handover. The rule entries are then bound to the corresponding signal fields in the field mapping table to form an executable rule operator library.

[0069] Separation and wake rules from the executable rule operator library are attached to the path set, turning and height restriction rules are attached to the nodes, and runway occupancy and handover rules are attached to the voxel domain and the corresponding nodes of the runway, forming a structural twin.

[0070] It should also be noted that: geometric elements and program elements are compiled into structural twin one, and an executable rule operator library is established using regulatory parameters and interface parameters to form structural twin two. This makes the regulatory parameters "endogenous" into executable entries in the digital twin, transforming compliance judgment from static clauses into a dynamic and recordable execution flow, reducing ambiguity in human interpretation, and improving the consistency and accuracy of rule implementation.

[0071] S3: Use the preprocessed program elements and historical running records to establish a behavioral simulation model, and use the structural twin two-driven behavioral simulation model to generate state event outputs.

[0072] S3.1: Extract the program point identifiers and program segment sequences for takeoff, landing, and overflight from the program elements in the normalized set of elements. Extract the flight trajectory data corresponding to the program point identifiers from the historical operation records. Use the data range of the flight trajectory data as the trigger condition. For example, if the flight's altitude at the "IAF" point is between 2500 meters and 2800 meters and its speed is between 250 knots and 280 knots, define "altitude ≤ 2800 meters and speed ≤ 280 knots" as the trigger condition at the "IAF" point.

[0073] Calculate the flight time between two consecutive program points in the historical operation record, and use the average flight time as the nominal duration of the program phase;

[0074] Extract speed and altitude profiles from historical operation records as phase parameters for the corresponding program phases. For example, in the program phase from "FAF" to "runway threshold", historical operation records show that the flight maintains a glide angle of 3 degrees and the airspeed decreases steadily from 150 knots to 130 knots. Define "glide angle of 3 degrees" and "speed profile [150 knots, 130 knots]" as phase parameters.

[0075] For all takeoff, landing, and overflight procedures, the corresponding triggering conditions, nominal duration, and stage parameters are sequentially connected to form the corresponding event template.

[0076] S3.2: Match all event templates one-to-one with the path set, node and voxel domain in the structural twin 2 to form an event template set;

[0077] Extract flight number, location update frequency, flight status, scheduled time and parking location information from historical operation records to form a flight event plan table;

[0078] The earliest scheduled flight is used as the simulation start time, the latest scheduled flight is used as the simulation end time, the position update frequency is used as the simulation step size, and the simulation start time, simulation end time and simulation step size are the timing configuration.

[0079] Flight status is used as a list of status fields, including position, altitude, speed, heading, and current procedure stage identifier. Each procedure stage and its corresponding triggering conditions are used as a stage transition table.

[0080] The priority of rule entries is used as the conflict determination order, and the timing configuration, state field list, stage transition table and conflict determination order are integrated into a behavioral simulation model.

[0081] S3.3: Use simulation step size to advance the behavior simulation model step by step. Within each simulation step size, perform the following operations in sequence: Check whether the current state of each flight is within the trigger condition corresponding to each program stage according to the stage transition table. If it is, update the current program stage to the next program stage.

[0082] Using the executable rule operator library in Structural Twin 2, the updated flight status is evaluated for compliance according to the conflict determination order, including separation, wake turbulence, and runway occupancy, to obtain compliance results;

[0083] Update the flight status using the stage parameters of the current program stage, record the updated flight status according to the status field list, mark the compliance results generated by the compliance determination, and generate status event output.

[0084] For example, if the flight's position meets the triggering condition (height < 5 meters) of the "grounding" phase in the event template set, the phase transition table updates the program phase to "taxiing". The executable rule operator library then checks the runway occupancy rules to ensure that the runway is not occupied. The flight's speed and position are updated according to the speed profile of the "taxiing" phase. The program phase of the flight is recorded as "taxiing" and marked as "phase transition complete", generating a status event output.

[0085] It should also be noted that if the updated flight status is non-compliant, for example, if the current flight has insufficient wake turbulence interval with the flight in front, the compliance result will be "wake turbulence conflict", and the "wake turbulence conflict" and flight status will be recorded as status events for output.

[0086] It should also be noted that: by using a structural twin-driven behavioral simulation model to generate state event outputs, a continuous evidence flow consistent with the path set, nodes, and voxel domains is formed, providing a unified input for subsequent target library mapping and online monitor evaluation. The digital twin thus has a time-series measurement basis oriented towards capacity, delay, and safety, reducing invalid simulations and redundant calculations.

[0087] S4: Establish a target database using preprocessed historical operation records and status event outputs, build an online monitor and maintain the target database to obtain online evidence status.

[0088] S4.1: Extract capacity, delay, and safety metrics from historical operation records. Based on capacity, delay, and safety metrics, list the target items, statistical objects, scrolling windows, sliding steps, aggregation methods, comparison relationships, and comparison values ​​for each item to form a list of target items.

[0089] The updated flight status from the status event output is filled into the target entry list to form the target library.

[0090] S4.2: Read each target entry in the target library and bind the corresponding field and unit in the status event output for each target entry. For example, for the target entry "Peak hour takeoffs on Pudong 36L runway [25, 30]", parse out all flight takeoff events using Pudong 36L runway in the status event output to form a monitoring instance of the corresponding target entry.

[0091] The simulation step size is used as the evaluation step size of the online monitor, the ratio of the rolling window in the target library to the evaluation step size is used as the sliding buffer capacity of the online monitor, the difference between the current time and the rolling window is used as the start point of the time window, and the current time is used as the end point of the time window to form the time window of the online monitor, thus completing the configuration of the online monitor.

[0092] The online monitor reads in the status event output one by one and accumulates the current indicator value of the monitored instance within the sliding buffer capacity. For example, the cumulative value of "take-off number of Pudong 36L runway" within each evaluation step cumulative time window is used as the step-by-step evaluation result of the monitored instance. The cumulative value of "take-off number of Pudong 36L runway" is the current indicator value of the monitored instance.

[0093] S4.3: The satisfaction value, margin value, and time position of each target item are calculated using the step-by-step evaluation results. The satisfaction value is a Boolean value, indicating whether the current indicator value is within the range of the target item. For example, if the current indicator value 26 is within the target item "Peak hour takeoffs [25, 30] of Pudong 36L runway", then the satisfaction value is 1. The margin value indicates the degree to which the current indicator value deviates from the range boundary of the target item. For example, if the margin of 26 from the lower limit 25 is 1, then the margin value is 1. The time position refers to the position of the current evaluation point relative to the total monitoring time. The satisfaction value, margin value, and time position of each target item together form the single target monitoring status.

[0094] S4.4: Verify the status of a single target monitoring status to obtain verified targets. The verification determination is as follows: if a target item satisfies a value of 1 within three consecutive evaluation steps, the corresponding target item is determined to be a verified target. The verified target is set to a frozen state and no longer participates in the streaming evaluation. A frozen list is generated and the frozen list is merged with the single target monitoring status that is currently undergoing verification determination into an online evidence status.

[0095] It should also be noted that: historical operation records and status event outputs are established as a target library and maintained by an online monitor to continuously generate online evidence status, enabling the digital twin to have online verification and early shutdown capabilities. It can stably measure capacity, delay and security targets from the three-dimensional perspective of satisfaction value, margin value and time position, shorten the verification cycle and improve the integrity of the evidence chain.

[0096] S5: Use online evidence status to determine early stopping, obtain the confirmation result and prefix trajectory, perform stepping and perturbation on the confirmation result and prefix trajectory to generate counterfactual perturbation, and prune to obtain the boundary scene set.

[0097] S5.1: Perform a continuity check on the satisfaction value of each target item in the online evidence state. When the satisfaction value of any target item is always 1 within three consecutive evaluation steps, it is recorded as "definitely satisfied". When the satisfaction value of any target item is not 1 and the margin value is negative within three consecutive evaluation steps, it is recorded as "definitely violated". Otherwise, it is recorded as "pending". Obtain the judgment result of "definitely satisfied", "definitely violated" or "pending". Summarize the judgment result of each target item and the state event output before the corresponding evaluation time into the confirmation result and prefix trajectory.

[0098] S5.2: Taking the confirmation result and the prefix trajectory as the starting point, two evaluation steps are taken forward and backward around the triggering conflict or critical satisfaction to obtain the time neighborhood. At the same time, adjustable objects are extracted from the structural twin, comparison parameters are extracted from the target library, and rule parameters of the corresponding rule entries are extracted from the executable rule operator library. Candidate change quantities with values ​​within the constraints of comparison relations, comparison parameters and rule parameters are generated for each adjustable object in the order of "single variable perturbation - joint perturbation", forming counterfactual perturbations.

[0099] It should also be noted that the adjustable objects include the extrapolation of turning points in the path set, the micro-shift of the planned time of nodes, and the micro-adjustment of the shift interval of the voxel domain.

[0100] S5.3: Perform short-range verification simulation of the counterfactual perturbation in the time neighborhood. For each counterfactual perturbation, count the current index value, satisfaction value and margin value of the corresponding target item in the time neighborhood to obtain the target satisfaction score table.

[0101] It should also be noted that the target satisfaction rating table records the candidate number, the object involved, the amount of change, the affected target item, the minimum margin in the time neighborhood, and the time of the first violation.

[0102] S5.4: Candidates with the same involved objects, the same change symbol, the same first violation time, and acting on the same path segment or the same transfer relationship are regarded as equivalence classes. The counterfactual perturbation with the smallest change in each equivalence class is retained. The dominance relationship is determined for the counterfactual perturbations that are not retained. When the minimum margin of all affected target entries of counterfactual perturbation A is not higher than that of counterfactual perturbation B and the first violation time is not later than that of counterfactual perturbation B, candidate B is deleted. Stability screening is performed on the counterfactual perturbations that are not deleted. The evaluation step size is expanded to twice the original size in the time neighborhood and re-verified. Candidates whose conclusions are reversed under the change of step size are deleted, and the pruned counterfactual perturbations are obtained.

[0103] S5.5: Archive the pruned counterfactual disturbances in layers according to "conflict type - path segment or transfer relationship - change magnitude". Solidify each pruned counterfactual disturbance together with the corresponding prefix trajectory, review window, first violation time and minimum margin to form a set of boundary scenarios.

[0104] It should also be noted that: by stepping and perturbing the confirmation results and prefix trajectories based on the online evidence status, a set of boundary scenarios is generated and pruned to cover critical and conflicting conditions with the smallest scale, avoiding scenario combination explosion, and improving the explanatory power, measurability and verification efficiency of digital twins for extreme operation and critical satisfaction.

[0105] S6: Establish a minimum change compliance model based on the boundary scenario set, solve for the minimum modification set, feed the minimum modification set back into the structural twin, and generate compliance evidence package.

[0106] S6.1: The boundary scenario set is used as the constraint condition, and the adjustable object is set as the decision set. The affected target item, the first violation time, and the minimum margin in the time neighborhood corresponding to each counterfactual disturbance in the boundary scenario set are transcribed into the compliance constraint. It is required that the comparison relationship and comparison value of all relevant target items in the corresponding time neighborhood are satisfied, forming the minimum change compliance model. The minimum change compliance model is a mixed integer linear programming based on the boundary scenario set, the target library, and the structural twin, and does not require training.

[0107] S6.2: Using a mixed-integer linear programming solver, the optimization objective is set as "minimum total change". The modification records in the historical compliance evidence package are used as the initial solution for a warm start. The optimization objective and constraint conditions are loaded, and the minimum change compliance model is relaxed to obtain a relaxed solution. The constraint conditions that are violated in the relaxed solution are located. For the violated constraint conditions, a cutting plane is constructed from the violation row according to the built-in rules of the mixed-integer linear programming solver and added to the minimum change compliance model. Branch and bound are performed on the adjustable objects in the decision set. The solutions are solved separately and the upper and lower bounds are updated with the current best feasible solution. At the same time, branches that are inferior to the best feasible solution are pruned.

[0108] The process is iterated in the order of "generating cut planes → branching and bounding → pruning → updating upper and lower bounds" until the global optimal gap is zero, thus obtaining the minimum modification set.

[0109] Furthermore, the minimum total change means that the sum of the absolute values ​​of the extrapolation of the turning points of the path set, the micro-shift of the planned time of the nodes, and the micro-adjustment of the shift interval of the voxel domain is minimized.

[0110] Relaxation solution for minimum change compliance model: Temporarily remove integer value restrictions corresponding to adjustable objects in minimum change compliance model, retain constraint conditions, keep "minimum total change" as the optimization, fill the initial solution into the corresponding adjustable objects, load the feasible value range of adjustable objects as variable upper and lower bounds into the mixed integer linear programming solver, use simplex method to improve the initial solution, and obtain relaxed solution;

[0111] The feasible range of values ​​for an adjustable object is the intersection of all constraints on the adjustable object;

[0112] The feasible range of the adjustable object is divided into two branch constraints and subproblems are solved separately. A mixed integer linear programming solver is used to relax each branch subproblem under the conditions of branch constraints and the addition of the cutting plane. The continuous relaxed solution is used as the lower bound. Heuristics and branch backtracking are used to find integer feasible solutions as the upper bound, forming global upper and lower bounds.

[0113] The best feasible solution at present is the relaxed solution that does not violate the constraints and has the smallest total change. Use global upper and lower bounds to prune branches that are inferior to the best feasible solution at present.

[0114] The global optimal gap refers to the difference between the upper and lower bounds of the global upper and lower bounds.

[0115] S6.3: Extract the minimum turning point extrapolation, minimum planned time micro-shift, and minimum transfer flow interval micro-adjustment from the minimum modification set, and accumulate them into the coordinate vector of the turning point corresponding to the path set in the structural twin II, the planned time of the node, and the flow interval of the voxel domain transfer relationship to obtain the reinjected structural twin II.

[0116] The re-driven behavior simulation model is used to generate new state event outputs by using the re-fed structural twin. The new state event outputs are then sent to the target library and online monitor to complete the full target verification and obtain the compliance evidence package.

[0117] It should also be noted that: by establishing a minimum change compliance model based on the set of boundary scenarios and solving it to obtain the minimum modification set, the model is fed back into the structural twin to complete the full target verification and generate a compliance evidence package. This transforms "whether it is satisfied" into an executable conclusion of "how to achieve the target at the lowest cost". The digital twin thus forms a closed-loop optimization and auditable comparison basis, supporting rapid iteration of the solution and long-term operation and maintenance compliance.

[0118] This embodiment also provides a computer device applicable to a digital twin-based airport airspace structure simulation and verification method, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to realize the digital twin-based airport airspace structure simulation and verification method proposed in the above embodiment.

[0119] The computer device can be a terminal, comprising a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, carrier networks, NFC (Near Field Communication), or other technologies. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device's casing, or an external keyboard, touchpad, or mouse.

[0120] This embodiment also provides a storage medium storing a computer program, which, when executed by a processor, implements a digital twin-based airport airspace structure simulation and verification method as proposed in the above embodiments. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0121] In summary, this invention achieves real-time verification and early shutdown for capacity, delay, and safety requirements by generating state event outputs through a structural twin-driven behavioral simulation model. This ensures strong coverage and non-redundancy of the boundary scenario set, addressing the lack of traceable simulation verification. Furthermore, by constructing a minimum change compliance model from the boundary scenario set and solving for the minimum modification set, the question of "whether it is satisfied" is transformed into an executable answer of "how to achieve the standard at the lowest cost." The online evidence status and compliance evidence package form an auditable and reproducible evidence chain, reducing invalid simulations, improving boundary coverage and decision-making feasibility, and solving the problem of lacking a minimum modification compliance closed loop.

[0122] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A simulation and verification method for airport airspace structure based on digital twins, characterized in that: include, Collect and preprocess operational data from airports and terminal areas; the operational data includes geometric elements, program elements, regulatory parameters, interface parameters, and historical operational records. The preprocessed geometric and program elements are compiled into a structural twin to obtain structural twin one. An executable rule operator library is built using the preprocessed rule parameters and interface parameters and connected to structural twin one to form structural twin two. A behavioral simulation model is established using preprocessed program elements and historical running records, and a structural twin two-drive behavioral simulation model is used to generate state event outputs. A target database is established using preprocessed historical operation records and status event outputs. An online monitor is built and maintained to obtain the online evidence status. Early stopping is determined using online evidence status to obtain confirmation results and prefix trajectories. Stepping and perturbation are applied to the confirmation results and prefix trajectories to generate counterfactual perturbations, and pruning is performed to obtain a set of boundary scenarios. A minimum change compliance model is established based on the set of boundary scenarios, and the minimum modification set is obtained by solving the model. The minimum modification set is then fed back into the structural twin to generate a compliance evidence package.

2. The airport airspace structure simulation and verification method based on digital twin as described in claim 1, characterized in that: The preprocessing process involves the following steps. Coordinate unification and topological verification are performed on geometric elements to obtain a geometric specification package. The program elements are then associated with the geometric specification package to form a standardized set of elements. The historical operation records are standardized in terms of timestamps and units to form a standardized set of operations; Standardize the regulatory parameters and interface parameters to generate a set of standardized regulatory interfaces.

3. The airport airspace structure simulation and verification method based on digital twin as described in claim 1, characterized in that: The process of compiling the preprocessed geometric elements and program elements into a structural twin to obtain structural twin one refers to mapping the geometric norm package in the element normalization set to nodes, edges, and voxel domains, and mapping the preprocessed program elements to a path set, thus forming structural twin one.

4. The airport airspace structure simulation and verification method based on digital twin as described in claim 1, characterized in that: The process of establishing an executable rule operator library using preprocessed rule parameters and interface parameters, and connecting it to structural twin one to form structural twin two, refers to instantiating the rule parameters in the rule interface normalization set into rule entries, and attaching the rule entries and interface parameters to structural twin one to obtain structural twin two.

5. The airport airspace structure simulation and verification method based on digital twin as described in claim 1, characterized in that: The process involves establishing a behavioral simulation model using preprocessed program elements and historical execution records, and generating state event outputs using a structural twin-driven behavioral simulation model. The specific steps are as follows: Event templates are defined based on program elements in the normalized set of elements and aligned with the path set to form an event template set. The preprocessed historical running records and event template set are used to define the timing configuration, state field list, stage transition table and conflict determination order, and associated with the executable rule operator library to form a behavior simulation model; The structural twin is used to perform compliance checks on the behavioral simulation model and generate state event outputs.

6. The airport airspace structure simulation and verification method based on digital twin as described in claim 1, characterized in that: The establishment of the target library using preprocessed historical operation records and status event outputs refers to mapping historical operation records in the normalized operation set to target entries, associating status event outputs with target entries, and forming the target library.

7. The airport airspace structure simulation and verification method based on digital twin as described in claim 1, characterized in that: The specific steps for constructing an online monitor and maintaining the target database to obtain the online evidence status are as follows. Each target entry in the target database is parsed to obtain a set of monitoring instances; Configure time windows, sliding caches, and evaluation steps for the monitoring instance set, and establish a field binding table between the monitoring instance set and the status event output to form an online monitor; Use the field binding table in the online monitor to perform streaming evaluation of status event outputs and generate stepwise evaluation results; The satisfaction value, margin value, and time position of each target item are calculated using the results of step-by-step evaluation, forming a single target monitoring status; The monitoring status of a single target is verified to obtain the verified targets. The verified targets are then set to a frozen state, and a frozen list is generated. The frozen list and the single-target monitoring status that is currently undergoing confirmation and judgment will be merged into an online evidence status.

8. The airport airspace structure simulation and verification method based on digital twin as described in claim 1, characterized in that: The pruning process is performed to obtain the boundary scene set. The specific steps are as follows. Short-range verification simulation is performed on counterfactual disturbances to generate a target satisfaction rating table; Based on the goal satisfaction rating scale, the counterfactual perturbations are deduplicated and pruned to generate a set of boundary scenarios.

9. The airport airspace structure simulation and verification method based on digital twin as described in claim 1, characterized in that: The steps for establishing a minimum change compliance model based on the boundary scenario set and solving for the minimum modification set are as follows: By using the set of boundary scenarios as the constraint conditions and the structural twin and the target library as the decision set, a minimum change compliance model is formed. The minimum change compliance model is solved using a mixed-integer linear programming solver to obtain the minimum modification set.

10. The airport airspace structure simulation and verification method based on digital twin as described in claim 1, characterized in that: The specific steps for re-feeding the minimum modification set into the structural twin to generate the compliance evidence package are as follows. Write the minimum set of modifications into the structural twin and re-drive the behavioral simulation model to generate new state event outputs; The new status event output is sent to the target library and online monitor to complete the full target verification and obtain the compliance evidence package.

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