A method and system for designing the turnover of internal support frames under slabs, taking into account schedule matching.

Abstract

This invention discloses a method and system for the turnover design of internal support frames under slabs, considering schedule matching, and relates to the fields of building construction formwork engineering and digital construction management technology. The method includes: dividing the work section based on a BIM model and arranging the frame; importing the schedule file, binding the schedule nodes to the work section bidirectionally, and constructing a three-dimensional correlation matrix of schedule-work section-component; extracting the projected area of ​​the slab bottom based on the correlation matrix and calculating the theoretical demand, calculating the replenishment and return quantities based on the loss rate and integrity rate, and releasing the available turnover quantity only when both the formwork removal strength and support layer space conditions are met simultaneously; establishing a multi-level priority queue for replenishment sources for optimal matching and scheduling; and generating a structured turnover table and entry / exit plan. The system includes a data access layer, a calculation layer, an interaction layer, and a storage layer. This invention achieves dynamic matching between support frame turnover design and construction schedule, significantly reducing material idle rate and rental costs, and eliminating safety hazards caused by unauthorized formwork removal.

Description

Technical Field

[0001] This invention relates to the fields of building construction formwork engineering and digital construction management technology. Specifically, it relates to a method, system and storage medium for the turnover design of internal support frames under slabs that takes into account the matching of schedule plans. It is particularly suitable for the refined turnover scheduling of support frames in high-rise buildings, large-span floor slabs and industrialized construction scenarios. Background Technology

[0002] In the construction of cast-in-place concrete structures, the internal support frame under the slab (such as disc-lock, coupler-lock, and cup-lock steel pipe supports) is the core temporary structure to ensure the quality of the floor slab formation and construction safety. The turnover management of the support frame is directly related to construction safety, project progress, and project cost.

[0003] Currently, some existing technologies attempt to improve the turnover management of support frames or formwork using information technology. For example, Chinese patent application CN201710145123 discloses a BIM-based method for rapid turnover of prefabricated building support systems. This method achieves rapid turnover of the support system between floors by establishing a BIM model, determining the types of support components, and creating QR code labels that are affixed to the components. This method mainly addresses the problem of component identification and positioning, but it fails to use the construction schedule as a driving factor for turnover design, nor does it establish a dynamic calculation relationship between schedule and turnover volume. Another example is Chinese patent application CN120596068A, which discloses a software design method for optimizing formwork turnover paths. It optimizes turnover paths through steps such as formwork matching design, turnover object selection, and turnover calculation. However, its focus is on the path optimization algorithm itself, without addressing the mechanical layout rules of the support frame, concrete curing cycle constraints, or quantitative comparison of multiple solutions. For example, Chinese patent application CN120596069A (a design method for template turnover calculation application software based on intelligent algorithms) further introduces intelligent algorithms for template turnover calculation. However, its technical solution is based on the pairing calculation of fixed rules and variable rules, which is a static template usage accounting tool. It still lacks the time-driven mechanism of schedule planning and the ability to dynamically recalculate the quantity difference.

[0004] However, the aforementioned existing technologies and traditional manual management methods all have the following technical drawbacks: First, there is a disconnect between progress and maintenance. Existing technologies do not incorporate the concrete strength growth curve and formwork removal time constraints into the turnover calculation system, leading to premature removal of support frames that could cause structural safety hazards, or excessive retention that could cause a surge in rental costs. Specifically, existing technologies lack a mechanism for unified representation and linkage between the time-dimensional maintenance cycle constraints and the spatial-dimensional constraints on the number of support layers, and cannot automatically determine the timing of releasing inventory on each floor when progress changes.

[0005] Second, the calculation of quantity discrepancies is crude and the physical model is distorted. Support frames are measured in units of "pieces / sets / tons," and differences in floor slab thickness, load, and upright spacing lead to significant variations in support density per unit area. More importantly, existing technologies often directly multiply the designed turnover number into the instantaneous supply-demand balance formula when calculating turnover volume. Mathematically, this is equivalent to allowing the same set of materials to be repeatedly used at the same construction node, severely deviating from the physical reality that support frames can only be erected and dismantled once per floor. This results in calculation results that are seriously inconsistent with the actual supply and demand relationship on the construction site. This technical flaw stems from a long-standing technical bias in the field—the assumption that incorporating the turnover number as a multiplier factor into the calculation formula is a given, without ever questioning the physical rationality of this approach.

[0006] Third, the scheduling of replenishment is inefficient. There is a lack of systematic matching mechanisms for issues such as specification inspection of disassembled support frames, integrity rate assessment, and the mixing of prematurely disassembled parts with standard components. When there is insufficient inventory of fully matching specifications, existing methods lack compromise matching strategies for specification downgrading or upgrading, often directly reporting errors or forcibly triggering external procurement, resulting in rigid scheduling. At the same time, there is a lack of a closed-loop management mechanism for automatically removing lost and scrapped materials from available inventory, leading to a continuous accumulation of discrepancies between inventory records and physical stock.

[0007] Fourth, the selection of solutions is subjective. The application ratio of early dismantling systems, the configuration of support layers, and leasing strategies lack quantitative evaluation models, making decisions reliant on experience and hindering the achievement of overall cost and schedule optimization.

[0008] Fifth, the software integration is highly dependent and lacks a disaster recovery mechanism. Existing auxiliary tools developed based on specific commercial software (such as YJK) rely excessively on the software's native application programming interface. When the interface becomes unavailable or the software version is upgraded, the system faces the risk of paralysis and lacks independent parsing and processing capabilities based on general data exchange formats (such as the industrial basic IFC format).

[0009] In summary, existing technologies lack an automated turnover design method that can deeply integrate schedule planning, maintenance cycle constraints, and support frame mechanical layout rules to achieve accurate dynamic difference calculation of physical models, intelligent damage compensation scheduling with specification substitution flexibility, and quantitative comparison of multiple schemes. Summary of the Invention

[0010] This invention aims to overcome the technical defects of existing technologies, such as reliance on manual experience for the turnover of internal support frames under slabs, distortion of physical models in quantity difference calculations, lack of specification substitution flexibility in compensation scheduling, difficulty in dynamically matching with progress plans and concrete curing cycles, resulting in high idle rates of support frames, uncontrolled rental costs, material shortages in key processes, or illegal demolding. It provides an automated, high-precision, and dynamically adaptive design method and system for the turnover of internal support frames under slabs.

[0011] To achieve the above-mentioned objectives, this invention provides a method for designing the turnover of an under-plate internal support frame that considers schedule matching. The method includes the following steps: The process of dividing the construction flow into sections involves identifying the location of construction joints and structural functional parts based on the building information model, and then dividing the construction flow into sections in accordance with the mandatory requirements for the number of support layers in the structural construction safety code. The progress linkage step involves importing the progress plan file and extracting the timing information of the work breakdown structure nodes, bidirectionally binding the progress nodes with the flow segment, and constructing a three-dimensional association matrix of progress-flow segment-component. The quantity difference calculation step involves extracting the bottom projection area of ​​each flow section according to the construction sequence based on the three-dimensional correlation matrix and calculating the support density per unit area. Combined with preset loss rate and integrity rate parameters, the theoretical demand, replenishment amount, and return amount of each flow section at each construction node are calculated. The replenishment amount is the difference between the available turnover amount and the theoretical demand amount of the current node. The return amount is the difference between the available turnover amount and the theoretical demand amount of the current node. The available turnover amount can only be released into the available inventory pool when both the demolding strength standard condition and the support layer space condition are met simultaneously. The scheduling process involves establishing a multi-level priority queue for loss replenishment sources and performing optimal matching and scheduling allocation of loss replenishment sources based on specification compatibility, transportation distance, and cost. The output steps of the plan are to generate a structured turnover table and an entry / exit plan based on the quantity difference calculation results and the scheduling allocation results.

[0012] In this method, when the schedule changes, an anti-jitter timer is started. The reconstruction of the three-dimensional correlation matrix is ​​triggered only after the timer's window expires and the change is confirmed to be valid, and the re-execution of the quantity difference calculation step and the scheduling step is driven.

[0013] In this method, the quantity difference calculation step calculates the theoretical demand D_{i,t} for the target flow segment i at construction node t according to the following formula: D_{i,t} = A_{i,t} × K_spec × (1 + λ) / η; Where A_{i,t} is the projected area of ​​the target flow segment i at the bottom of the plate at node t, K_spec is the unit area support density of the target flow segment, λ is the material loss rate, and η is the on-site usable integrity rate. The compensation amount ΔQ and the return amount Q_return are output according to the following logic: ΔQ = max(0, D_{i,t} - Q_avail); Q_return = max(0, Q_avail - D_{i,t}); Where Q_avail is the available turnover between adjacent nodes, which is obtained by deducting the loss from the dismantling amount of the previous node.

[0014] In this method, during the quantity difference calculation step, the system calculates the actual integrity rate of the disassembled and returned materials in real time. When the actual integrity rate is lower than the preset integrity rate threshold, the system automatically removes the unqualified materials from the available inventory pool and marks them as pending scrapping or repair.

[0015] In this method, during the scheduling step, when there is insufficient inventory of fully matching specifications, the system initiates a specification substitution matching strategy, searching for alternatives from high specifications to low specifications or compatible specifications of the same type based on a preset substitution penalty coefficient.

[0016] In this method, during the scheduling step, the multi-level compensation source priority queue is arranged from high to low priority as follows: floor dismantling support frames that have met the demolding strength standards for the same building, basement or podium dismantling inventory, cross-project transfer pool, and external leased or purchased resources.

[0017] In this method, the scheduling step employs a minimum-cost maximum flow algorithm with capacity constraints to solve for the optimal scheduling allocation scheme of the compensation source. The objective function is to minimize the total scheduling cost. For substitution schemes, the total cost is supplemented with a product term of the substitution penalty coefficient and the number of substitutions. min Σ(C_transport + C_handling + C_lease + α_k × Q_substitute) Where C_transport is the transportation cost, C_handling is the secondary handling cost, C_lease is the lease cost, α_k is the penalty coefficient for the corresponding substitute solution, and Q_substitute is the quantity of substitute solutions provided.

[0018] In this method, during the scheduling step, when the scheduling of the damage replenishment source cannot meet the needs of the construction node within the preset time constraint, the system automatically outputs suggested instructions for adjusting the flow section or the construction speed.

[0019] In this method, after the output step, a scheme comparison step is also included: based on different flow segmentation strategies, the turnaround time assumption N_turn, the application ratio of early dismantling system or the weight of compensation source call, multiple turnaround schemes are generated in parallel. The turnaround time assumption N_turn is only used as a parameter for the economic evaluation of the scheme in the cost amortization calculation, and is not used in the instantaneous supply and demand balance calculation of physical quantity difference; a multi-dimensional evaluation vector including cost saving rate, number of days of project duration impact, frequency of turnaround path intersection and early dismantling system utilization rate is constructed, and a multi-criteria decision algorithm is used to quantitatively compare and select each scheme and output a recommended scheme.

[0020] To achieve the above-mentioned objectives, the present invention also provides a turnover design system for an under-plate internal support frame that considers schedule matching, the system comprising: The data access layer includes a building information model parser, a schedule parser, and a material ledger interface. The building information model parser supports two modes: native software format parsing and general industrial data format parsing. When native format parsing fails, it automatically switches to the general data format parsing mode. The computational layer includes a flow section topology builder, a 3D correlation matrix generator, a quantity difference dynamic calculator, a scheduling optimizer, and a scheme comparison engine. The 3D correlation matrix generator has a built-in anti-jitter timer, which starts a timing window upon receiving a progress change event, and only performs matrix reconstruction after the window expires and the change is confirmed to be valid. The quantity difference dynamic calculator includes a demolding condition determiner and a real-time integrity rate statistician. The demolding condition determiner determines the release conditions of inventory on each floor in both time and space dimensions. The real-time integrity rate statistician calculates the actual integrity rate of materials dismantled and returned to the warehouse and automatically removes unqualified materials from the available inventory pool. The scheduling optimizer includes a specification substitution matcher and a constraint conflict resolver. The specification substitution matcher searches for alternative solutions based on a substitution penalty coefficient when there is insufficient inventory to fully match specifications. The constraint conflict resolver outputs suggested instructions for flow section adjustment or construction speed adjustment when there is no solution in the scheduling process. The interaction layer includes a 3D viewport, timeline, parameter panel, comparison dashboard, and report generator. The storage layer includes a local database and cloud synchronization nodes.

[0021] Compared with the prior art, the solution of the present invention has the following beneficial effects: First, this invention constructs a three-dimensional correlation matrix of schedule-flow section-component, which bidirectionally binds the work decomposition structure nodes of the schedule plan with the flow section and supporting structure components, establishing a dynamic coupling mechanism between the schedule plan and the turnover design. This enables the turnover design to be automatically updated in conjunction with the schedule changes, realizing a fundamental shift from static material layout to schedule-driven design.

[0022] Secondly, this invention strictly adheres to the physical reality that support frames can only be erected and dismantled once at the same construction node. It removes the design turnover rate from the instantaneous supply-demand balance formula and repositions it as a parameter in the scheme's economic evaluation, correcting a long-standing technical bias in the field and ensuring that the quantity difference calculation accurately reflects the real supply and demand relationship at the construction site. Simultaneously, this invention incorporates the time constraint of the concrete curing cycle and the spatial constraint of "retaining two layers of support" into a unified inventory release judgment framework. Only when the inventory simultaneously meets the time condition for demolding strength and the spatial condition for the number of support layers can it be released into the available turnover volume transfer chain, fundamentally eliminating the safety hazards of unauthorized demolding.

[0023] Third, this invention establishes a multi-level priority queue for replenishment sources and initiates a specification substitution matching strategy when there is insufficient inventory of fully matching specifications. Based on the substitution penalty coefficient, it searches for alternative solutions from high-specification substitution for low-specification or compatible specifications of the same type, enabling the scheduling system to have flexible adaptability when facing scarce resources. At the same time, through real-time statistics of the integrity rate and an automatic rejection mechanism for non-conforming materials, it ensures a continuous closed loop of consistency between accounts and physical inventory.

[0024] Fourth, this invention sets up a dual-mode system at the data access layer: native software format parsing and Industrial Basic Class (IFC) general data format parsing. When native format parsing fails or the corresponding software interface is unavailable, it automatically switches to the general data format parsing mode, ensuring that the system has independent working capabilities under different software ecosystems and solving the problem of excessive dependence on specific commercial software ecosystems.

[0025] Fifth, this invention, through an event debouncing mechanism, avoids the unnecessary occupation of system resources and interface lag in scenarios with frequent progress changes, thereby improving system stability and user experience. Through parallel generation of multiple solutions and the TOPSIS quantitative comparison engine, it provides managers with data-driven scientific decision support. Attached Figure Description

[0026] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0027] Figure 1 This is an overall flowchart of the method of the present invention.

[0028] Figure 2 This is a schematic diagram of the system architecture and embedded interaction of the host software of the present invention.

[0029] Figure 3 A logic diagram for constructing and dynamically recalculating the three-dimensional correlation matrix of the progress-flow section.

[0030] Figure 4 This is a diagram of the turnover difference calculation and closed-loop scheduling model.

[0031] Figure 5This is a schematic diagram of the interface for quantitative comparison and decision-making output of multiple turnover options.

[0032] Figure 6 This is a schematic diagram of the turnover path topology network for single and multi-unit support frames. Detailed Implementation

[0033] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below with reference to specific illustrations.

[0034] To address the long-standing technical problems in the turnover management of internal support frames under slabs, such as the disconnect between progress and maintenance, distortion of the physical model for quantity difference calculation leading to serious discrepancies between the calculation results and the supply and demand relationship at the construction site, lack of flexibility in specification substitution for compensation scheduling, subjective scheme selection, and excessive reliance on specific commercial software interfaces, this invention proposes a closed-loop technical solution of "progress-driven → quantity difference calculation → intelligent scheduling → multi-dimensional decision-making".

[0035] This invention establishes a dynamic coupling mechanism between the schedule and the turnover design. Unlike traditional methods where the schedule serves only as a time reference, this invention constructs a three-dimensional correlation matrix of schedule, flow section, and component. This matrix bidirectionally binds each work breakdown structure node of the schedule to specific construction flow sections and supporting structural components, enabling the turnover design to automatically update in response to schedule changes. Simultaneously, an event debouncing mechanism is introduced. Upon receiving a schedule change event, a timing window is activated, and subsequent refactoring operations are only performed after the window expires and the change is confirmed to be valid. This avoids unnecessary system resource consumption and interface lag caused by frequent schedule changes.

[0036] This invention constructs a dynamic calculation model for the turnover difference based on a precise physical model. Adhering strictly to the physical reality that support frames can only be erected and dismantled once at the same construction node, this invention removes the design turnover count from the instantaneous supply-demand balance formula and repositions it as a parameter for evaluating the scheme's economic efficiency. Simultaneously, this invention incorporates the time constraint of the concrete curing cycle and the spatial constraint of "retaining two layers of support" into a unified inventory release judgment framework. Only when the inventory simultaneously meets the time condition for demolding strength and the spatial condition for the number of support layers can it be released into the available turnover transfer chain. Furthermore, this invention ensures a continuous closed loop of consistency between inventory and records through real-time statistics of the integrity rate and an automatic rejection mechanism for unqualified materials.

[0037] This invention implements intelligent hierarchical scheduling of replenishment sources with flexible specification substitution. By establishing a multi-level priority queue for replenishment sources, and initiating a specification substitution matching strategy when the inventory of perfectly matching specifications is insufficient, this invention searches for alternative solutions from high-specification substitution for low-specification or compatible specifications of the same type based on a substitution penalty coefficient. This enables the scheduling system to have flexible adaptability when facing scarce resources, rather than directly reporting errors and shutting down. Simultaneously, this invention automatically triggers a constraint conflict resolution mechanism when scheduling becomes unsolvable, outputting suggested instructions for adjusting the flow segment or construction speed to prevent the system from entering an unsolvable deadlock state.

[0038] Fourth, it achieves loose coupling dependency on specific commercial software ecosystems. This invention sets up a dual-mode system at the data access layer: native software format parsing and Industrial Basic Class (IFC) general data format parsing. When native format parsing fails or the corresponding software interface is unavailable, it automatically switches to the general data format parsing mode, ensuring that the system has independent working capabilities under different software ecosystems.

[0039] like Figure 2 As shown, the underboard internal support frame turnover design system provided by the present invention, which takes into account the matching of the schedule plan, adopts a layered architecture design, which includes a data access layer 100, a computing layer 200, an interaction layer 300 and a storage layer 400 from the bottom layer to the top layer.

[0040] The data access layer 100 is configured to interface with external data sources, receiving and parsing various types of input data. The data access layer 100 includes three core components: a building information model parser 110, a schedule parser 120, and a materials ledger interface 130.

[0041] Building Information Modeling (BIM) parser 110 receives and parses BIM files from structural design software, extracting structural geometry, construction joint locations, and structural functional component information. Schedule parser 120 receives and parses schedule files from project management software, extracting the codes, names, timing information, and logical relationships of work breakdown structure (WBS) nodes. Materials ledger interface 130 interfaces with JSON-formatted data from an enterprise resource planning (ERP) system or materials management system to obtain on-site inventory information and material specifications.

[0042] The schedule parser 120 is used to receive and parse schedule files from project management software, and extract the codes, names, timing information and logical relationship information of the work breakdown structure nodes.

[0043] The Materials Ledger Interface 130 is used to interface with the Enterprise Resource Planning System or Materials Management System to obtain on-site inventory information and material specifications.

[0044] The computational layer 200 is the core processing layer of the system, containing a pipeline topology builder 210, a 3D correlation matrix generator 220, a support density matcher 230, a quantity difference dynamic calculator 240, a scheduling optimizer 250, and a scheme comparison engine 260. The pipeline topology builder 210 generates a pipeline topology structure with safety constraints based on the structural information and safety specifications provided by the access layer. The 3D correlation matrix generator 220 bidirectionally binds progress nodes to pipelines, constructing a progress-pipeline-component 3D correlation matrix. This generator has a built-in anti-jitter timer; upon receiving a progress change event, a timing window is started, and matrix reconstruction is only performed after the window expires and the change is confirmed to be valid. The support density matcher 230 matches the specifications and quantities of various members from the material specification library based on structural load parameters. The quantity difference dynamic calculator 240 accurately calculates the quantity differences in the physical model. The scheduling optimizer 250 solves for the optimal scheduling allocation scheme for compensation sources. The scheme comparison engine 260 enables parallel generation of multiple schemes and TOPSIS quantitative comparison.

[0045] The interaction layer 300 is responsible for interacting with the user and providing a graphical user interface. The interaction layer is presented as a plug-in interface of the host software, including a 3D viewport 310 (used to display the structural model and support frame layout), a timeline 320 (used to display the temporal relationship between the schedule and turnover plan), a parameter panel 330 (used to configure calculation parameters such as loss rate λ, integrity rate η, and anti-shake timing window duration), a comparison dashboard 340 (used to display the comparison results of multiple schemes), and a report generator 350.

[0046] The storage layer 400 is responsible for persistent data storage. The storage layer includes a local lightweight database 410 for storing the current project's solution data, and a cloud synchronization node 420 for enabling multi-terminal data sharing. The storage layer interfaces with the enterprise resource planning system through a Representational State Transfer (REST) ​​application programming interface (API).

[0047] The following section provides a further explanation of the configuration schemes for each component in this system.

[0048] like Figure 2 As shown, the building information model parser 110 in the data access layer 100 of this system contains a geometric information extraction sub-component 111, a general format parsing sub-component 112, a construction joint identification sub-component 113, and a functional part marking sub-component 114.

[0049] The geometric information extraction sub-component 111 is configured to extract the geometric dimensions and spatial coordinates of structural components such as beams, slabs, columns, and walls from the building information model.

[0050] The general format parsing subcomponent 112 is configured to parse the Industrial Basic Class (IFC) general data format, and automatically switches to this mode when the native software format parsing fails.

[0051] The construction joint identification sub-component 113 is configured to automatically identify the location of construction joints based on the construction joint marking information in the structural design documents.

[0052] The functional part marking sub-component 114 is configured to automatically mark the basement roof area and the standard floor area based on elevation information.

[0053] The progress parsing component 120 in the data access layer 100 of this system includes a file format adaptation subcomponent 121, a semantic parsing subcomponent 122, and a logical relationship extraction subcomponent 123.

[0054] Among them, the file format adaptation sub-component 121 is configured to support the parsing of multiple mainstream schedule file formats; The semantic parsing sub-component 122 is configured to perform text parsing on the names and descriptions of progress nodes, and extract semantic information such as the flow section, floor, and component type implied therein; The logical relationship extraction sub-component 123 is configured to extract the preceding, following, and parallel relationships between progress nodes and construct the dependency graph of the progress network.

[0055] like Figure 2 and combined Figure 3 As shown, the internal structure of the three-dimensional association matrix generator 220 in the computation layer 200 of this system specifically includes: a mapping rule base 221, a two-way binding sub-component 222, a de-jitter timer 223, and an adjacency list storage sub-component 224.

[0056] Among them, the mapping rule base 221 is configured to store the mapping rules from the naming rules of progress nodes to the encoding of pipeline segments; The two-way binding sub-component 222 is configured to establish a two-way index between the progress node 301 and the flow segment 302; The anti-jitter timer 223 is configured to start a timing window after receiving a progress change event, and trigger matrix reconstruction only when the change is confirmed to be valid after the window expires; The adjacency list storage sub-component 224 is configured to store a three-dimensional association matrix in an adjacency list data structure 340 and support multi-directional retrieval.

[0057] like Figure 2 and combined Figure 4As shown, the internal structure of the quantity difference calculation component 240 in the calculation layer 200 of this system includes a parameter configuration sub-component 2401, a quantity analysis sub-component 2402, a demand calculation sub-component 2403, a sliding window transfer sub-component 2404, a demolding condition determiner 2405, a real-time integrity rate statistician 2406, and a graph traversal sub-component 2407.

[0058] The parameter configuration sub-component 2401 is configured to receive the loss rate λ and integrity rate η parameters configured by the user. The engineering quantity analysis sub-component 2402 is configured to extract the bottom projection area A_{i,t} of each flow section according to the construction sequence based on the three-dimensional correlation matrix 300, and calculate the unit area support density K_spec in combination with the slab thickness, concrete self-weight and construction live load. The demand calculation sub-component 2403 is configured to calculate the theoretical demand D_{i,t} based on the projected area A_{i,t} of the bottom plate and the support density K_spec per unit area, according to the following formula: D_{i,t} = A_{i,t} × K_spec × (1 + λ) / η, where N_turn is not included; The sliding window pass subcomponent 2404 is configured to perform sliding window pass calculation of available turnover Q_avail between adjacent nodes; The demolding condition determiner 2405 is configured to determine the inventory release conditions in both the time dimension (concrete curing strength meets the standard) and the spatial dimension (floor location meets the requirement of retaining two floors); The 2406 real-time integrity rate statistician is configured to calculate the actual integrity rate of disassembled and returned materials and automatically remove defective materials from the available inventory pool. Graph traversal subcomponent 2407 is configured to re-search for adjacency propagation paths based on breadth-first search or depth-first search algorithms when the flow order changes.

[0059] like Figure 2 and combined Figure 4 As shown, the internal structure of the scheduling optimization component 250 in the computing layer 200 of this system includes a priority queue management subcomponent 2501, a compatibility verification subcomponent 2502, a specification substitution matcher 2503, a flow network construction subcomponent 2504, an optimization solution subcomponent 2505, and a constraint conflict resolver 2506.

[0060] The priority queue management subcomponent 2501 is configured to maintain the priority order of multi-level compensation sources; the compatibility verification subcomponent 2502 is configured to verify the compatibility between the compensation source specifications and the demand specifications, and maintain the M_compat matrix; the specification substitution matcher 2503 is configured to search for alternative solutions from high specifications to low specifications or compatible specifications of the same type based on the substitution penalty coefficient α when there is insufficient inventory of fully matching specifications; the flow network construction subcomponent 2504 is configured to construct the scheduling problem as a minimum cost flow network with capacity constraints; the optimization solution subcomponent 2505 is configured to execute the minimum cost maximum flow algorithm and output the optimal scheduling scheme, with the objective function containing the substitution penalty term α×Q_substitute; and the constraint conflict resolver 2506 is configured to output suggested instructions for adjusting the flow section or construction speed when there is no solution to the scheduling problem.

[0061] like Figure 2 and combined Figure 5 As shown, the scheme comparison component 260 in the computing layer 200 of this system specifically includes a scheme parallel generation sub-component 261, an evaluation index calculation sub-component 262, a TOPSIS decision sub-component 263, and a visualization output sub-component 264.

[0062] The parallel generation subcomponent 261 is configured to drive the system to generate multiple schemes in parallel based on different combinations of strategy parameters. The design turnover number N_turn is only passed to the evaluation index calculation subcomponent as an economic evaluation parameter. The evaluation index calculation subcomponent 262 is configured to calculate the four-dimensional evaluation vector V = [C_save, T_impact, F_cross, R_early] for each scheme. N_turn is introduced as a cost amortization factor in the calculation of C_save. The TOPSIS decision subcomponent 263 is configured to perform range normalization, distance calculation and proximity ranking. The visualization output subcomponent 264 is configured to generate visualization comparison results such as radar chart 510 and scatter plot 520.

[0063] In the interactive layer 300 of this system, the report generator 350 is mainly composed of a data aggregation sub-component 351 and a Gantt chart generation sub-component 352.

[0064] Among them, the data aggregation sub-component 351 is configured to aggregate data such as turnover path information, loss amount ΔQ, return amount Q_return, and loss source identifier into a structured data table; the Gantt chart generation sub-component 352 is configured to overlay and render the entry and exit plan and the original schedule plan on the same time axis, and use color to mark the warning nodes.

[0065] Based on the above-mentioned design system for the turnover of the under-slab internal support frame considering schedule matching, the present invention further provides a design method for the turnover of the under-slab internal support frame considering schedule matching.

[0066] See Figure 1 The present invention provides a method for designing the turnover of the under-plate inner support frame that takes into account the matching of the schedule plan. Based on the above system, it includes seven core steps. Each step is executed collaboratively by the components of each layer of the system. The data access layer 100 provides input data, the calculation layer 200 executes the core calculation logic, the interaction layer 300 provides parameter configuration and result output, and the storage layer 400 provides data persistence.

[0067] Step S1 is the process of dividing the flow section and arranging the frame based on structural constraints.

[0068] This step is completed collaboratively by the flow section topology builder 210 and the support density matcher 230. The flow section topology builder 210 takes the building information model as input, identifies the location of construction joints, functional structural parts, and the basement roof area, and, in conjunction with the mandatory requirements regarding the number of support layers in structural construction safety codes, divides the overall structure into several construction flow sections. Subsequently, within each flow section, the support density matcher 230 completes the three-dimensional design and mesh layout of the internal support frame based on structural load conditions and construction process parameters, generating the initial turnover topology 610. (See [link to relevant documentation]). Figure 6 This step provides a spatial basis for subsequent schedule linkage and turnover calculations.

[0069] Step S2 is the time-driven and dynamic connection step of the schedule plan.

[0070] This step is completed collaboratively by the schedule parser 120 and the 3D association matrix generator 220. The schedule parser 120 receives the external schedule file and extracts the timing information and logical relationships of the work breakdown structure nodes through parsing. The 3D association matrix generator 220 binds these schedule nodes bidirectionally with the flow segments generated in step S1, constructing a schedule-flow segment-component 3D association matrix 300. This matrix is ​​the data hub of the entire turnaround design, establishing the mapping relationship between the time dimension (i.e., schedule nodes), the spatial dimension (i.e., flow segments), and the material dimension (i.e., supporting structural components). When the schedule changes, the anti-jitter timer 223 built into the 3D association matrix generator 220 triggers the reconstruction of the matrix after confirming the change is valid, and drives the linked updates of all downstream calculation stages.

[0071] Step S3 is the engineering quantity analysis and specification configuration mapping step.

[0072] This step is performed by the quantity analysis sub-component 2402 of the quantity difference dynamic calculator 240. The quantity analysis sub-component 2402 calls the quantity analysis function in sequence according to the construction sequence recorded in the three-dimensional correlation matrix, and automatically extracts the bottom projection area of ​​each flow section; then, it calculates the required support density per unit area by combining parameters such as slab thickness, concrete self-weight and construction live load, and matches the specific specifications of uprights, horizontal bars and diagonal braces from the material specification library accordingly; finally, it outputs the frame material configuration list for each flow section by taking into account the turnover path and the number of support layers.

[0073] Step S4 is the dynamic calculation and adaptive recalculation step for turnover difference.

[0074] This step is executed by the quantity difference dynamic calculator 240, with its various sub-components working collaboratively. This step constructs an accurate physical model for calculating turnover quantity difference, strictly adhering to the physical reality that the support frame can only be erected and dismantled once at the same construction node. The demand calculation sub-component 2403 calculates the theoretical demand for each flow section at each construction node. The sliding window transfer sub-component 2404 calculates the compensation and return quantities through the sliding window transfer of available turnover between adjacent nodes. The demolding condition determiner 2405 performs inventory release determination under dual constraints of time and space dimensions. The real-time integrity rate statistician 2406 calculates the actual integrity rate of dismantled and returned materials in real time and automatically removes unqualified materials from the available inventory pool. The graph traversal sub-component 2407 uses a graph traversal algorithm to re-search adjacent transfer paths and implement incremental recalculation of quantity difference when the construction flow sequence changes.

[0075] Step S5 is the intelligent matching and closed-loop scheduling step for loss replenishment sources.

[0076] This step is executed by the scheduling optimizer 250, whose sub-components work collaboratively. The priority queue management sub-component 2501 establishes a multi-level priority queue for replacement sources; the compatibility verification sub-component 2502 performs specification compatibility verification; the specification substitution matcher 2503 initiates specification substitution matching when fully matching specifications are insufficient; and the flow network construction sub-component 2504 and the optimization solution sub-component 2505 use the minimum cost maximum flow algorithm to solve for the optimal scheduling allocation scheme. When there is no solution for scheduling, the constraint conflict resolver 2506 triggers the constraint conflict resolution mechanism, outputting suggested instructions for adjusting the flow segment or construction speed, thus achieving a closed-loop scheduling of "dismantling-replenishment-use".

[0077] Step S6 is the step of generating the structured turnover table and the entry / exit plan.

[0078] This step is executed by the report generator 350, where the data aggregation sub-component 351 aggregates the calculation results and scheduling instructions from the preceding steps into a structured data table, generating an entry and exit plan that includes time nodes, quantities, specifications, and source channels. The Gantt chart generation sub-component 352 generates a visual Gantt chart, overlaying the entry and exit plan with the original schedule plan on the same timeline, and using color to identify warning nodes.

[0079] Step S7 is the parallel generation and quantitative comparison of multiple turnover schemes.

[0080] This step is executed by the scheme comparison engine 260. The scheme parallel generation sub-component 261 generates multiple complete turnover schemes in parallel based on different combinations of strategy parameters. The design turnover number N_turn is only used as a parameter for cost amortization calculation in the scheme's economic evaluation and is not involved in the instantaneous supply-demand balance calculation of physical quantity differences. The evaluation index calculation sub-component 262 calculates the four-dimensional evaluation vector, the TOPSIS decision sub-component 263 performs multi-criteria decision ranking, and the visualization output sub-component 264 generates a comparison dashboard to output recommended schemes.

[0081] The following describes the specific implementation plan for each step in the design method for the turnover of the inner support frame under the slab, which takes into account the matching of the schedule, in conjunction with the specific system configuration.

[0082] Step S1 in this method is completed collaboratively by the flow segment topology builder 210 and the support density matcher 230 in the system.

[0083] The flow section topology builder 210 first extracts the geometric information and topological relationships of structural components through the building information model interface. The flow section topology builder 210 calls the geometric information extraction sub-component 111 of the building information model parser 110 to identify the location coordinates of all construction joints and the boundaries of structural functional parts in the structure, and automatically marks the basement back-top area and the standard floor area.

[0084] After completing the above information extraction, the flow section topology builder 210 reads the preset structural construction safety specification library to obtain the mandatory requirements regarding the number of support layers (such as the requirement to "retain two layers of structural support"). The flow section topology builder 210 treats these safety constraints as insurmountable hard boundaries and forcibly reserves the overlapping area of ​​the upper and lower support layers when dividing the flow section, thereby generating a flow section boundary with a safety buffer.

[0085] The flow segment division employs a constrained spatial partitioning algorithm. This algorithm treats construction joints and structural expansion joints as insurmountable boundaries, and then divides the flow segments according to the requirements of area balance and structural integrity, generating the optimal flow segment division scheme.

[0086] Subsequently, for each divided flow segment, the support density matcher 230 calculates the required support bearing capacity for each area based on the structural load model, reads the specifications of available members from the material selection library, and automatically generates a grid layout scheme for the uprights by combining construction process parameters (such as the modularity of the disc buckle, step distance restrictions, etc.). The output of the support density matcher 230 includes the position coordinates of the uprights in each flow segment, the connection scheme of the horizontal members, the arrangement ratio of the diagonal braces, and a list of the quantities of various members, forming the initial turnover topology 610 of the single unit.

[0087] In this method, step S2 is completed collaboratively by the schedule parser 120 and the three-dimensional correlation matrix generator 220.

[0088] The schedule parser 120 first receives and parses the externally imported schedule file. The file format adaptation subcomponent 121 of the schedule parser 120 identifies the file format, the semantic parsing subcomponent 122 extracts the attribute information of each work breakdown structure node, including node code, node name, planned start time, planned end time, predecessor node relationship and resource load information, and the logical relationship extraction subcomponent 123 extracts the logical dependencies between schedule nodes.

[0089] After extracting the progress information, the 3D association matrix generator 220 uses a matching algorithm to bidirectionally bind the progress nodes to the pipeline segments generated in step S1. This matching algorithm first performs semantic parsing on the names and descriptions of the progress nodes to extract the implicit pipeline segment identification information; then, it matches the parsing results with the pipeline segment codes through rule mapping, establishing a first-level mapping relationship from progress nodes to pipeline segments. Based on this, the 3D association matrix generator 220 establishes a second-level mapping relationship from pipeline segments to the support structure component list according to the structural component information corresponding to each pipeline segment. The superposition of these two levels of mapping relationships forms a progress-pipeline-component 3D association matrix 300. This matrix uses a mapping rule library 221 to store the mapping rules from progress node naming rules to pipeline segment codes, a bidirectional binding sub-component 222 to establish a bidirectional index between progress node 301 and pipeline segment 302, and an adjacency list storage sub-component 224 to store the 3D association matrix using an adjacency list data structure and support multi-directional retrieval.

[0090] After the three-dimensional correlation matrix of a single project is constructed, the system further aggregates the turnover plans of multiple single projects upwards along the tower crane coverage radius and material storage path, generating a cross-regional integrated turnover topology network 620. (See [link]). Figure 6 .

[0091] The system employs an event-driven architecture to handle schedule changes and incorporates a debouncing mechanism to handle frequent changes. When the schedule changes, the system publishes a schedule update event. The debouncing timer 223 built into the 3D association matrix generator 220 starts a timing window, the duration of which is configured by the user in the parameter panel 330. During the timing window, the system temporarily stores all arriving schedule change events and accumulates the number of changes. Only when the timing window expires does the system confirm the change is valid and execute the subsequent association matrix reconstruction operation; if new change events continue to arrive during the timing window, the system resets the timing window and restarts the timing. This debouncing mechanism effectively avoids the unnecessary occupation of system resources and user interface lag caused by frequent schedule changes.

[0092] After confirming the validity of the changes, the system uses a directed acyclic graph to detect logical conflicts between progress nodes. If problems such as overlapping time periods or insufficient maintenance cycles are found, incremental reconstruction of the association matrix is ​​triggered—only the subgraph regions affected by the changes are recalculated to avoid performance bottlenecks caused by full calculation.

[0093] Step S3 in this method is performed by the quantity analysis subcomponent 2402 of the quantity difference dynamic calculator 240.

[0094] The engineering quantity analysis sub-component 2402 analyzes the time axis recorded along the three-dimensional correlation matrix, node by node according to the construction sequence.

[0095] For each target node, the quantity analysis subcomponent 2402 first extracts the net projected area of ​​the slab bottom corresponding to that flow segment from the building information model based on the flow segment identifier bound to that node. During the extraction process, the system automatically deducts the area of ​​non-floor slab areas such as walls, column capitals, and beams to ensure the accuracy of the projected area.

[0096] After obtaining the projected area of ​​the slab bottom, the engineering quantity analysis sub-component 2402 reads the structural design parameters of the flow section, including the slab thickness, concrete unit weight, and uniformly distributed live load during construction. Based on these parameters, the system calculates the axial force that the uprights need to withstand and the overall overturning resistance requirements of the frame according to the principles of structural mechanics.

[0097] The engineering quantity analysis sub-component 2402 calls the built-in verification module of the support density matcher 230, which conforms to industry safety technical standards. Based on the back calculation results, this module automatically matches the specifications of the uprights (such as pipe diameter and wall thickness), the horizontal bar spacing, and the diagonal bracing arrangement ratio that meet the load-bearing requirements from the material specification library. The matching process comprehensively considers the stable load-bearing capacity of the uprights, the bending stiffness of the horizontal bars, and the anti-lateral displacement capacity of the diagonal bracing.

[0098] Based on the above matching results, the engineering quantity analysis sub-component 2402 calculates the number of various types of members required per unit area, i.e., the support density per unit area K_spec. Multiplying the support density per unit area by the projected area of ​​the bottom of the flow section, and then by the corresponding safety factor, yields the theoretical requirement of various types of members for that flow section.

[0099] When outputting the scaffolding material configuration list for each flow section, the engineering quantity analysis sub-component 2402 also integrates turnover path information and support layer constraints—for areas that require retained support, the configuration list is updated accordingly with the number of members needed for that area. The final output configuration list contains complete information such as the model, unit weight, quantity, and number of node fasteners for each type of member.

[0100] Step S4 in this method is executed by the dynamic differential calculator 240, with its various sub-components working together.

[0101] Users can configure the following core parameters through parameter configuration sub-component 2401 according to the actual situation of the project: material loss rate λ (reflecting the normal loss ratio of the support frame during disassembly, transportation and use) and on-site usable integrity rate η (reflecting the proportion of rods that can be directly used after disassembly to the total disassembled quantity).

[0102] The demand calculation sub-component 2403 calculates the theoretical demand D_{i,t} for the target flow segment i at construction node t according to the following formula: D_{i,t} = A_{i,t} × K_spec × (1 + λ) / η; Where A_{i,t} is the projected area of ​​the target flow segment i on the bottom of node t, and K_spec is the support density per unit area corresponding to the flow segment.

[0103] The sliding window transfer subcomponent 2404 calculates the available turnover Q_avail between adjacent nodes. Let Q_avail(t-1) be the available turnover after node t-1 is disassembled. Then the available turnover of node t is obtained by deducting the loss from the disassembly amount of the previous node.

[0104] However, not all disassembly quantities can enter the sliding window transfer chain of Q_avail. The demolding condition determiner 2405 is equipped with a dual-condition constraint inventory release determination mechanism: Time condition – The formwork removal time must meet the concrete curing cycle requirements. The formwork removal condition determiner 2405 determines whether the floor has reached the specified formwork removal strength based on the concrete strength growth curve. Only after the strength meets the standard can the support frame inventory for that floor enter the release candidate set.

[0105] Spatial Conditions – The floor location must meet the safety requirement of “retaining two layers of support.” The formwork removal condition determiner 2405 tracks the floor number N_current of the current construction floor in real time. Only when the floor number to be released l ≤ (N_current - 2) can the support frame inventory of that floor be released. For floors that do not meet the spatial conditions, even if their concrete strength has reached the standard, their support frame inventory is still forcibly locked and cannot enter the Q_avail transfer chain.

[0106] Only when both the above time and space conditions are met can the dismantling amount of node t-1 be included in the available turnover amount Q_avail of node t.

[0107] The compensation amount ΔQ and the return amount Q_return output by the demand calculation sub-component 2403 are output according to the following physical logic: ΔQ = max(0, D_{i,t} - Q_avail) Q_return = max(0, Q_avail - D_{i,t}) The physical meaning of the above formula is as follows: when the available turnover capacity cannot meet the theoretical demand of the current node, a compensation requirement is generated, and the compensation amount is the difference between the two; when the available turnover capacity exceeds the theoretical demand of the current node, a return of material is generated, and the return amount is the difference between the two. This formula strictly follows the physical reality that the support frame can only be used once at the same node, which is fundamentally different from the erroneous practice in existing technologies of multiplying the number of turnovers by the available capacity.

[0108] After the support frame is disassembled at each node, the real-time integrity rate statistician 2406 calculates the actual integrity rate η_actual of the disassembled and returned materials by real-time input of on-site inspection data or by connecting to intelligent inspection equipment. When η_actual is lower than the preset integrity rate threshold η, the real-time integrity rate statistician 2406 automatically removes the unqualified materials from the available inventory pool, marks them as pending scrap or repair, and generates a corresponding scrap list. Only the net available quantity after the rejection process enters the Q_avail sliding window transfer chain of the sliding window transfer sub-component 2404 to ensure consistency between the inventory and the records.

[0109] The graph traversal subcomponent 2407 uses a sliding window caching mechanism to store the available turnover status of each node. When the construction sequence changes, the graph traversal subcomponent 2407 re-searches for adjacency transmission paths between segments based on breadth-first search or depth-first search graph traversal algorithms. During the re-search process, the graph traversal subcomponent 2407 only updates the available turnover transmission paths in the subgraph regions affected by the change in the sequence, without recalculating the quantity differences of all nodes.

[0110] Step S5 in this method is executed by the scheduler optimizer 250, whose sub-components work together.

[0111] The scheduling optimizer 250 first scans the on-site material ledger system through the material ledger interface 130 to obtain all available support frame inventory information.

[0112] Priority queue management subcomponent 2501 establishes a multi-level loss replenishment source queue according to the following priorities: The first priority is to dismantle the support frames of floors in the same building that have met the demolding strength requirements. These support frames are located in the same construction site, with the shortest transportation distance and the lowest secondary handling cost. The second priority is the demolition inventory in the basement or podium area - although this part of the inventory is not on the same floor, it still belongs to the same single project and is relatively easy to access; The third priority is the cross-project available allocation pool—when the inventory within the same unit cannot meet the replenishment needs, the system searches for available resources from the cross-project material allocation pool at the enterprise level. The fourth priority is external leasing or procurement—when the above three levels of internal resources cannot meet the needs, the system initiates the external leasing or procurement process.

[0113] After identifying candidate replacement sources, the compatibility verification subcomponent 2502 first performs a compatibility verification of fully matching specifications. The compatibility verification subcomponent 2502 maintains a specification compatibility matrix M_compat, which records the fully matching relationships between members of the same specification.

[0114] When the inventory of a perfectly matched specification is insufficient to meet the replenishment requirement, specification substitute matcher 2503 initiates a specification substitute matching strategy. This strategy searches for alternatives according to the following priority: First-order substitution: Higher specifications of the same type replace lower specifications. For example, when Φ48×3.5 uprights are in short supply, Φ60×3.2 uprights are allowed as substitutes. The specification substitution matcher 2503 sets a substitution penalty coefficient α_high_to_low for this high-to-low substitution scheme, which reflects the increase in material cost caused by the substitution.

[0115] The second generation prioritizes substitution based on compatible specifications of the same type. For example, vertical poles with different wall thicknesses but the same diameter can be substituted for each other after the load-bearing capacity calculation has passed. The specification substitution matcher 2503 sets a substitution penalty coefficient α_compatible for such compatible substitutions, which reflects the verification cost incurred due to the compatible substitution.

[0116] Third-generation priority: Cross-category substitution between early-release system heads and standard members (provided mechanical calculations permit). The specification substitution matcher 2503 sets the cross-category substitution penalty coefficient α_cross.

[0117] The substitution penalty coefficient α is included in the objective function of the scheduling optimization model as an additional cost term, enabling the system to make a weighted comparison and selection between the perfect matching scheme and the substitution scheme. The specification substitution matcher 2503 gives the scheduling system flexible adaptability when facing scarce resources, avoiding rigid failure modes such as direct error reporting or shutdown due to insufficient perfect matching specifications.

[0118] For various candidate compensation sources (including substitution schemes), the flow network construction sub-component 2504 constructs the scheduling problem as a minimum-cost flow network with capacity constraints, and the optimization solution sub-component 2505 uses a minimum-cost maximum flow algorithm with capacity constraints to solve for the optimal scheduling allocation scheme. The objective function of this algorithm is to minimize the total scheduling cost. For substitution schemes, an additional penalty term of α×Q_substitute is added to the total cost. min Σ(C_transport + C_handling + C_lease + α_k × Q_substitute) Where C_transport is the transportation cost, C_handling is the secondary handling and loading / unloading cost, C_lease is the rental cost, α_k is the penalty coefficient for the corresponding alternative, and Q_substitute is the quantity of alternatives provided.

[0119] Early-release system heads and standard rods employ dual-channel independent inventory management. The system manages early-release system heads and standard rods as two independent inventory categories, maintaining separate inventory ledgers, specification parameters, and turnover records for each. This independent management approach allows early-release system heads to be prioritized for rapid demolding scenarios in non-load-bearing areas, while standard rods are used for regular support in load-bearing areas.

[0120] When the scheduler optimizer fails to meet the compensation requirements of the construction node within the preset time constraint after searching all priority queues and matching specifications (i.e., scheduling has no solution), the constraint conflict resolver 2506 does not directly report an error and stop the machine. Instead, it automatically outputs the following adjustment suggestion instructions: (1) Suggestion for adjusting the flow section: Divide the current construction flow section into smaller sub-segments to reduce the total amount of support frames required for a single pour; (2) Suggestions for adjusting construction speed: Adjust the construction interval between adjacent flow sections to allow more time for material turnover; (3) Suggestion for adjusting the schedule: postpone the planned start time of the current node until the source of the damage is in place before proceeding with construction.

[0121] The aforementioned suggestions and instructions are pushed to the interaction layer for management personnel to review and make decisions, ensuring that the system can still provide users with actionable solutions in extreme situations.

[0122] The system has an inventory safety threshold monitoring mechanism. When the available inventory of a certain category or specification falls below the preset safety threshold, the system automatically triggers an alert and generates a purchase requisition or cross-project transfer instruction, which is then sent to the enterprise resource planning system or materials management system via the application programming interface (API).

[0123] Step S6 in this method is executed by report generator 350.

[0124] The data aggregation sub-component 351 aggregates information such as turnover path information, loss amount ΔQ and return amount Q_return at each node, and loss source identifier into a structured data table.

[0125] The system calculates the lead time for the support frame to arrive on site based on the planned start time of the formwork node. The lead time for arrival on site consists of three components: logistics and transportation time (transportation time from the location of the damage source to the construction site), arrival and acceptance time (time for quality inspection and quantity counting of the support frame after it arrives on site), and stacking and positioning time (time from the arrival of the support frame to the completion of stacking and positioning preparation).

[0126] The calculation of the exit time includes the demolding and cleaning cycle—the time required from the start of dismantling the support frame to the completion of cleaning, packaging, and readiness for exit.

[0127] The Gantt chart generation sub-component 352 overlays and renders the entry and exit plans with the original schedule on the same timeline, and uses color to mark warning nodes—yellow indicates that the inventory is approaching the critical value, and red indicates that there is a risk of material shortage.

[0128] The system uses a template engine to bind structured data to output reports in Excel or PDF format.

[0129] Step S7 in this method is executed by the scheme comparison engine 260.

[0130] The parallel generation sub-component 261 drives the system to execute steps S1 to S6 in parallel by setting multiple different combinations of strategy parameters, generating multiple complete turnover plans. The variable strategy parameters include: the segmentation strategy of the flow section (coarse or fine division), the design turnover assumption N_turn of the support frame (this parameter is only used for economic evaluation and does not participate in the physical quantity difference calculation in step S4), the application ratio of the early dismantling system, and the weight allocation of the compensation source, etc.

[0131] Regarding the precise positioning of the design turnover number N_turn: In this invention, N_turn is strictly defined as an economic evaluation parameter rather than a physical quantity difference calculation parameter. N_turn does not appear in the instantaneous supply and demand balance calculation in step S4; it only appears as a cost amortization factor in the scheme economic evaluation in step S7, calculating the cost of each support frame allocated to a single use over its entire lifespan. This approach accurately reflects the physical reality that the support frame can only be used once at the same construction node, while also reasonably assessing the cost-saving effect of multiple material turnovers from an economic perspective. It fundamentally solves the technical defect in existing technologies where the turnover number is incorrectly multiplied into the instantaneous supply and demand balance formula, leading to severely distorted calculation results.

[0132] The evaluation index calculation sub-component 262 constructs a four-dimensional evaluation vector V = [C_save, T_impact, F_cross, R_early] to evaluate each scheme, where: C_save represents the savings rate in support frame rental or procurement costs, reflecting the economic benefits of the solution—N_turn is introduced as a cost amortization factor in the calculation of this indicator. T_impact represents the number of days that affect the critical path duration, reflecting the project's ability to guarantee schedule. F_cross represents the frequency of intersections of the turnover path, reflecting the complexity of the solution at the logistics scheduling level. R_early represents the utilization rate of the early dismantling system, reflecting the efficiency of the scheme in utilizing early dismantling technology and equipment.

[0133] The TOPSIS decision sub-component 263 employs the TOPSIS multi-criteria decision algorithm for quantitative comparison and selection of solutions. This algorithm first performs range normalization on the raw data for each dimension to eliminate the influence between different units; then, it calculates the distance between each solution and the positive and negative ideal solutions based on preset weights; finally, it calculates the relative closeness of each solution, sorts them from highest to lowest closeness, and outputs recommended solutions.

[0134] The weights for each dimension can be preset by users through the analytic hierarchy process or adjusted directly by dragging and dropping on the interactive interface to meet the different preferences of different projects for objectives such as cost and schedule.

[0135] The visualization output sub-component 264 generates a comparison dashboard, including a radar chart 510 (showing the comprehensive performance of each scheme in four dimensions), a cost-time scatter plot 520 (showing the distribution of each scheme in a two-dimensional plane of cost and time), and a highlighted recommended scheme 530. Users can click "Apply Optimal Parameters" with one click to automatically write back all parameters corresponding to the recommended scheme to the current project configuration.

[0136] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A method for designing the turnover of internal support frames under slabs considering schedule matching, characterized in that, The method includes: The process of dividing the construction flow into sections involves identifying the location of construction joints and structural functional parts based on the building information model, and then dividing the construction flow into sections in accordance with the mandatory requirements for the number of support layers in the structural construction safety code. The progress linkage step involves importing the progress plan file and extracting the timing information of the work breakdown structure nodes, bidirectionally binding the progress nodes with the flow segment, and constructing a three-dimensional association matrix of progress-flow segment-component. The quantity difference calculation step involves extracting the bottom projection area of ​​each flow section according to the construction sequence based on the three-dimensional correlation matrix and calculating the support density per unit area. Combined with preset loss rate and integrity rate parameters, the theoretical demand, replenishment amount, and return amount of each flow section at each construction node are calculated. The replenishment amount is the difference between the available turnover amount and the theoretical demand amount of the current node. The return amount is the difference between the available turnover amount and the theoretical demand amount of the current node. The available turnover amount can only be released into the available inventory pool when both the demolding strength standard condition and the support layer space condition are met simultaneously. The scheduling process involves establishing a multi-level priority queue for loss replenishment sources and performing optimal matching and scheduling allocation of loss replenishment sources based on specification compatibility, transportation distance, and cost. The output steps of the plan are to generate a structured turnover table and an entry / exit plan based on the quantity difference calculation results and the scheduling allocation results.

2. The method according to claim 1, characterized in that, In the progress linkage step, when the progress plan changes, an anti-jitter timer is started. The reconstruction of the three-dimensional correlation matrix is ​​triggered only after the timer window expires and the change is confirmed to be valid, and the re-execution of the quantity difference calculation step and the scheduling step is driven.

3. The method according to claim 1, characterized in that, In the quantity difference calculation step, the theoretical demand D_{i,t} for the target flow section i at construction node t is calculated according to the following formula: D_{i,t} = A_{i,t} × K_spec × (1 + λ) / η; Where A_{i,t} is the projected area of ​​the target flow segment i at the bottom of the plate at node t, K_spec is the unit area support density of the target flow segment, λ is the material loss rate, and η is the on-site usable integrity rate. The compensation amount ΔQ and the return amount Q_return are output according to the following logic: ΔQ = max(0, D_{i,t} - Q_avail); Q_return = max(0, Q_avail - D_{i,t}); Where Q_avail is the available turnover between adjacent nodes, which is obtained by deducting the loss from the dismantling amount of the previous node.

4. The method according to claim 1, characterized in that, In the quantity difference calculation step, the system calculates the actual integrity rate of the disassembled and returned materials in real time. When the actual integrity rate is lower than the preset integrity rate threshold, the system automatically removes the unqualified materials from the available inventory pool and marks them as pending scrapping or repair.

5. The method according to claim 1, characterized in that, In the scheduling step, when there is insufficient inventory of fully matching specifications, the system initiates a specification substitution matching strategy, searching for alternatives from high specifications to low specifications or compatible specifications of the same type based on a preset substitution penalty coefficient.

6. The method according to claim 1, characterized in that, In the scheduling step, the multi-level replenishment source priority queue is arranged from high to low according to the following priorities: floor dismantling support frames that have met the demolding strength standards of the same unit, basement or podium dismantling inventory, cross-project transfer pool, and external leased or purchased resources.

7. The method according to claim 1, characterized in that, In the scheduling step, the minimum cost maximum flow algorithm with capacity constraints is used to solve for the optimal scheduling allocation scheme of the compensation source. The objective function is to minimize the total scheduling cost. For the substitution scheme, the total cost is increased by adding a product term of the substitution penalty coefficient and the number of substitutions. min Σ(C_transport + C_handling + C_lease + α_k × Q_substitute) Where C_transport is the transportation cost, C_handling is the secondary handling cost, C_lease is the lease cost, α_k is the penalty coefficient for the corresponding substitute solution, and Q_substitute is the quantity of substitute solutions provided.

8. The method according to claim 1, characterized in that, In the scheduling steps, when the scheduling of the damage replenishment source cannot meet the needs of the construction node within the preset time constraint, the system automatically outputs suggested instructions for adjusting the flow section or the construction speed.

9. The method according to claim 1, characterized in that, Following the output step, a scheme comparison step is also included: based on different flow segmentation strategies, the turnaround time assumption N_turn, the application ratio of early dismantling system, or the weight of compensation source call, multiple turnaround schemes are generated in parallel. The turnaround time assumption N_turn is only used as a parameter for the economic evaluation of the scheme in the cost amortization calculation, and is not used in the instantaneous supply and demand balance calculation of physical quantity difference. A multi-dimensional evaluation vector is constructed, which includes cost saving rate, number of days of project duration impact, frequency of turnaround path intersection, and utilization rate of early dismantling system. A multi-criteria decision algorithm is used to quantitatively compare and select each scheme and output a recommended scheme.

10. A turnover design system for an under-plate internal support frame considering schedule matching, characterized in that, The system includes: The data access layer includes a building information model parser, a schedule parser, and a material ledger interface. The building information model parser supports two modes: native software format parsing and general industrial data format parsing. When native format parsing fails, it automatically switches to the general data format parsing mode. The computational layer includes a flow section topology builder, a 3D correlation matrix generator, a quantity difference dynamic calculator, a scheduling optimizer, and a scheme comparison engine. The 3D correlation matrix generator has a built-in anti-jitter timer, which starts a timing window upon receiving a progress change event, and only performs matrix reconstruction after the window expires and the change is confirmed to be valid. The quantity difference dynamic calculator includes a demolding condition determiner and a real-time integrity rate statistician. The demolding condition determiner determines the release conditions of inventory on each floor in both time and space dimensions. The real-time integrity rate statistician calculates the actual integrity rate of materials dismantled and returned to the warehouse and automatically removes unqualified materials from the available inventory pool. The scheduling optimizer includes a specification substitution matcher and a constraint conflict resolver. The specification substitution matcher searches for alternative solutions based on a substitution penalty coefficient when there is insufficient inventory to fully match specifications. The constraint conflict resolver outputs suggested instructions for flow section adjustment or construction speed adjustment when there is no solution in the scheduling process. The interaction layer includes a 3D viewport, timeline, parameter panel, comparison dashboard, and report generator. The storage layer includes a local database and cloud synchronization nodes.

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